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Collaborative Research: PACMAN – Cyberinfrastructure for Discovering Climate Change Impacts on Water Resources across

Alaska and the Hawaiian Islands

2. Project Summary The proposed 3-year project seeks to develop and demonstrate the capability of a Pacific Area Climate Monitoring and Analysis Network (PACMAN). PACMAN will yield a more reliable understanding of the impacts of climate warming on fresh water resources and communities in Alaska and Hawaii. PACMAN’s capabilities will include: (1) real-time access to synoptic satellite data and in-situ sensor systems, deployed throughout Alaska and the Hawaiian Islands; (2) integration of these datasets with archival data from existing research databases and drawn from sophisticated web-harvesting capabilities; (3) redundant archival of all data and information products, as well as; (4) real-time distributed simulation from supercomputing centers in Alaska and Hawaii, together with; (5) a collaborative framework for visualization and multi-dimensional mapping; (6) development of and reliance upon open-source web tools, and finally; (7) development of an agent-based framework for assessing societal impacts, and; (8) open distribution to researchers and policy makers in Alaska, Hawaii, and around the world through the Internet.

Intellectual Merit This core cyberinfrastructure to be developed under this proposal will enable research focused on measuring and understanding the macro- and micro-scale processes that influence fresh water and its ties to the social, cultural, and environmental wellbeing of communities in Alaska and Hawaii. The grand challenge is to be able to understand the dynamics of the integrated climate-water-socialsystem from the local to global scales, as a basis for evaluating the effects of climate change on water resources. The research builds on, supports, and integrates many disciplines including ecology, conservation biology, chemistry, ocean and earth sciences, soil sciences, hydrology, environmental engineering, GIS, mathematics, resilience and social-ecological modeling. The integration framework proposed here goes beyond discipline-based inquiry and is fundamental to the understanding of the impact of climate variability and change on ecosystems function and biodiversity – the core objective of Alaska EPSCoR’s current RII award. It is further proposed that the powerful, state-of-the art environmental monitoring and information management system initiated in the previous RII Hawaii EPSCoR grants will serve as the core platform and will be further developed to handle the complex data processing, simulation, sharing, and integration needs of diverse teams of researchers in various targeted thematic areas.

Broader Impacts The PACMAN consortium will not only be an effective research tool but will enhance the abilities of Alaskan and Hawaiian communities to understand, plan for, and respond to changing climate conditions. It will inform effective policies that build resilience in fresh water resource management at multiple scales of control. The current proposal will build upon the successes of previous Alaska and Hawaii EPSCoR RII educational and public outreach plans, as well as the Pacific and Alaska Regional Integrated Science and Assessment (RISA) programs funded through NOAA.

PACMAN will incorporate capabilities that are relevant to addressing other ‘real-world’ issues that most directly affect the coupled human-environment systems of the North Pacific, and will provide

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data and information products that are appropriate for, and capable of advancing a broad suite of cultural, economic, educational, and environmental missions across Alaska and Hawaii. It will accomplish this in two ways: 1) through the development of a highly accessible agent-based model capable of assessing the consequences of different hydrological scenarios and 2) through the establishment of an External Advisory Group, consisting of members drawn from potential end-user groups such as land holders, native Alaskan and Hawaiian groups, NGOs, K-12 schools, and government agencies. The PACMAN consortium will look to the EAG for guidance on such issues as research prioritization, relevant information products, appropriate data format designs, delivery characteristics, and other matters that will optimize the societal benefits of PACMAN. The development of PACMAN vis-à-vis partnering with the EAC will enable this consortium to better model social-ecological system dynamics in a manner that is highly transferable to other locales.

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TABLE OF CONTENTSFor font size and page formatting specifications, see GPG section II.C.

Total No. of Page No.*Pages (Optional)*

Cover Sheet for Proposal to the National Science Foundation

Project Summary (not to exceed 1 page)

Table of Contents

Project Description (Including Results from PriorNSF Support) (not to exceed 15 pages) (Exceed only if allowed by aspecific program announcement/solicitation or if approved inadvance by the appropriate NSF Assistant Director or designee)

References Cited

Biographical Sketches (Not to exceed 2 pages each)

Budget (Plus up to 3 pages of budget justification)

Current and Pending Support

Facilities, Equipment and Other Resources

Special Information/Supplementary Documentation

Appendix (List below. )(Include only if allowed by a specific program announcement/solicitation or if approved in advance by the appropriate NSFAssistant Director or designee)

Appendix Items:

*Proposers may select any numbering mechanism for the proposal. The entire proposal however, must be paginated.Complete both columns only if the proposal is numbered consecutively.

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TABLE OF CONTENTSFor font size and page formatting specifications, see GPG section II.C.

Total No. of Page No.*Pages (Optional)*

Cover Sheet for Proposal to the National Science Foundation

Project Summary (not to exceed 1 page)

Table of Contents

Project Description (Including Results from PriorNSF Support) (not to exceed 15 pages) (Exceed only if allowed by aspecific program announcement/solicitation or if approved inadvance by the appropriate NSF Assistant Director or designee)

References Cited

Biographical Sketches (Not to exceed 2 pages each)

Budget (Plus up to 3 pages of budget justification)

Current and Pending Support

Facilities, Equipment and Other Resources

Special Information/Supplementary Documentation

Appendix (List below. )(Include only if allowed by a specific program announcement/solicitation or if approved in advance by the appropriate NSFAssistant Director or designee)

Appendix Items:

*Proposers may select any numbering mechanism for the proposal. The entire proposal however, must be paginated.Complete both columns only if the proposal is numbered consecutively.

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4. Project Description

4.1 Current status of consortium’s cyberinfrastructure Building upon a long-standing tradition of collaboration and leveraging substantial university capabilities, the Alaska and Hawaii EPSCoR jurisdictions have established a consortium which is now poised to initiate a 3-year project to develop the Pacific Area Climate Modeling and Analysis Network (PACMAN). PACMAN is envisioned as a distributed research environment able to support climate monitoring, modeling and planning activities which advance understanding immediate and long-term precipitation patterns across the North Pacific. Expanding on existing capabilities and partnerships in remote sensing, informatics, climate and weather research, and supercomputing, PACMAN provides new and important capabilities for real-time data acquisition, data storage, mining and integration of heterogeneous data, advanced modeling and visualization capabilities, and appropriate open-source distribution and sharing over the Internet.

PACMAN integrates and expands on a variety of cyber-capabilities of the consortium, including: two Department of Defense (DoD) supported, university affiliated supercomputing facilities: the Arctic Region Supercomputing Center (ARSC) and the Maui High Performance Computing Center (MHPCC); the International Arctic Research Center’s IARC-JASDA Information System (IJIS), the Geographic Information Network of Alaska (GINA) , UA’s Scenarios Network for Alaska Planning(SNAP); UA’s Forecasting Environmental Resilience of Arctic Landscapes (FERAL), InteleSense Technologies, Inc.,�the Office of Advanced Cyberinfrastructure (OACI), the Institute for Integrated Earth Observing Systems (IIEOS) and the Hawaii Biodiversity Mapping Program (HBMP) at UH.

Underlying all cyberinfrastructure is an advanced data network that ties together data, computing resources, visualization capabilities and most importantly, people. Hawaii and Alaska are faced with unique geographical challenges once one goes beyond the campus networks; they are the only two states that rely on access to submarine fiber for intra- and interstate connectivity. A further challenge is that Hawaii and Alaska are the only two states in the country without dark fiber connectivity to the national research networks (Internet2 and National LambdaRail). Rather, both states must rely on single waves (lambdas) made available through non-durable temporary arrangements. To connect Hawaii, PACMAN will utilize the 10Gbps Australian-provided link between UH-Manoa and the Pacific Northwest Gigapop in Seattle that has been supported by the NSF IRNC and NIH/ NCRR “Lariat” programs. Similarly, Alaska participants will be connected via the recent donation from GCI Alaska for use of a 10Gbps circuit between Fairbanks and the Pacific Northwest Gigapop in Seattle. The focus of PACMAN networking work will be to ensure adequate network performance between Alaska and Hawaii and full connectivity among all labs engaged in the research activities proposed as exemplar uses of the PACMAN cyberinfrastructure.

4.2 Results from Relevant Prior Support Alaska: Alaska has been an EPSCoR state since 2001 and is now on its third research infrastructure improvement (RII) award. Previous RII awards have served to increase research capacity in key scientific areas for Alaska, including cold regions infrastructure, high latitude contaminants, environmental physiology and population genetics. The current (Phase III) grant is funding a groundbreaking program applying an integrative approach to biology, physical science and social science to reach a deeper understanding of resilience and vulnerability in the North.

Alaska EPSCoR has made a significant impact on the research and development enterprise in Alaska. It has raised the profile of research at the University of Alaska (UA) by helping to build research development offices at each main campus, as well as creating new, effective cross-campus

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communication and coordination of research among both UA faculty and administrators. It has built connections to Alaska’s rural campuses by funding research and outreach activities there. It has raised the profile of research statewide by triggering creation of the State Committee on Research (SCoR), comprising leaders in academia, state government and the private sector.

Alaska EPSCoR has been an effective advocate for state funding for new research buildings, such as the Integrated Sciences Building at the University of Alaska Anchorage (UAA) and the proposed Bioscience building at the University of Alaska Fairbanks (UAF). Alaska EPSCoR also has used NSF funding directly to improve physical research infrastructure such as major equipment.

The bulk of Alaska’s NSF EPSCoR funding, however, has gone toward building research capacity among faculty and students. Since 2001, a total of 36 faculty members, working throughout the state of Alaska, have been hired or supported partially through Alaska EPSCoR funds. Faculty research also has been facilitated through numerous internal awards and other funding mechanisms, including 38 postdoctoral positions; 33 research seed grants; 28 grants for early-career researchers; 11 equipment grants; 11 faculty course buyouts; and four outreach grants.

This funding has been leveraged into millions more in research funds. Since 2001, Alaska EPSCoR-affiliated researchers have obtained more than $64 million in external funding and have published more than 400 refereed articles. As shown in Table 4.2.1, the first ten months of Phase III is keeping pace or improving in all of these key areas:

Table 4.2.1. Extramural Grant Funding to EPSCoR-Affiliated UA Faculty

PHASE FACULTY # OF AWARDS FUNDING TOTAL JOURNAL ARTICLES

1(01-04) 69 86 $26 million 116

2(04-07) 56 110 $29 million 175

3(07-5/08) 127 28 $9 million 42

Alaska EPSCoR has sponsored research by a significant number of graduate and undergraduate students, 191 graduate and 97 undergraduate fellowships in all. Numerous travel grants also have allowed students and faculty to disseminate their research and to network with peers.

In addition, Alaska EPSCoR maintains an active community outreach program. Its K-12 programs have involved 119 directly-funded K-12 students. Hundreds more have taken part in one or more of Alaska EPSCoR’s innovative outreach programs, which focus mostly on rural Alaska Natives. Furthermore, business outreach through the Alaska Small Business Innovation Research (SBIR) Bridge Grant program has resulted in millions of dollars in contracts to national agencies.

Alaska EPSCOR has maintained a commitment to diversity. Of its 288 undergraduate and graduate fellowships, for example, 139 have gone to women, 35 to Asians, 11 to Native Alaskans and 2 to African-Americans. And EPSCoR’s diversity has increased markedly over time: for example, of 27 2007-08 graduate fellows, 15 are women, 2 are Native Alaskans, 5 are Asian-Americans, 3 are disabled, 3 are first-generation students, and 6 are non-traditional students. Six of nine 2008 Early-Career Fellows are women or minorities. Eight of the 11 2007-08 faculty buyout recipients are women.

Hawaii: Hawaii has successfully used its first two EPSCoR awards to develop nationally competitive programs in the three interrelated disciplines of Evolutionary Genetics, Ecosystems Research and Information Technology for Environmental Research. This has been accomplished in part because HI EPSCoR has engaged and gained support from top-level University of Hawaii (UH) System administrators, State officials, and key business leaders through the development of the EPSCoR

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Statewide Committee. Strategic discussions focus on the statewide relevance and impact of ongoing research, especially in relation to economic development. An early step towards success was the EPSCoR-enabled hiring of 13 new faculty in these interdisciplinary areas that added to the state's intellectual infrastructure. Substantial investments were also made in the state’s institutional infrastructure (buildings, equipment, and administrative capacity). The dividends paid by these investments have been substantial. As illustrated in Table 4.2.1, EPSCoR-affiliated UH faculty have obtained more than $69M in extramural funding from 2003-2007. Substantial and consistent increases in the number of proposals submitted and the values of the awards during this period indicate a continuing trend toward the improving competitiveness of our program.

Table 4.2.2. Extramural Grant Funding to EPSCoR-Affiliated Faculty

YEAR PROPOSALS PROPOSALS SUCCESS AGGREGATE SUBMITTED AWARDED RATE VALUE

2003 39 29 74% $7,841,019

2004 65 48 74% $10,517,737

2005 57 32 56% $12,334,894

2006 91 71 78% $25,245,500

2007 85 40 47% (31 pending) $13,367,898

Researchers involved in the EPSCoR program have also established a solid base of scientific excellence and intellectual merit as documented by the publications that have been generated by the faculty, students and staff. Over 200 articles written by EPSCoR-affiliated faculty and their students were published in peer reviewed journals between 2003 and 2007; a similar number of technical reports and presentations were delivered to various government departments, non-government agencies, and professional societies. An equally important contribution resulting from past support is the students who have been trained by the EPSCoR scientists and educators who have contributed to the training of 363 students, 240 of whom were female. This cohort of students includes substantial numbers of individuals under-represented in S&T fields: 87 Native Hawaiian/Pacific Islander, 36 Filipino, 26 Hispanic, 10 Native American, and 2 African-American students.

This large and diverse body of knowledge now serves the general scientific community but also lays the foundation for Track 2. The EPSCoR programs in both Hawaii and Alaska have contributed to advancing our states’ goal of providing a well-trained, home-grown workforce. In order to build sustainability of Alaska’s and Hawaii's increasing research competitiveness we must continue to improve the state’s intellectual resources (in the form of advanced capabilities of faculty, and of Science, Technology, Engineering and Mathematics (STEM)-trained students injected into the state's workforce), infrastructural resources (e.g., environmental monitoring equipment and substantially enhanced and interconnected cybertechnology capabilities), and institutional cooperation (e.g., enhanced collaboration between campuses, and state agencies associated with STEM-based economic development) will contribute to the sustainability of Alaska’s and Hawaii's trajectory of increasing research competitiveness.

4.3 Cyberinfrastructure-enabled Science and Engineering Projects 4.3.1 Introduction The cyberinfrastructure we seek to build is composed of four elements: computing and storage hardware, networked sensors and remote sensing data, integrative software, and human expertise. The proposed cyberinfrastructure adds new capabilities building on existing UAF and UH expertise

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in supercomputing, sensor deployment in remote environments, satellite remote sensing, web services software development, and environmental and human systems modeling. The new hardware and improved sensor connectivity will be the foundation for cyberinfrastructure-enabled science and engineering in the extreme north and south environments of the westernmost United States.

Alaska and Hawaii are situated at the Northern and Southern margins of the North Pacific Ocean, respectively. They both, however, face particularly immense challenges with fresh water availability as climate variability continues to increase. Temperature over Alaska has risen by about 2-3oC since the mid-20th century [e.g. Whitfield 2003], along with which atmosphere circulation and weather patterns and associated amount and distribution of precipitation have changed [e.g. Zhang et al. 2004; 2008]. Life in the extreme, dry conditions of Interior and Northern Alaska seasonally depends upon near-surface waters perched on a rapidly thawing (Romanovsky et al., 1999; Osterkamp et al., 1999; Serreze et al., 2000) underlayment of permafrost. Many of Alaska’s rivers and streams are sourced in alpine and tidewater glaciers most of which are undergoing unprecedented retreat associated with increasing air temperatures (Hinzman et al, 2005; Molina, 2007). The Hawaiian Islands have also felt the effects of a changing climate. In Honolulu, Hawaii, the average temperature has increased 4.4°F over the last century, and precipitation has decreased approximately 20% over the last 90 years (Karl et al., 1996).

In both Alaska and Hawaii, social, economic, and environmental wellbeing depend critically on understanding future precipitation trends to guide effective water-use policies and collective social response. However, accurately projecting rainfall trends in a warming climate requires a fuller understanding and synthesis of several key factors:

1. Variability of and global-warming-forced changes in PDO, ENSO, and storm tracks. Situated at the north and south ends of the North Pacific Ocean, the interannual and decadal climate variability of Alaska and Hawaii are predominantly and interactively governed by two of the three most prominent global-scale leading modes: the Pacific Decadal Oscillation (PDO) and the El Nino-Southern Oscillation (ENSO) (e.g., Mantua and Hare 2002; Newman et al. 2003; L'Heureux et al. 2004). The tropical anomalous heating excited Pacific/North American teleconnection pattern (PNA) builds an atmospheric bridge linking tropical and mid- and high-latitude climate over the Pacific Ocean section (e.g., Alexander et al., 2002). The North Pacific Ocean is also a famous area where extra-tropical cyclonic storm energetically develops, and its northern portion lies in the dominant pathway of storm tracks (e.g., Zhang et al. 2004). The PDO and ENSO represent large scale climate and atmospheric circulation patterns, playing a modulating role in temporal and spatial structure of storm tracks, while cyclonic storms are major elements to redistribute water budget and bring rainfall. Therefore, complex interactions across different time scales of atmospheric circulations, atmosphere-ocean interface, and between low- and high-latitudes occur in this area. Meanwhile, along with the global warming forced by greenhouse gas emissions, substantial climate changes have been observed across the North Pacific Ocean and the adjacent Arctic Ocean, including an increase of frequency of ENSO, a decrease of amplitude of PDO, and a poleward shift in storm tracks (e.g., Timmermann et al., 1999; Meehl et al. 2000; Zhang et al., 2004; Zhang et al. 2008), which further complicate the above-mentioned interactions.

2. The roles of aerosols on cloud condensation. Hygroscopic aerosols injected into the troposphere increase the number and spectra of cloud condensation nuclei (CCN) and/or ice nuclei (IN). Under saturated conditions more CCN and IN compete for the excess water vapor leading to smaller, but more numerous cloud droplets and cloud-ice crystals (e.g. Rogers and

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Yau 1989; Ruddiman 2001) and resulting in enhanced cloud albedo (Twomey effect). Cloud life time increases because the smaller sizes diminish coalescence and riming, and decrease precipitation formation efficiency. Reduced droplet sizes also delay freezing which again minders the efficiency of precipitation formation. The role of IN, however, can also be towards an increase of precipitation formation efficiency. Due to the lower saturation vapor pressure over ice than water, ice crystals grow at the expense of cloud droplets in mixed phase clouds (Findeisen-Bergeron process).

3. The global GCM simulations and regional meso-scale model downscaling. The fully coupled global atmosphere-ocean general circulations model (GCM) is a fertile tool for simulating present-day and projecting future climate variability and change. Simulations by GCMs also provide a unique approach to get insight into particular physical processes for investigating and understanding mechanisms of climate variability and change, because many aspects and parameters cannot be directly observed in the real world. Tens of GCMs developed by major modeling centers over the world have been used for climate change assessment by IPCC (e.g., IPCC 2007). The global GCMs are important in this proposed project to detect and understand large scale climate variability and changes across the North Pacific Ocean and linking Alaska and Hawaii. However, their coarse resolution limits their capability to well capture synoptic and meso-scale weather systems and associated heterogeneous distributions of precipitations. For instance, the resolution of T85 was used in the CCSM for the IPCC simulations, which has 256 and 128 grid points in latitude and longitude, respectively. The grid spacing is about 1.41 degree. So, for better simulating and understanding local weather systems and associated rainfall over Alaska and Hawaii, regional meso-scale model will be employed, which can have a resolution as high as less than 10 km. Finer scale projections of future conditions are generally not directly available. However, local topography can have profound effects on climate at much finer scales, and almost all land management decisions are made at much finer scales. As policymakers continue to grapple with climate change issues there is a growing need for the development of model assessment methodologies (e.g., comparison between observations and simulations) as well as downscaling methodologies (e.g., empirical or dynamic) in order to make GCMs useful tools for regional climate change planning. The North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu) is doing such an effort for North America but only part of Alaska is included and Hawaii is completely out of the study domain. Thus this proposed activity will serve the high-resolution climate scenario needs for Alaska and Hawaii.

4. The current status of freshwater resources in Alaska and Hawaii. Alaska and Hawaii have very different environments but many of the same fresh water issues. Alaska has a very wide range of environments from coastal rain forest to Arctic desert. Hawaii’s environment ranges from dry and wet coastal lowlands to snow-covered volcanic peaks. One area that both Alaska and Hawaii have in common is our lack of data that would allow us to understand our freshwater resources, their sustainability, and their vulnerability to climate change. Although Alaska has more land area, more coastline, and more river miles than any other state, Alaska has only 26 active river gages, one quarter of the second largest state, Texas. Hawaii has 32 stations.Alaska has only 21 first order weather stations. First order stations are those maintained professionally by the NWS or the Federal Aviation Administration. There are also stations associated with the U.S. Cooperative Observing Network. Coop stations in Alaska number in the hundreds and have varying record lengths, varying degrees of instrumentation and reporting frequency. The coop network includes the U.S. Historical Climatology Network (USHCN). These are high-quality observations of monthly temperature and precipitation that have the least

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amount of non-climate biases, such as station moves and changes in instrumentation with good data homogeneity. There are 47 USHCN sites in Alaska. Weather and gaging stations are used to report precipitation, relative humidity, temperature, and other parameters critical to the understanding of water resources. These stations are also needed for forecasting, modeling, and groundtruthing remotely sensed data. The total number of professionally maintained river gages and precipitation gages are inadequate to understand the water resources in Alaska and Hawaii. An important opportunity to add to our capacity are stations maintained by scientists, state agencies, or non-governmental organization that do not currently report real time or are not connected to any sensor network. With a modest amount of funding, these additional stations will be upgraded to real-time reporting. These enhancements of the cyber-infrastructure that connects stations will increase our capacity to understand water resources at a fraction of the cost of installing new station infrastructure.

While our ability to monitor freshwater resources in Alaska and Hawaii is limited, the available evidence suggests that freshwater is being severely impacted by a warming climate. The freshwater that occurs in areas of thawing permafrost in Alaska, for example, is changing and in some cases resulting in a massive-scale drying of the environment (White et al, 2007). It is critical that we understand this transformation.

5. The role of social responses in feedbacks affecting the hydrological system. It is widely recognized that behaviors of individuals can grossly change the dynamics of ecosystems. Recently, the development of cybertools referred to as agent based models has allowed data to be incorporated into modeling architectures which reflect the emergent properties of coupled social ecological systems. Components can form a complex system in which any given state of the system is the result of the interactions and feedbacks between the smaller systems and system components (Waldrop 1992). Assessing social-hydrological systems is inherently difficult, as interactions between systems and components lead to non-linear results that are difficult to predict based solely on knowing the inputs involved (Holling 2001). In addition, behaviors in complex systems can operate at varied time and spatial scales. Social decisions and actions can occur relatively quickly and often occur at a community or local level, while environmental changes are often, though not always, slower and can affect much larger areas (Geist 2005; Forbes 1999; Alessa et al. 2008a).

4.3.2 Intellectual Merit The proposed 3-year project seeks to develop and demonstrate the capability of a Pacific Area Climate Monitoring and Analysis Network (PACMAN) is designed to yield a more reliable understanding of the impacts of climate warming on fresh water resources and communities in Alaska and Hawaii. PACMAN’s capabilities include: (1) real-time access to synoptic satellite data and in-situ sensor systems, deployed throughout Alaska and the Hawaiian Islands; (2) integration of these datasets with archival data from existing research databases and drawn from sophisticated web-harvesting capabilities; (3) redundant archival of all data and information products, as well as; (4) real-time distributed simulation through a modeling and integration core involving supercomputing centers in Alaska and Hawaii, together with; (5) a collaborative framework for visualization and multi-dimensional mapping; (6) development of and reliance upon open-source web tools; (7) development of an agent-based framework for assessing societal impacts, and; (8) open distribution to researchers and policy makers in Alaska, Hawaii, and around the world through the Internet.

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The proposed core cyberinfrastructure will enable research focused on measuring and understanding the processes and dynamics that influence immediate and long-term rainfall characteristics that sustain the social, cultural, and environmental wellbeing of Alaska and Hawaii. This project does not propose new research per se but rather develops an integrated cyber-capability which will enable diverse groups of practitioners to utilize information in ways that are not currently possible. This will allow the research community to better understand those systems which influence precipitation from the molecular to global scale, and to understand how they are linked and interact as a basis for evaluating the effects of climate change on water resources.

The integration of innovative sensor networks and remotely sensed data is essential to the understanding and interpretation of the North-South Pacific corridor from Alaska to Hawaii. This corridor is the United States’ avant garde for weather and climate and affects millions of residents and users alike. The corridor from Alaska to Hawaii captures the intersection of three of the four major climate modes: the Arctic Oscillation (AO), PDO, and ENSO. Each climate phenomenon impacts the precipitation patterns, frequency, intensity, and form on the west coast of the contiguous United States.

Sensor networks that include measurements of precipitation, temperature, atmospheric radiation, river stage, or CCN are maintained in Alaska and Hawaii. Many report results in real time but few are integrated thus greatly reducing their capacity to inform research and management activities. The stations are monitored and maintained by many different groups of scientists or agencies and possess different levels of sophistication. While the stations are useful to the scientists who run them, they are of limited value to the scientific community in general without integration and connections that transcend projects and project specific needs. A cyber-network of all these stations would ensure that the stations are abiding by authorized protocols for data validation and formatting and are integrated and useable for deriving regional scale information. These data then become useful for validating and heightening the value of synoptic data from polar orbiting satellites which can, in turn, spatially extend important climate information across the North Pacific. A novel addition to these networks will be the development of a human sensor array (discussed below) built upon the highly successful NSF-funded Bering Sea Subnetwork (http://bssn.net) which establishes a distributed network of human observers capable of systematically collecting observations of environmental change. By integrating these sensor networks and combining them with satellite derived information, PACMAN will be much greater than the sum of its parts (Figure 4.3.1).

4.3.2a Leveraging Existing Capabilities

This effort expands upon a long-standing strategic partnership linking Alaska and Hawaii strengthened recently through the creation of a Center of Excellence in Maritime, Island, and

Figure 4.3.1. Nested scales of observation in PACMAN from remote satellite observing at global scales, airborne observing at regional scales and buoy/instrument-based marine terrestrial networks. The implementation of a human sensor array layer (bottom wedge) adds a scale of resolution that works synergistically with other sensor data to better resolve the heterogeneity of change.

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Extreme Environment Security (CIMES; http://cimes.hawaii.edu/partners.htm) funded through the Department of Homeland Security (DHS). CIMES assembles expertise and infrastructure for monitoring and heterogeneous sensor integration that will provide momentum and sustainability to the current proposal. PACMAN will also heavily leverage previous investments by various state and federal sources including NSF EPSCoR in both Alaska and Hawaii. In Alaska, NSF has supported an EPSCOR program since 2001 and is currently funding the program at $3 million a year. Alaska EPSCoR’s current configuration dovetails well with the proposed PACMAN project: Like PACMAN, EPSCoR is focused on using integrative frameworks, techniques and technology to examine climate variability and change. Alaska EPSCoR also is focused specifically on ecological data collection and modeling.

Alaska EPSCoR’s current research focus is on integrative science. Biology, physical science and social science components are all linked together in an integration core, in which research results are synthesized into real-world models. EPSCoR’s integration efforts are currently concentrated on two platforms: Social-Ecological Hotspots (SES) Mapping, and Forecasting Environmental Resilience for Arctic Landscapes (FERAL; http://ram.uaa.alaska.edu/Feral.html). Both platforms entail the use of complex datasets to create focused integrative geographic models in a manner similar to that which would be employed by PACMAN.

In addition to these thematic and structural similarities, in some instances water systems fall directly under Alaska EPSCoR’s purview: co-PI Lil Alessa developed the Arctic Water Sources Vulnerability Index, a composite index used to evaluate Alaska communities’ access to fresh water. Integrating this platform into PACMAN’s cyberinfrastructure will provide a valuable link between the climatic trends observed in PACMAN and the people which they will affect.

Alaska EPSCoR also supports a number of education and outreach programs which can partner with PACMAN to increase the involvement of Alaska and Hawaii residents in the research and its results. Leveraging EPSCoR’s existing infrastructure in this area will enable PACMAN to create a more effective outreach program and make a direct connection to Alaskans, especially the rural residents most likely to be affected by changes in water availability.

In Hawaii, this effort will leverage previous investment by NSF EPSCoR at the University of Hawaii and its industry Partner, InteleSense Technologies, which resulted in the creation of an advanced platform integrating the use of wireless sensor technologies for regional scale environmental monitoring, Grid computing with 3D geospatial data visualization / exploration, and a secured internet-based portal user interface (Kido et al. 2008). This cyberinfrastructure has significant power to cross-connect among technologies / scientific disciplines and thus has the core capability necessary to address the challenges presented by climate change on water resources in coupled human-environment systems.

In addition, satellite remote sensing data is captured and distributed in near-real-time at both UAF and UH, and through partnerships with NASA, NOAA and the DoD. Satellite remote sensing data is the most effective means to extend site-specific data into a broader, synoptic context. Both the Alaska landmass and the Pacific Ocean transect between Alaska and Hawaii is very sparsely monitored with in-situ instruments. In order to draw broad spatial inferences over these regions, in-situ sensor data will be integrated with data from satellites, including imagery, wind, cloud, atmospheric moisture, and radiation products, and atmospheric soundings through the Intelesense integrated platform to provide this data, as well as distributed simulation, visualization, and collaboration capabilities to researchers in Alaska, Hawaii, and collaborators around the globe.

The UAF Geographic Information Network of Alaska (GINA: http://gina.alaska.edu) has longstanding collaborations in place with NOAA. In addition to operating two satellite ground receiving station on

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campus, GINA also maintains a dedicated OC-3 data line to the NOAA-NESDIS Fairbanks Command and Data Acquisition Station (FCDAS; http://www.fcdas.noaa.gov/)—NOAA’s main reception facility for its constellation of polar orbiting satellite. Data from hundreds of satellite passes per day received by NOAA in both Fairbanks and Barrow is exchanged in near-real time between the two facilities. These satellite data are processed to images and other information products in near real time and provided to a broad spectrum of operational and emergency response entities. Of particular note are the specialized products produced for the NOAA National Weather Service’s Alaska Region Office. The mid and low latitudes are well covered by geostationary satellites orbiting over the equator. In partnership, GINA, FCDAS, and NOAA scientists produce analogous image, cloud, water vapor, and radiance temperature products for the high latitudes using polar orbiting satellites operated by NOAA, NASA, and the DoD enhancing forecasts, emergency response, and science for the North Pacific and Arctic Oceans. GINA also assembles mosaics and animations of the broad region visible from polar orbiting satellite data captured in Fairbanks giving scientists and forecasters a dynamic, synoptic view over the Pole.

The primary satellites used for production of environmental information products are the NOAA POES, NASA Terra and Aqua, and Air Force DMSP satellites. Hundreds of products are generated each day in near real time. A few that are relevant to this proposal’s ocean and atmospheric emphasis include: natural color imagery, ocean color, sea surface temperature, cloud mask, cloud phase, aerosol optical depth, land surface temperature, cloud top pressure, and total precipitable water vapor.

The UAF IARC JAXA Information System (IJIS) is a core element contributing to PACMAN’s climate data and information needs over high latitudes. In turn, PACMAN will enable IARC to better meet its goal of fostering arctic research in an international setting to advance understanding, preparation for, and adaption to the pan-arctic impacts of climate change by extending capability and complementing the other computing services that exist through the consortium. Furthermore, as IARC’s mission expands to include climate impacts, planning, and adaptation, computational enhancements to IJIS that enable model development, testing and validation will be essential. The datasets and analysis tools required for model validation and for synthesis of Arctic data add to the need for a comprehensive Arctic data and information activity. The upgrades proposed herein would permit analyses of massive data sets such as the Arctic reanalysis and observing system experiments; and other data synthesis activities. Both basic process studies and complex synthesis of the Arctic system require appropriate computational facilities that permit integration of disparate datasets and rigorous numerical analyses. High-volume remote sensing datasets are essential for such activities.These advances will also support development, hosting and distribution of the Arctic System Model (ASM)and model components that strengthen our understanding of the interconnected components of the regional system. The initial core model will include atmosphere, ocean, sea ice, and selected land components and will be constructed in a manner that allows investigators to add or exchange components.

While IARC can contribute to the development and testing of some ASM components, the expertise required to develop a fully coupled system model clearly extends beyond a single institution and into the broader community. Collaborations with researchers in Hawaii will enable better simulations of the North Pacific circulation and the Aleutian Low Pressure System, both of which are critically important in affecting weather in Alaska, Hawaii and the western U.S.

The Scenarios Network for Alaska Planning (SNAP; http://www.snap.uaf.edu/ ) is a collaborative organization linking the University of Alaska, state, federal, and local agencies, and NGOs whose mission is to provide timely access to management-relevant scenarios of future conditions in Alaska. The primary products of the network are (1) datasets and maps projecting future conditions for

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selected variables, and (2) rules and models that develop these projections, based on historical conditions and trends. These scenarios are developed by using high resolution climate data such as Prism (e.g., http://www.wcc.nrcs.usda.gov/climate/prism.html) to downscale information from various relevant GCMs and are always accompanied by metadata that clearly describe the methods and assumptions underlying the projections. Network participants have the responsibility of interpreting these scenarios objectively to potential users. These products also serve to communicate information and assumptions among researchers and to identify knowledge and data gaps requiring further research.

4.3.2b Cyberinfrastructure as the “Integrator of Data and Disciplines”

Adequately addressing the complex effects of climate change on water resources will require the development of a new generation of cyber-tools and services for data discovery and management, fusion and integration, analyses and visualization. Rapid advances in technology such as smart sensor networks used in combination with high-resolution imagery will contribute to improving environmental data quantity and quality; however, the new cybertechnology must accommodate massive amounts of raw data that are produced daily by scientists and engineers. This need is expected to grow as further advances in sensors and sensor networks, computational modeling and simulation and automated data acquisition systems continue to improve and are directed at studying climate change effects. This will necessitate collaboration across disciplinary boundaries with the potential of developing entirely new methodologies, experiential design, and even new fields of knowledge. The establishment of a cyberenvironment that fosters this type of transdisciplinary research is mandatory in order to understand complex climate change effects on human-environment systems and their global interactions. In addition, these new cyber-enabling technologies must be readily available, open-sourced, user-friendly, and internet-based in order cross “boundaries” to connect science with decision making so that regulatory adjustments can be implemented quickly and effectively with input from local stakeholders.

The InteleSense-based environmental monitoring component of PACMAN consists of dedicated data acquisition devices which are able to interface generically with individual or groups of sensors which could be deployed to form a “smart” distributed mesh sensor network. Such a mesh network is able to relay data packets across long distances to a remote base station with units functioning as repeaters and/or gateways depending on location in the network. At the base station, sensor data can be uplinked over the internet to a server where other data sources were integrated and clients given access to sensor data processed for viewing in charts or tables using a secure web–based open-source geospatial visualizer. The current system utilizes a number of software-based “agents and crawlers” which obtain information from Internet-based sources, parses this information, and adds it to the database. Currently, Inteleview integrates over 315,000 layers of data and will have access to close to a million layers by the middle of the 2009 calendar year including geospatial imagery (e.g. Ikonos, Quickbird, Landsat, LIDAR, USGS maps, etc.) and information on weather (e.g. real-time cloud cover, NWS warnings, etc.), oceans (e.g. NOAA buoy data, shipping routes, reefs, etc.), and the atmosphere (e.g. worldwide CO2, heat flux, atmospheric carbon, etc.). All of this information is integrated, organized and viewable by end-users geospatially for exploration in 3D on a global scale. The goal is to provide an easily accessible global integrated georepository of all information relevant to anyplace on the planet.

In order to handle large amounts of climatic and environmental data and to provide a mechanism to integrate data from distant sources, the Intelesense Grid was developed- an ultra-reliable grid-based extendable computing cluster whose parent nodes are housed in an award-winning server facility in Silicon Valley with redundant power and high-bandwidth network connections. This state-of-the-art system integrates grid computing capability into the cyberinfrastructure platform so that data from

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many sources can be seamlessly linked into a federated set of information resources and middleware. This facilitates resources sharing, coordination, management and processing using the latest in emerging grid-based technologies. The grid infrastructure handles the metadata, system catalogs, and data store, providing authenticated user access to information and tools. As part of this proposal, this grid-based distributed computing cluster will be extended to integrate compute and storage servers at Alaska and Hawaii to form a seamless, interoperating, cohesive system for data sharing, analysis, and visualization.

Portals may be readily customized to satisfy specific user requirements and interface with a “data sharing engine” that outputs directly to a 3D visualizer via a set of linked computer servers. The 3D data visualization and exploration engine builds upon InteleView (http://www.intelesense.net/) and GINA’s Swathviewer (http://sv.gina.alaska.edu/) open-source, thin-client applications that may be downloaded for free from the respective websites. PACMAN portals will be designed with a variety of collaborative features to support a distributed community of interest, allowing researchers from any location to work together in a shared online space. PACMAN portals also provide for data and imagery storage, upload/download tools, and directly interface with Google Earth and ESRI ARCGIS-based GIS files to directly accept KML/KMZ files, ESRI shape files, Geotiffs, and other data for viewing and exploring over 3D terrain. This feature thus makes possible the integration of Google Earth and ESRI GIS maps seamlessly with the thousands of geospatial information layers currently available on InteleView. In addition, Portals provide a “next generation” Internet-based environment for serving all kinds of data to the research community and public and thus empower people to collaborate and share data from anywhere.

An important element of PACMAN’s integration and modeling core is UA’s Forecasting Environmental Resilience in Arctic Landscapes (FERAL) developed during Alaska EPSCoR’s Phase III. This agent-based approach allows individuals or other social units (i.e., agents) to make decisions based on evolving social and environmental components that together makeup the environmental setting addressed. FERAL captures human-water dynamics at multiple scales, applying the Repast Simphony (Repast S) architecture as its underlying software (North et al., 2005). FERAL is able to address interacting systems and components over varied spatial and behavioral scales. In a social-ecological modeling approach, different and appropriate models are selected for use based on their utility to address specific behavioral phenomena (e.g., water use, hydrological evolution, etc.). In other words, an approach that couples multiple types of models (i.e., 1-4 in Section 4.3 above) is employed in order to capture the best available behavioral dynamics relevant for the scales addressed. This can allow feedbacks between the systems to be examined with the emergent actions of these feedbacks evolving the overall system.

4.3.2c Goals and Objectives of this Proposal:

This proposal seeks to develop and demonstrate the utility of a PACMAN, an infrastructure for integrating in-situ sensor systems deployed across large areas of rugged terrain across Arctic and tropical climates, together with existing satellite and aerial imagery and archival data from existing research databases, to enable real-time distributed simulation from supercomputing capabilities in Alaska and Hawaii, and provided in a collaborative visualization framework to researchers in Alaska, Hawaii, and around the world. Generalized data flow through PACMAN is shown in Figure 4.3.2.

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Figure 4.3.2: PACMAN Data Flow:

Deployed Sensor Networks

Alaska/Hawaii

Deployed Sensor Networks

Alaska/Hawaii

Real-Time SatelliteParameters

Alaska/Hawaii

Real-Time SatelliteParameters

Alaska/Hawaii

Distributed Simulation/Modeling Computation/ StorageARSC, MHPCC, etc.

Distributed Simulation/Modeling Computation/ StorageARSC, MHPCC, etc.

Collaborative visualization/portalsAlaska/Hawaii

Collaborative visualization/portalsAlaska/Hawaii

Other DataArchive/Web Harvested

Alaska/Hawaii

Other DataArchive/Web Harvested

Alaska/Hawaii

Inte

grat

ion

&

Mo

delin

g C

ore

Data IntegrationInteleSense GridData IntegrationInteleSense Grid

Task

1

Task

2

Task

3 Internet

Task 1: Data Acquisition and Integration:

a. Integrate existing sensor networks in Alaska and Hawaii using telemetry and on-line reporting.The cyberinfrastructure described above will receive data from existing, deployed sensor networks from universities, state, and federal agencies, and private industry. From our previous work, sensor networks comprising weather, water quality and flow, imagery, and other sensors have been previously deployed across the Hawaiian Islands and similar sensor networks exist across Alaska. Many of these stations transmit their data, but some currently perform internal logging. These stations would be augmented to provide real-time data and be integrated with the system above.

Table 4.3.1 Example Integrated Data Sources

Category Data Integrated

InteleNet web harvested Real-time weather, water, air, imagery/video, biotelemetry, tracking

Surface Imagery Landsat visible & vegetation, USGS maps and urban area Ikonos, Quickbird, daily whole-Earth MODIS data, real-time NOAA, MODIS through direct broadcast.

Atmospheric NOAA CO2 sensor network; volcanic aerosols; arctic haze; dust, PM10,PM2.5

Weather Real-time cloud cover (NOAA GOES, POES; MODIS)

Ocean NOAA Ocean Depth data OGS WMS, MODIS, AVHRR, SeaWIFS SST

Geographic Placenames, political boundaries, military bases, population density, languages, etc.

Aerial Quickbird imagery, ResourceMapping LIDAR/imagery, NOAA hurricane imagery

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b. Integrate in situ data and remotely sensed data. The proposed cyberinfrastructure will be designed to integrate localized, in-situ data into broader context through the use of synoptic satellite observations. This task requires assembling source data sets of disparate types and normalizing them into shared, widely adopted open standards for use in applications such as models and visualization. The Open Geospatial Consortium (OGC) SensorML open standard, coupled to other OGC mapping, feature, and coverage standards will be the basis of this effort.

Relevant datasets currently available to this project include (but are not limited to) those shown below in Table 4.3.1.

The in situ data emerging from this infrastructure will be sufficient for the validation of parameters derived from satellite sources, such as surface temperature, column water abundance, etc. Satellite remote sensing measurements of these parameters will provide important, spatially and temporally resolved, quantified and validated, data for use in atmospheric and hydrological models.

Thus, the integrated suite of ground-based measurements and satellite remote sensing data collected, unified and dispersed in this effort provide vital data for assimilation into atmospheric and hydrologic models, such as the Weather Research & Forecasting (WRF) model, which will allow the prediction of changes in the hydrological cycles over Hawaii, Alaska and the North Pacific. Therefore, modeling experts are needed to provide guidance on the locations and types of measurements needed to conduct the atmospheric and hydrological modeling efforts this project would support. These experts would identify the needed form of the data emerging from this infrastructure to ensure its use by a maximum number of users.

In Year 1 additional stations will be upgraded to send real-time information by telemetry or cellular capability. Year 2 will continue telemetry upgrades and address data integration to produce a single network of stations with appropriate metadata protocols, validation approaches, etc. Year 3 will complete these activities. �

Task 2: Simulation and Distributed Computation:

Subtask 2.a: Create an enhanced, open, supercomputing-quality storage and analysis facility for UA and UH researchers. PACMAN’s modeling and integration core will benefit from affiliation with ARSC and MHPCC and is built around the expertise and capability of existing information systems and related expertise described in Section 4.3.2a.

A high-capacity disk storage system consisting of 1 PB of spinning disk and 1 PB of tape will be deployed sequentially using the following multi-year strategy:

0.5 petabyte (PB) disk storage during year 1;

1PB Sun StorageTek STK3500 tape silo during year 2, and;

An additional 1PB disk storage in year 3.

These capabilities will be augmented by three new clusters located at UAF:

A 640 processor node cluster (quad core) yielding 6.8 TFLOPs will be purchased during year 1.

An additional 960 node (six core) cluster will yield 10 TFLOPs assembled in year 2, and,

An additional 1280 node (twelve core; 13TFLOPs) cluster will be brought online in the third year,

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This strategy yields a total of 29.8 TFLOPs of new computing power by end of project. System administrators at UAF will be funded through this project to support these systems. They will be backstopped by ARSC’s existing help desk and technical support staff.

Subtask 2.b: Create the software and personnel expertise to better exploit existing in-situ sensor data, remotely sensed data, and model output. This effort will build on existing open standards work with SensorML and the Semantic Web and existing expertise at UA and UH regarding data handling and processing and implementation of open standards data formats.

Subtask 2.c: Integrate with data acquisition infrastructure. Under this subtask we would provide all data sources (sensors, imagery, database information, etc) from the integrated data acquisition system directly to the supercomputing centers to enable real-time simulation to be performed. In addition, the output from these simulations would be available in real-time through the visualization portal created for this project.

Subtask 2.d: Use Cases and Applications:

Model validation: Data consolidated and normalized through open standards protocols will be used to initialize and validate models developed through other projects.

User support: The Sensor Web data will be exploitable by users through toolkits fielded by this project that simplify common needs such as database deployment, grid computing, visualization, file sharing, and data backup and security.

Application workflows: Building on the Sensor Web data and other open standards data sets, researchers will be given access to workflow toolkits that allow them to connect data objects and processing toolsets together in an object-oriented graphical environment. Output from these workflows will be easily importable into visualization and analysis tools.

Cloud dynamics: In-situ sensor data coupled to satellite data and model output will enable new and innovative cloud dynamics modeling to be performed under separately funded projects. The unique capabilities of the Sensor Web available to the researchers will provide new opportunities and capabilities for research that impacts Alaska, Hawaii, and the Pacific.

Task 3: Worldwide collaborative visualization – portal development

Grid-based infrastructures such as the GEOscience Network (GEON) (e.g. Nambiar et al. 2006) are necessary to integrate the diverse datasets required to understand, integrate, and interpret the complex processes of earth systems. Portals establish a dynamic framework for interoperability within Grid infrastructures providing “…secure, customizable, personalizable, integrated access to dynamic content from a variety of sources, in a variety of source formats, wherever needed” (Smith 2004). Operationally, portals acts as “gateways” between users and various high-level services with “portlets”, usually built in Java, functioning as self-contained pluggable user interface links to those services (Chohan 2005). Portals and portlets constructed in this project will connect users through authentication engines to data resources managed and processed by the InteleSense Grid to allow researchers to visualize all integrated data from this project (including sensor data, satellite and aerial imagery, archival database information, etc.). Real-time simulation of results will be viewable through Java InteleView applets embedded within portals which will allow for interactive exploration of these data that may be integrated with distributed datasets from around the globe.

Task 4: Demonstration/Application

In order to demonstrate the entire cyberinfrastructure in a specific use case, a demonstration objective will be to detect variability of and changes in atmospheric circulation and weather patterns

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over Alaska and Hawaii, and their linkage across the North Pacific Ocean, and to identify underlying interactive physical processes across synoptic and climate scales and between low- and high-latitudes.

To achieve this scientific objective and consider the large amount of computational resources and data storage needed for this study, we will conduct synthetic multi-scale study across the North Pacific Ocean with an extension to the adjacent Arctic Ocean and tropical Pacific Ocean, and integrates satellite remote sensing data, in situ observations, and large-scale general circulation and meso-scale weather model simulations with the proposed improvement of cyberinfrastructure.

Subtask 4.1: Data collection and archive. The primary data sets for atmospheric circulation and storm track analysis include the gridded National Centers for Environmental Prediction (NCEP) –National Center for Atmospheric Research (NCAR) reanalysis data and ERA-40, which are products from global assimilation systems and assume dynamics and thermodynamic consistency. However, the coarse resolution of these reanalysis data is incapable to resolve fine resolution weather features and physical processes, and indirect parameters related to cloud, water and energy budgets generally lack accuracy. So, we will also collect in-situ observations and satellite remote sensing data covering Alaska, Hawaii and adjacent area. The in-situ observations and satellite data can also be used for assimilation with meso-scale model simulations and model result validation.

Subtask 4.2: Statistic and diagnostic analyses. Various advanced statistical methods, e.g., EOF analysis, SVD analysis, MTM spectral analysis, will be employed to detect interannual variability and long-term changes of atmospheric circulation patterns and storm track patterns. Diagnostic analysis of cloud, water and energy budgets will be conducted to understand the role of the interactions between storm and general circulation and between low and high latitude climate.

Subtask 4.3: Storm identification and tracking algorithm. To understand how storm track shapes and impacts atmospheric circulation and weather patterns over Alaska, Hawaii and their linkage across the North Pacific Ocean, we will further improve an storm identification and tracking algorithm which we have recently developed (Zhang et al. 2004). The improvement will be focused on the identification of the storm influential area, within which diagnostic analysis can be conducted to investigate interactions between storm and general circulations.

Subtask 4.4: Large-scale general circulation/climate model simulations. Simulations by large-scale general circulation/climate models helps to provide the parameters which cannot be directly observed or lack accuracy in reanalysis data. Model sensitivity experiments can also help to isolate or identify roles of particular processes in the detected circulation and weather pattern variability and change. We will employ multi-model and multi-model-ensemble simulation approach to enhance robustness of modeling results. The models to be used are the NCAR CCSM and MPI-M ECHAM5, which have been implemented and tested on ARSC supercomputers for various studies. A relatively high resolution of T85 is favored for the atmospheric component model in the NCAR CCSM, which has 256 and 128 grid points in latitude and longitude. A higher resolution of T106 will be used in the atmospheric component model in the MPI-M ECHAM5, which has 320 and 160 grid points zonally and meridionally. The curvilinear coordinator is employed in the ocean and sea ice component models in the both NCAR CCSM and MPI-M ECHAM5 to avoid singularity of the North Pole, which can have resolutions as high as about 10 km.

Subtask 4.5: Regional meso-scale model downscaling. The regional meso-scale model WRF will be employed to refine the picture of atmospheric circulation and weather pattern changes in Alaska and Hawaii at a resolution of 10-20 km with about 45 height levels. This will include evaluation of impacts on surface air temperature, precipitation, wind field, and ocean/sea ice properties, as well as

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extreme events and water and energy budgets. Comparison and correlation analysis between Alaska and Hawaii will be conducted.

4.3.2d Knowledge Systems for Harnessing Cyberinfrastructure in Water Resource Management

In order effectively deal with ‘real world’ challenges from climate change impacts on water resources, “knowledge systems” (Cash et al.) must be developed that can harness large quantities of transdisciplinary (Max-Neef 2005) data for processing in the cyberinfrastructure platform. Detection and monitoring systems providing data to the cyberinfrastructure from deployed sensors, for example, acquire, organize and store data to determine patterns for the purpose of mounting appropriate responses (Balasubramaniyan et al 1997). Human observing networks constructed as a distributed array of human sensors in local communities are also valuable being able to observe their environments on a regular basis and report in rich detail on change and response. Using systematic and rigorous design principles, they are capable of detecting events that indicate that the system is operating unusually (Dasgupta and Attoch-Okine 1997). In addition, the collective memory of humans in intimate resource roles holds information about environmental variability that extends beyond the knowledge being acquired by traditional science approaches. This knowledge makes some residents, and often, indigenous peoples, capable of observing changes with a level of precision that no other sensors can replicate. Moreover, sub-populations of resource intimate residents, in particular those who have had extensive land-schooling (e.g., elders, hunters, fishermen, taro farmers), often retain long memories of environmental variability and change (Alessa et al 2007). Humans as sensors, then, are a valid independent source of information that, when appropriate methods of data collection are used, are capable of providing insight to the questions of system change, social impacts and recursive feedbacks to biophysical environments. Understanding how to develop appropriate adaptation strategies to change is especially critical particularly related to water resources. Processes of hydrological change are heterogeneous and this heterogeneity is more pronounced at finer scales (Jenssen 2006). Successful responses to change are dependent on understanding how change is occurring at local scales. Key pre-requisites for adaptation include the need for understanding the trajectories and rates of change as well as the impediments that potentially limit response (Adger 1999). Thus, the need for reliable and meaningful community monitoring networks that document change at fine scales (Schuler 1994, Provan and Milward 2001) will become critical as climate change scenarios unfold. Table 4.3.2 outlines the systematic approach by which human derived data will be structured for compatibility with satellite and sensor data.

4.3.2e Local and Indigenous Knowledge Network Development in Alaska and Hawaii

Parallel efforts are being undertaken in Alaska and Hawaii to develop protocols and technologies to incorporate indigenous knowledge into management systems. For example, the Alaska Center for Climate Assessment and Policy is collaborating with the NOAA-funded Regional Integrated Sciences and Assessment Programs (http://www.climate.noaa.gov/cpo_pa/risa/) in the Pacific Islands and the American Southwest to build a local and indigenous climate knowledge network with specific focus on drought vulnerability and adaptation. In addition, UA’s Bering Sea Subnetwork (BSSN) has developed systematic protocols for the development of large-scale environmental change observing networks focused specifically on water and water associated resources (http://bssn.net). These projects closely fit the Alaska EPSCoR theme of building resilience within integrated social-ecological systems in a rapidly changing North. The goals of this project are to:1) build collaborative strength in the area of local knowledge and indigenous approaches to hydrological change and adaptation; 2) document local and indigenous coping strategies and scientific information needs

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related to drought, water availability, and water quality; 3) strengthen cross-regional communication and shared learning; and 4) build capacity for cross-cultural communication between local indigenous resource decision-makers and the climate scientists.

Table�4.3.2.�Summary�of�the�main�scientific�approaches�and�methodologies�that�will�be�used�to�integrate�human�observations�with�other�sensor�data�in�PACMAN.�

Approach� Methodology Data�Areas�

Survey�

Provides�systematic�qualitative�data�

Semi�structured�interviews�administered�by�trained�local�coordinators;�Cognitive�Interviewing�used�for�testing;�Key�respondent�and�Elders�unstructured�interviews�

Tabulated�Survey�Data�

Summaries�

Spatial�Synthesis:�Assembly�of�information�in�GIS�

Integrates�data�from�survey�with�other�sensor�data�using�SES�hotspots�methodology�

�

Community�derived�and�biophysical�Western�science�data�compiled�in�ArcGIS�as�regional�composite�with�local�scale�resolution�to�tabular�and�qualitative�data�or�data�and�narrative�

Interactive�GIS�map�with�accessible�Graphic�User�Interface�(GUI)�showing�regional�observations�

With�local�scale�data�as�embedded�attributes�

Development�of�Rule�Based�Algorithms�for�Agent�Based�Models�

Provides�accessible�and�adaptive�insight�into�consequences�of�change�

Combine�Delphi�methodology�(involving�community�experts)�with�agent�rule�development�

In the Kahalu’u, Kona study site on Hawaii island (description below), The Kohala Center, Redlands Institute and the Edith Kanaka’ole Foundation are developing a prototype for an “ethnoscience atlas”, the core component of a “digital geocollaboratory” that are bringing together indigenous Hawaiian and Western scientific knowledge to challenge each others views about the natural world in an attempt to sustainably manage precious natural resources in the region such as water. While complementarities between Hawaiian and Western ways of knowing were identified, knowledge systems were found to radically differ, but coexist in place and time. Through development of ‘virtual environments’ as advanced elements of cyberinfrastructure, it is thought that indigenous and Western scholars may traverse each other’s worlds from a common geographic point of entry, allowing them to experience alternative worldviews and insight into how knowledge is constructed. Building this prototype will lead to the full realization of the potential of the geocollaboratory, fostering transdisciplinary interaction, research, and learning.

The cross-fertilization of ideas made possible by the Alaska – Hawaii collaboration in this project will lead to innovative cyberinfrastructure relevant to addressing water resource management needs by incorporating both Western and indigenous knowledge systems and a holistic view of the coupled human-environment system. This will be fostered through at least one exchange visit of Western / indigenous scholars between Alaska and Hawaii as well as the use of extensive videoconferencing to foster collaboration.

Regional-scale assessment tools have been used in Alaska and Hawaii to evaluate the “health and integrity” (Haskell et al. 1992) of human-environment systems and will provide additional tools and

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data sources for cyberinfrastructure developed in the Project. The Arctic Water Resources Vulnerability Index (AWRVI; http://ram.uaa.alaska.edu/AWRVI.htm) is a composite water index used to evaluate the well-being of Arctic communities with respect to fresh water (Alessa et al., 2008b). It integrates a range of existing and community-specific water-related data and information into a series of indicators to give an overall score. AWRVI provides a holistic profile of a community’s key water issues, allowing for intra-community and inter-community comparison and analysis. Communities can use it to identify where strengths and weaknesses exist in water management. Hawaii’s “Watershed Health Index” (WHI) (Kido 2006) utilizes GIS-based land use data for each of the state’s 571 delineated watersheds to evaluate “health” based upon levels of human impact and the related Stream “Index of Biological Integrity (Kido 2001) which utilizes a set of standardized metrics to evaluate levels of native species presence along stream continua from “mountain-to-sea”.

These tools will be integrated into cyberinfrastructure to assess the resilience and vulnerability of people in the Arctic and Hawaii to changes in water resources. Freshwater is critical to the sustainability of humans in the Arctic and in isolated Pacific islands. People face uncertainty in their day-to-day lives due to environmental changes. The need for communities to determine their vulnerability to changes in freshwater resources is becoming more urgent. The Arctic and Hawaii present a challenging set of factors: very remote communities, high energy costs, a rapidly changing climate, and an often limited abundance of fresh water. The AWRVI and WHI provide the opportunity to see the ‘big picture’ of the water that communities rely on is important to making good decisions. It provides a framework to map and assess water resources, use values and potential vulnerabilities under certain conditions.

4.3.3 Broader Impacts In addition to being an effective research tool, PACMAN is designed to enhance the abilities of Alaskan and Hawaiian communities to understand, plan for, and respond to changing climate conditions – and establish effective policies that build resilience in fresh water resource management. The current proposal will build upon the successes of previous Alaska and Hawaii EPSCoR RII educational and public outreach plans, as well as the highly acclaimed Pacific and Alaska Regional Integrated Science and Assessment (RISA) programs funded through NOAA.

In addition, PACMAN will incorporate capabilities that are relevant to addressing other ‘real-world’ issues that most directly affect the coupled human-environment systems of the North Pacific, and will provide data and information products that are appropriate for, and capable of advancing a broad suite of cultural, economic, educational, environmental and cultural missions across Alaska and Hawaii. In order to ensure that this important component of PACMAN’s mission is accomplished, the consortium will establish an External Advisory Group EAC, consisting of members drawn from potential end-user groups such land holders, native Alaskan and Hawaiian groups, NGOs, K-12 schools, and government agencies. The PACMAN consortium will look to the EAG for guidance on such issues as research prioritization, information products, appropriate data format designs, delivery characteristics, and other matters that will optimize the societal benefits of PACMAN. Thedevelopment of PACMAN vis-à-vis partnering with the EAC will enable researchers to better model social-ecological system dynamics in a manner that is highly transferable to other locales.

Deployment of PACMAN will provide broad and measurable impacts in the following specific areas:

Sustainability: Intensifying human impacts to watershed catchments coupled with the cascading effects of climate change seriously threaten the health and integrity of water resources in coupled human-environment systems globally. The InteleSense-based cyberinfrastructure invented in

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previous EPSCoR RIIs and further developed in this Project with its sophisticated but flexible, open-sourced, portal-based Grid information infrastructure and ability to leverage innovations in sensor technologies on regional scales, has the potential to meet the practical needs of social – ecological systems challenged by humanity’s expanding global environmental impact. Its underlying strength lies in its ability to cross-connect science across discipline boundaries (Guston 1999) to influence decision making so as to initiate the new forms of transdisciplinary collaboration within academia, industry, government, and citizens in local communities to more effectively manage water resources for sustainability in a world altered by climate change. A proof-of-concept will be developed in this project to gauge the utility of PACMAN as a comprehensive, working platform for the study, monitoring, and management of water resources as a transferable “model system” through the involvement of local user and stakeholder groups in our study sites.

Education: As this network has sensor and analysis nodes at many sites across Alaska and Hawaii, PACMAN also has significant potential for creating opportunities for STEM education at the K-20 levels. This was effectively demonstrated in previous RIIs in the use of InteleSense-based sensors and portals in use case examples with 5th graders at Hokulani Elementary School and 10th graders at Farrington High School in Honolulu, Oahu (Hawaii EPSCoR Newsletter vol. 12 Fall 2008 http://www.epscor.hawaii.edu/news.php). These efforts will continue in the new project and be expanded to include collaborations with schools in the Kahalu’u, Kona area that are currently working in educational outreach programs of The Kohala Center. The Project will also provide support for a Graduate level Field Course started in 2007-2008 by UH Manoa’s Botany Department / The National Tropical Botanical Garden and led by Dr. David Burney in various sites on Kauai with an emphasis on the paleoecology at the Makauwahi Cave Reserve. Twenty-eight students enrolled in the successful 2007-2008 Field School and were able to accumulate accredited graduate course credit through evening lectures and “hands on” participation in excavations, native plant restorations, and visits to remote biodiversity reserves. In the current Project, a cyberinfrastructure module will be added to the curriculum so as to expose students to practical applications of wireless environmental sensing, internet portal development and Grid-based computing as applied to water resource monitoring at the Project’s study sites.

Cyberinfrastructure outreach will also be connected to The Kohala Center’s “Citizen Science Program” which is currently collecting near-shore water samples for laboratory analysis of ammonia, E.coli, nitrate, nitrite, organo-phosphates, and is collecting data in-situ on: chloroform, conductivity, dissolved oxygen, pH, and turbidity. Data collections by volunteers will be enhanced through the development / use of PDAs that will interface seamlessly with custom databases hosted onInteleSense servers and accessed through sophisticated custom portals. The Kohala Center’s portal will house an instructional “primer” on the use of six pertinent data layers within the server / geospatial database system to engage the Kahalu’u community, citizen scientists, K-12 classes, and visiting scientists in the effective use of the cyberinfrastructure. Included will be the data provided by the Citizen Science Program and local information that supports and affects community interest in the health of the ahupua‘a. The cyberinfrastructure will facilitate access by the general community and serve as the jumping-off point for those members of the community with advanced interests and/or cyber-skills. The Kohala Center’s effort will include an aggressive community outreach program through both volunteer networks, Public Service Announcements, scheduled interviews and paid advertising in the media.

Economic Development – Cyberinfrastructure applications on display at the expanding technology test bed sites statewide have considerable leveraging capacity, by serving to draw the attention of the broader public to the potential for the uses of the technology in activities such as species recovery, water resource monitoring, remote sensing, animal tracking, etc. For example, based upon

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the results of previous RIIs in cyberinfrastructure development, “spin off” projects at UH Manoa were subsequently funded in 2008-2009 with the Hawaii Division of Forestry & Wildlife and The Department of the Army (Biological Resources Division Schofield) for monitoring sediment inputs to streams from managed watersheds, remote surveillance of a sensitive plant propagation nursery, and monitoring of feral pig traps in remote areas of the Waianae Mountains on Oahu. Clearly, these innovative demonstration projects, have significant economic development potential for any local or state economy.

In collaboration with Kona Laboratories, which has a proven record of inventions for water quality monitoring applications in Hawaii, we will use our technology test bed sites for the production / development of new wireless sensors for monitoring localized climate and water resource dynamics such as evaporation, cloud / fog drip, aerosols, and particulates in surface water.

4.4 Diversity Plan Both the University of Hawaii and the University of Alaska have significant proportions of minority students. In Hawaii, these are primarily Native Hawaiians, Filipinos and Pacific Islanders, while Native Alaskans make up much of the University of Alaska’s minority population. It is our intention that leadership teams, faculty, staff and student participants from both states accurately reflect this diversity. Our intent is that 40 percent of participants in the program be members of groups underrepresented in the STEM fields, including ethnic minorities and women. All efforts will be made to extend this number across all levels of contributions to the program, from members of the governing body to K-12 students. This will be accomplished through a variety of means. First, in order to earn the interest and imprimatur of indigenous populations, both the Alaskan and Hawaiian components will incorporate a high degree of cultural sensitivity into their overall research foci and strategies. The Alaska component will shape its education and outreach efforts on 2000’s Recommendations from the Working Group on Arctic Science Education to the National Science Foundation:

All science education programs must be relevant, inquiry-based, and aligned with national and state science content standards; arctic science education programs must be sensitive to the geographic location of their audience as well as the audience’s prior knowledge; programs should include both traditional Native knowledge and Western science perspectives; and researchers need to communicate with arctic communities about upcoming research activities. The Hawaiian component will also be operated with sensitivity to cultural concerns. It will be organized around the historic Native Hawaiian ahupua’a concept of naturally integrated land-sea resource connectivity within island watersheds. Research will be conducted within the traditional Native Hawaiian idioms of IkePono (“knowledge that is right”) and Aloha ‘Aina (“love of the land.”) Cultural guidance of Native Hawaiian and Pacific Islander populations will be incorporated into the project.

In order to better incorporate diverse viewpoints into the makeup of Track II, efforts will be made in both states to recruit diverse governing bodies and management teams. Several members of the joint management team will be designated as the Education and Community Outreach subgroup, responsible for involving members of the community in the Track II project and disseminating its results throughout the project area. Diversity means selecting members from underrepresented groups, but also ensuring that participants in the program come from across the campus systems of both UH and UA and, consequently, from throughout the geographic areas of both states.

The project will involve Alaskan and Hawaiian Natives through a variety of outreach and educational efforts. Undergraduate research grants, graduate student fellowships, summer internships and other educational opportunities will rope in a cross-section of the student bodies at UA and UH. Wherever

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possible, research projects will be designed which stretch across both jurisdictions and involve student workers from both states, making the work a broadening experience for all students involved. Research design, data gathering, and cyber-enabled data distribution, manipulation, and evaluation will all be used as teaching tools by the education and outreach component of the program.

Recruitment and retention of diverse students will also be accomplished through leveraging with existing programs:

Pacific Alliance Leverage: NSF funded the Pacific Alliance to encourage indigenous Americans to pursue degrees in sciences and engineering. This program originated at the partner campuses in Manoa, Anchorage, and Fairbanks, along with the University of Washington. The Track II project will provide additional funding to these programs to enable them to devise additional retention vehicles that directly involve our research focus. We will build on the relationships of the Pacific Alliance involving Alaska Native serving, Native Hawaiian serving, and Tribal College institutions.

EPSCOR Leverage: UH and UA both have EPSCOR programs which incorporate strong K-12 outreach. These programs have considerable reach into their respective K-12 communities for both teachers and students, and many of them target indigenous populations. The program at UA also targets students who live in remote and extreme environments. Track II will provide additional funding to these programs - which may be matched by EPSCOR funds - to enable them to devise additional outreach vehicles that directly involve Track II experiences and materials.

The involvement of diverse students will dovetail with the program’s dissemination efforts. The focus will be on disseminating results to affected communities with high percentages of underrepresented minorities. Keeping affected residents informed of the research will encourage them to become actively involved in the project.

4.5 Dissemination and Communication Plan The largest obstacle for communication is, of course, the enormous distance separating Alaska and Hawaii. This will be overcome through the use of state-of-the-art telecommunications technology to enable real-time videoconferencing.

This has already proven a tenable method for linking these two far-flung jurisdictions. A key example is the Local and Indigenous Knowledge network, an extant NOAA-funded collaboration between Alaska, Hawaii and Arizona working on creating a climate knowledge network through the recruitment of indigenous observers. The project is utilizing videoconference technology to host a series of three virtual conferences over the 2008-09 academic year, linking indigenous resource decision-makers in Alaska, the Pacific Islands and the American Southwest through university campuses and other remote rural sites.

This project will emulate the Local and Indigenous Knowledge Project, but it will also leverage it as a foundation upon which to build our own outreach efforts. Working off of advances the NOAA project has already made, we will be able to improve and streamline communications efforts.

In terms of direct outreach, we intend to fund an Outreach Coordinator to mount and coordinate outreach efforts for both jurisdictions. This person will be in charge of dissemination strategies such as a web site, printed materials and public presentations to a variety of groups.

Cyberinfrastructure will play a key role in our communication and dissemination efforts, and not just in terms of transatlantic videoconferencing: model visualization will be a key component of research. Translating algorithms and models into 2-D and 3-D animation will be a necessary step for our

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researchers but will also lead to attention-grabbing public demonstrations in places like the Imaging Center on the University of Alaska Fairbanks campus.

In addition to the Local and Indigenous Knowledge network, other extant programs and collaborations can be leveraged to augment our own outreach work. The ability to partner with Alaska and Hawaii EPSCoRs (see 4.4, above) will strengthen education efforts in particular, as both programs contain strong K-12 components. These existing programs can be expanded in size and scope and linked together along logical lines to allow students and stakeholders in the respective Hawaii and Alaska programs to interact with one another. Other independent K-12 programs can also be developed under the aegis of the Outreach Coordinator.

The Hawaii and Alaska programs can also complement each other in various ways. UA has a stronger social science element than UH, much of which is focused on rural populations and thus increases interactions between UA researchers and indigenous peoples. UH undertakes less social science research but has a very well-established system of community outreach.

In addition, both jurisdictions are moving forward with projects (including the aforementioned Local and Indigenous Knowledge network) which incorporate local indigenous people, who are often acquainted with the minutiae of local climate variations, as “human sensors” to detect and report on changes in microclimate. By intimately involving local residents in our efforts, such strategies succeed both in furthering both research and outreach.

4.6 Evaluation and Assessment Plan Evaluation and Assessment of design and build of the proposed cyberinfrastructure and other technical merits across this consortium will be led by Mr. Tom Heinrichs, Associate Director of GINA. Evaluation of the societal benefits, diversity challenges, and broader impacts will be spearheaded by Dr. Judith K. Inazu, Associate Director of the Social Science Research Institute at the University of Hawaii-Manoa and Director of the institute’s Office for Evaluation and Needs Assessment. Dr. Inazu already evaluates Hawaii EPSCoR and a number of other NSF and NIH award programs in the state. Dr. Inazu will conduct a rigorous, systematic and comprehensive evaluation of the Track II project throughout its life.

While the evaluation process will be coordinated by Heinrichs and Inazu, it will conducted by selected members of the jurisdictional governing committees (see Section 4.8 below) as well as the External Advisory Committee. The evaluation will focus on assessing long-term, broad, macro-level system changes as well as short-term, specific, institutional, unit, and individual-level changes. A combination of formative (process) and summative (outcome) evaluation approaches utilizing both qualitative and quantitative data will be used to monitor inputs, resources, and activities; identify and document implementation difficulties; and assess the effectiveness of project activities in attaining the goals of the project. The critical evaluation questions are whether the investment into Alaska and Hawaii’s research infrastructure has accomplished the project’s scientific and societal objectives (as detailed under Sections 4.3, 4.4, and 4.5 above), has strengthened the individual research capacities of both jurisdictions, and has fostered an increased level of cooperation between the two.

More specifically, evaluators will seek answers to the following questions; timelines shown in parentheses:

1. Are grant activities being implemented as planned? (conducted annually) 2. How have Alaska and Hawaii’s science and technology capabilities been enhanced by

development of PACMAN? (evaluated mid-project, end of project) 3. What are the specific barriers to the success of the project (identified in first year) and how have

they been overcome (assessed end of project)?

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4. How have grant activities improved Alaska and Hawaii’s research infrastructure? (end of project) 5. What impact has the project had on K-12, undergraduate and graduate students? (end project) 6. How diverse is the leadership group of the project and the cohort of project participants? (initially,

then each year) 7. What impact has the project had on local communities? (second and third year)

A variety of data collection measures will be utilized to obtain this information. These include:

1. An ongoing review of documents from the project; 2. Individual, methodical interviews with major project stakeholders and beneficiaries, including

project leaders, university leaders, governing body members, select external stakeholders, researchers, Alaska Natives, Hawaii Natives, and Pacific Islanders, and educators;

3. Online survey questionnaires to gather background, activity and social-network data from reseachers, stakeholders, educators and students; and

4. Bibliometric analyses of curricula vitae of researchers.

In order to create a framework for expected progress, prior to the grant start date the management team – with the cooperation of the evaluator – will develop a strategic plan including details on planned activities, time frames, divisions of responsibilities, and specific milestones. The result of this process will be a concrete schedule for achieving the grant’s research, education and outreach goals.

For the duration of the grant, metrics will be collected on an annual basis, with results reported to the NSF immediately upon compilation. Formative evaluation is expected to occur throughout the grant period, although more time will be devoted to these activities during the initial start-up process. A comprehensive evaluation of the program will be made subsequent to expiration of the grant, for inclusion in the final report to NSF.

4.7 Sustainability Plan The potential sustainability of this project must be considered on several levels:

Sustainability of research advancement and infrastructure. This project is based largely on the utilization of cutting-edge technology, much of which will continue to be developed and refined over the course of the project. The project is designed with the flexibility to allow participating researchers to quickly incorporate these advances. This ability to quickly utilize relevant improvements will enable the project to maintain its intellectual output, its attractiveness to prospective participants, and its contribution to Alaska and Hawaii’s scientific and technological activities.

The increased investment in targeted cyberinfrastructure necessitated by the project will have lasting effects, leading to long-term increased research competitiveness in atmospheric science and other fields. Measurement devices and systems developed in conjunction with the Track II project will remain useful after its conclusion. The advanced telecommunications and visualization technologies used in this project will maintain their utility after its close, and have potential uses far beyond the limits of this specific endeavor. The increased competitiveness fostered by this improved infrastructure will benefit Alaska, Hawaii, and the United States in the long term.

Sustainability of educational advancement and human resource development: The project’s heavy student involvement will help build the next generation of researchers. By incorporating indigenous ways of knowing into the program structure, the project has the potential to involve and energize a cross-section of Hawaiians and Alaskans currently underrepresented in the

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STEM fields. Their contributions to science and technology will linger long after this grant has ended. The human resources development aspect of the project will inherently increase sustainability through training research assistants and other employees to become the researchers of the future, and increasing the knowledge base and experience of everyone working on the project.

Sustainability of research connectivity: The project promises to bring Alaskan and Hawaiian scientists together as never before. Just as this project will build on some of the connections made in the Local and Indigenous Knowledge network (see 4.5, above), future crossjurisdictional projects can be built upon the successes of this one. There are significant commonalities between Alaska and Hawaii’s particular scientific challenges and concerns, and this project has the potential to strengthen existing research links between the two states and develop new ones.

Sustainability of extramural funding and support: Atmospheric modeling is a growing field, fueled by the increasingly urgent need to understand the functioning of various ecosystems as climate change threatens to subject them to major disruptions. There is also a growing understanding that collaborations between far-flung areas will be necessary in order to grasp the large-scale symptoms of climate change. In utilizing recent advances in climate science to study such a large transect, Alaskan and Hawaiian researchers are positioning themselves to receive significant amounts of research funding into the foreseeable future.

4.8 Management and Coordination Plan At the highest level, the project will be overseen by a committee whose membership is drawn from the pair of existing EPSCoR jurisdiction governing bodies: the State Committee on Research (SCoR) for Alaska and the Statewide Committee for Hawaii. Both bodies consist of a number of high-level academics, administrators, business people and other officials. These two bodies will meet shortly after initiation of the program to select 3 members from each committee to fill the Alaska-Hawaii Oversight Committee (AHOC). The consortium has invited Mr. Lawrence Hartig, Commissioner of the Alaska Department of Environmental Conservation, chair of Governor Palin’s Climate Change Subcabinet (http://climatechange.alaska.gov) and member of SCoR to be the chair of the AHOC.

As previously noted, the consortium will look toward an External Advisory Committee composed of representatives from various user groups to further ensure that PACMAN is ground in practicality and relevance as well as technical prowess. Ms. Vera Kingeekuk Metcalf, Native Alaskan, director of the Eskimo Walrus Commission and member of the US Arctic Research Commission has been approached to lead the EAC. This committee will comprise 8-12 members drawn from potential end-user groups such land holders, native Alaskan and Hawaiian groups, NGOs, K-12 schools, and government agencies. The PACMAN consortium will look to the EAG for guidance on such issues as research prioritization, information products, appropriate data format designs, delivery characteristics, and other matters that will optimize the societal benefits of PACMAN.

The Alaska PI and Project Director, Dr. Virgil Sharpton, will chair the Joint Management Team (JMT) consisting of the senior personnel (PIs and Co-PIs) from both institutions and co-chaired by Kenneth Kanoshiro, the Hawaii PI. The JMT will interface periodically with AHOC and EAC to develop and implement plans and approaches that effectively meet user needs and ensure sustainability of the program. The responsibilities of members of the JMT are summarized in Table 4.8.1.

JMT will hold two face-to-face meetings each year, one in Alaska and one in Hawaii. Other meetings will take place monthly or bimonthly and be staged by videoconference. (It is worth noting that cyberinfrastructure is as integral an aspect of project management as it is of the project itself.)

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Subgroups of the committee, including the Education and Community Outreach subgroup (see 4.4, above) will also videoconference as necessary.

The consortium’s Co-Investigators (listed as other senior personnel) constitute the Joint Technical Team whose responsibilities include the day-to-day operations of PACMAN, technical oversight and implementation of strategies, approaches, and recommendations coming through the JMT from AHOC and EAC. Specific responsibilities are listed in Table 4.8.1.

The JMT and JTT will be assisted by a small group of (part-time) salaried employees. Two part-time project coordinators, one in Alaska and one in Hawaii, will be in charge of the day-to-day operations of the project under the aegis of the management team. An Outreach Coordinator (see 4.4, above) will be in charge of outreach and education efforts, assisted by a graduate student. A part-time Fiscal Officer and an Administrative Coordinator will round out the small office staff. Other personnel will be employed on part-year contracts as needed; much of the administrative, educational and science support will be shared with other organizations affiliated with joint science support facilities on both the Alaska and Hawaii campuses.

Table 4.8.1: Roles and Responsibilities of Senior Investigator Team Investigator Role Responsibility Sharpton Alaska PI/PD Overall Project Direction, Chair of JMT, Oversee progress in all tasks,

convene JMT meetings, interact with EAC and AHOC, GINA integration, etc.

Gaines Hawaii PI UH - VP for Research & Graduate Education Alessa Alaska Co-PI UAA; EPSCoR Track 1; FERAL Integration, Task 2 Hinzman Alaska Co-PI IARC IJIS, Task 2 White Alaska Co-PI INE; RISA/Sensor Upgrades, Task 1; Community Outreach Williams Alaska Co-PI ARSC Integration, Oversight of System Administrators Kaneshiro Hawaii Co-PI UHM, Director of Center for Conservation Research & Training;

Project Director for Track 2 Montgomery Hawaii Co-PI Intelesense Technologies; Task 1, 2, 3. Kido Hawaii Co-I UHM; Stream Ecologist; Director Hawaii Stream Research Center;

Task 1; Co-Leads Outreach effort. Lassner Hawaii Co-PI VP for Information Technology; Task 1, 2, 3. X. Zhang Alaska Co-I IARC; Task 4; Task 2 guidance Cahill Alaska Co-I GI/Department of Atmospheric Sciences; Task 4 Aerosols J. Zhang Alaska Co-I ARSC; Task 4 Mesoscale Modeling Molders Alaska Co-I GI/Department of Atmospheric Sciences; Task 4 Aerosols Newby Alaska Co-I ARSC Integration; Task 2, Oversight of System Administrators Heinrichs Alaska Co-I GINA Integration,Tasks 1,2, 3; Leads Technical Evaluation Gp. Schweitzer Alaska Co-I UAF; EPSCoR Track 1; Co-Leads Outreach effort Smith Alaska Co-I Liaise with UA Office of Information Technology Porter Hawaii Co-I UHM; School of Ocean Earth Science & Technology; Task 1, 4.

4.9 Mentoring Activities for Post-Docs While this project does not request support directly for post-doctoral researchers, it shows institutional support for one unnamed post-doc. This person will be mentored by Dr. X Zhang and will receive career guidance activities in grant writing, research compliance (including export regulations) and support to allow appropriate participation in this project.

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