The View from Both Sides: Pathways to Working at NASA and ...
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TheViewfromBothSides:PathwaystoWorkingatNASAandPersonalPerspec>vesonJCET
1. GSFCEarthScienceDivisionOverview
2. StudentandCareerPathsatGSFCandNASA
3. TheJCET-GSFCRela>onship
4. PostdocScience:TwoExamples
Steve PlatnickDeputy Director for Atmospheres, Earth Sciences Division
NASA Goddard Space Flight Center (GSFC)
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1.GSFCEarthSciencesDivisionOverview
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GSFCEarthSciencesDivision:WhatWeDoSatellite Obs., Algorithms, Data
Processing/Distribution, Data Analysis
Suborbital (Airborne, Ground)
Modeling Processes/Earth System/Climate
AppliedSciences
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NASACommunica>on:Web,SocialandPrintedMedia
NASA Earth Observatory, Science Visualization Studio, @NASA, etc.
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NASACommunica>on:Web,SocialandPrintedMedia
NASA Earth Observatory, Science Visualization Studio, @NASA, etc.
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NASACommunica>on:Web,SocialandPrintedMedia
NASA Earth Observatory, Science Visualization Studio, @NASA, etc.
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NASA Science Communication Support Office
NASACommunica>on:Face-to-Face
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Goddard Institute for Space Studies
Code 611Chief, Gavin Schmidt
Deputy, Ron Miller
Director – James IronsDeputy Director – VacantAssociate Director for Institution Planning and Development – VacantAssociate Director for Mission Planning and Technology Development – Tammy BrownAssistant Director for Operations – VacantAssistant Director for IT – Rosa KaoChief Technologist – Matthew McGillAirborne Science Manager – VacantApplied Sciences Manager – Stephanie UzOutreach Lead – Trena Ferrell
Field Support OfficeCode 610.W
Chief, David WolffAssistant, John Moisan
Deputy Director for Atmospheres –Steven Platnick
Associate Deputy Director – Karen Mohr
Deputy Director for Hydrosphere, Biosphere, and Geophysics – Christa Peters-Lidard
Assistant Deputy Director – Torry Johnson
Mesoscale Atmospheric Processes LaboratoryCode 612
Chief, George Huffman
Assistant, Vacant
Terrestrial Information Systems Laboratory
Code 619Chief, Edward MasuokaAssistant, Robert Wolfe
Global Modeling and Assimilation Office
Code 610.1Chief, Steven PawsonAssistant, Steve Cohn
Global Change Data Center
Code 610.2Chief, Stephen Wharton
Assistant, TBD
Earth Sciences Division – Code 610
Atmospheric Chemistry and
Dynamics LaboratoryCode 614
Chief,James Gleason
AssistantTBD
Climate and Radiation
LaboratoryCode 613
Chief, Lazaros
OreopoulosAssistant,
Vacant
CryosphericSciences
LaboratoryCode 615
Chief,Thorsten Markus
Assistant,Sophie Nowicki
Ocean EcologyLaboratoryCode 616
Chief, Carlos Del
CastilloAssistant,
Bryan Franz
Hydrological Sciences
LaboratoryCode 617
Chief,Matthew Rodell
Assistant,Mike Jasinski
Geodesy and GeophysicsLaboratoryCode 61A
Chief, Scott Luthcke
Assistant, Terrence Sabaka
BiosphericSciences
LaboratoryCode 618
Chief,Douglas Morton
Associate,Lahouari Bounoua
Civil Servants: 211 Non-Civil Servants: 1150
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6 / 11
27 / 84
22 / 96
8 / 90
12 / 94
11 / 54 12 / 79 20 / 122 11 / 80 8 / 53 13 / 57 20 / 91 19 / 150
3/4/2019
9
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GSFCEarthSciencesDivision:WhoWeAreWorkforce Civil Servants: 211 Non-Civil Servants : 1,150 Total: 1,261
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1959 Vanguard II (11 kg)
1960-65 TIROS 1-10 (127 kg)
2013 Landsat 8 (1510 kg)
2002 Aqua (3120 kg)2017 JPSS-1 (1930 kg)
ExampleGSFCMissionsOvertheDecades
courtesy Ron Gelaro/GSFC
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3U (IceCube)2U1U
Photo Credit: ISS and NanoRacks
ReturnoftheSmallSat
ICECube [NASA GSFC]TROPICS [MIT, NASA]
(Time-Resolved Obs. of Precip. structure and storm Intensity with a Constellation of Smallsats)
3U cubesat (1U=10x10x10 cm), 883 GHz cloud radiometer
(launched 2017)
Six 3U cubesat constellation, microwave radiometer, build completed
end of 2019, awaiting ride
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3U (IceCube)2U1U
Photo Credit: ISS and NanoRacks
ReturnoftheSmallSat
ICECube [NASA GSFC]TROPICS [MIT, NASA]
(Time-Resolved Obs. of Precip. structure and storm Intensity with a Constellation of Smallsats)
3U cubesat (1U=10x10x10 cm), 883 GHz cloud radiometer
(launched 2017)
Six 3U cubesat constellation, microwave radiometer, build completed
end of 2019, awaiting ride
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1960-65 TIROS 1-10 (127 kg)
ExampleGSFCMissionsOvertheDecades
In 1965, 450 TIROS images were put together to produce the first complete global view of the Earth's weather patterns.
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1960-65 TIROS 1-10 (127 kg)
ExampleGSFCMissionsOvertheDecades
In 1965, 450 TIROS images were put together to produce the first complete global view of the Earth's weather patterns.
Suomi NPP VIIRS22 April 2019
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2.StudentandCareerPathsatGSFC&NASA
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NASASupportOpportuni>esforCollegeStudents
• Internshipprogram:summer(10weeks),academicyear(16weeks),studentmustbefull>meenrolled,paids>pend
• StudentResearchAssistantorCollaborator:flexibleschedule,part/full>me,s>pendarrangesviaadvisor
• GraduateFellowships
- FINESST:FundedthroughNASAHQ,~100awards
- OfficeofSTEMEngagement:~10awards,requires10-weekresearchexperienceatNASAcenterforeachyearoffellowship
courtesy B. Meeson/GSFC
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NASAPostdoctoralProgram(NPP)
• Two-yearappointment(3rdyearop>on)workingwithNASAcivilservant.ProgramcurrentlyadministeredbyUniversi>esSpaceResearchAssocia>on(USRA).
• Includess>pend,professionaltravelallowance,NASA-supportedinsurance,reloca>ontoNASAcenter.
• Applica>onsaccepted3>mes/year:March,July,November
- Compe>>veprocess.Limitedslots!
- Applicantssubmitaresearchproposalinresponsetopostedresearchopportuni>esandconversa>onwithprospec>vecivilservantadvisors.
courtesy B. Meeson/GSFC
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Non-NPPPostdoctoralandCareerEmploymentatGSFC
• GSFCEarthScienceshasthreecoopera>veagreementsinplace:JCET(UMBC),GESTAR(USRA,MorganSt.),ESSIC(UMCP)
- Coopera>veagreementscien>ststypicallyhaveon-siteGSFCoffices
- Can/encouragedtowritePIproposals(typicallywithGSFCCivilServantscien>sts)
- JCETisuniqueinencouraging“affilia>on”withanUMBCdepartment
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3.TheJCET-GSFCRela>onship
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ExampleGSFCandJCETPathways:ATwo-wayStreet
JCETUMBC
Academic Departments
GSFC Civil Service
NPP (LaRC)NPP (GSFC)
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ExampleGSFCandJCETPathways:ATwo-wayStreet
JCETUMBC
Academic Departments
GSFC Civil Service
NPP (LaRC)NPP (GSFC)
Demoz,Lyapus>n,Markus,Marshak,Oreopoulos,Platnick,Sullivan,Torres
RemerDemoz*,Mar>ns,Zhang,
Sparling,McMillan(Phys.)Halverson(Geog.)
Zhaiseveral
Sullivan,Espinosa,Miller
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ExampleGSFCandJCETPathways:ATwo-wayStreet
JCETUMBC
Academic Departments
GSFC Civil Service
NPP (LaRC)NPP (GSFC)
Demoz,Lyapus>n,Markus,Marshak,Oreopoulos,Platnick,Sullivan,Torres
RemerDemoz*,Mar>ns,Zhang,
Sparling,McMillan(Phys.)Halverson(Geog.)
Zhaiseveral
Sullivan,Espinosa,Miller
Atmo. Phys.Track
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JCETLegacy:Atmo.PhysicsProgramCurriculum
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4.NPPScience:TwoExamples
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NPPScience,DanMiller:MachineLearningApproachesforCloudandAerosolRemoteSensing
View
ing
Angl
eVi
ewin
g An
gle Info about molecular and
aerosol scattering
Polarized Reflectance
Total Reflectance
Primary cloudbow
Synthe>callytrainedfeedforwardneuralnetwork
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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2016-09-22
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12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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NN re corrNJK rePP re
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2016-09-22
2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
0
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tot [-
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NN tot corrNJK totPP tot
2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
0
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r e [m
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I & DOLP noise tanh
NN re corrNJK rePP re
2016-09-22
2016-09-22
2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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tot [-
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NN tot corrNJK totPP tot
2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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I & DOLP noise tanh
NN re corrNJK rePP re
2016-09-22
2016-09-22
2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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NN re corrNJK rePP re
2016-09-22
2016-09-22
2016-09-22
12 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 13Time Series (UTC)
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2016-09-22
The airborne Research Scanning Polarimeter (RSP) produces a large multi-spectral multi-angular dataset for each observation. Using machine learning techniques we developed a fast retrieval of cloud properties using the full RSP dataset. This retrieval can be used as a rapid first-guess to accelerate slower but more rigorous retrievals. We applied this to cloud and aerosol observations made during the ORACLES sub-orbital field campaign.
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NPPScience,ReedEspinosa:Retrievalsusingahybridimplementa>onofDarkTargetandGRASPAerosolalgorithms
A new retrieval has been developed (DT-GRASP) combining the pixel preparation techniques of the Dark Target algorithm and the versatile inversion capabilities of GRASP. The flexibility of GRASP allows a priori assumptions to be derived from a joint retrieval with AERONET. When the tuned retrieval is applied exclusively to space-based observations from MODIS very good agreement is found with the measured aerosol optical depth (τ).
“enhanced” GRASP(exclusively space-based)
Aerosol properties retrieved from space
Satelliteobservations
Dark Target cloud masking,
pixel selection & gas corrections
Tune GRASP a priori assumptions via a joint retrieval of satellite and AERONET data
λ = 0.56 μm
WMO AOD Error Envelope Target