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Use of Observing System Experiments to Assess and Account for Changes in the Global Observing System Robert Atlas Laboratory for Atmospheres NASA Goddard Space Flight Center

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Use of Observing System Experiments to Assess and Account for Changes in the Global Observing System Robert Atlas Laboratory for Atmospheres NASA Goddard Space Flight Center. Background. - PowerPoint PPT Presentation

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Use of Observing System Experiments to Assess and Account for

Changes in the Global Observing System

Robert Atlas

Laboratory for AtmospheresNASA Goddard Space Flight Center

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Background

Basic Problem: Introduction of new observing systems or changes in existing observing systems (in terms of coverage, accuracy, bias, or resolution)can introduce spurious climatic signals.

Potential Solutions:1. Preprocessing of observations for reanalysis to decrease

inhomogeneities. 2. Reduce model bias3. Improve interpretation of reanalysis trends through Observing

System Experiments (OSE) and Observing System Simulation Experiments (OSSE), and through comparisons with single or limited data sources.

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OBSERVING SYSTEM SIMULATION EXPERIMENTS

OBJECTIVES:

1. To provide a QUANTITATIVE assessment of the potential impact of proposed observing systems on data assimilation, and numerical weather prediction.

2. To evaluate new methodology for the processing and assimilation of space-based data.

3. To evaluate tradeoffs in the design and configuration of proposed observing systems (e.g. coverage, resolution, accuracy and data redundancy).

4. Can also be used to determine the ability of existing observing systems to detect climatic trends and to optimize the global observing system for climate monitoring.

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SIMULATION STUDIES CONDUCTED BY NASA GLA1. EVALUATED THE RELATIVE IMPACT OF TEMPERATURE, WIND AND

MOISTURE DATA - These experiments showed wind data to be more effective than mass data in correcting analysis errors and indicated significant potential for space-based wind profile data to improve weather prediction.The impact on average statistical scores for the northern hemisphere was modest, but in approximately 10% of the cases a significant improvement in the prediction of weather systems over the United States was observed.

2. EVALUATED THE RELATIVE IMPORTANCE OF UPPER AND LOWER LEVEL WIND DATA.- These experiments showed that the wind profile data from 500hpa and higher provided most of the impact on numerical forecasting.

3. EVALUATED DIFFERENT ORBITAL CONFIGURATIONS AND THE EFFECT OF REDUCED POWER FOR A SPACE-BASED LASER WIND SOUNDER (LAWS).- These experiments showed the quantitative reduction in impact that would result from proposed degradation of the LAWS instrument.

4. DETERMINED DRAFT DATA REQUIREMENTS OF SPACE-BASED LIDAR WINDS.-These experiments evaluated different coverages, resolutions, and accuracies for lidar wind measurements to estimate both research and operational requirements for the Global Tropospheric Wind Sounder (GTWS) Mission.

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SIMULATION STUDIES CONDUCTED BY NASA GLA

5. DEVELOPED AND TESTED IMPROVED METHODOLOGY FOR ASSIMILATING SATELLITE SCATTEROMETER DATA. - Applying this methodology resulted in the demonstration of the first significant positive impact of real scatterometer data in 1983.

6. DEVELOPED AND TESTED DIFFERENT METHODS FOR ASSIMILATING SATELLITE SURFACE WIND SPEED DATA.- This led to assimilation of SSM/I wind speed data to improve ocean surface wind analyses.

7. EVALUATED THE QUANTITATIVE AND RELATIVE IMPACT OF ERS AND NSCAT YEARS PRIOR TO THEIR LAUNCH.- These results were confirmed after the launch of both instruments.

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OBJECTIVES OF THE CURRENT OSSE

• TO EVALUATE THE POTENTIAL FOR SPACE-BASED WIND PROFILE DATA TO IMPROVE ATMOSPHERIC ANALYSES AND NUMERICAL WEATHER FORECASTS USING THE CURRENT NASA/GLA DATA ASSIMILATION SYSTEMS.

• TO EVALUATE THE IMPACT OF SPACE-BASED WIND PROFILES ON THE ANALYSIS AND FORECASTING OF PHENOMENA NOT PREVIOUSLY STUDIED IN OSSEs.

• TO DETERMINE IF THE IMPACT OF SPACE-BASED WIND PROFILES WOULD BE SUBSTANTIALLY REDUCED IN THE PRESENCE OF ADVANCED SOUNDER OR WITH A MORE ACCURATE FORECAST MODEL.

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DESCRIPTION OF EXPERIMENT

• A new nature run was generated using the NASA NCAR FVGCM at .5 deg resolution for the period from September 11 to December 31, 1999.

• A detailed evaluation of the nature run was performed.

• All conventional and satellite observations (that are currently assimilated at NASA) were simulated with existing coverages and expected accuracies.

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DESCRIPTION OF EXPERIMENT

• Space-based wind profiles were simulated first in a very idealized way, with the same coverage as TOVS, 1m/s accuracy at all levels and no degradation due to cloud effects; in later experiments somewhat more realistic lidar winds with attenuation due to clouds, but still 1m/s accuracy were assimilated.

• The OSSE system was calibrated through comparison with real data impact experiments.

• The results of the OSSE were evaluated in terms of standard metrics (rms, anomaly correlation) and new metrics ( cyclones, jet streaks, hydrologic cycle).

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NASA/GODDARD NATURE RUN• Model

• FVCCM (Finite-Volume Community Climate Model)

• Resolution•• Horizontal: 0.5lat x 0.625lon (regular grid)• Vertical: Surface + 35 pressure levels• (1000 Hpa to 0.4 Hpa)

• Time Period

• 1999 Sept. 11 00Z to 1999 December 31 18Z

• Every 6 hours.

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The Finite-volume GCM

• The finite-volume GCM (fvGCM) is DAO’s modeling system based on a finite-volume dynamical core and the community built physical parameterizations and land surface model.

• Current physical parameterizations are based on the NCAR CCM3. Future versions will be based on the Cummunity Atmosphere Model (CAM) and the Common Land Model (CLM)

• Partners in future developments of the fvGCM:

NCAR, DOE/LLNL, and CSU

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DJF 500-mb eddy height

fvCCM (15-yr amip-2 run)

DJF 500-mb eddy height

ECMWF analysis (15-yr)

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Simulated Eye Wall: wind speed

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Hurricane Floyd tracks form National Hurricane Center observed best track, NASA DAO Finite Volume DataAssimilation System (FVDAS) 1o 1.25o analysis, and FVCCM model 5-day forecast starting at 0000 UTC 12September 1999.

fvDAS ASSIMILATION AND FORECAST OF HURRICANE FLOYD

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SUMMARY OF OSSEs USING FVCCM NATURE RUN

GLOBAL DATA ASSIMILATION SYSTEM USED:

GEOS-3, 1 X 1 deg horizontal resolution

FVDAS, 1 x 1.25 deg horizontal resolution

SPINUP: 35 days

PERIOD OF ASSIMILATION: Sept. 11 - Oct. 31, 1999

CALIBRATION EXPERIMENTS (REAL and SIMULATED):

CTRL (Conventional Data + TOVS + CTW + QSCAT)

CTRL-ALL SAT (Conventional Data only)

CTRL-SAT TEMP (Conventional Data + CTW + QSCAT)

CTRL-QSCAT (Conventional Data + TOVS + CTW)

SIMULATED DATA EXPERIMENTS:

CTRL + Lidar Winds (with varying coverage)

CTRL + Advanced Sounder + Lidar winds

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Potentional Impact of new space-based observations on Hurricane Track Prediction

Based on OSSEs at NASA Data Assimilation Office

• Tracks• Green: actual track• Red: forecast beginning 63 hours before

landfall with current data• Blue: improved forecast for same time

period with simulated wind lidar

• Save ~ $1M/mile per hurricane for improved landfall forecast

• Lidar in this one case• Reduces landfall prediction error by 66%• Potentially save > $165M

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IMPACT OF LIDAR WINDS ON CYCLONE PREDICTION

5-day Average Reduction in Position Error

Global: 35 km (10% improvement)N. America: 48 km (11% improvement)

10-day Average Reduction in Position Error

Global; 66 km (17% improvement)N.H.X.T: 17 km (5% improvement)S.H.X.T: 48 km (24% improvement)

Reduction in Hurricane Landfall Position Error

For United States: 239 km (66% improvement) at 63h

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Potential Impact of Lidar Winds in the presence of a more advanced

forecast model

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CONCLUSIONS

1. OSE and OSSE provide an effective tool to aid in the interpretation of trends observed in model reanalyses, as well as to help determine the optimimum global observing system (GOS) for both weather and climate analysis.

2. OSE and OSSE should be routinely performed to assess subtle changes to the GOS, as well as major changes resulting from the introduction of new observing systems.

3. Development of an OSSE system for climate has already begun but will require substantial investment.

4. As with weather applications, great care must be taken to ensure the realism of the OSSE’s and in the interpretation of OSSE results.