evaluation of wrf using high-resolution soil initial
DESCRIPTION
Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land Information System. University of Maryland WRF Workshop, 14 September 2007 Presented by: Jonathan L. Case. Project overview / Hypothesis Experiment design Results Land Information System vs. Eta comparison - PowerPoint PPT PresentationTRANSCRIPT
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Evaluation of WRF Using High-Resolution Soil Initial Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land Information SystemConditions from the NASA Land Information System
University of Maryland WRF Workshop, 14 September 2007Presented by: Jonathan L. Case
• Project overview / Hypothesis
• Experiment design
• Results – Land Information System vs. Eta comparison– Impacts on short-term numerical forecasts
• Summary / Future Work
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Project OverviewProject Overview
• Hypothesis: Can short-term mesoscale numerical forecasts of sensible weather elements be improved by using optimally-tuned, high-resolution soil fields?
• Project Goals: Investigate and evaluate the potential benefits of using high-resolution land surface data derived from NASA systems and tools on regional short-term numerical guidance (024 hours)– Use LIS software to initialize soil temperature and moisture
in the WRF model
– Examine one month period with relatively benign weather• Isolate influence of land-atmosphere interactions
• May 2004 over Florida peninsula
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Experiment DesignExperiment Design
• LIS offline simulation using Noah LSM– Nested 9-km/3-km grid domain over SE U.S.– Simulation from 1 May 2002 to 1 June 2004– Output every 12 hours during May 2004
to initialize WRF runs– Atmospheric forcing datasets
• North American Land Data Assimilation System (NLDAS; hourly, ~14 km)• Global Data Assimilation System (GDAS; 6-hourly, ~52 km)• GDAS used where NLDAS forcing is missing
• Compare regional WRF simulations with high-resolutionLIS soil data to WRF runs with Eta model soil data– Calculate verification statistics at 80 surface stations– Plot fields to compare phenomenology differences
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• Common characteristics– Nested grids: 9-km and 3-km spacing– Noah LSM– Daily 24-hour forecasts during May 2004
initialized at 0000 UTC and 1200 UTC– Atmospheric initial & boundary conditions
from NCEP Eta model on 40-km grid
• Differences– Control WRF: Initial soil data from Eta model– LIS/WRF experiment: Initial soil data from 2+ year
LIS run on exact WRF grids
Control WRF and LIS/WRF ConfigurationControl WRF and LIS/WRF Configuration
9-km
3-km
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Daily 0-10 cm initial soil moisture (%)Daily 0-10 cm initial soil moisture (%)(0000 UTC values during May 2004)(0000 UTC values during May 2004)
Eta soil moisture LIS soil moisture
Difference (LIS – Eta)
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Daily 0-10 cm initial soil moisture (%)Daily 0-10 cm initial soil moisture (%)(0000 UTC values during May 2004)(0000 UTC values during May 2004)
Eta soil moisture LIS soil moisture
Difference (LIS – Eta)
LIS SubstantiallyDrier
• Much more detail in LIS (as expected)• LIS drier, especially over N. FL & S. GA• LIS slightly more moist over Everglades
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Daily 0-10 cm initial soil temperature (°C)Daily 0-10 cm initial soil temperature (°C)(0000 UTC values during May 2004)(0000 UTC values during May 2004)
Eta soil temperature LIS soil temperature
Difference (LIS – Eta)
• LIS systematically cooler over most of domain
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0-10 cm initial soil moisture (%)0-10 cm initial soil moisture (%)(1200 UTC 6 May 2004)(1200 UTC 6 May 2004)
Eta soil moisture LIS soil moisture
Difference (LIS – Eta)
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Sample Sea Breeze Evolution DifferencesSample Sea Breeze Evolution Differences(9-hour forecast valid 2100 UTC 6 May)(9-hour forecast valid 2100 UTC 6 May)
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Sample Sea Breeze Evolution DifferencesSample Sea Breeze Evolution Differences(10-hour forecast valid 2200 UTC 6 May)(10-hour forecast valid 2200 UTC 6 May)
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Sample Sea Breeze Evolution DifferencesSample Sea Breeze Evolution Differences(11-hour forecast valid 2300 UTC 6 May)(11-hour forecast valid 2300 UTC 6 May)
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Sample Sea Breeze Evolution DifferencesSample Sea Breeze Evolution Differences(12-hour forecast valid 0000 UTC 7 May)(12-hour forecast valid 0000 UTC 7 May)
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Sample Sea Breeze Evolution DifferencesSample Sea Breeze Evolution Differences(Meteogram plots at 40J and CTY)(Meteogram plots at 40J and CTY)
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Verification Stats: 0000 UTC CycleVerification Stats: 0000 UTC Cycle(29 forecasts @ 80 surface stations)(29 forecasts @ 80 surface stations)
2-m Temperature Errors (°C): 0000 UTC Cycle
-3
-2
-1
0
1
2
3
0 3 6 9 12 15 18 21 24Forecast Hour
Err
or (°
C)
Bias-CONRMSE-CONBias-LISRMSE-LIS
2-m Dewpoint Errors (°C): 0000 UTC Cycle
-3
-2
-1
0
1
2
3
0 3 6 9 12 15 18 21 24Forecast Hour
Err
or (°
C)
• LIS/WRF runs reduced RMS errors by a few tenths of a degree over most forecast hours
• Nocturnal warm bias and daytime cold bias both improved
• Not much change in dewpoint verification stats• LIS/WRF daytime dewpoints about 0.5°C lower than control WRF• Wind Speed (not shown): LIS/WRF improved nocturnal high bias
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Summary / Preliminary ConclusionsSummary / Preliminary Conclusions
• Configured and tested LIS/WRF on Florida case– Initial soil fields generated on exact WRF grids– LIS generated soil fields cooler and drier than Eta model
• Simulated atmosphere sensitive to changes in soil characteristics provided by LIS– Demonstrated positive improvement in sea-breeze prediction
on 6 May– Improvements in diurnal prediction of 2-m temperatures during whole
month (both 0000 and 1200 UTC forecast cycles)
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Backup SlidesBackup Slides
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Proposed Future Activities with LIS/WRFProposed Future Activities with LIS/WRF
• Merge MODIS sea-surface temperatures with LIS soil data• Study impacts of LIS soil data on convective initiation
– Different regional domains & cases– Varying weather regimes (e.g. supercells vs. air-mass storms)
• New case study period over Tennessee Valley– Very warm March followed by killing freeze in early April 2007– Use real-time MODIS greenness fraction products in LIS/WRF system
• Regional modeling ensembles– Summertime forecast sensitivity to soil initial condition perturbations– Run different LSMs within LIS/WRF for ensemble members
• Pathway to operational regional LIS/WRF runs
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N Alabama / SE Tennessee Apr 5, 2007 (Before freeze)
Alabama Freeze Case: April 2007Alabama Freeze Case: April 2007
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N Alabama / SE Tennessee April 8, 2007 (After Freeze)
Alabama Freeze Case: April 2007Alabama Freeze Case: April 2007
Proposal: • Use real greenness fraction data in LIS/WRF simulations, derived from MODIS vegetation index composite products• Measure impact on WRF forecasts compared to climo datasets
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Soil Moisture: Grid-Wide Stats; Land PointsSoil Moisture: Grid-Wide Stats; Land Points
0-10 cm So il Mo isture: Mean & SD
0
5
10
15
20
25
1 6 11 16 21 26 31
Day (May 2004)
Vo
lum
etri
c W
ater
(%
)
C ontro l Mean LISW R F MeanC ontro l S D LISW R F S D
40-100 cm So il Mo isture: Mean & SD
0
5
10
15
20
25
1 6 11 16 21 26 31
Day (May 2004)
Vol
um
etri
c W
ater
(%
)
• LIS is a few % drier than Eta model in volumetric soil moisture • Variation about mean is very similar to Eta model soil moisture
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Soil Temp: Grid-Wide Stats; Land PointsSoil Temp: Grid-Wide Stats; Land Points
0-10 cm Soil T em p: Mean & SD
0
5
10
15
20
25
30
35
1 6 11 16 21 26 31
Day (M ay 2004)
Tem
per
atu
re (
°C)
C ontro l Mean LIS W R F MeanC ontro l SD LIS W R F S D
40-100 cm So il T em p: Mean & SD
0
5
10
15
20
25
30
1 6 11 16 21 26 31
D ay (M ay 2004 )
Tem
per
atu
re (
°C)
• LIS 0-10 cm soil temperatures typically cooler than Eta at 00z
• LIS 0-10 cm soil temperatures about the same or slightly warmer at 12z
• LIS deeper soil temperatures consistently colder than Eta
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Sample Sea Breeze Evolution DifferencesSample Sea Breeze Evolution Differences(Forecasts from 1200 UTC 6 May Simulations)(Forecasts from 1200 UTC 6 May Simulations)
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Verification Stats: 1200 UTC CycleVerification Stats: 1200 UTC Cycle(Surface station 40J)(Surface station 40J)
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Verification Stats: 1200 UTC CycleVerification Stats: 1200 UTC Cycle(Surface station CTY)(Surface station CTY)