Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land

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transitioning unique NASA data and research technologies to the NWS

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)



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


• 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)



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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(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 L IS W R F MeanC ontro l S D LIS W 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)

Vo

lum

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 So il T em p: Mean & SD

0

5

10

15

20

25

30

35

1 6 11 16 21 26 31

D ay (M ay 2004)

Te

mp

era

ture

(°C

)

C ontro l Mean L IS W R F MeanC ontro l S D 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)

Te

mp

era

ture

(°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)

Documents

Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land