Climate FDDA. Andrea Hahmann NCAR/RAL/NSAP February 26, 2008

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1 Climate FDDA Andrea Hahmann NCAR/RAL/NSAP February 26, 2008

2 Outline Climate downscaling - the basics Method (ATEC ranges) - Climo-FDDA Possible application of Climo-FDDA data at the ranges Available data and examples of use Andrea Hahmann, Forecaster s Conference, February

3 Climate downscaling Downscaling is method for obtaining highresolution climate or climate change information from relatively coarse-resolution large-scale models; Global models have resolutions of km; Impact (coupled) models require resolution at scales of 10 km or less; Two main methods: statistical and/or dynamical downscaling Andrea Hahmann, Forecaster s Conference, February

4 Statistical downscaling Development of statistical relationships between local climate variables (e.g. surface air temperature, precipitation) and large scale predictors (e.g., sea-level pressure) Similar to model output statistics (MOS) large-scale analysis Predictors (Global/Regional Model) local value Predictants (values at local scale) Andrea Hahmann, Forecaster s Conference, February

5 Dynamical downscaling One-way nesting technique; Uses output from large-scale model to drive a fine spatial scale numerical atmospheric model (Limited area model; LAM); MM5/WRF RTFDDA Andrea Hahmann, Forecaster s Conference, February

6 Statistical versus dynamical downscaling Statistical downscaling Assumes global model captures temperature and precipitation trends Cheap (no need for expensive model simulations) Statistical regressions might not be valid for future climates Clifford Mass, Univ. of Washington Dynamical downscaling Represents regional weather processes Expensive (long LAM runs required) May produce local trends not depicted by global models Andrea Hahmann, Forecaster s Conference, February

7 Mesoscale model + FDDA Nudging of observations prevents the LAM solution from deviating from the given large-scale state global model (reanalysis) mesoscale model (RT-FDDA) von Storch et al (2000) Andrea Hahmann, Forecaster s Conference, February

8 Climo-FDDA (CFDDA) Climo-FDDA uses the RT-FDDA system (MM5/WRF mesoscale model + assimilation of observations) to build a database of gridded weather phenomena over a particular region of earth Weather database extends over many years (usually 20-40) which are then combined to estimate the expected weather and its associated variability and/or uncertainty over a particular region Andrea Hahmann, Forecaster s Conference, February

9 Climo-FDDA (Cont.) Climo-FDDA extends the climatography from the observation locations (SAMS, RAOB, etc.) to a fine-resolution grid using a dynamically consistent tool (takes into account fineresolution topography, land, coastline, etc.) Andrea Hahmann, Forecaster s Conference, February

10 Climo-FDDA procedure Year 1 Year 2 Year 3 global analysis observations global analysis observations global analysis observations LAM+ FDDA LAM+ FDDA LAM+ FDDA regional anal regional anal regional anal Post-processing Mean Variance Correlation Freq Occurrence Year N global analysis observations LAM+ FDDA regional anal Output to coupled model Andrea Hahmann, Forecaster s Conference, February

11 Possible applications of Climo- FDDA data at the ranges Help locate weather-sensitive installations (air strips, roads, permanent test siting) Help decide on time of the year and location for a specific test (how hot/cold, how windy) - apply weather-specific thresholds; Possible uses for quality control of observations Help locate new observing systems Andrea Hahmann, Forecaster s Conference, February

12 Example 1: Eastern Med Experimental runs for the Eastern Mediterranean region; RT- FDDA (MM5); NCEP/NCAR reanalysis; surface + upper air observations January ; focus on water resources (wet season) Andrea Hahmann, Forecaster s Conference, February

13 Is the MM5 simulation of the large-scale in sync with the driving analysis? MM5 no FDDA NNRP Analysis MM5 + FDDA Andrea Hahmann, Forecaster s Conference, February

14 Rain Gauge Precipitation validation: January Merged TRMM (IR + microwave + gauges) MM5 Domain 2 (15 km) Andrea Hahmann, Forecaster s Conference, February

15 Climo-FDDA data cube Many ways of compositing the data to obtain useful climatologies - some examples follow Andrea Hahmann, Forecaster s Conference, February

16 Example 2: DPG September mean 10-meter wind vectors mean 2-meter temperature mean 10-meter wind vectors; standard deviation of 10-meter wind speed Andrea Hahmann, Forecaster s Conference, February

17 Wind speed frequency distributions Histograms of the 10-meter wind speed (all hours, Sept 15-30, ) at Callao Gate S02 (40.18 N, W) SAMS (S02) CFDDA wind speed (m/s) wind speed (m/s) Andrea Hahmann, Forecaster s Conference, February

18 MM5 sfc Wind Climatology at ATC Jan-Feb 06:00 UTC 0600 GMT 18:00 UTC Andrea Hahmann, Forecaster s Conference, February

19 Frequency of occurrence 00:00 UTC 06:00 UTC Frequency of occurrence of wind speed above 7.5 m/s 12:00 UTC 18:00 UTC Andrea Hahmann, Forecaster s Conference, February

20 Future plans Three Climo-FDDA runs underway for: ATC, summer (June-August), 5 years WSMR, winter (December-February), 5 years DPG, winter (December-Feruary), 5 years Complete climatologies for all ranges/times later Data available through the MetVault; Easy access (dicing of data cube ): Simple data-processing scripts available to range forecasters Andrea Hahmann, Forecaster s Conference, February

21 Thanks for your attention! Any questions? Andrea Hahmann, Forecaster s Conference, February

22 References von Storch, H., H. Langenberg, and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev., 128, Cliff Mass, Univ. of Washington web pages: fpage.html Andrea Hahmann, Forecaster s Conference, February