VERIFICATION OF A DOWNSCALING SEQUENCE APPLIED TO MEDIUM RANGE METEOROLOGICAL PREDICTIONS FOR GLOBAL FLOOD PREDICTION Nathalie Voisin, Andy W. Wood and Dennis P. Lettenmaier Civil and Environmental Engineering 2007 AGU Fall Meeting H23F-1682
VERIFICATION OF A DOWNSCALING SEQUENCE APPLIED TO MEDIUM RANGE METEOROLOGICAL PREDICTIONS FOR GLOBAL FLOOD PREDICTION
Nathalie Voisin, Andy W. Wood and Dennis P. Lettenmaier
Civil and Environmental Engineering 2007 AGU Fall Meeting H23F-1682
University of Washington, Seattle December 11, San Francisco
2. MEDIUM RANGE LARGE SCALE FLOOD PREDICTION SCHEME
3. BIAS CORRECTION
We describe a prototype system for medium range (up to two week lead) flood prediction in large rivers, which is intended for global implementation – particularly in river basins having limited in situ meteorological observations. The procedure draws from the experimental North American Land Data Assimilation System (NLDAS) and the University of Washington West-wide Seasonal Hydrologic Forecast System for streamflow prediction. Meteorological forecasts based on a numerical weather prediction model serve both as the forcing for hydrologic model initialization and forecasts for lead times up to fifteen days. The hydrologic component of the system is the Variable Infiltration Capacity (VIC) macroscale hydrology model. In the prototype, VIC is spun up for forecast initialization using daily ERA-40 precipitation, wind, and surface air temperature. In hindcast mode, VIC is driven by global NCEP ensemble 15-day re-forecasts (NOAA/ESRL) that are bias corrected with respect to ERA-40 and spatially disaggregated using two higher spatial resolution satellite products: Global Precipitation Climatology Project (GPCP) 1DD daily precipitation and Tropical Rainfall Measuring System (TRMM) 3B42 precipitation are used to spatially disaggregate NCEP re-forecasts precipitation during the 15-day forecast period. The use of forecast models and satellite remote sensing data in this procedure reduces the need for in situ precipitation and other observations in parts of the world where surface networks are critically deficient, but where a global hydrologic forecast capability arguably would have the greatest value. The prototype system was implemented at one-half degree spatial resolution and tested during the 1979-August 2002 period. We verify forecast error statistics resulting from the application of the entire downscaling sequence for the Mississippi River Basin (where ample data for model evaluation exist) .
Notes: 1) Extreme values use fitted (rather than empirical) distributions; 2) quantile mapping includes correction for intermittency
Several years back
Medium range forecasts
NCEP Reforecasts (Hamill et al. 2006)15 ensemble members – 15 day forecast – 2.5 degree (fixed GFS version of 1998)
surrogate for near real time analysis fields
Bias correction at 2.5 degree, with respect to ERA-40 (Ensures consistency between spinup and the reforecasts)
Downscaling sequence of the precipitation forecasts
1979-2001 CDF for the Mississippi basin, daily mean precipitation (mm)
Annual January July
Downscaling to 0.5 degree
Downscalingfrom 2.5 to 0.5 degree
using the Schaake Shuffle ( Clark et al. 2004) with higher spatial resolution satellite GPCP 1dd (Huffman et al. 2001) and TRMM 3B42 precipitations
VIC Hydrology Model
model spin up
(0.5 degree global simulation)
Hydrologic forecast simulation
(0.5 degree global simulation: stream flow, soil moisture, SWE, runoff )
Several years back
Medium range forecasts ( up to 2 weeks)
4. VALIDATION OF THE BIAS CORRECTION
5. PRECIPITATION FORECAST VERIFICATION OVER THE MISSISSIPPI BASIN, 1979-2001 PERIOD
Number of days difference
The bias correction is performed independently for each 2.5 degree cell, for each lead time of the forecast and for each week of the year. Those plots show how different the bias correction effects might be depending on the location of the cell, here as an annual average.
IS THE SKILL OF THE FORECASTS MAINTAINED OR IMPROVED AFTER THE BIAS CORRECTION STEP, with respect to ERA-40?
Difference in the number of precipitation events >= 1mm in the 1979-2001 period:
(GFS refcst avg – Obs)
Annual CDF for Cell (35oN, 102.5oE)
Annual CDF for Cell (40oN, 90oE)
The bias correction increases the precipitation amount for small events, and slightly decreases it for larger events.
The bias correction decreases the precipitation amount all events.
1979-2001 daily mean precipitation (mm) for the Mississippi Basin
Because the bias correction is independent for each lead time, the bias corrected mean is flattened for all lead times; long lead time forecasts are not wetter than short lead times anymore.
Note that both corrections for intermittency and extreme value fitting adds water; the bias corrected forecast mean remains higher than the ERA-40 mean.
-Ensemble standard deviation decreased.
1) Impact of bias correction on forecast verification:
2) Would a subsequent step of forecast calibration improve the reliability?
at 2.5 degree
from 2.5 to 0.5 degree
Forecast calibration ?