1 / 34

Global Flood and Drought Prediction

Global Flood and Drought Prediction. European Geosciences Union General Assembly 2006 Vienna, Austria, 2006 April 4th Nathalie Voisin, Dennis P. Lettenmaier Department of Civil and Environmental Engineering University of Washington Seattle, USA.

nerina
Download Presentation

Global Flood and Drought Prediction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Global Flood and Drought Prediction European Geosciences UnionGeneral Assembly 2006Vienna, Austria, 2006 April 4th Nathalie Voisin, Dennis P. Lettenmaier Department of Civil and Environmental Engineering University of Washington Seattle, USA Credit: Philip Wijmans/ACT-LWF Trevo, Mozambique, February 2000 , http://gbgm-umc.org/umcor/00/mozphotos.stm

  2. Outline • Background and Objective • Data and models • Toward developing global hydrology forecast capability • Approach • Data Processing : bias correction and downscaling of the forecasts • Preliminary results: forecast issued on Feb 4th 2000 • Future work

  3. -1-Background

  4. Need for flood prediction globally? www.dartmouth.edu/~floods, Dartmouth Flood Observatory

  5. Global Floods and Droughts • Floods • $50-60 billion USD /year, worldwide ( United Nations University) • 520+ million people impacted per year worldwide • Estimates of up to 25,000 annual deaths Mostly in developing countries; Mozambique in 2000 and 2001, Vietnam and others (Mekong) in 2000. • Droughts • 1988 US Drought: $40 billion (1988 drought: NCDC ) • Famine in many countries: 200,000 people killed in Ethiopiain 1973-74 Source: United Nations University, http://update.unu.edu/archive/issue32_2.htm http://www.unu.edu/env/govern/ElNIno/CountryReports/inside/ethopia/Executive%20Summary/Executive%20Summary-txt.html 1988 drought: NCDC : http://lwf.ncdc.noaa.gov/oa/reports/billionz.html

  6. Objective Predict streamflow and associated hydrologic , soil moisture, runoff, evaporation and snow water equivalent : 1. At a global scale • Spatial consistency • To cover ungauged or poorly gauged basins 2. Time scales: • Short term for floods • Seasonal (or longer) for drought 3. Freely disseminate information for agriculture, energy, food security ,and protection of life and property

  7. -2-Data and models

  8. Meteorological Data - Surface observations: Uneven global coverage Various attempts to grid globally We use Adam et al. (2006) 1979-1999 (0.5 degrees) and ERA-40 - Precipitation derived from satellite: Various products available, mostly either passive microwave and/or infra-red Issue with climatology and consistency ( especially important for seasonal prediction) - Climate Models: ECMWF and NCEP Re-analysis products, for at least 25 years Ensemble forecast products Quasi all or all required input data for our hydrologic model available

  9. The Hydrologic Model VIC - Already calibrated and validated at 2 degree resolution on over 26 basins worldwide(Nijjsen et al. 2001) • Calibrated and validated at 0.5 degree over the Arctic domain • Ongoing with UW and Princeton globally at 0.5 degree resolution

  10. Real time forecasting using VIC The Seasonal Westwide Forecastoperational over the entire western US seasonal forecast of streamflow The Surface Water Monitor operational over the entire western US daily analysis of soil moisture

  11. -3-Toward developing global hydrology forecast capability

  12. INITIAL STATE Forecast System Schematic * soil moisture snowpack streamflow, soil moisture, snow water equivalent, runoff local scale (1/2 degree) weather inputs Hydrologic forecast simulation Hydrologic model spin up Ensemble Reforecasts NCEP Reforecasts (Hamill 2006), bias corrected and downscaled ( NCEP GFS, ECMWF ESP) ECMWF ERA40 (or Analysis) Downscaling using observations (Adam et al 2006) Later on: CMORPH, MODIS, AMSR-E, others SNOTELUpdate NOWCASTS SEASONAL FORECASTS (drought) Several years back Month 0 SHORT TERM FORECASTS (flood) * Similar experimental procedure as used by Wood et al (2005) West-wide seasonal hydrologic forecast system

  13. Spin Up • ECMWF ERA40 reanalysis for retrospective forecasting • Assume ERA40 is the truth • Later use ERA40 analysis field, bias corrected to match ERA40 characteristics

  14. The Meteorological Forecasts Retrospective forecasting: Reforecasts • Tom Hamill (2006) NOAA • NCEP-MRF, 1998 version • 1979-present • 15-day forecasts issued daily • 15 member ensemble forecast • 2.5 degree resolution Real Time forecasting: ECMWF and/or NCEP (future)

  15. Data processing The climatology statistics to be conserved in the forecasts are : - the frequency of occurrence of rain- the peaks - accumulated amounts (mean) Using quantile-quantile mapping technique

  16. Data processing: Bias Correction Non-exceedance probability plots (MRF in green, ERA40 in black ) Systematic Bias Occurrence of Precipitation

  17. Data processing: Downscaling • Inverse square distance interpolation from 2.5 down to 0.5 degree resolution • Integration of observation based spatial variability at 0.5 degree: • Use observations based Adam et al. (2006) global dataset (0.5 degree resolution) • Shifting : • makes the Adam et al. average temperature field at 2.5 degree match ERA40, • Derive the temperature range for each 0.5 degree cell within the 2.5 degree cell • Scaling of the precipitation and the wind field so that the ratio Value(0.5)/Value(2.5) is conserved

  18. Satellite imagery of cloud activity on 1 Feb 2006 Satellite imagery of cloud activity on 2 Feb 2006 Preliminary results February 2000 floods in the Northern Part of South Africa: • Tropical depression moving southward from Beira, then continuing west into Zimbabwe, Botswana and South Africa • Sustained rain during the period 4 to about 14 February Tropical depression Boloetse track (pink) and forecasted direction (red) http://gisdata.usgs.net/sa_floods/

  19. Preliminary results – 2000 Feb 4th 5 day acc. PRECIPITATION ERA 40 GFS reforecast 15 ensembles avg LEAD 1 LEAD 1 LEAD 2 LEAD 2

  20. Preliminary results – 2000 Feb 4th 5 day acc. RUNOFF ERA 40 GFS reforecast 15 ensembles avg LEAD 1 LEAD 1 LEAD 2 LEAD 2

  21. Preliminary results – 2000 Feb 4th Basin Avg Hydrologic Variables Prediction (ERA40 in red, GFS in black ) Zambeze Basin, Africa NO BIAS CORRECTION BIAS CORRECTION

  22. Preliminary results – 2000 Feb 4th Basin Avg Hydrologic Variables Prediction (ERA40 in red, GFS in black ) Limpopo Basin, Africa NO BIAS CORRECTION BIAS CORRECTION

  23. Preliminary results – 2000 Feb 4th Basin Avg Hydrologic Variables Prediction (ERA40 in red, GFS in black ) Colorado Basin, North America NO BIAS CORRECTION BIAS CORRECTION

  24. Preliminary results – 2000 Feb 4th Basin Avg Hydrologic Variables Prediction (ERA40 in red, GFS in black ) Ganges Basin, Asia NO BIAS CORRECTION BIAS CORRECTION

  25. Preliminary results – 2000 Feb 4th Basin Avg Hydrologic Variables Prediction (ERA40 in red, GFS in black ) Elbe Basin, Europe NO BIAS CORRECTION BIAS CORRECTION

  26. Preliminary results – 2000 Feb 4th The bias correction : • beneficial for ALL input variables (P, Tavg,Wind) • does not substitute for missed precipitation/temperature peaks/lows BUT the correction for the occurrence of rain correction should help • brings consistency between the control run ( model or observations, or both) and the forecasts

  27. -4-Future Work

  28. Future Work Retrospective forecasting: • Finish up the small scale variability implementation in the code • Refined precipitation occurrence correction • Further evaluation of the retrospective forecasts: using GFS reforecasts and eventually archived ECMWF 10 day, monthly and seasonal forecasts • Predictions in forms of percentile and anomalies with respect to the climatology

  29. Future Work Operational real time forecasting: • Once a week • Use several climate model forecasts: • ECMWF 10 day forecast • ECMWF monthly forecast • ECMWF seasonal forecast • GFS 6-10 day forecast • Improvement of the initial conditions: e.g. assimilation of satellite soil moisture; snow

  30. Thank You! Credit: Philip Wijmans/ACT-LWF Trevo, Mozambique, February 2000 , http://gbgm-umc.org/umcor/00/mozphotos.stm

  31. Preliminary results – 2000 Feb 4th Snapshots Hydrologic Variables Prediction (ERA 40) 5 day acc. PRECIPITATION 5 day acc. RUNOFF

  32. Preliminary results – 2000 Feb 4th Snapshots Hydrologic Variables Prediction (ERA 40) 5 day avg. SOIL MOISTURE 5 day avg. SWE

  33. Preliminary results – 2000 Feb 4th 5 day acc. PRECIPITATION ERA 40 GFS reforecast ensemble #14

  34. Preliminary results – 2000 Feb 4th 5 day acc. RUNOFF ERA 40 GFS reforecast ensemble #14

More Related