1. Oct 2012 The FEWS NET’s Rainfall Enhancement Process Chris Funk 1, Pete Peterson 2, Marty Landsfeld 2, Andrew Verdin, Diego Pedreros 1, Joel Michaelsen 2, Greg Husak 2, Bolesto Romero 2 1 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD. FEWS NET. 2 Climate Hazard Group, UCSB/Geography dpt. 3 Food Security Early Warning System (FEWS NET). 4 UCSB Geography Dpt. 5 Universidad de Costa Rica. Abstract:. 2 - Use FCLIM to Unbias Satellite Estimated Rainfall Definitions: A - Validation Comparison of the different stages of the rainfall improving process: TRMM, FTIP and FTIP plus available stations. B – Validation Analysis FEWS NET uses rainfall accumulations from the Tropical Rainfall Measuring Mission (TRMM) estimates produced by NASA (0.25 degree, c.25 km, spatial resolution) to evaluate available precipitation for rain fed agriculture. A preliminary comparison of TRMM and independent stations reveals large differences between the two (Figure 1). The spatial resolution of TRMM estimates is particularly a concern, given the narrow land mass and the topographic dynamics in regions such as Central America and the Caribbean. In response to both the low correlation and coarse resolution of the TRMM estimates, FEWS NET sought to enhance satellite estimated rainfall by complementing it with higher spatial resolution climatologic fields along with other satellite and ground station data. Satellite Estimated Rainfall from the Tropical Rainfall Measuring Mission (TRMM), July 21-31, 2009. 1 - Develop a Climatology A - FCLIM-TRMM – IR Precipitation (FTIP) The FTIP combines percent anomalies from TRMM and IR and multiplies it by the FCLIM. B - Climate Hazards IR Precipitation (CHIRP) CHIRP combines two sources of IR data, B1 (1981 – 2008) and CCP–IR (2000 – present). It builds monthly models of rainfall trained on TRMM-V7 and derives coefficients a and b, such that: rain rate = a * CCD + b (IRP) where CCD is the percentage of observation where IR temp < threshold CHIRP (1981-present) = FCLIM * (IRP %normal) FCLIM: FEWS Climatology – a climatological field calculated using multivariable regression TRMM: Tropical Rainfall Measurement Mission satellite-derived rainfall estimate TRMM-RT: real time TRMM FTIP: FEWS NET-TRMM-IR-Precipitation derived from TRMM, IR and FCLIM. CHIRP: Climate Hazards Group IR Precipitation 3 - Station Database FTIP pentad (5-day) accumulations Rainfall values mm/pent FTIP plus available station data results in the Improved Rainfall Estimate (IRE ) Daily Precipitation (from 1832) number of stations = 120,898 number of records = 955,887,417 Monthly Precipitation (from 1697) number of stations = 142,384 number of records = 45,748,550 Sources: Data were prioritized based on their origins. Data Sources including national met services, GHCN, GSOD, GTS and others The FEWS Climatology (FCLIM) is derived from station averages combined with rainfall predictors such as topography (elevation, slope, aspect) and geography (lat/long, proximity to coast). Relationship between rainfall and Elevation We first select define window of interest, good spatial coverage with stations and similar topography. Select best predictors for the region of interest. Search for available stations within a radius (1.5 to 5 degrees) elevation Latitude Satellite rainfall Radius=150km Extract value of predictors at each station location. Create a simple linear model, and use the parameters to estimate the value at a given pixel Define region Select predictors Estimate rainfall value for each pixel Estimate value for a pixel FCLIM February Master station, first priority support station, lower priority 10Km radius The FTIP (FEWS NET–TRMM-IR-Precipitation), July 21-31, 2009. FCLIM dek X 3B42 Dek X (TRMM) Average 3B42 X IR Dek X Average IR X IR % anomalyTRMM % anomalyFCLIM (Climatology) CHIRP 2012.10.6 0.05, global, unbiased, rainfall pentad (mm) with 2 days lag. Funk, C., G. Husak, et al. (2007). "Third generation rainfall climatologies: satellite rainfall and topography provide a basis for smart interpolation, Crop and Rangeland Monitoring Workshop.“ Verdin, J. and R. Klaver (2002). "Grid cell based crop water accounting for the Famine Early Warning System " Hydrological Processes 16: 1617-1630. Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F. & Wolff, D. B. 2007: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales. Journal of Hydrometeorology 8, 38-55. Janowiak J. E., R. J. J., and Y. Yarosh. 2001: A Real-Time Global Half-hourly Pixel-Resolution Infrared Dataset and Its Applications. Bull. Amer. Meteor. Soc. 82, 205-217. References