Research and Operational Application of TRMM- Based, Fine Time Scale Precipitation Analyses R.F. Adler 1, G.J. Huffman 1,2, D.T. Bolvin 1,2, S. Curtis 3, G. Gu 1,4, E.J. Nelkin 1,2 1: NASA/GSFC Laboratory for Atmospheres 2: Science Systems and Applications, Inc. 3: East Carolina University 4: UMBC Goddard Earth Sciences and Technology Center Outline 1.TRMM Status 2.The MPA 3. Examples 4. Planned Enhancements

1. TRMM STATUS – TRMM Version 5 Ocean Rainfall Previous operational version for TRMM standard products ~20% range between radar and passive microwave ocean estimates

1. TRMM STATUS – TRMM Version 6 Ocean Rainfall Test Results (Not Final Versions) ~5% range between radar and passive microwave ocean estimates Processing/reprocessing for Version 6 began in May 2004 May 1998 August 1998

1. TRMM STATUS – Future Operations TRMM has evolved from an experimental mission into the core satellite for a constellation preceding and evolving into GPM. PR, TMI, VIRS, LIS all working nominally; spacecraft systems in excellent shape. In Spring 2004 NASA decided to end TRMM; however, outcry from science community resulted in continuation until end of 2004 and review by National Academy of Science (8-10 Nov.). National Academy will recommend TRMM future based on value of data for science and operational forecasting for 1) TRMM ops. through 2005, with a controlled re-entry using134 kg of fuel; or 2) use of all 134 kg of fuel for science operation, which would extend potential mission life to ~2011; overlap with GPM possible (GPM launch in 2010). Flight operations cost for TRMM: $4M/yr (full cost). NASA safety organization does not require TRMM controlled re-entry.

2. THE MULTI-SATELLITE PRECIPITATION ANALYSIS (MPA) TRMM by itself yields sparse coverage: TRMM PR (red) + TRMM TMI (cyan) Long-term microwave record covers ~40% of 20°N-S in 3 hr: + SSM/I (3 sat.; yellow) New microwave satellites raise + AMSR-E (blue) coverage to ~80% of 20°N-S in 3 hr:+ AMSU-B (3 sat.; green) IR 50°N-S, missing at higher latitudes(black)

Instant- aneous SSM/I TRMM AMSR AMSU 30-day HQ coefficients 3-hourly merged HQ Hourly IR Tb Hourly HQ-calib IR precip 3-hourly multi-satellite (MS) Monthly gauges Monthly SG Rescale 3-hourly MS to monthly SG Rescaled 3-hourly MS Calibrate High-Quality (HQ) Estimates to “Best” Merge HQ Estimates Match IR and HQ, generate coeffs Apply IR coefficients Merge IR, merged HQ estimates Compute monthly satellite-gauge combination (SG) 30-day IR coefficients 2. THE MPA – Flow Diagram “Best” in HQ is TMI for real- time; TCI for non-real-time Green shading done async in real time, trailing avg. Blue shading only done non-real time, adds value Cyan boxes are inputs Yellow boxes are calibration coefficients Orange boxes are products

2.THE MPA – Detailed Example Hurricane Isabel; microwave swaths in light grey

3. EXAMPLES – Accumulation from Tropical Storms Affecting the U.S. Mainland in 2004 Order of appearance: Alex, Bonnie, Charlie, Gaston, Frances, Ivan, Jeanne, Matthew

3. EXAMPLES – Near-real-time analysis of flooding event in Hispaniola, May 2004 A minor low pressure tracked north, unleashing >450 mm of rain in south-central Hispaniola. Kevin Laws (NOAA FEWS-Net) had reviewed the MPA-RT and CMORPH analyses by 12Z 26 May. Hourly IR product

3. EXAMPLES – Hispaniola flooding (cont.) Further analysis showed the following; correctly alerted to a problem amounts likely too high by a factor of ~2 Re-doing the IR calibration by including data from the event days gave a more reasonable answer.

3. EXAMPLES – Potential-Flood Monitoring Product simple thresholds for 1-, 3-, 7- day accumulations oceans are masked out focuses attention on potential problems updated on the Web daily 7-day 3-day1-day Typhoon Tokage snapshots from 22 October 2004 flooding and mudslides in western Japan 67 deaths, 21 missing >23,000 dwellings destroyed

3. EXAMPLES – Updates to the El Niño Onset Index (EOI) in Real Time The basic index is a measure of the spectral power in the day band of a wavelet analysis in the gradient of precipitation in the east-central Indian Ocean. [Gradient is taken as the difference of the averages over the two boxes shown below; white is low climatological precipitation, yellows and reds are high.] The index is only considered (black) when the trailing 6-month-average gradient is positive (higher precip near Sumatra). The EOI has correctly foreshadowed 6 of last 7 El Niño events with no false alarms. The EOI is computed with the MPA, then with the GPCP Satellite-Gauge combination when available. NINO3,4 ENSO Index EOI

3. EXAMPLES – West African Monsoon The seasonal cycle of precipitation is shown, with zonal winds at three levels for comparison. Latitudinal values are averaged over 10°W-10°E for the years

WestwardWestwardEastwardEastwardWestwardWestwardEastwardEastward 3. EXAMPLES – West African Monsoon (cont.) Spectral analysis of West African rainfall as a function of latitude for (a) early, and (b) late monsoon season. Emphasis shifts north and to westward-propagating waves, but a stationary component is still important.

4. PLANNED ENHANCEMENTS The Real-Time MPA IR calibration will be done more frequently (every time?). The Real-Time MPA will get a bias adjustment scheme, likely based on prior gauge data. We need to make progress on practical approaches to providing gridded error estimates, and combining disparate precip estimates. TOVS and AIRS will be used to extend the MPA concept to higher latitudes. prior success in GPCP One-Degree Daily product We plan to apply MPA concepts to the GPCP products. We plan to apply the MPA to GPM-era data.

Web sites: RT: ftp://aeolus.nascom.nasa.gov/pub/merged or RT imagery: 3B42RT subsetting: Version 6:

3. EXAMPLES – Hispaniola flooding (cont.) Potential flood monitoring product simple thresholds for 1-, 3-, 7-day accumulations oceans are masked out focuses attention on potential problems updated on the Web daily 7-day 3-day1-day

3. EXAMPLES – USAID, USGS Use the Real-Time for Crop Forecasts the USAID Famine Early Warning System Network (USAID/FEWS- Net) is a joint program of DoS, USGS, NOAA goal is crop and weather assessment around the world TRMM real-time Multi-Satellite Precipitation Analysis (MPA) tested in 2003; first results are promising MPA now in quasi-operational use in Central America, Africa, and western Asia deficits in Water Requirement Satisfaction Index match field reports of reduced yields figure courtesy of G. Senay, USGS/EDC timing of rain arrivals match field reports figure courtesy of G. Senay, USGS/EDC

3. WHAT’S LEFT TO DO? (cont.) Example CPC daily validation page (Janowiak); note variety of statistical measures.

1. INTRODUCTION (cont.) Bowman, Phillips, North (2003, GRL) validation by TOGA TAO gauges 4 years of Version 5 TRMM TMI and PR 1°x1° satellite, 12-hr gauge, each centered on the other each point is a buoy the behavior seems nearly linear over the entire range wind bias in the gauges is not corrected Slope = 0.96Slope = 0.68