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DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20111
Global Precipitation Products for Data-Denied Regions
Stanley Q. KidderCenter for Geosciences/Atmospheric Research
Colorado State University
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20112
Outline
Review of current satellite rainfall methods (Add sites to be covered)
Outline of CIRA products Blended RR Blended TPW ORI
Critique of current RR methods/outline of possible techniques Need motion Need accumulation Need orographic enhancement Need TPW for forecasts
The proposal
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20113
Importance
Detection of precipitation is critical for the success of military operations. Air operations at sea or over land, mobilization of heavy equipment on third world roads, operation of laser-based systems, and deployment of resources in flood-prone regions all rely on timely and accurate prediction of rainfall events.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20114
History
Because of its importance, precipitation has been estimated from satellite observation since the earliest weather satellites
Two (of many) sources of information about these early attempts: Barrett, E. C., and D. W. Martin, 1981: The Use of Satellite Data
in Rainfall Monitoring. Academic Press, New York. Kidder, S. Q., and T. H. Vonder Haar, 1995: Satellite Meteorology:
An Introduction. Academic Press, San Diego.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20115
Current “Real Time” Precipitation Sources
The University of California Irvine PERSIANN project (Sorooshian et al. 2000) (See http://chrs.web.uci.edu/persiann/)
uses GEO IR and visible imagery in a neural network system to produce global precipitation grids. The PERSIANN system has since been extended to use TRMM, NOAA and DMSP microwave data to “calibrate” higher resolution IR data.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20116
Current “Real Time” Precipitation Sources
The Climate Prediction Center’s CMORPH/QMORPH (Joyce et al. 2004) (See http://www.cpc.ncep.noaa.gov/products/janowiak/cmorph_description.html)
Based on microwave observations calibrated with TRMM data. Uses IR winds to move raining pixels between satellite obervations. QMORPH is the forecaster product, and moves precipitating pixels forward in time to the hour or half hour.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20117
Current “Real Time” Precipitation Sources
CIRA’s Blended Rain Rate (http://cat.cira.colostate.edu) Being developed for operational implementation at NESDIS
Blends data from currently six satellites (see next slide) Uses a histogram-matching technique to make it appear that all observations are from the same
instrument No motion.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20118
Current Blended RR Satellite Suite
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 20119
Regularly Spaced Constellation
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201110
Current “Real Time” Precipitation Sources
NASA Goddard’s TRMM Multi-satellite Precipitation Analysis (TMPA) (Huffman et al. 2007) (See http://precip.gsfc.nasa.gov/index.html)
Combines TMI , AMSR-E, and AMSU-B/MHS microwave measurements. Gaps are filled using IR data. No motion Latency is an issue (~5 hours)
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201111
Current “Real Time” Precipitation Sources
The NESDIS Hydro-Estimator (Scofield and Kuligowski, 2003) (See http://www.star.nesdis.noaa.gov/smcd/emb/ff/HydroEst.php)
Uses GEO IR data in a single channel algorithm GFS model low level humidity estimates to adjust for sub-cloud evaporation over arid regions. No microwave data are used.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201112
Current “Real Time” Precipitation Sources
The Naval Research Laboratory (NRL) Blended-Satellite Precipitation Technique (Turk and Miller 2005) (See http://www.nrlmry.navy.mil/sat-bin/rain.cgi)
uses GEO IR observations, calibrated using passive microwave observations, plus the microwave observations themselves (when available) to produce 3-hr rainfall accumulations.
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201113
Summary of the Current State
IR provides frequent, high-resolution observations but IR looks only at the outside of the cloud; precipitation must be inferred.
Microwaves view the precipitation-size droplets or crystals inside the cloud, but at lower frequency and resolution.
Current products are mostly aimed at instantaneous rainfall rates, whereas forecasters need accumulated rainfall
To calculate accumulation—given the motion of raining systems—some sort of propagation scheme must be employed
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201114
QMORPH 5-Day (6-hour)
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201115
QMORPH 1-Day (hourly)
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201116
Blended RR 5-Day (6-hourly)
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201117
Blended RR 1-Day (hourly)
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201118
5-Day Comparison
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201119
1-Day Comparison
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201120
From Kelly Howell’s Thesis
y = 0.0224x1.8551
R² = 0.9985
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
0 - 15 mm 15 - 30 mm 30 - 45 mm 45 - 60 mm 60 - 75 mm
Prob
. of P
reci
p.
TPW Range
Threshold = 0.1 mm hr-1
TPW might be useful for
determining how long precipitation
lasts
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201121
What Is Needed
3 hr accumulations Short-term forecast (nearcast) Motion Orographic enhancement
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201122
Blended Total Precipitable Water
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201123
06Z 14 Oct 2009
250 50 75 mm
Blended TPW (mm) and 850 hPa GFS Winds
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201124
Elevation (m)
0 1000 2000 3000 4000
Terrain
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201125
ORI TPW * V•H
Orographic Rain Index
TPW = Blended Total Precipitable Water advected to product time
V = 850 hPa GFS wind vector at product time
H = Terrain height
V•H terrain-induced vertical velocity
ORI moisture * liftUnits = mm * m/s
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201126
Observed precipitation (inches) 06Z Tue 13 Oct 15Z Wed 14 Oct
00Z 14 Oct 2009
250 +0 50 100 150 200
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201127
Observed precipitation (inches) 06Z Tue 13 Oct 15Z Wed 14 Oct
00Z 14 Oct 2009
DoD Center for Geosciences/Atmospheric Research at Colorado State University VTC 12 September 201128
Global Precipitation Products for Data-Denied Regions
We propose to develop a blended rain accumulation product which addresses some of these problems. In outline, the product might be constructed as follows:
1. The instantaneous satellite rain rate observations, both infrared and microwave, would be gathered for an integration period of perhaps three hours. (Though at first only microwave observations would be used.)
2. The instantaneous observations would be “calibrated” using histogram adjustment to a reference instrument, so that artifacts due to differing instruments would be lessened.
3. The rain observations would be propagated in time using model winds, and perhaps TPW values, which could possibly be used to estimate changes in intensity of the observed rain rates in time.
4. Rain accumulations during the analysis period would be calculated for each grid box of the analysis domain.
5. Terrain induced rain would be added to the accumulations.
6. Model forecasted rain accumulations could be used to modify/constrain the satellite-estimated accumulations.