Bob Joyce : RSIS, Inc. John Janowiak : Climate Prediction Center/NWS Phil Arkin : ESSIC/Univ. Maryland Pingping Xie: Climate Prediction Center/NWS 0000Z,

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Presentation transcript:

Bob Joyce : RSIS, Inc. John Janowiak : Climate Prediction Center/NWS Phil Arkin : ESSIC/Univ. Maryland Pingping Xie: Climate Prediction Center/NWS 0000Z, 30Nov 2001 Global, Microwave-based, Precipitation Analyses from Satellite at ½ Hr & 8 km Scales 0030Z, 30Nov Z, 30Nov Z, 30Nov 2001 TRMM AMSU SSM/I

Two primary types of precipitation algorithms: Infrared (GPI, convective-stratiform, OPI)  (-) indirect - can only sense cloud-top temperature  (+) very good sampling characteristics (time & space) Passive Microwave (SSM/I, MSU, AMSU):  (+) considerably better estimate than IR – “sees” thru cloud and can directly sense information from hydrometeors  (-) poor temporal sampling (polar orbit platforms)

Pessimist: “The food here is terrible!” Optimist: “Ah yes, but such huge portions!” Microwave & IR data Combined statistically Pragmatist: Meld together the IR & microwave data to take advantage of the strengths of each  Vicente (U. Wisc.)  Turk (NRL, Monterey)  Adler and Huffman (NASA/GSFC)  Kuligowski (NOAA/NESDIS)

Our Approach  Use the IR and microwave data but do NOT mix them  Use the IR only as a transport and “morphing” mechanism  Here we use precipitation algorithms developed by Ferraro (NESDIS: AMSU-B & SSM/I) and Kummerow (CSU: TRMM) but method is algorithm independent.  Enables the generation of spatially and temporally complete precipitation fields while maintaining a pure, albeit manipulated, microwave-based analysis

2.5 o “Advection vectors” are computed from IR for each 2.5 o gridbox andall microwave pixels contained in that grid box are propagated in the direction of that vector

precip 2.5 o IR Spatial Correlation Domain for Computation of “Advection Vectors” IR (t+0)IR (t+1/2 hr)

Advection Rates for 00Z 30 Nov 2001 ZONAL MERIDIONAL |………………. EAST …………|………… WEST ………………| (pixels/hour) |………………. NORTH ……...|…………SOUTH ………………| (pixels/hour)

Actual Microwave Observations t+0t+2 hrst+1/2 hrt+1 hrt+1.5 hr t+ 1/2 hrt+1 hrt+1.5 hr IR Time interpolation weights Interpolated “observations” t+1/2 hrt+1 hrt+1.5 hr

“Validation”

Initial microwave passNext microwave pass Valid time is 5 hours after the “initial” pass and 2.5 hours before the “next” pass Microwave estimates propagated byIR. Microwave data from overpasses between the “initial” and “next” overpasses were withheld in this test to assess the performance of the technique. Validating analysis is in the lower-center frame. Validating analysis, ie. the microwave pass between the “initial” and “next” microwave passes that was withheld.

SatelliteRadar

Microwave-Advected GPCP “1DD” GPI (IR)

Potential Applications  Real-time quantitative global precipitation monitoring  Disaster mitigation  Provide timely updates for U.S. interests abroad  Numerical model initialization & validation  Improve diurnal cycle in the models  Diagnostic studies: diurnal cycle in particular

 Account for precipitation that forms and dissipates between microwave overpasses  Refine advection vector computation  Continue validation effort  Test/Include new precipitation products as they become available – method is not restricted to particular algorithms or sensors Continuing Work

Finis

mm/day Figure 5

Initial microwave passNext microwave pass Microwave propagated by IR Another test – this one is over The South Atlantic Convergence Zone (SACZ) Valid time is 1.5 hours after the “initial” pass and 6 hours before the “next” pass Validating microwave data

(t + 0 hr) 5 o + 12 pixels Spatial Lag Correlation of IR pixel temperature among nearby 5 o x 5 o grid boxes to determine propagation direction (t + 1/2 hr) 5o5o 5o5o