Improvement of the orographic/nonorographic rainfall classification scheme with a static stability information in the GSMaP algorithm

Munehisa K. Yamamoto and Shoichi ShigeGraduate School of Science, Kyoto University

IntroductionThe orographic/nonorogrpahic rainfall classification scheme is implemented to the latest

standard version (V6) of Global Satellite Mapping of Precipitation (GSMaP) algorithm for passive microwave radiometers. The scheme consists of orographically forced upward motion and moisture flux convergence (Q) given at surface. The scheme well operate over the Asian region dominating shallow orographic rainfall. However, it is not always suited for North America because deep convective systems are also detected from the scheme. Therefore, the scheme is switched off for regions where strong lightning activity occurs in the rainfall type database. In order to improve the orographic rainfall detection, an static stability information of lower troposphere (dT/dz_low) is examined to the scheme instead of Q suggested by Shige and Kummerow (2014, Spring Meeting of the Meteorological Society of Japan).

Indices of orographic rainfall detectionOrographically forced upward motion Moisture flux convergence

Static stability information h: Elevation derived from SRTM30（averaged over a horizontal length scale of 50 km）

u, v: Horizontal surface wind from GANALq: Water mixing ratioTv: Virtual temperature

A case of heavy rainfall in Typhoon Morakot (2009)(a) w (b) Q (c) dTv/dz

[m s-1] [10-6 s-1][K km-1]

Fig. 3 Horizontal distributions of (a) orographically forced upward motion, (b) moisture flux convergence, and (c) static stability for lower troposphere on 8 Aug. 2009 18UTC.

Fig. 4 Horizontal distributions of near surface rainfall rate from (a) TRMM PR, (b) GPROF, (c) GSMaP1, (d) GSMaP2, and (e) GSMaP3. The orbit number is #66832, 20:38UTC.

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PR: TRMM PR2A25 near surface rain（as a truth data）GPROF:TRMM TMI2A12surface rainGSMaP1: GSMaP without the orographic rainfall schemeGSMaP2: GSMaP with the orographic rainfall scheme (w > 0.01 m s-1, Q > 0.3 10-6 s-1)GSMaP3: GSMaP with the orographic rainfall scheme (w > 0.01 m s-1, dTv/dz > -5.5 K km-1)（GSMaP2 is almost the same as GSMaP standard product (V6))

Global distribution of dTv/dz

Difference in monthly mean rainfall amount（GSMaP−PR）(a) GSMaP2-PR (b) GSMaP3-PR

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Fig. 5 Differences in monthly mean rainfall amounts between PR data and those obtained with (a) GSMaP2 and (b) GSMaP3.

Fig. 1 Distributions of dTv/dz at 8 Aug. 2009 18UTC.

Fig. 2　Precipitation profile models for convective (upper column) and stratiform (lower column) rainfall used to produce LUT (titled as original) for nonorographic rainfal l retrieval and for orographic rainfall retrieval within 5°−5° box over 15 °−20°N, 70°−75°E for GSMaP2 and GSMaP3.

CSI based on different rainfall thresholds

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Fig. 6 Critical Success Index (CSI) for June-August 2007 based on different rainfall threshods for GPROF (blue), GSMaP1 (green), GSMaP2 (yellow), and GSMaP3 (red) algorithms over land regions in (a) Asia (15°−20°N, 70°−75°E) and (b) the United States and Mexico (15°−40°N, 115°−90°W).

Fig. 7 Difference in zonal mean latitudinal rainfall with PR data for JJA 2007 for the GPROF (blue), GSMaP1 (green), GSMaP2 (yellow), and GSMaP3 (red) algorithms over (a) global land, (b) Africa (20°W−60°E), (c) Asia/Oceania (65°E−160°E), and (d) America (50°W−30°E).

Difference in zonal mean latitudinal rainfall

Y a m a m o t o , M . K . a n d S . S h i g e ( 2 0 1 4 ) : I m p l e m e n t a t i o n o f a n orographic/nonorographic rainfall classification scheme in the GSMaP algorithm for microwave radiometers. Atmos. Res. (in print)

http://dx.doi.org/10.1016/j.atmosres.2014.07.024

P1.20

Distribution of dTv/dz (Fig. 1 ) shows tha t the land regions over Asia have relatively stable conditions ( > - 5 . 5 K k m - 1 ) w h i l e r e l a t i v e l y u n s t a b l e conditions (< -6.0 K km-1) appears over the Siera Madre Mountains around the Un i t ed S ta tes and Mexico. Considering the s o m e c a s e s o f h e a v y rainfall, a threshold of the orogrpahic rainfall condition is set as > -5.5 K km-1.

In the heavy orographic rainfall case over Taiwan caused by Typhoon Morakot (2009) (Fig. 4a), large Q extends over the e n t i r e T a i w a n ( F i g . 3 b ) , relatively stable conditions are found over nor th -wes t to south-east. The ra in fa l l amount f rom G P R O F ( F i g . 4 b ) a n d GSMaP1 (Fig. 4c) d id not estimated for heavy rainfall. However, GSMaP3 (Fig. 4e) can estimate the heavy rainfall as well as GSMaP2 (Fig. 4d).

The vertical profiles of rainfall over the western coast of Indian sub-continent for GSMaP2 (Fig.2 center) and GSMaP3 (Fig. 2 right) are lower than those for original tain type (Fig. 2 left). The same profiles but every 0.5 K k-1 from -6 K km-1 to -4.5 K km-1 shows that the dTv/dz is more s tab le , the ver t ica l p ro f i les become lower (not shown).There is few case under the orographic rain condition over the western coast of the Uni ted States and Mexico.

Apparent underestimations occur along the WesternGhats Mountains in India and along the Arakan Mountains in Myanmar for both GPROF and GSMaP1. We clearly see that both GSMaP2 (Fig. 5a) and GSMaP3 (Fig5. b) captured rainfall maximums not only over the weste coast of India, but also some orographic regins that showed severe underestimation us ing GSMaP1. Moreover , the ra in fa l l maximum can be found over the inland regions for GSMaP3. The critical success index (CSI) over regions in Asia shows that GSMaP2 is higher than GSMaP3. This may be due to false alarm for some areas. However, we can see that GSMaP3 is better score than GSMaP2 from the differences between zonal mean latitudinal rainfall from PR data (Fig. 7).

SummaryThe global distributions of dT/dz_low showed that more stable conditions are found

over the western coast of the Indian subcontinent in which shallow orographic rainfall dominates. Less stable condition appears over the North America and Africa in which deep convective precipitation frequently occurs. The GSMaP rainfall estimates with the scheme using Q and dT/dz_low are compared with the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data for some cases appeared heavy orographic rainfall and seasonal mean rainfall. The orographic heavy rainfall area detected by dT/dz_low is more accurate than that by Q. A verification score and zonal mean rainfall amounts obtained from the TRMM Microwave Imager are better agreement with those from the PR over Asian region. We suggest that more simple detection of orographic rain condition is available using the static stability than the previous orographic classification scheme.