13:45 〜 14:00
[ACG36-13] Statistical analysis of precipitation system characteristics observed by GPM/DPR over high-latitude land
キーワード：降水システム、衛星降水レーダ、全球降水観測(GPM)
A statistical analysis of precipitation system characteristics is conducted, using three-dimensional precipitation measurements by the dual-frequency precipitation radar (DPR) onboard the Global Precipitation Measurement (GPM) core observatory. The main focus of this study is to find a globally uniform method that efficiently describe the difference in the precipitation characteristics for different types of precipitation systems, and efficiently classify them.
We use the 2AKu version 06A product of GPM/DPR. The analysis period is July and January 2015-2020 for Northern and Southern Hemispheres, respectively, corresponding to the summertime of each hemispheres. The analysis domain is 65S-65N, and we especially focus on two land regions over 45N-65N and 20S-0S to compare the precipitation characteristics between the high-latitudes and tropics. Meso-scale boxes with 20 and 21 pixels (~100 km x 100 km) in along-track and cross-track direction, respectively, are set in the DPR swath, and several statistics for precipitation characteristics are calculated: Area, total precipitation, mean precipitation-top height, and so on.
Among many possible combinations of these statistics, we found that two statistics, stratiform area ratio (SAR) and stratiform precipitation efficiency (SPE), are efficiently describe the difference among the observed precipitation systems. The SAR is defined as the ratio of stratiform precipitation area to the total precipitation area in the box. The SPE is defined as the ratio of mean stratiform precipitation rate to the sum of it and mean convective precipitation rate. While organized precipitation systems such as squall-lines tend to have broad range of SAR but low SPE, precipitation systems partially related to extratropical cyclones tend to have high values of both SAR and SPE. Such difference in SPE between the two system types probably reflects the difference in precipitation production processes.
Precipitation systems can be classified into four categories by setting globally constant thresholds for SAR and SPE. Geographical distributions of dominant precipitation categories classified by the SAR-SPE plane clearly illustrates regional precipitation characteristics.
We use the 2AKu version 06A product of GPM/DPR. The analysis period is July and January 2015-2020 for Northern and Southern Hemispheres, respectively, corresponding to the summertime of each hemispheres. The analysis domain is 65S-65N, and we especially focus on two land regions over 45N-65N and 20S-0S to compare the precipitation characteristics between the high-latitudes and tropics. Meso-scale boxes with 20 and 21 pixels (~100 km x 100 km) in along-track and cross-track direction, respectively, are set in the DPR swath, and several statistics for precipitation characteristics are calculated: Area, total precipitation, mean precipitation-top height, and so on.
Among many possible combinations of these statistics, we found that two statistics, stratiform area ratio (SAR) and stratiform precipitation efficiency (SPE), are efficiently describe the difference among the observed precipitation systems. The SAR is defined as the ratio of stratiform precipitation area to the total precipitation area in the box. The SPE is defined as the ratio of mean stratiform precipitation rate to the sum of it and mean convective precipitation rate. While organized precipitation systems such as squall-lines tend to have broad range of SAR but low SPE, precipitation systems partially related to extratropical cyclones tend to have high values of both SAR and SPE. Such difference in SPE between the two system types probably reflects the difference in precipitation production processes.
Precipitation systems can be classified into four categories by setting globally constant thresholds for SAR and SPE. Geographical distributions of dominant precipitation categories classified by the SAR-SPE plane clearly illustrates regional precipitation characteristics.