Wednesday, 25 January 2012: 11:00 AM
Improving Precipitation Retrieval Using Total Lightning Data : A Multi-Sensor and Multi-Platform Synergy Between GOES-R and GPM
Room 257 (New Orleans Convention Center )
GOES-R will fly two major weather instruments : the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), defining remarkable advances in spatial, temporal and spectral resolutions from today's geostationary satellite constellation. GOES-R ABI Quantitative Precipitaion Estimation (QPE) algorithm requires microwave-based rain rates as a calibration target, where the upcoming Global Precipitation Measurement Mission (GPM) satellite will be of great value. The microwave rainfall retrievals over land have made significant strides in the last few years, but the retrieval algorithms still have room for improvements. The better microwave rain rate estimates will result in better ABI QPE. Microwave precipitation signals are sensitive to the presence of ice, which is the key parameter for lightning generation. Lightning activity is also a good indicator of deep convection. One of the main difficulties in microwave rainfall retrievals over land is to delineate convective and stratiform precipitation from precipitating clouds. In this matter, collocated total lightning observations can improve the microwave segregation of precipitation in convective and stratiform, and also refine the rainfall retrievals necessary for the GOES-R QPE. In this scope, we focus on using the lightning measurements to provide a constraint on the microwave convective-stratiform index (CSI), which is the convective rain fraction in a pre-defined resoulution. To achieve this goal, we use TRMM Microwave Imager (TMI), TRMM Precipitation Radar (PR), and TRMM Lightning Imaging Sensor (LIS) as proxy data for GPM and GLM, respectively. Currently, the TMI CSI is trained with the TRMM PR using radiometer radiances and polarization inputs as predictors. The TRMM precipitation radar has the advantage of higher resolution and the ability to actively sense hydrometeors through the depth of the column. The LIS sensor operates as a lightning event detector, where several events are grouped in space and time to determine a “flash”. Flash initiation rate is related to the recharging rate of a local electric field, which happens most readily where active inter-hydrometeor charge separation is taking place, i.e., in deep convective cores. We examine multiple years of LIS total radiances and flash rates, in conjunction with the TMI and PR co-located data. The relationships between lightning, convective characteristics and ice scattering intensity over land as measured by radiances and flash occurrences and rates, radar reflectivity vertical structures, and 85 GHz brightness temperatures (TB), are analyzed. From four years (2002-2005) of TRMM version 6 data and fourteen millions rain observations over land, 7% shows lightning activities which is defined by LIS flash rate greater than 0; 13.5% of the lightning occur in stratiform and 86.5% in convective. In general, radar reflectivity increases with increasing flash rate both on the surface and the vertical structure, with the higher reflectivity for convective than stratiform. For rain systems without lightning, 85 GHz TB peaks at 260 K for both convective and stratiform and drop off sharply to lower brightness temperatures. For rain systems with lightning activity, 85 GHz TB are uniformly distributed from 100-280 K for convective and narrowly distributed from 200-280 Kelvin for the bulk of stratiform. Based on analysis of the relationships between lightning flash rate and rain type distribution, a method that incorporates lightning flash rates to classify microwave convective fraction, which is correlated with the likelihood of convection, is developed. The new method clusters TMI TB with respect to LIS flash rates. For example, for a given set of TMI TB, the new classification yields higher probability of convection with more rigorous lightning activity as indicated by LIS flash rates. This lightning-microwave convective fraction and rain rate estimates are evaluated using 2006-2009 TRMM data. The general conclusion is that lightning data contain useful information in microwave convection fraction and microwave estimated rain rate, particularly in moderate to intense convection. Preliminary result shows a reduction of about 5% in the root-mean-square-error of TMI convective fraction and rain rate estimates from using LIS flash rates.