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Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluationet al. 2018 ; Pettersen et al. 2020 ). Deeper cloud structures that are characteristic of midlatitude winter cyclones are generally easier for PMWs to detect due to strong scattering signals from ice particles and higher reflectivity values that can be detected by radars with reduced sensitivity. Shallow snowfall, however, presents unique PMW detection complexities at higher latitudes since its radiative signal can be difficult to discern over snow-covered surfaces. Depending on radar
et al. 2018 ; Pettersen et al. 2020 ). Deeper cloud structures that are characteristic of midlatitude winter cyclones are generally easier for PMWs to detect due to strong scattering signals from ice particles and higher reflectivity values that can be detected by radars with reduced sensitivity. Shallow snowfall, however, presents unique PMW detection complexities at higher latitudes since its radiative signal can be difficult to discern over snow-covered surfaces. Depending on radar
correlated to regional climate conditions. Subsequent versions of GPROF addressed this by constraining the TRMM (ocean only) GPROF retrievals by two environmental parameters, namely total precipitable water (TPW) and sea surface temperature (SST) ( Kummerow et al. 2011 ). Moving forward to GPM, these same techniques were adapted to land surfaces, by replacing the SST with the 2 m air temperature commonly available from forecast and reanalysis models. In a series of papers describing and testing the Cloud
correlated to regional climate conditions. Subsequent versions of GPROF addressed this by constraining the TRMM (ocean only) GPROF retrievals by two environmental parameters, namely total precipitable water (TPW) and sea surface temperature (SST) ( Kummerow et al. 2011 ). Moving forward to GPM, these same techniques were adapted to land surfaces, by replacing the SST with the 2 m air temperature commonly available from forecast and reanalysis models. In a series of papers describing and testing the Cloud
1987 ; Kemball-Cook and Weare 2001 ). GCMs have traditionally struggled to properly simulate the MJO, and inaccuracies in their simulated heating profiles are one possible factor ( C. Li et al. 2009 ). At smaller scales, LH is a fundamental energy source for the maintenance and intensification of tropical cyclones ( Schubert and Hack 1982 ; Nolan et al. 2007 ). Because it is an integral part of the phase changes of water, LH is closely tied to cloud systems and precipitation. And despite its
1987 ; Kemball-Cook and Weare 2001 ). GCMs have traditionally struggled to properly simulate the MJO, and inaccuracies in their simulated heating profiles are one possible factor ( C. Li et al. 2009 ). At smaller scales, LH is a fundamental energy source for the maintenance and intensification of tropical cyclones ( Schubert and Hack 1982 ; Nolan et al. 2007 ). Because it is an integral part of the phase changes of water, LH is closely tied to cloud systems and precipitation. And despite its
Enhancing PMW Satellite Precipitation Estimation: Detecting Convective Classinformation is limited to the lightning-active clouds and era of GLM satellite sensors. Fig . 2. Distributions of total precipitation fraction as a function of DPR-combined (V5) convective fraction. The x axis ranges from zero (fully stratiform) to one (fully convective) in 0.2 increments. Light blue: current operational GPROF (V5) retrieval; gray: DPR-combined (V5); bright blue: GPROF when provided DPR-combined information on convective/stratiform flag. Given the four-decade-long effort in linking PMW
information is limited to the lightning-active clouds and era of GLM satellite sensors. Fig . 2. Distributions of total precipitation fraction as a function of DPR-combined (V5) convective fraction. The x axis ranges from zero (fully stratiform) to one (fully convective) in 0.2 increments. Light blue: current operational GPROF (V5) retrieval; gray: DPR-combined (V5); bright blue: GPROF when provided DPR-combined information on convective/stratiform flag. Given the four-decade-long effort in linking PMW
( Thompson et al. 2008 ) was used to provide microphysical simulation of clouds that are connected to satellite observation operators in radiance data assimilation, and Noah land surface model was used in atmospheric and land coupled simulation as well as within LIS spinup process. Boundary forcing came from the Global Forecast System ( Whitaker et al. 2008 ). Hourly accumulated rainfall fields (currently NU-WRF EDAS does not facilitate output temporal resolutions finer than hourly) are generated at 3-km
( Thompson et al. 2008 ) was used to provide microphysical simulation of clouds that are connected to satellite observation operators in radiance data assimilation, and Noah land surface model was used in atmospheric and land coupled simulation as well as within LIS spinup process. Boundary forcing came from the Global Forecast System ( Whitaker et al. 2008 ). Hourly accumulated rainfall fields (currently NU-WRF EDAS does not facilitate output temporal resolutions finer than hourly) are generated at 3-km
, or clouds. We focus on the information that can be obtained from knowledge of the past precipitation state at the central location c and neighboring locations. This focus on past precipitation rather than multivariate drivers enables a relatively simple analysis of a single gridded dataset. Moreover, we assume that past precipitation somewhat integrates these other drivers, as it directly captures the duration and movement of events. Depending on a storm’s size, shape, speed, and direction of
, or clouds. We focus on the information that can be obtained from knowledge of the past precipitation state at the central location c and neighboring locations. This focus on past precipitation rather than multivariate drivers enables a relatively simple analysis of a single gridded dataset. Moreover, we assume that past precipitation somewhat integrates these other drivers, as it directly captures the duration and movement of events. Depending on a storm’s size, shape, speed, and direction of
