2019 PMM Science Team
The National Aeronautics and Space Administration (NASA), Science Mission Directorate, Earth Science Division has selected new projects from the 2018 Precipitation Measurement Missions (PMM) Science Team focus area solicitation. PMM projects focus on investigations related to satellite observations of precipitation using measurements from, but not limited to, the Global Precipitation Measurement (GPM) Core Observatory, GPM mission constellation partner spacecraft, and the Tropical Rainfall Measuring Mission (TRMM). Specifically the PMM program supports three types of investigations: (1) The continued enhancement and validation of GPM and TRMM retrieval algorithms; (2) The use of satellite and ground measurements for physical process studies to gain a better understanding of precipitation, the global water cycle, climate, weather, and/or concomitant improvements in numerical models from cloud resolving to climate scales; and (3) The development of methodologies for improved hydrological modeling and applications of these satellite measurements.
NASA received a total of 130 proposals and has selected 40 for funding. The total funding from NASA anticipated for these investigations is approximately $15.6 million over three years. The selected investigations are listed below, including Principal Investigator, institution, title, and abstract. Co-Investigators are not listed here. Please note that eight other PIs from the 2016 PMM call have been approved to continue their activities through the NASA Center Internally Funded Scientist Model (IFSM) Work Packages as listed at https://pmm.nasa.gov/PMM-science-team
Last Name | First Name | Affiliation | Proposal Title |
---|---|---|---|
Adams | Ian | Goddard Space Flight Center | Scattering Assessment for Precipitating Particles (SAPP): Evaluating and Characterizing Hydrometeor Habit and Scattering Models |
Barros | Ana | Duke University | Microphysics, Vertical Structure and Scaling of Orographic Precipitation Across the Global Tropics |
Berg | Wesley | Colorado State University | Enhancing Consistency and Quantifying Precipitation Uncertainties for an Evolving Radiometer Constellation |
Chandrasekar | Chandra V. | Colorado State University | GPM Global Observations and Precipitation Microphysics: Algorithm Support, Enhancement, Cross Validation, and Application |
Del Genio | Anthony | NASA Goddard Space Flight Center | Analyses of Organized Convective System Sizes, Durations and Diabatic Heating Profiles to Inform GCM Development |
Durden | Stephen | Jet Propulsion Laboratory | DPR Retrievals over Land – Validation and Improvement |
Fenni | Ines | University of California, Los Angeles | Efficient and Accurate Calculation of Single-Scattering Properties of Realistic Hydrometeors for Better Interpretation of Microwave Observations |
Foufoula-Georgiou | Efi | University of California, Irvine | Improving GPM Passive Microwave Retrieval and Multi-Sensor Merging: a Nonlocal Formulation Accounting for the 3D Structure of Rain |
Funk | Chris | University of California, Santa Barbara | Ag Out – An Enhanced IMERG-based Agricultural Outlook System to Support Food Security and Agriculture in the Developing World |
Gebremichael | Mekonnen | University of California, Los Angeles | Improved Application of GPM IMERG Rainfall for Maximizing Power Generation in East Africa |
Grecu | Mircea | Morgan State University | Improved Detection and Quantification of Precipitation by the TRMM/GPM Combined Algorithm |
Heymsfield | Gerald | NASA Goddard Space Flight Center | Organizational and Structural Characterization of Precipitating System in Cold and Warm Regimes over Orographic Regions Using Observations and Models |
Kidd | Christopher | University of Maryland, College Park | Advancing Precipitation Retrievals from Cross-Track Passive Microwave Sensors |
Kim | Min-Jeong | Morgan State University | Satellite Data Assimilated 4D Global Precipitation Products from the GEOS System in Support of the GPM Mission |
Kirschbaum | Dalia | NASA Goddard Space Flight Center | Characterizing and Communicating Global IMERG Error Estimates for End User Applications |
Kirstetter | Pierre-Emmanuel | University of Oklahoma, Norman | Bridging the Global Precipitation Measurement (GPM) Level II and Level III precipitation Using Multi-Radar/Multi-Sensor-GPM (MRMS-GPM) |
Kulie | Mark | University of Wisconsin, Madison | GPM Snowfall Retrieval Improvements: A Multifaceted Approach Using New Algorithm Components and Ground-Based Observations |
Kummerow | Christian | Colorado State University | Understanding GMI Observations in Orographic Precipitation Rain and Snow |
Li | Xiaowen | Morgan State University | Active Convective Cores and Their Organization Observed by GPM Satellite and Applications to Improving Cloud-Resolving Simulations |
Liao | Liang | University of Maryland Baltimore County | Studies on Single- and Dual-Wavelength DPR Retrievals: Algorithm Development, Evaluation and Validation |
Liu | Chuntao | Texas A&M University - Corpus Christi | Toward Monitoring Global Intense Convection Using Assive Microwave Satellite Observations |
Liu | Guosheng | Florida State University | Improving Algorithm Components Related to Ice and Snow for GPM Precipitation Retrievals |
Mace | Gerald | University of Utah, Salt Lake City | Surface-Observed Precipitation over the Southern Ocean from the RV Investigator: Evaluation of Processes and Comparison with GPM |
Martin | Elinor | University of Oklahoma, Norman | Analysis of TRMM-GPM Observations to Improve Process-Level Understanding and Modeling of Precipitation and Latent Heating in Tropical Easterly Waves |
Matsui | Toshihisa | University of Maryland, College Park | Systematic Storm-Scale Simulations and Observations from the NASA Wallops Precipitation Research Facility |
McPartland | Linette | Goddard Space Flight Center | Using GPM in an Optimal Estimation Lagrangian Framework (OELaF) to Quantify Moisture Transport in Arctic Cyclones |
Nesbitt | Stephen | University of Illinois, Urbana-Champaign | Using GPM Ground Validation Data for Improved Precipitation Retrievals of Ice and Mixed Phase Precipitation |
Oreopoulos | Lazaros | Goddard Space Flight Center | Combined Analysis of GPM and MODIS Datasets to Unveil the Climatological Relationships Between Clouds and Precipitation |
Pettersen | Claire | University of Wisconsin, Madison | Leveraging GPM and Ground-Based Measurements to Examine High-Latitude Extreme Precipitation |
Rapp | Anita | Texas A & M, College Station | Towards Understanding Variability in Precipitation-Anvil Area Relationships |
Reed | Kevin | State University of New York, Stony Brook | Quantifying the Link Between Organized Convection and Extreme Precipitation |
Rutledge | Steven | Colorado State University | Cloud Microphysical Studies and Precipitation Estimation Using GPM |
Schumacher | Courtney | Texas A & M, College Station | Analysis of Overturning Meridional Circulations Across the Tropics Using TRMM PR and GPM DPR Observations and a GCM Precipitation Radar Simulator |
Tanelli | Simone | Jet Propulsion Laboratory | Experimental Solver for DPR measurements Affected by Higher-Order Effects |
Tavakoly | Ahmad | University of Maryland, College Park | Enabling the U.S. Army Streamflow Prediction Tool to Utilize GPM Products in Operation |
Thompson | Elizabeth | University of Washington, Seattle | Comparison of Oceanic Acoustic Rain Measurements with Downscaled IMERG Rainfall for the Study of Air-Sea Interaction |
Turk | Francis | Jet Propulsion Laboratory | Establishing Self-Consistency Amongst Precipitation Estimates from Constellation Radiometers to Account for Surface and Environmental Variability Throughout the TRMM+GPM Era |
Williams | Christopher | University of Colorado, Boulder | Analyzing NASA Ground Validation Observations to Quantify the Impact of Precipitation Non-Uniform Beam Filling (NUBF) on Satellite Rainfall Retrieval Algorithms |
Wood | Norman | University of Wisconsin, Madison | Investigating Orographic Snowfall Processing over Complex Terrain on the DPR Domain |
Zhang | Fuqing | Pennsylvania State University | Advanced Hurricane Analysis and Prediction Through Convection-Allowing Ensemble Assimilation of Multi-Sensor All-Sky Satellite Radiance Observations |