Object-Based Comparison of Data-Driven and Physics-Driven Satellite Estimates of Extreme Rainfall.

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects.

Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System.

Many existing models that predict landslide hazards utilize ground-based sources of precipitation data. In locations where ground-based precipitation observations are limited (i.e.

Using citizen science to expand the global map of landslides: Introducing the Cooperative Open Online Landslide Repository (COOLR).

Robust inventories are vital for improving assessment of and response to deadly and costly landslide hazards. However, collecting landslide events in inventories is difficult at the global scale due to inconsistencies in or the absence of landslide reporting. Citizen science is a valuable opportunity for addressing some of these challenges.

Satellite Precipitation Characterization, Error Modeling, and Error Correction Using Censored Shifted Gamma Distributions.

Satellite multisensor precipitation products (SMPPs) have a variety of potential uses, but suffer from relatively poor accuracy due to systematic biases and random errors in precipitation occurrence and magnitude. We use the Censored Shifted Gamma Distribution (CSGD) to characterize the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA), a commonly-used SMPP, and to compare it against the rain gage-based North American Land Data Assimilation System Phase 2 (NLDAS-2) reference precipitation dataset across the conterminous United States. The CSGD describes both the occurrence and the magnitude of precipitation.

THE GLOBAL PRECIPITATION MEASUREMENT (GPM) MISSION FOR SCIENCE AND SOCIETY.

The GPM mission collects essential rain and snow data for scientific studies and societal benefit.

A heuristic approach to global landslide susceptibility mapping.

Landslides can have significant and pervasive impacts to life and property around the world. Several attempts have been made to predict the geographic distribution of landslide activity at continental and global scales. These efforts shared common traits such as resolution, modeling approach, and explanatory variables.

So, how much of the Earth's surface covered by rain gauges?

The measurement of global precipitation, both rainfall and snowfall, is critical to a wide range of users and applications. Rain gauges are indispensable in the measurement of precipitation, remaining the standard for precipitation information across the Earth's surface for hydro-meteorological purposes. However, their distribution across the globe is limited: over land their distribution and density is variable, while over oceans very few gauges exist and where measurements are made, they may not adequately reflect the rainfall amounts of the broader area.