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Under the auspices of the National Polar-orbiting Operational Environmental Satellite System's (NPOESS) Integrated Program Office (IPO), the Naval Research Laboratory (NRL) has developed “NexSat” ( public-access online demonstration over the continental United States (CONUS) of near-real-time environmental products highlighting future applications from the Visible/Infrared Imager/Radiometer Suite (VIIRS). Based on a collection of operational and research-grade satellite observing systems, Nex-Sat products include the detection, enhancement, and where applicable, physical retrieval of deep convection, low clouds, light sources at night, rainfall, snow cover, aircraft contrails, thin cirrus layers, dust storms, and cloud/ aerosol properties, all presented in the context of value-added imagery. The purpose of NexSat is threefold: 1) to communicate the advanced capabilities anticipated from VIIRS, 2) to present this information in near–real time for use by forecasters, resource managers, emergency response teams, civic planners, the aviation community, and various government agencies, and 3) to augment the NRL algorithm development multisensor/model-fusion test bed for accelerated transitions to operations during the NPOESS era. This paper presents an overview of NexSat, highlighting selected products from the diverse meteorological phenomenology over the CONUS. [ABSTRACT FROM AUTHOR]

A rainfall nowcasting system is developed that identifies locations of raining clouds on consecutive infrared geosynchronous satellite images while predicting the movement of the rain cells for up to 10 h using cloudmotion-based winds. As part of the analysis, the strengths and weaknesses of various kinds of cloud wind filtering schemes and both steady and nonsteady storm advection techniques as forecast operators for quantitative precipitation forecasting are evaluated. The first part of the study addresses the development of a probability matching method (PMM) between histograms of equivalent blackbody temperatures (EBBTs) and Special Sensor Microwave Imager (SSM/I)-derived rain rates (RRs), which enables estimating RRs from instantaneous infrared imagery and allows for RR forecasts from the predicted EBBT fields. The second part of the study addresses the development and testing of the nowcasting system built upon the PMM capability and analyzes its success according to various skill score metrics. Key processes involved in the nowcasting system include the retrieved cloud-motion wind field, the filtered cloud-motion wind field, and the forecasting of a future rain field by storm advection and EBBT tendencies. These processes allow for the short-term forecasting of cloud and rain locations and of rain intensity, using PMM-based RRs from different datasets of infrared Geostationary Meteorological Satellite (GMS) and Geostationary Operational Environmental Satellite (GOES) imagery. For this study, three convective rain sequences from the Caribbean basin, the Amazon basin, and the Korean peninsula are analyzed. The final part of the study addresses the decay of forecast accuracy with time (i.e., the point at which the asymptotic limit on forecast skill is reached). This analysis indicates that the nowcasting system can produce useful rainfall forecast information out to approximately 6 h. [ABSTRACT FROM AUTHOR]

Understanding and forecasting hurricanes remains a challenge for the operational and research communities. To accurately predict the Tropical Cyclone (TC) evolution requires properly reflecting the storm's inner core dynamics by using: (i) high-resolution models; (ii) realistic physical parameterizations. The microphysical processes and their representation in cloud-permitting models are of crucial importance. In particular, the assumed Particle Size Distribution (PSD) functions affect nearly all formulated microphysical processes and are among the most fundamental assumptions in the bulk microphysics schemes. This paper analyzes the impact of the PSD assumptions on simulated hurricanes and their synthetic radiometric signatures. It determines the most realistic, among the available set of assumptions, based on comparison to multi-parameter satellite observations. Here we simulated 2005′s category-5 Hurricane Rita using the cloud-permitting community Weather Research and Forecasting model (WRF) with two different microphysical schemes and with seven different modifications of the parametrized hydrometeor properties within one of the two schemes. We then used instrument simulators to produce satellite-like observations. The study consisted in evaluating the structure of the different simulated storms by comparing, for each storm, the calculated microwave signatures with actual satellite observations made by (a) the passive microwave radiometer that was carried by the Tropical Rainfall Measuring Mission (TRMM) satellite—the TRMM microwave imager TMI, (b) TRMM's precipitation radar (PR) and (c) the ocean-wind-vector scatterometer carried by the QuikSCAT satellite. The analysis reveals that the different choices of microphysical parameters do produce significantly different microwave signatures, allowing an objective determination of a "best" parameter combination whose resulting signatures are collectively most consistent with the wind and precipitation observations obtained from the satellites. In particular, we find that assuming PSDs with larger number of smaller hydrometeors produces storms that compare best to observations. [ABSTRACT FROM AUTHOR]

Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI + Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%-50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%-50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms.

Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 σ o measurements include 1) direct Ku-band σ o intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times.