Incorporation and Use of Earth Remote Sensing Imagery within the NOAA/NWS Damage Assessment Toolkit.

Severe weather events including tornadoes, damaging winds, hail, and their combination produce changes in land surface vegetation and urban settings that are frequently observed through remote sensing. Capabilities continue to improve through a growing constellation of governmental and commercial assets, increasing the spatial resolution of visible, near to shortwave infrared, and thermal infrared remote sensing. Here, we highlight cases where visual interpretation of imagery benefitted severe weather damage assessments made within the NOAA/NWS Damage Assessment Toolkit. Examples demonstrate utility of imagery in assessing tracks and changes in remote areas where staffing limitations or access prevent a ground-based assessment.

Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria.

A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island's settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community.

Transforming Satellite Data into Weather Forecasts.

Teaser: A NASA project spans the gap between research and operations, introducing new composites of satellite imagery to weather forecasters to prepare for the next generation of satellites.

Comparisons of Modeled and Observed Reflectivities and Fall Speeds for Snowfall of Varied Riming Degrees during Winter Storms on Long Island, New York.

Derived radar reflectivities and fall speeds for four Weather Research and Forecasting (WRF) Model bulk microphysical parameterizations (BMPs) run at 1.33-km grid spacing are compared with ground-based, vertically pointing Ku-band radar, scanning S-band radar, and in situ measurements at Stony Brook, New York. Simulations were partitioned into periods of observed riming degree as determined manually using a stereo microscope and camera during nine winter storms. Simulations were examined to determine whether the selected BMPs captured the effects of varying riming intensities, provided a reasonable match to the vertical structure of radar reflectivity or fall speed, and whether they produced reasonable surface fall speed distributions. Schemes assuming nonspherical mass-diameter relationships yielded reflectivity distributions closer to observed values. All four schemes examined in this study provided a better match to the observed, vertical structure of reflectivity during moderate riming than light riming periods. The comparison of observed and simulated snowfall speeds had mixed results. One BMP produced episodes of excessive cloud water at times, resulting in fall speeds that were too large. However, most schemes had frequent periods of little or no cloud water during moderate riming periods and thus underpredicted the snowfall speeds at lower levels. Short, 1-4-h periods with relatively steady snow conditions were used to compare BMP and observed size and fall speed distributions. These limited data suggest the examined BMPs underpredict fall speeds of cold-type snow habits and underrepresent aggregates larger than 4-mm diameter.