This study used space-and ground-based sensors in conjunction meteorological and traffic information to evaluate the impact of the COVID-19 containment measures on air pollution in California by comparing data from March-April 2020 to the similar period in 2019. Although significantly lower pollution levels were observed throughout the COVID-19 containment period in 2020 compared to 2019, our meteorological analysis found that periods of enhanced precipitation likely contributed to the cleaner environment over the Central Valley and southern California. Therefore, we focused our assessment on a 19-day period of drier conditions across the region. During this period, TROPOspheric Monitoring Instrument (TROPOMI) data revealed strong reductions in tropospheric NO 2 of 40% in Los Angeles, 38% in Fresno, and about 20% in Bakersfield and San Francisco when compared to 2019. The reductions were mostly within about 10% of the decrease in vehicle miles traveled (VMT), which indicates that the decrease in traffic-related NO x due to the COVID-19 lockdown was an important driver of the NO 2 reduction. Ozone Monitoring Instrument (OMI) data showed similar NO 2 reductions to TROPOMI over Los Angeles during the lockdown, but drastically different results over the other cities where little to no reductions were observed. The close agreement between ground-based and TROPOMI observations indicated that a more accurate assessment of the impacts from the COVID-19 lockdown can be accomplished using TROPOMI rather than OMI data, which is attributed to its improved resolution and sensitivity that can better characterize NO 2 pollution associated with fine-scale emissions. Altogether, the space-and ground-based observations provide strong evidence that the containment measures led to NO 2 reductions of around 35% in Los Angeles and Fresno and 25% in San Francisco and Bakersfield relative to 2019, along with decreases in PM 2.5 and improved air quality at the surface.

applied research communities gathered to learn and discuss the game-changing capabilities of the TEMPO instrument for enhancing health and air quality applications after launch in 2022. Pre-launch planning for fundamental and applied research experiments using TEMPO data were introduced to the participants.

Infrequent lightning flashes occurring outside of surface precipitation pose challenges to Impact-based Decision Support Services (IDSS) for outdoor activities. This paper examines the remote sensing observations from an event on 20 August 2019 where multiple cloud-to-ground flashes occurred over 10 km outside surface precipitation (lowest radar tilt reflectivity <10 dBZ and no evidence of surface precipitation) in a trailing stratiform region of a mesoscale convective system. The goal is to demonstrate the fusion of radar with multiple lightning observations and a lightning risk model to demonstrate how reflectivity and differential reflectivity combined provided the best indicator for the potential of lightning where all of the other lightning safety methods failed.Thirteen lightning flashes were observed by the Geostationary Lightning Mapper (GLM) within the trailing stratiform region between 2100 and 2300 UTC. The average size of the thirteen lightning flashes was 3184 km2, with an average total optical energy of 7734 fJ. Seventy-five NLDN flash locations were coincident with the thirteen GLM flashes, resulting in an average of 5.8 NLDN flashes (in-cloud (IC) and cloud-to-ground (CG)) per 37 GLM flash. Five of the GLM flashes contained at least one positive cloud-to-ground flash (+CG) flash identified by the NLDN, with peak amplitudes ranging between 66 and 136 kA. All eight CG flashes identified by the NLDN were located more than 10 km outside surface precipitation. The only indication of the potential of these infrequently large flashes was the presence of depolarization streaks in differential reflectivity (ZDR) and enhanced reflectivity near the melting layer.

A lightning risk assessment for application to human safety was created and applied in 10 West Texas locations from 2 May 2016 to 30 September 2016. The method combined spatial lightning mapping data, probabilistic risk calculation adapted from the International Electrotechnical Commission Standard 62305-2, and weighted average interpolation to produce risk magnitudes that were compared to tolerability thresholds to issue lightning warnings. These warnings were compared to warnings created for the same dataset using a more standard lightning safety approach based on National Lightning Detection Network (NLDN) total lightning within 5 nautical miles of each location. Four variations of the calculation as well as different units of risk were tested to find the optimal configuration to calculate risk to an isolated human outdoors.The best performing risk configuration using risk 10min−1 or larger produced the most comparable results to the standard method, such as number of failures, average warning duration, and total time under warnings. This risk configuration produced fewer failures than the standard method, but longer total time under warnings and higher false alarm ratios. Median lead times associated with the risk configuration were longer than the standard method for all units considered, while median down times were shorter for risk 10min−1 and risk 15min−1. Overall, the risk method provides a baseline framework to quantify the changing lightning hazard on the storm-scale, and could be a useful tool to aid in lightning decision support scenarios.