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Robert A Lucchesi

Publications and source records attributed to Robert A Lucchesi.

8 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

File Specification for MERRA-2 Climate Statistics Products

The Modern Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) contains a wealth of information that can be used for weather and climate studies. By combining the assimilation of observations with a frozen version of the Goddard Earth Observing System (GEOS), a global analysis is produced at an hourly temporal resolution spanning from January 1980 through present (Gelaro et al., 2017). It can be difficult to parse through a multidecadal dataset such as MERRA-2 to evaluate the interannual variability of weather that occurs on a daily timescale, let alone determine the occurrence of an extreme weather event. Furthermore, it was recognized that standard metrics were needed to evaluate climate change among climate models and international research efforts. As a result of these concerns, the Expert Team on Climate Change Detection and Indices (ETCCDI) developed a set of indices that represent the frequency and intensity of extreme weather events using a daily time series of 2-m air temperature (T2m) and precipitation (Alexander et al., 2016). These indices were used as a basis to comprise a list of fields that represent daily extreme temperature and precipitation events, heatwaves, multi-day precipitation, as well monthly percentile statistics from the MERRA-2 dataset. Also included in this data product is a climatological long term mean and standard deviation representing the interannual variability on a monthly timescale.

MERRA-2↗
NASA NTRS2021

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25 degree) global constituent prediction system from NASA’s Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA’s broad range of space-based and in-situ observation sand to support flight campaign planning, support of satellite observations, and air quality research. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide analyses and 5-day forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community.Evaluation of GEOS-CF against satellite, ozone sonde and surface observations show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to -0.3, normalized root mean square errors (NRMSE) between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants under a variety of meteorological conditions, yet also highlight current limitations, such as an over prediction of summertime ozone over the Southeast United States. GEOS-CFv1.0 generally overestimates aerosols by 20-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions.The 5-day hourly forecasts have skill scores comparable to the analysis. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

GEOS-CF↗
NASA NTRS2021

Global Impact of COVID-19 Restrictions on the Atmospheric Concentrations of Nitrogen Dioxide and Ozone

Social-distancing to combat the COVID-19 pandemic has led to widespread reductions in air pollutant emissions. Quantifying these changes requires a business-as-usual counterfactual that accounts for the synoptic and seasonal variability of air pollutants. We use a machine learning algorithm driven by information from the NASA GEOS-CF model to assess changes in nitrogen dioxide (NO2) and ozone (O3) at 5,756 observation sites in countries from January through June 2020. Reductions in NO2 coincide with timing and intensity of COVID-19 restrictions, ranging from 60% in severely affected cities (e.g., Wuhan, Milan) to little change (e.g., Rio de Janeiro, Taipei). On average, NO2 concentrations were (13-23) % lower than business as usual from February 2020 onward. China experienced the earliest and steepest decline, but concentrations since April have mostly recovered and remained within 5% to the business-as-usual estimate. NO2 reductions in Europe and the US have been more gradual with a halting recovery starting in late March. We estimate that the global NOx (NO+NO2) emission reduction during the first 6 months of 2020 amounted to 3.1 (2.6-3.6) TgN, equivalent to 5.5(4.7-6.4) % of the annual anthropogenic total. The response of surface O3 is complicated by competing influences of non-linear atmospheric chemistry. While surface O3 increased by up to 50% in some locations, we find the overall net impact on daily average O3 between February -June 2020 to be small. However, our analysis indicates a flattening of the O3 diurnal cycle with an increase in nighttime ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production.

Christoph A Keller↗
NASA NTRSDate not supplied

Impact of COVID-19 Restrictions on Atmospheric Concentrations of O3 and NO2 Across the Globe

We use a machine learning algorithm combining information from the NASA GEOS composition forecast (GEOS-CF) model and surface observations of nitrogen dioxide (NO2) and ozone (O3) at more than 5,000 observation sites to assess the impact of COVID-19 restrictions on surface air quality in 46 countries. Our methodology removes the compounding impacts of meteorology, seasonality and atmospheric chemistry on air pollution, thus allowing for a quantitative estimate of the change in surface air quality following COVID-19 containment measures. Compared to GEOS-CF model predictions that do not include emission reductions related to COVID-19 restrictions, surface observations show a drop in surface NO2 of up to 60% after the implementation of lockdowns. Average NO2 concentrations between February 2020 to June 2020 were 18% lower than business as usual. The earliest and strongest declines are observed over China, followed by Europe and the US. While NO2 concentrations over China recovered within 2 months, the recovery has been slower over Europe and the US. The impact of COVID-19 restrictions on O3 is complicated by non-linear atmospheric chemistry. Locally, O3 can show a short-term increase of up to 50% as a result of the decrease in NO2, which leads to a reduction in night time titration. However, this effect is offset by a decrease in photochemical production during the day. Our results indicate that these two competing processes resulted in a net zero change in average surface ozone during the first 5 months of the pandemic. The results also indicate that the reduced photochemical production becomes increasingly important over time. Our analysis is based on surface observations and model simulations available in near real-time, and we will present an up-to-date view of the short and medium-term impacts of COVID-19 restrictions on air quality around the world.

COVID-19↗