The NOAA National Centers for Environmental Prediction (NCEP) implemented the NOAA Environmental Modeling System (NEMS) Global Forecast System (GFS) Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5-day dust forecasts at 1° × 1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders, as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.

The NEMS GFS Aerosol Component Version 2.0 (NGACv2) for global multispecies aerosol forecast has been developed at the National Centers of Environment Prediction (NCEP) in collaboration with the NESDIS Center for Satellite Applications and Research (STAR), the NASA Goddard Space Flight Center (GSFC), and the University at Albany, State University of New York (SUNYA). This paper describes the continuous development of the NGAC system at NCEP after the initial global dust-only forecast implementation (NGAC version 1.0, NGACv1). With NGACv2, additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. The smoke emissions are from the NESDIS STAR's Global Biomass Burning Product (GBBEPx), blended from the global biomass burning emission product from a constellation of geostationary satellites (GBBEP-Geo) and GSFC's Quick Fire Emission Data Version 2 from a polar-orbiting sensor (QFED2). This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been used by many applications such as for regional air quality model lateral boundary conditions, satellite sea surface temperature (SST) physical retrievals, and the global solar insolation estimation. Positive impacts have been seen in these applications.

This study compares soil moisture analyses from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) global reanalysis (R-1) and the later NCEP– Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP) global reanalysis (R-2). The R-1 soil moisture is strongly controlled by nudging it to a prescribed climatology, whereas the R-2 soil moisture is adjusted according to differences between model-generated and observed precipitation. While mean soil moisture fields from R-1 and R-2 show many geographic similarities, there are some major differences. This study uses in situ observations from the Global Soil Moisture Data Bank to evaluate the two global reanalysis products. In general, R-2 does a better job of simulating interannual variations, the mean seasonal cycle, and the persistence of soil moisture, when compared to observations. However, the R-2 reanalysis does not necessarily represent observed soil moisture characteristics well in all aspects. Sometimes R-1 provides a better soil moisture analysis on monthly time scales, which is likely a consequence of the deficiencies in the R-2 surface water balance.

While surface concentrations of ozone are routinely monitored, ozone aloft is infrequently measured, but critical for a full understanding of ozone production and transport. In this study, twenty‐six balloon‐borne ozonesondes were launched near the north shore of central Long Island in the summers of 2018 and 2019 as part of the Long Island Sound Tropospheric Ozone Study (LISTOS). The observed vertical ozone profiles are presented and analyzed with additional data sources and modeling tools, including lidar wind profiles from the New York State Mesonet, back trajectories based on 3 km resolution high‐resolution rapid refresh model data, and surface data, aircraft observations, sonde, and ozone lidar measurements from other LISTOS participants. Special attention is given to the region of interest for ozone pollution in the lower troposphere, from the surface to 2 km altitude. Cases analyzed in detail illustrate events with high ozone levels observed in the lower troposphere, often with pronounced vertical structure in the profile. Specifically, easily discernible layers are identified with ozone excursions of up to 40 ppb over short vertical distances. Analysis indicates that synoptic and local meteorological processes can combine to generate the observed vertical profiles. Hot, sunny days with high‐pressure systems are accompanied by high precursor emissions due to increased power demands, plentiful radiation for photochemistry, and stagnation of synoptic winds. Under these conditions, meso‐ and smaller‐scale flows like low‐level jets and sea/bay/land breeze circulations may dominate synoptic flow to produce shearing and the complex vertical layered structure observed.

Changes in energy and environmental policies along with changes in the energy markets of New York State over the past two decades, have spurred interest in evaluating their impacts on emissions from various energy generation sectors. This study focused on quantifying these effects on VOC (volatile organic compounds) emissions and their subsequent impacts on air quality within the New York City (NYC) metropolitan area. NYC is an EPA nonattainment region for ozone (O₃) and likely is a VOC limited region. NYC has a complex coastal topography and meteorology with low-level jets and sea/bay/land breeze circulation associated with heat waves, leading to summertime O₃ exceedances and formation of secondary organic aerosol (SOA). To date, no comprehensive source apportionment studies have been done to understand the contributions of local and long-range sources of VOCs in this area. This study applied an improved Positive Matrix Factorization (PMF) methodology designed to incorporate atmospheric dispersion and photochemical reaction losses of VOCs to provide improved apportionment results. Hourly measurements of VOCs were obtained from a Photochemical Assessment Monitoring Station located at an urban site in the Bronx from 2000 to 2021. The study further explores the role of VOC sources in O₃ and SOA formation and leverages advanced machine learning tools, XGBoost and SHAP algorithms, to identify synergistic interactions between sources and provided VOC source impacts on ambient O₃ concentrations. Isoprene demonstrated a substantial influence in the source contribution of the biogenic factor, emphasizing its role in O₃ formation. Notable contributions from anthropogenic emissions, such as fuel evaporation and various industrial processes, along with significant traffic-related sources that likely contribute to SOA formation, underscore the combined impact of natural and human-made sources on O₃ pollution. Findings of this study can assist regulatory agencies in developing appropriate policy and management initiatives to control O₃ pollution in NYC.