The Daily 8-Hour Maximum and Annual O3 Concentrations for the Contiguous United States, 1-km Grids, Version 1.10 (2000-2016) data set contains estimates of ozone concentrations at a high resolution spatially (1-km grid cells) and temporally (daily) for the years 2000 to 2016. These predictions incorporated various predictor variables such as Ozone (O3) ground measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) monitoring data, land-use variables, meteorological variables, chemical transport models and remote sensing data, along with other data sources. After imputing missing data with machine learning algorithms, a geographically-weighted ensemble model was applied that combined estimates from three types of machine learners (neural network, random forest, and gradient boosting). The annual predictions were computed by averaging the daily 8-hour maximum predictions in each year for each grid cell. The results demonstrate high overall model performance with a cross-validated R-squared value against daily observations of 0.90 and 0.86 for annual averages. In version 1.10, we have enhanced the completeness of daily O3 predictions by employing linear interpolation to impute missing values. Specifically, for days with small spatial patches of missing data with less than 100 grid cells, we used inverse distance weighting interpolation to fill the missing grid cells. Other missing daily O3 predictions were interpolated from the nearest days with available data. Annual predictions were updated by averaging the imputed daily predictions for each year in each grid cell. These daily 8-hour maximum and annual O3 predictions allow public health researchers to respectively estimate the short- and long-term effects of O3 exposures on human health, supporting the U.S. EPA for the revision of the National Ambient Air Quality Standards for O3. The data are available in RDS and GeoTIFF formats for statistical research and geospatial analysis.

ACCLIP_Merge_WB57-Aircraft_Data is the pre-generated merge files created from a variety of in-situ instrumentation collecting measurements onboard the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete.

ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.

The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.

This dataset provides monthly globally gridded freshwater wetland methane emissions from 2001-2018 in nmol CH4 m-2 s-1, g C-CH4 m-2 d-1, and TgCH4 grid cell-1 month-1. The data were derived from a six-predictor random forest upscaling model (UpCH4) trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites covering bog (8), fen (8), marsh (10), swamp (6), and wet tundra (11) wetland classes and distributed across Arctic-boreal (20), temperate (16), and (sub)tropical (7) climate zones. Weekly mean CH4 fluxes were computed from half-hourly FLUXNET-CH4 Version 1.0 fluxes. Each grid cell CH4 flux prediction was weighted by fractional grid cell wetland extent to estimate CH4 emissions using the primary global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) product and an alternate Global Inundation Estimate from Multiple Satellites GIEMS version 2 global wetland map. Both WAD2M and GIEMS-2 maps were modified with several correction data layers to represent the monthly area covered by vegetated wetlands, excluding open water and coastal wetlands. The data products are: mean daily fluxes with no adjustment for wetland area (i.e., flux densities assuming hypothetical 100% wetland cover); mean daily fluxes adjusting for WAD2M or GIEMS-2 wetland area; and by-pixel monthly sum of freshwater wetland methane emissions adjusting for WAD2M or GIEMS-2 wetland area. The data are provided in NetCDF4 format.

Not technically a data set, this is a report of the cross-comparison of data collected by various flux aircraft. Reports of these analyses are available as TIF and ASCII files.

The TROPESS Chemical Reanalysis SO2 2-Hourly 2-dimensional Product contains the surface concentrations of sulfur dioxide. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.

The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The TROPESS Chemical Reanalysis OH 2-Hourly 2-dimensional Product contains the surface concentrations of the hydroxyl radical. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.

The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The TROPESS Chemical Reanalysis PAN 2-Hourly 2-dimensional Product contains the surface concentrations of peryoxyacetyl nitrate. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.

The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The TROPESS Chemical Reanalysis Surface Aerosol O3 2-Hourly 2-dimensional Product contains the surface concentrations of ozone. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.

The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The TROPESS Chemical Reanalysis NO 2-Hourly 2-dimensional Product contains the surface concentrations of nitric oxide. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.

The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The TROPESS Chemical Reanalysis NO2 2-Hourly 2-dimensional Product contains the surface concentrations of nitrogen dioxide. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.

The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.