The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational on the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Terra satellite since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version of the MISR aerosol products. The level 2 (swath) product, which is reported on a 4.4 km spatial grid, is designated as version 23 (V23) and contains retrieved aerosol optical depth (AOD) and aerosol particle property information derived from MISR's multi-angle observations over both land and water. The changes from the previous version of the algorithm (V22) have significant impacts on the data product and its interpretation. The V23 data set is created from two separate retrieval algorithms that are applied over dark water and land surfaces, respectively. Besides increasing the horizontal resolution to 4.4 km compared with the coarser 17.6 m resolution in V22 and streamlining the format and content, the V23 product has added geolocation information, pixel-level uncertainty estimates, and improved cloud screening. MISR data can be obtained from the NASA Langley Research Center Atmospheric Science Data Center at https://eosweb.larc.nasa.gov/project/misr/misr_table (last access: 11 October 2019). The version number for the V23 level 2 aerosol product is F13_0023. The level 3 (gridded) aerosol product is still reported at ${\mathrm{0.5}}^{\circ }\times {\mathrm{0.5}}^{\circ }$ spatial resolution with results aggregated from the higher-resolution level 2 data. The format and content at level 3 have also been updated to reflect the changes made at level 2. The level 3 product associated with the V23 level 2 product version is designated as F15_0032. Both the level 2 and level 3 products are now provided in NetCDF format.

Reliable projections of wildfire and associated socioeconomic risks are crucial for the development of efficient and effective adaptation and mitigation strategies. The lack of or limited observational constraints for modeling outputs impairs the credibility of wildfire projections. Here, we present a machine learning framework to constrain the future fire carbon emissions simulated by 13 Earth system models from the Coupled Model Intercomparison Project phase 6 (CMIP6), using historical, observed joint states of fire-relevant variables. During the twenty-first century, the observation-constrained ensemble indicates a weaker increase in global fire carbon emissions but higher increase in global wildfire exposure in population, gross domestic production, and agricultural area, compared with the default ensemble. Such elevated socioeconomic risks are primarily caused by the compound regional enhancement of future wildfire activity and socioeconomic development in the western and central African countries, necessitating an emergent strategic preparedness to wildfires in these countries.

Motivated by limitations in current satellite‐based dust source identification techniques, this study examines dust emissions and concentrations over North Africa and the Middle East during 2000–2016 by analyzing stereo and optical products from the Multiangle Imaging SpectroRadiometer instrument on the National Aeronautics and Space Administration polar‐orbiting Terra satellite. Based on the occurrence of fast‐moving, near‐surface dust plumes from the Multiangle Imaging SpectroRadiometer cloud motion vector product, dust sources in the study region are identified in geographical depressions, including the Bodélé Depression, which represents the leading source. The West African El Djouf desert generates substantial dust emissions, which are typically underestimated by aerosol loading‐based dust source identifications. In response to local vegetation cover anomalies, dust emissions and concentrations increased at 15% year⁻¹ over the Middle East and decreased at 12% year⁻¹over the central Sahel during 2001–2013 but partly recovered toward their climatological means afterward.

Asian dust, primarily emitted from the Taklamakan and Gobi deserts, has been reported to reach remote destinations, such as North America. However, the relative contribution of the Taklamakan and Gobi deserts to dust loadings through long-range transport remains unaddressed in any observational study. Here, the climatology of Asian dust activation and potential for transport is investigated using stereo observations of dust sources from the Multi-angle Imaging SpectroRadiometer (MISR) instrument combined with observation-initiated trajectory modeling. MISR-derived dust plume top height and dust plume motion vectors confirm the peak of dust activation and transport potential in spring over the Gobi Desert and in both spring and summer over the Taklamakan Desert. The long-range trajectory patterns of Asian dust, including the influence on North America through trans-Pacific transport, are assessed using extensive forward trajectories initiated by MISR dust plume observations. The trajectory analysis reveals latitude-dependent spread of dust trajectories from the Taklamakan and Gobi deserts, with Taklamakan dust dominantly affecting to the south of 50^∘ N and Gobi dust primarily affecting to the north of 50^∘ N in North America. The Asian dust activation and transport potential exhibit substantial seasonal and interannual variability, motivating future studies on the potential drivers.

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon‐chemistry‐climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi‐layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present‐day biomass and carbon uptake in comparison to observations.