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ATom Measures Greenhouse Gases and Pollution

Atmospheric Tomography Mission (ATom)

Atmospheric Tomography Mission (ATom) is an Earth Venture Suborbital-2 mission.

NASA's Atmospheric Tomography Mission (ATom) mission conducts atmospheric profiles for systematic, global-scale sampling of the atmosphere.

Globally Consistent Hydrologic Soil Groups

Global distribution of hydrologic soil groups at 250-m spatial resolution.

Global distribution of hydrologic soil groups at 250-m spatial resolution. Hydrologic soil groups A, B, C, and D correspond to low, moderately low, moderately high, and high runoff potential, respectively. Wet soils are assigned a dual HSG (e.g., HSG A/D) and have high runoff potential due to the presence of a water table within 60 cm of the surface. A less restrictive group can be assigned if these soils are drained (e.g., HSG-A).

High-resolution and globally consistent hydrologic soil groups are provided in a new dataset.

Visualize Airborne Data

The Airborne Data Visualizer showing CO2 and CH4 concentrations

Screenshot of the Airborne Data Visualizer showing a flight from the ACT-America campaign. CO2 and CH4 concentrations are shown from the B-200 aircraft on July 11, 2016.

A new tool allows users to explore airborne data from multiple missions.

PhenoCam Vegetation Phenology

PhenoCam images showing two seasons at the Arbutus Lake site in NY.

PhenoCam images from February and July 2013 at the Arbutus Lake site in New York.

Vegetation phenology observations and raw imagery from the PhenoCam network are now available from the ORNL DAAC.

MODIS Net Evapotranspiration Now Available

Timeseries of MODIS ET

The MOD16A2, Net Evapotranspiration, data product is now available from the MODIS Global Subsets Tool. The image shows a stacked timeseries of ET data from 2001 - 2018 for a location in central North America.

The MOD16A2, MODIS/Terra Net Evapotranspiration 8-Day Collection 6, product is now available through the MODIS Global Subsets Tool.

Forest Recovery in the Amazon

Photos of recovering burned (left) and unburned (right) sampling sites

Photos of recovering burned (left) and unburned (right) sampling sites show vegetation changes due to burning and recovery of aboveground biomass after burning. Photos courtesy of I. Numata.

Data was collected to characterize the post-fire recovery of tropical forests in Acre, Brazil.

Aboveground Biomass in the Arctic Tundra

AGB shown in Beaufort Coastal Plain and Brooks Foothills ecoregions of the North Slope of Alaska.

The best estimate (50th percentile) of 30-m shrub dominance (shrub/plant AGB) for non-water portions of the Beaufort Coastal Plain and Brooks Foothills ecoregions of the North Slope of Alaska.

Estimates of aboveground biomass for the North Slope of Alaska are provided in a new dataset.

Tropical Forest Inventory in Brazil

Geographical location of the Tapajos National Forest, PA, Brazil, outlined in yellow.

Location of the Tapajos National Forest, PA, Brazil, outlined in yellow. The gray lines are GLAS sampling flight tracks from 2003 to 2009 and the blue circles are the forest plots sampled. The pictures on the right illustrate three of the stands where plots were located (Goncalves et al., 2017).

Forest inventory data from the Tapajos National Forest in Brazil were used to calibrate GLAS LiDAR estimates of forest biomass.

Forest fires in the ABoVE domain

The ABoVE study domain

The ABoVE study domain showing cumulative annual burned areas derived from AVHRR for 1989 - 2000.

A long-term record of annual forest fire burned area and daily hotspots are provided in a new ABoVE dataset.

Calculate Climate Anomalies from Daymet

Climate normal and anomaly calculated from Daymet

Climate anomaly (right panel) in minimum daily temperature for year 1990 compared to the long-term normal (left panel). The climate normal and anomaly were calculated for a single 2-degree tile from the Daymet dataset.

New Jupyter notebook tutorials show how to access and visualize Daymet climate data from within Python and how to calculate climate normals and anomalies.

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