NEX-DCP30: Ensemble Stats for NASA Earth Exchange Downscaled Climate Projections

NASA/NEX-DCP30_ENSEMBLE_STATS
Dataset Availability
1950-01-01T00:00:00Z–2099-12-01T00:00:00Z
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("NASA/NEX-DCP30_ENSEMBLE_STATS")

Description

The NASA NEX-DCP30 dataset is comprised of downscaled climate scenarios for the conterminous United States that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5, see Taylor et al. 2012) and across the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs, see Meinshausen et al. 2011) developed for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The purpose of these datasets is to provide a set of high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions.

The dataset contains monthly projections covering the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). It includes ensemble statistics calculated for each RCP from all model runs available for the pr, tasmin, and tasmax bands.

NEX-DCP30 was prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS).

Bands

Resolution
927.67 meters

Bands

Name Units Min Max Description
pr_mean kg/m^2/s 0* 0.0006*

Monthly mean of the daily precipitation rate at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)

pr_quartile25 kg/m^2/s 0* 0.0004*

25th quartile of the precipitation at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)

pr_median kg/m^2/s 0* 0.0006*

Median of precipitation at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)

pr_quartile75 kg/m^2/s 0* 0.0008*

75th quartile of the precipitation at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)

tasmin_mean K 247.58* 311.09*

Monthly mean of the daily-minimum near-surface air temperature

tasmin_quartile25 K 243.28* 310.06*

25th quartile the daily-minimum near-surface air temperature

tasmin_median K 246.87* 311.12*

Median of the daily-minimum near-surface air temperature

tasmin_quartile75 K 248.42* 312.59*

75th quartile of the daily-minimum near-surface air temperature

tasmax_mean K 258.47* 326.48*

Monthly mean of the daily-maximum near-surface air temperature

tasmax_quartile25 K 256.13* 325.52*

25th quartile of the daily-maximum near-surface air temperature

tasmax_median K 257.89* 326.28*

Median of the daily-maximum near-surface air temperature

tasmax_quartile75 K 260.2* 328.2*

75th quartile of the daily-maximum near-surface air temperature

* estimated min or max value

Image Properties

Image Properties

Name Type Description
scenario STRING

Name of the CMIP5 scenario. It is one of: 'historical', 'rcp26', 'rcp45', 'rcp60', 'rcp85', where 'historical' designates retrospective model runs (pre-2006).

month DOUBLE

Calendar month

Terms of Use

Terms of Use

This dataset is in the public domain and is available without restriction on use and distribution. See NASA's Earth Science Data & Information Policy for additional information.

Citations

Citations:
  • Thrasher, B., J. Xiong, W. Wang, F. Melton, A. Michaelis and R. Nemani (2013), Downscaled Climate Projections Suitable for Resource Management, Eos Trans. AGU, 94(37), 321. doi:10.1002/2013EO370002

Explore with Earth Engine

Code Editor (JavaScript)

var dataset = ee.ImageCollection('NASA/NEX-DCP30_ENSEMBLE_STATS')
                  .filter(ee.Filter.date('2018-07-01', '2018-07-30'));
var monthlyMeanMinimumAirTemperature = dataset.select('tasmin_mean');
var monthlyMeanMinimumAirTemperatureVis = {
  min: 247.0,
  max: 311.0,
  palette: ['blue', 'purple', 'cyan', 'green', 'yellow', 'red'],
};
Map.setCenter(-115.356, 38.686, 5);
Map.addLayer(
    monthlyMeanMinimumAirTemperature, monthlyMeanMinimumAirTemperatureVis,
    'Monthly Mean Minimum Air Temperature');
Open in Code Editor