Abstract
This data article reports the global datasets of land surface state changes including daily maximum and minimum temperature, diurnal temperature range, surface precipitation, snow cover, soil moisture and outgoing longwave radiation associated with the Madden-Julian Oscillation (MJO), which are related to the research article entitled “Variation of Global Diurnal Temperature Range Associated with the Madden-Julian Oscillation” published in the Journal of Atmospheric and Solar-Terrestrial Physics by Lin and Qian (2019). The changes of surface air temperature and diurnal temperature range are calculated from two datasets: the Berkeley surface air temperature and the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) surface air temperature. The change of surface precipitation is derived from the NOAA CPC daily surface precipitation. The change of snow cover is calculated from the MODIS satellite data. The change of soil moisture is derived from the European Space Agency combined satellite data. The change of outgoing longwave radiation is calculated from NOAA satellite measurements. All of the data are stored in separate netcdf files and deposited at PANGAEA. These datasets can be used as observational benchmarks for evaluating the MJO simulations in global climate models, and in studies of MJO's impacts on global physical systems, public health, and ecosystems.
Highlights
This data article reports the global datasets of land surface state changes including daily maximum and minimum temperature, diurnal temperature range, surface precipitation, snow cover, soil moisture and outgoing longwave radiation associated with the Madden-Julian Oscillation (MJO), which are related to the research article entitled “Variation of Global Diurnal Temperature Range Associated with the Madden-Julian Oscillation” published in the Journal of Atmospheric and Solar-Terrestrial Physics by Lin and Qian (2019)
The changes of surface air temperature and diurnal temperature range are calculated from two datasets: the Berkeley surface air temperature and the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) surface air temperature
These datasets can be used as observational benchmarks for evaluating the MJO simulations in global climate models, and in studies of MJO's impacts on global physical systems, public health, and ecosystems
Summary
Global datasets of land surface state changes associated with the Madden-Julian Oscillation This data article reports the global datasets of land surface state changes including daily maximum and minimum temperature, diurnal temperature range, surface precipitation, snow cover, soil moisture and outgoing longwave radiation associated with the Madden-Julian Oscillation (MJO), which are related to the research article entitled “Variation of Global Diurnal Temperature Range Associated with the Madden-Julian Oscillation” published in the Journal of Atmospheric and Solar-Terrestrial Physics by Lin and Qian (2019). The changes of surface air temperature and diurnal temperature range are calculated from two datasets: the Berkeley surface air temperature and the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) surface air temperature.
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