Observed humidity trends in dry regions contradict climate models

This dataset contains post-processed observation-based and model-based data between 1980 and 2020 to support the study the humidity trends. The intercomparison indicates that the observed humidity trends in dry regions contradict the climate model simulations. This may indicate a major gap of hydroclimate-related processes in the climate models.

To Access Resource:

Questions? Email Resource Support Contact:

  • Chi-Fan Shih
    chifan@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  1980
    End:  2020

Keywords

Resource Type dataset
Temporal Range Begin 1980
Temporal Range End 2020
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links N/A
Additional Information N/A
Resource Format HDF5/NetCDF4
Standardized Resource Format NetCDF
Asset Size 0.00 MB
Legal Constraints

Creative Commons Attribution 4.0 International License
Access Constraints None
Software Implementation Language N/A

Resource Support Name Chi-Fan Shih
Resource Support Email chifan@ucar.edu
Resource Support Organization UCAR/NCAR - Research Data Archive
Distributor NCAR Research Data Archive
Metadata Contact Name N/A
Metadata Contact Email rdahelp@ucar.edu
Metadata Contact Organization NCAR Research Data Archive

Author Simpson, Isla
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 2023-09-27
Digital Object Identifier (DOI) https://doi.org/10.5065/5jz0-0n57
Alternate Identifier d583119
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress completed
Metadata Date 2025-06-24T15:05:03Z
Metadata Record Identifier edu.ucar.rda::d583119
Metadata Language eng; USA
Suggested Citation Simpson, Isla. (2023). Observed humidity trends in dry regions contradict climate models. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/5jz0-0n57. Accessed 25 June 2025.

Harvest Source