With the rapid development of atmospheric science, computer science and all other related technologies, massive amounts of weather and climate data are generated daily and made available to the public. These data include conventional weather observation, weather observation networks for specific purposes, volunteer meteorological observation, multi-channel satellite image, radar image, various reanalyzed weather and climate change data, output of models for weather forecast/climate prediction and future climate change projection, etc.

Changes in global surface temperature relative to the reference period 1995-2014 under the scenario SSP1-2.6 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes in global surface temperature relative to the reference period 1995-2014 under the scenario SSP2-4.5 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes in global surface temperature relative to the recent reference period 1995-2014 under the scenario SSP3-7.0 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes in global surface temperature relative to the recent reference period 1995-2014 under the scenario SSP5-8.5 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes (%) in global precipitation relative to the reference period 1995-2014 under the scenario SSP1-2.6 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes (%) in global precipitation relative to the reference period 1995-2014 under the scenario SSP2-4.5 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes (%) in global precipitation relative to the reference period 1995-2014 under the scenario SSP3-7.0 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Changes (%) in global precipitation relative to the reference period 1995-2014 under the scenario SSP5-8.5 based on CMIP6 models[WMO:KNMI] (For education purpose only)
Reanalysis, forecast and simulation data

    For most data users, it is a huge challenge to process or extract useful information from such multi-sources and large amounts of data to achieve their goals.DeepVisum has professional data scientists who have a strong background in weather/climate and have extensive experience in handling such large-scale weather/climate data.With the efforts of our scientists, DeepVisum has established a weather/climate big-data data-lake. Combining existing big data and new data, we can provide your bussiness with any relevant data services to meet your needs.

Historical Climate Observation data
Global Future Climate Change Projection and Downscled Local Data
Radar Rainfall Monitering Data
Annual Average temperature in China and surrounding areas (1991-2020)
Annual average temperature change 2011-2020 vs 1981-2010
Annual total precipitation in China and surrounding areas
Annual total precipitation change (%) 2011-2020 vs 1981-2020
Annual average temperature changes in China and surrounding areas under different scenarios in the 2050s and 2080s based on projections of 7 models run by Chinese academic institutes
Annual precipitation changes in China and surrounding areas under different scenarios in the 2050s and 2080s based on projections of 6 models run by Chinese academic institutes
Global Temperature Changes in the past 10 years
Global precipitation changes (%) in the past 10 years