Road traffic emissions of nitrogen oxides (NOx), carbon monooxide (CO) and volatile organic compounds (VOC) influence the concentration of ozone (O3) and methane (CH4) in the atmosphere. These greenhouse
This project provides variables from MPI-ESM1-2 CMIP6 experiments performed by DKRZ, MPI-M and DWD in the context of the BMBF funded CMIP6 DICAD project (FKZ 01LP1605A). The experiments are described at
This archive contains the source code of ICON-ESM-V1.0, primary data, and supplementary material connected to the article “Jungclaus, J.H. et al.: The ICON Earth System Model V1.0” as submitted to the
The datasets in this project are developed as a part of a project associated with the Indian Institute of Technology Delhi, India, and the National Mission for Clean Ganga, Government of India. We have
PDRMIP is a climate model intercomparison project that ran from the end of 2013 until completion in 2021. In PDRMIP a number of different climate models have been used to explore whether differences in
In order to better understand the global coastal systems and the dangers and risks associated with them, it is important to examine the atmosphere, the land, hydrology, the ocean and especially their interactions
SOLCHECK will significantly advance the understanding and quantification of the solar contribution to past, present, and future climate evolution in the Northern Hemisphere on decadal to centennial timescales.
GRoW-SaWaM (BMBF): The SaWaM-Project, which is funded by the German Federal Ministry of Education and Research (BMBF) within the "Water as a global Resource (GRoW)“ initiative, aims at the development
The IMLAND project investigates climate change adaptation options within the agricultural sector. It focuses on the region of Northeast Lower Saxony, which is the largest irrigation area in Germany. In
Global climate models have difficulties to simulate the northward extension of the monsoonal precipitation over north Africa during the mid-Holocene as revealed by proxy data. A common feature of these
Dynamical downscaling of global gridded data sets from operational analyses, reanalyses, paleoclimate simulations and climate projections for various regions and time periods by a numerical weather prediction
The primary goal of HadCRU_MLE is to combine instrumental observations with physically realistic statistical models to produce maximum likelihood estimates of surface temperature anomalies and other physical