Spatially comprehensive representations of past weather and climate are an important basis for analyzing climate variations and for modelling weather-related impacts on the environment and natural resources. Such gridded datasets are also indispensable for validation and downscaling of climate models. Increasing demands for, and widespread application of grid data, call for efficient methods of analyses to integrate the observational data, and a profound knowledge of the potential and limitations of the datasets in applications.

Modern spatial climatology seeks to improve the accuracy, coverage and utility of grid datasets. Prominent directions of the actual development in the field are the following:

• Establish datasets for new regions and extend coverage to larger, multi-national and continental domains, building on data collection and harmonization efforts.
• Develop datasets for more climate variables and improve the representation of cross-variable relationships.
• Integrate data from multiple observation sources (stations, radar, satellite, citizen data, model-based reanalyses) with statistical merging, machine learning and model post-processing.
• Extend datasets back in time, tackling the challenges of long-term consistency and variations in observational density.
• Improve the representation of extremes, urban climates, and small-scale processes in complex topography.
• Quantify uncertainties and develop ensembles that allow users to trace uncertainty through applications.
• Advance the time resolution of datasets to the sub-daily scale (resolve the diurnal cycle), building on methods of spatio-temporal data analysis.

This session addresses topics related to the development, production, and application of gridded climate data, with an emphasis on statistical analysis and interpolation, inference from remote sensing, or post-processing of re-analyses. Particularly encouraged are contributions dealing with new datasets, modern challenges and developments (see above), as well as examples of applications that give insights on the potential and limitation of grid datasets. We also invite contributions related to the operational production at climate service centers, such as overviews on data suites, the technical implementation, interfaces and visualisation (GIS), dissemination, and user information.

The session intends to bring together experts in spatial data analysis, researchers on regional climatology, and dataset users in related environmental sciences, to promote a continued knowledge exchange and to fertilise the advancement and application of spatial climate datasets.