The DWD climate predictions website: towards a user-oriented seamless climate service based on subseasonal, seasonal and decadal predictions
Authors: Paxian Andreas , Mannig Birgit , Tivig Miriam , Stanley Kelly , Ziese Markus , Pasternack Alexander , Pankatz Klaus , Wehring Sabrina , Lorenz Philip , Fröhlich Kristina , Kreienkamp Frank , Früh Barbara 
Published: July 2023

The DWD climate predictions website www.dwd.de/climatepredictions presents different climate predictions on a common website to support decision-making processes on different time scales: post-processed subseasonal prediction products derived from the IFS forecasts provided by ECMWF for the coming weeks and operational seasonal and decadal predictions of the German climate prediction system for the coming months and years.
The user-oriented evaluation and design of this climate service was developed in cooperation with users from various sectors (e.g. water, energy, agriculture or forestry) and is consistent across all time scales. The website offers maps, time series and tables of ensemble mean and probabilistic predictions in combination with their skill. The products are displayed for weekly, 3-month as well as 1- and 5-year temperature means and precipitation sums for different regions (world, Europe, Germany, German regions).
For Germany, the statistical downscaling EPISODES is used to reach high spatial resolution required by several German climate data users. A lead-time dependent bias correction is applied, and decadal predictions are recalibrated to improve drift and ensemble spread. We use the MSESS and RPSS to evaluate the skill of climate predictions compared to reference predictions (applied by users as an alternative to climate predictions), e.g. the &#8216;observed climatology&#8217; or &#8216;uninitialized climate projections&#8217;. The significance is tested at a 5% level.
Different layers of complexity are presented: Within the &#8216;basic climate predictions&#8217; section, a traffic light indicates if regional-mean predictions are significantly better (green), not significantly different (yellow) or significantly worse (red) than a reference prediction. Within the &#8216;expert climate predictions&#8217; section, prediction maps show per grid box the prediction (via the color of dots) and its skill (via the size of dots). The co-development of this climate service with users from different sectors improves its comprehensibility and usability. Outlooks are regularly communicated, and user feedback loops are continuously performed to evaluate and improve this climate service.
Drought-related variables and indices such as the climatic water balance (precipitation minus potential evapotranspiration), SPI (standardized precipitation index) or SPEI (standardized precipitation evaporation index) are evaluated and will soon be included in the climate outlook. Cooperation work is ongoing to use climate predictions to forecast soil moisture and groundwater levels. Plans for future extensions of this climate service include multi-year seasonal predictions, multi-model predictions, large-scale and extreme indices (e.g. for ENSO, NAO, heat), and tools to further clarify the presented information (e.g. video clips or interactivity). Finally, we work on a time series combining observations, subseasonal, seasonal and decadal climate predictions and climate projections, the next step towards a seamless climate service for Germany.