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GTS Bulletin: WVDL31 EDZF - Warnings (details are described in the abstract)

The WVDL31 TTAAii Data Designators decode as: T1 (W): Warnings T1T2 (WV): Volcanic ash clouds (SIGMET) A1A2 (DL): Germany (The bulletin collects reports from stations: EDGG;EDZF;) (Remarks from Volume-C: FIR SIGMET)

GTS Bulletin: WSDL31 EDZF - Warnings (details are described in the abstract)

The WSDL31 TTAAii Data Designators decode as: T1 (W): Warnings T1T2 (WS): SIGMET A1A2 (DL): Germany (The bulletin collects reports from stations: EDGG;EDZF;) (Remarks from Volume-C: FIR SIGMET)

GTS Bulletin: FADL41 EDZF - Forecast (details are described in the abstract)

The FADL41 TTAAii Data Designators decode as: T1 (F): Forecast T1T2 (FA): Aviation area /GAMET/advisories A1A2 (DL): Germany T1T2ii (FA41): Aviation area/advisories(The bulletin collects reports from stations: EDGG;EDZF;) (Remarks from Volume-C: GAMET)

GTS Bulletin: SAEU30 EDZW - Surface data (details are described in the abstract)

The SAEU30 TTAAii Data Designators decode as: T1 (S): Surface data T1T2 (SA): Aviation routine reports A1A2 (EU): Europe (The bulletin collects reports from stations: LGAT;ATHINAI AP HELLINIKON;EFHK;HELSINKI VANTAA ;EGCC;MANCHESTER ;ESMS;MALMOE STURUP ;EKCH;COPENHAGEN KASTRUP ;EGSS;LONDON STANSTED ;EBBR;BRUSSELS ;ENFB;STATFJORD B;LGTS;THESSALONIKI MACEDONIA INT ;LGEL;ELEFSIS ;LOWW;VIENNA INT ;EGKK;LONDON GATWICK ;EGPK;GLASGOW PRESTWICK ;EGLL;LONDON HEATHROW ;ESSA;STOCKHOLM-ARLANDA ;ESGG;GOTHENBURG-LANDVETTER ;) (Remarks from Volume-C: COMPILATION FOR REGIONAL EXCHANGE)

The Climate Change Workflow of the Flood Event Explorer: Analysis of climate-driven changes in flood-generating climate variables

The Climate Change Workflow is part of the Flood Event Explorer (FEE, Eggert et al., 2022), developed at the GFZ German Research Centre for Geosciences in close collaboration with Helmholtz-Zentrum Hereon , Climate Service Center Germany. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). The goal of the Climate Change Workflow is to support the analysis of climate-driven changes in flood-generating climate variables, such as precipitation or soil moisture, using regional climate model simulations from the Earth System Grid Federation (ESGF) data archive. It should support to answer the geoscientific question How does precipitation change over the course of the 21st century under different climate scenarios, compared to a 30-year reference period over a certain region? Extraction of locally relevant data over a region of interest (ROI) requires climate expert knowledge and data processing training to correctly process large ensembles of climate model simulations, the Climate Change Workflow tackles this problem. It supports scientists to define the regions of interest, customize their ensembles from the climate model simulations available on the Earth System Grid Federation (ESGF), define variables of interest, and relevant time ranges. The Climate Change Workflow provides: (1) a weighted mask of the ROI ; (2) weighted climate data of the ROI; (3) time series evolution of the climate over the ROI for each ensemble member; (4) ensemble statistics of the projected change; and lastly, (5) an interactive visualization of the region’s precipitation change projected by the ensemble of selected climate model simulations for different Representative Concentration Pathways (RCPs). The visualization includes the temporal evolution of precipitation change over the course of the 21st century and statistical characteristics of the ensembles for two selected 30 year time periods for the mid and the end of the 21st century (e.g. median and various percentiles). The added value of the Climate Change Workflow is threefold. First, there is a reduction in the number of different software programs necessary to extract locally relevant data. Second, the intuitive generation and access to the weighted mask allows for the further development of locally relevant climate indices. Third, by allowing access to the locally relevant data at different stages of the data processing chain, scientists can work with a vastly reduced data volume allowing for a greater number of climate model ensembles to be studied; which translates into greater scientific robustness. Thus, the Climate Change Workflow provides much easier access to an ensemble of high-resolution simulations of precipitation, over a given ROI, presenting the region’s projected precipitation change using standardized approaches and supporting the development of additional locally relevant climate indices.

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