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Monthly mean snow depth: maps

Maps of monthly mean snow depth derived from SYNOP observations on a 0.1x0.1 degree grid, provided by WMO RA VI Regional Climate Centre (RCC) on Climate Monitoring WMO-RA6-RCC-CM

Langjährige Niederschlagsverteilung 1961-1990 (Umweltatlas)

Langjährige Niederschlagsverteilung (1961-1990) in Berlin und dem näheren Umland (Gesamtjahr, Sommer, Winter), Bearbeitungsstand Juli 1994.

GTS Bulletin: ISAH02 HKNS - Observational data (Binary coded) - BUFR (details are described in the abstract)

The ISAH02 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISA): Routinely scheduled observations for distribution from automatic (fixed or mobile) land stations (e.g. 0000, 0100, … or 0220, 0240, 0300, …, or 0715, 0745, ... UTC) A2 (H): 90°E - 0° tropical belt(The bulletin collects reports from stations: HKNS;) (Remarks from Volume-C: XXX)

Langjährige Niederschlagsverteilung 1981-2010 (Umweltatlas)

Langjährige Niederschlagsverteilung in Berlin und dem näheren Umland (Gesamtjahr, Winter- und Sommerhalbjahr). Es wurden die Niederschläge der Wasserwirtschaftsjahre 1981-2010 zugrunde gelegt. Diese umfassen den Zeitraum vom 01.11.1980 bis zum 31.10.2010.

GTS Bulletin: HHXL30 EDZW - Grid point information (GRIB) (details are described in the abstract)

The HHXL30 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HH): Height A1 (X): Global Area (area not definable) A2 (L): 84 hours forecast T1ii (H30): 300 hPa (Remarks from Volume-C: H+ 84 (GLOBAL MODEL) HEIGHT 300 HPA)

GTS Bulletin: HVXC92 EDZW - Grid point information (GRIB) (details are described in the abstract)

The HVXC92 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HV): Northward wind component A1 (X): Global Area (area not definable) A2 (C): 12 hours forecast T1ii (H92): 925 hPa (Remarks from Volume-C: H+ 12 (GLOBAL MODEL) WIND COMPONENT 925 HPA)

Model Output Statistics for Borkum-Süderstraße (E006)

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

Model Output Statistics for Berlin-Alexanderplatz (10389)

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

Model Output Statistics for IBRA (41265)

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

Natuerliche Waldentwicklung im Alpenvorland Bayerns

Die nacheiszeitliche Waldentwicklung im sueddeutschen Alpenvorland ist bisher nur innerhalb des an Seen und Mooren reichen Gebietes der letzten Vereisung untersucht worden. In dem genannten Vorhaben wird versucht, diese Untersuchungen auch auf das ehemals nicht vergletscherte Gebiet auszudehnen. Hierbei kommt es sowohl auf die Ermittlung der generellen Zuege in der nacheiszeitlichen Vegetationsentwicklung dieses Raumes an, als auch auf die Untersuchung der Vegetationsgeschichte einzelner Spezialstandorte.

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