Computational module of geoinformational web-system for climate - PowerPoint PPT Presentation

Computational module of geoinformational web-system for climate change analysis: method, data and results for Siberia T. Shulgina, Gordov E.P, Okladnikov I.G, Titov A.G. Institute of Monitoring of Climatic and Ecological Systems SB RAS Siberian Center for Environmental Research and Training, Tomsk, Russian Federation

Method Abstract The report presents description of computational Parameters of investigation: module aimed at mathematical • Station data, Reanalysis data; and statistical analysis of • Meteorological parameter; spatially-distributed • Spatial and temporal resolution. environmental data series. To characterize dynamics of meteorological parameters, Data selection module computational module allows performing mathematical Data analysis module comparison meteorological characteristics calculated based on different datasets and Archive of calculation results calculating the statistical characteristics, climate Investigation results: extreme indices and frequency • Reliable data; • Climatic characteristics analysis; of weather events. • Archive of calculation results.

Data Assimilation Dataset Time range Data resolution Temperature method NCEP/NCAR 1951 – 2001 2Т: 00, 12 h Reanalysis 2.5 °× 2.5 ° 3D-Var 17 Levels NCEP/DOE 1979 – 2003 4Т: 00, 06, 12, 18 h AMIP II 2.5 °× 2.5 ° 3D-Var Reanalysis 17 Levels ECMWF 1957 – 2004 4Т: 00, 06, 12, 18 h ERA-40 2.5 °× 2.5 ° 3D-Var Reanalysis 23 Levels ECMWF ERA 1989 – 2010 T: 10 d INTERIM 0.25 °× 0.25 ° 4D-Var Precipitation Reanalysis Surface JMA/CRIEPI 1979 – 2009 4T: 00, 06, 12, 18h JRA-25 2.5 °× 2.5 ° 3D-Var Reanalysis 23 Levels APHRODITE 1951 - 2007 T: 1 d JMA 0.25 °× 0.25 ° Surface NOAA-CIRES 1908 - 1958 4T: 00, 06, 12, 18h 20th Cen. 2.0 °× 2.0 ° Rean. 9092с 1951 - 2000 212 stations over Synoptic Siberia territory Network

Data analysis ECMWF ERA-40 data. Data analysis procedures 1958 – 2001. 1. Climatic characteristics Trend of growing Statistical characteristics season duration (daily temperature > 5 °С ). Time dynamics indices of meteorological parameters Indices correlating with forest production 2.Spatial and temporal dynamics Correlation and trend Statistical tests Interpolation methods Software: APHRODITE JMA data. 1958 – 2000. • IDL (Interactive Data Language) Trend of precipitation • Python intensity (R >= 1 mm). • ArcMap

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