Analysis of Climatic and Environmental Changes Using CLEARS Web-GIS Information-Computational System: Siberia Case Study

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1 Analysis of Climatic and Environmental Changes Using CLEARS Web-GIS Information-Computational System: Siberia Case Study A G Titov 1,2, E P Gordov 1,2, I G Okladnikov 1,2, T M Shulgina 1 1 Institute of Monitoring of Climatic and Ecological Systems SB RAS 2 Tomsk Branch of the Institute of Computational Technologies SB RAS

2 Introduction! Substantial climate changes are observed in Northern regions ( particularly in Siberia )! Significant Influence on dynamics of global climate processes! Lack of reliable estimates of climatic parameters! Detailed study of regional climate variability required! Multidisciplinary, spatially distributed research process! Informational-computational support of integrated studies for Earth sciences required 2

3 Problem statement! Complex analysis of geophysical datasets for monitoring and forecast of climate and ecosystems changes! Meteorological observations! Reanalysis and modeling results! Remote sensing products! Integration of heterogeneous datasets of huge size! Applying verified data processing algorithms! Providing access to data processing and visualization tools via unified graphical user interface 3

4 Approach! Combined usage of Web and GIS technologies! Concentration of computational resources! Geophysical dataset storage system! Required functionality implemented within Internet portal! Great variety of application tasks to be solved in the area of Earth Science! Software framework for rapid development of thematic information-computational Web-GIS systems! CLEARS - CLimate and Environment Analysis and Research System 4

5 CLEARS General Architecture 5

6 Current state: datasets! Reanalysis (ERA-40, JRA-25, NCEP/NCAR, NOAA-CIRES, ERA Interim, APHRODITE Water Resources)! Meteorological stations data! Landsat 4-7, GLS, MODIS imagery! Set of georeferenced vector and raster maps ( land cover, NDVI, )! High-resolution meteorological datasets for selected regions (WRF model output)! Total amount: 15 Tb! Reanalysis are converted to NetCDF/HDF5 data files 6

7 Current state: functionality! Computational modular kernel! Data access, processing and visualization of results! ITTVIS IDL 7.0! Extensible, supports user modules! Input: GRIB1, NetCDF (including WRF output), HDF5! Output: PostScript, GeoTIFF, ESRI Shapefile, NetCDF, XML! Calculation modules! Mathematical and statistical analysis! Modeling data verification! Landsat imagery processing 7

8 Current state: shaded plots Intra-annual extreme temperature range Monthly maximum 1-day precipitation ECMWF ERA-40 Reanalysis NOAA-CIRES XX Century Global Reanalysis 8

9 Current state: contour plots 9 Near surface air temperature, January mean 9

10 Current state: graphical output Average annual temperature at surface Average daily temperature at 2m ECMWF ERA Interim Reanalysis WRF Model output 10

11 Landsat imagery processing => 1. Near RGB 2. NDVI 3. 11

12 Graphical user interface 1. NDVI background 2. Contour plot of mean air temperature 3. Landsat images 12

13 Siberia case study: state of the art! On-going climatic changes in Siberia are strongly pronounced and spatially non-uniform (inhomogeneous??)! Air temperature trends in the second half of the 20th century were quite high (more than 0.2 C/10 yr)! In some regions of West Siberia ( "hot spots" ), a temperature rise of 0.5 C/10 yr observed, mostly in the winter and spring seasons! Trends obtained from observations and reanalyses data are contradictory! Further studies of spatiotemporal behavior of regional climatic characteristics are required 13

14 ! Network of meteorological stations is irregular and even sparse, 59 stations chosen! Modeled data usage! How to select appropriate dataset? 14

15 Dataset selection algorithm! Reconstruction Surface air temperature of reanalysis and temperature precipitation values data the retrieved weather stations locations from the ECMWF ERA Interim reanalysis and APHRODITE JMA reanalysis datasets, respectively, are statistically consistent with reliable in situ meteorological! For the reconstructed and in situ time series of surface air temperature and precipitation, mean and root-mean-square errors observations. were calculated 15

16 Analysis of surface air temperature dynamics Trends of surface air temperature for the period averaged for: year, winter, summer, spring, autumn 16

17 Analysis of precipitation dynamics Trends of precipitation totals for winter (a) and summer (b) during the period 17

18 Dynamics of bioclimatic indices Trends of the growing season length and the sum of the growing degree days during the period 18

19 Siberia case study: main results! The most reliable spatio-temporal characteristics of surface temperature and precipitation in Siberia are provided by ERA Interim and APHRODITE JMA Reanalyses, respectively! Significant positive trends of growing season length accompanied by statistically significant increase of sum of growing degree days for the south of Western Siberia revealed! Tendency to an increase of vegetation ecosystems productivity across the south of Western Siberia (55-60 N, E) in the past several decades 19

20 Conclusion The CLEARS functionality providing tools for comparison of modeling and observational data as well as for reliable climatological analysis allows obtaining new results characterizing regional manifestations of global change. Each analysis performed using the system leads also to generation of the archive of spatio-temporal data fields ready for subsequent usage by other specialists. In particular, the archive of bioclimatic indices obtained will allow performing further detailed studies of interrelations between local climate and vegetation cover changes, including changes of carbon uptake related to variations of types and amount of vegetation and spatial shift of vegetation zones. 20

21 Acknowledgements! This work is partially supported by RFBR grants # and # a, SB RAS Basic Program Projects and ! RFBR travel grant # з 21

22 Thank you for your attention! 22

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