1 / 21

Advertisement: CM SAF

Advertisement: CM SAF. Radiation. Water Vapor. Clouds. EUMETSAT Satellite Application Facility on Climate Monitoring www.cmsaf.eu Provides satellite-derived climate data of geophysical variables Regional, up to global coverage Currently, data available from Jan 1982 to Feb 2012

ernestjones
Download Presentation

Advertisement: CM SAF

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Advertisement: CM SAF Radiation Water Vapor Clouds • EUMETSAT Satellite Application Facility on Climate Monitoringwww.cmsaf.eu • Provides satellite-derived climate data of geophysical variables • Regional, up to global coverage • Currently, data available from Jan 1982 to Feb 2012 • Spatial resolution from 0.03° to approx. 1° • Data freely available in netcdf-format • User-friendly data access via the Web User Interface: www.cmsaf.eu/wui • Toolkit (example data + software): www.cmsaf.eu/tools • CM SAF Community Site available via EUMETSAT: training.eumetsat.int

  2. Analyzing the Stability of Gridded Surface Radiation Data Sets Jörg Trentmann1, Richard Müller1, Arturo Sanchez-Lorenzo2, Martin Wild2 1Deutscher Wetterdienst, EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF)2Eidgenössische Technische Hochschule (ETH), Zürich

  3. Motivation • Gridded Climate Data Sets (e.g., satellite, reanalysis, surface obs) become increasingly available • Three aspects of Climate Data Records should be evaluated: • Climatology (mean) • Temporal Variability (anomalies) • Temporal Stability (trend) • Validation of gridded data sets often does not assess the temporal stability / homogeneity • Validation of a satellite-derived climate data set of solar irradiance using surface measurements

  4. Data Set • CM SAF Meteosat(Posselt et al., 2012) • 1983 – 2005; 0.03 deg; Meteosat Full Disk, monthly/daily/hourly • 6 different satellite instruments (of the same type) used! Does this data set fulfill the requirements for climate quality?

  5. Reference Data Set • GEBA: • Global Energy Balance Archive, hosted at ETH Zürich • > 200 surface stations globally • starting 1930s • Here: ca. 50 European stations starting 1983

  6. Data Set Validation • Validation Strategy: • Climatological measures (mean, variability) • Evaluation of the stability • Comparison of linear trends • Temporal evolution of the bias • Application of homogeneity test

  7. Results: Climatology • Bias in the order of ± 5 W/m2 • Absolute bias: ~ 10 W/m2 • Correlation of anomalies between 0.8 and 0.9

  8. Data Set Evaluation • Evaluation Strategy: • Climatological measures (mean, variability) • Evaluation of the stability • Comparison of linear trends • Temporal evolution of the bias • Application of homogeneity test

  9. 1. Compare Linear Trends Warszawa: CM SAF Meteosat / GEBA • Positive trends in both time series: GEBA: +5.3 W/m2/dec • CM SAF: +2.3 W/m2/dec • Trends agree within their level of significance

  10. 1. Compare Linear Trends Mean all stations: CM SAF Meteosat / GEBA Positive trends in both time series: GEBA: +3.6 W/m2/dec CM SAF: +1.8 W/m2/dec

  11. Data Set Evaluation • Evaluation Strategy: • Climatological measures (mean, variability) • Evaluation of the stability • Comparison of linear trends • Temporal evolution of the bias • Application of homogeneity test

  12. 2. Analyze Bias Time Series Warszawa: CM SAF Meteosat GEBA Significant negative trend of 3 W/m2/dec in the bias time series

  13. 2. Analyze Bias Time Series Mean all stations: CM SAF Meteosat GEBA Significant negative trend of 1.76 W/m2/dec in the mean bias time series

  14. Data Set Evaluation • Evaluation Strategy: • Climatological measures (mean, variability) • Evaluation of the stability • Comparison of linear trends • Temporal evolution of the bias • Application of homogeneity tests

  15. 3. Homogeneity Test Penalized Maximum T test(PMT, Wang et al., 2008): Warszawa: CM SAF Meteosat GEBA • Detects changes of the mean • Model assuming constant values and (multiple) shifts • Software and documentation readily available

  16. 3. Homogeneity Test • No clear shift detected in all time series • Maximum of (negative) shifts in 1993-1995 • Very few shifts after 1995

  17. 3. Homogeneity Tests Homogeneity Test (SNHT) • Shifts detected in 1987 and 1994 (corresponding to changes in satellite) • No shift detected after 1994, data set is homogeneous between 1994 and 2005

  18. 1. Linear Trends (> 1994) Compare CM SAF Meteosat / GEBA after 1994 Trend Bias • Consistent linear trends (~ 4.6 W/m2/dec) • Zero trend in the bias time series • High homogeneity of the CM SAF Meteosat data set after 1994 in Europe

  19. Trend in Surface Radiation Spatial distribution of linear trend (1994 – 2005) based on CM SAF Meteosat • Substantial variability (decrease in Mediterranean!) • Mean Trend: 3.1 W/m2/dec

  20. Conclusions • Temporal stability of gridded climate data setsneed to be evaluated • Linear trends in surface irradiance in Europe tend to be reproduced by CM SAF data set • Inhomogeneities have been detected in theCM SAF data set before 1994 • The trend in surface irradiance in Europe between1994 and 2005 is spatially inhomogeneous • Outlook: • Compare with independently-derivedgridded data sets (e.g., surface obs,reanalysis) • Evaluate the homogeneity of the surfacedata using multiple gridded data sets

More Related