The ICA&D concept Robert Leander Royal Netherlands Meteorological Institute On behalf of the ECA&D project team Aryan van Engelen Else van den Besselaar Albert Klein Tank Gerard van der Schrier

Contents Definition and purpose what is the ICA&D concept? Key components Components and their connection Implementation requirements Look and feel of the web-portal A swift browse through the ECA&D site Lets fantasize about the WACA&D site Contents

Daily station data Quality controlled Regional Climate changes indices Definition and purpose Characteristics International Climate International Climate Assessment & Dataset

ICA&D examples ECA&D, SACA&D, LACA&D….

For example ??? ECA&D, SACA&D, LACA&D…. why not WACA&D ?

Contents Key components MySQL database Apache Webserver Fullcycle: QC Blending Index calculation Homogeneity tests Trends, climatology, extreme analysis Development Maintenance of data + metadata Update cycle

Contents Key components MySQL database Apache Webserver MySQL database Apache Webserver Fullcycle: QC Blending Index calculation Homogeneity tests Trends, climatology, extreme analysis DevelopmentOperational Maintenance of data + metadata Update cycle

Updating series + metadata Quality control Blending stations Indices calculation Homogeneity tests Trend analysis climatology, anomalies and extreme analysis …. Update cycle Fullcycle: QC Blending Index calculation Homogeneity tests Trends, climatology, extreme analysis Update cycle Bash-scripting, C/F77 routines Manual intervention required

Updating raw series + metadata Quality control Blending stations Indices calculation Homogeneity tests Trend analysis climatology, anomalies and extreme analysis …. Fullcycle: QC Blending Index calculation Homogeneity tests Trends, climatology, extreme analysis Update cycle Bash-scripting, C/F77 routines Fully automated process Update cycle

Fullcycle: QC Blending Index calculation Homogeneity tests Trends, climatology, extreme analysis Update cycle Blending Extending and completing a station series with data from nearby stations Stations within certain proximity and within a certain range of altitude are considered, depending on the element SYNOP data is the least preferred source …. only used if no suitable historical data available

Fullcycle: QC Blending Index calc. Homogeneity Trends, climatology, extreme analysis Update cycle Index calculation ETCCDI indices (same as in RClimdex) Additional Impact-related indices Comfort indices like UTCI, Tourism index Specific agricultural indices Viticulture-related indices Hydrological indices like hydrologic intensity HY-INT (Giorgi) And more … new index definitions can smoothly be integrated into the system

Fullcycle: QC Blending Index calculation Homogeneity Trends, climatology, extreme analysis Update cycle Homogeneity Four tests on some indices (RR, TGG, etc): Von Neumann Ratio Test Buishand Range Test Alexanderson SNHT Pettit Test } Identify break Classification of series: suspect3 or more tests detect change doubtfull2 tests detect break usefullnot more than 1 test detects break

Fullcycle: QC Blending Index calculation Homogeneity Trends, …. Update cycle Various analyses For those series whose series are not suspect Climatology Anomalies Trends Returnvalues

Contents Database (devel) MySQL database Primary variables (daily resolution): tg,tx,tn,rr,hu,ss,sd,cc,ff,fx,dd Raw daily series Blended daily series QC results Annual index series Homogeneity test results Station metadata Analyses results Trends Climatology Extremes ….. } Operational database Update cycle Webserver (devel) New raw data

Contents Web server(s) Apache Webserver Apache Webserver Internal web-serverExternal web-server External DatabaseInternal Database PHP – based JPGRAPH for plotting MapServer / MapScript for mapping

Separate linux-based development and operational system. Web-content generation real-time Apache 2.0, MySQL , PHP Mapserver (maps), Jpgraph (plots) C, shell scripting (update cycle) Fortran (some of the calculations, gridding) Infrastructure Summarizing:

ECA Website walkthrough..

2009 ECA&D : data inventory

2009 ECA&D : (Raw) Daily data Raw and blended daily station data for the take… …..but ONLY the PUBLIC data !! The participant decides

2009 ECA&D walkthrough: Daily data Raw and blended daily station data for the take… …..but ONLY the PUBLIC data !! The participant decides

2009 ECA&D : Extreme events

2009 ECA&D : Extreme events

2009 ECA&D : Indices

2009 ECA&D : Timeseries plots

2009 ECA&D : Index time series May 20 May 2010

2009 ECA&D : Indices maps

2009 ECA&D : Indices maps

2009 ECA&D walkthrough

2009 ECA&D : Index map: RR1

2009 ECA&D : Index map: RH

2009 ECA&D : Climatology RR1

2009 ECA&D : Anomalies RR1

2009 ECA&D : Trend RR1

WACA&D : CWD Trend

WACA&D : CWD Trend

2009 WACA&D : CWD Trend

ICA&D is useful in climate monitoring Participants can profit from the analyses Still they have full control over data distribution The system is simpel in design and straightforward to maintain and extend We are there to share the software, our innovations and assist in the local setup The ICA&D concept is very well portable Conclusion

Meteorologist: What is the use of climate data ??

Thank You for your attention! Merci beaucoup pour votre attention!