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Developing a Caribbean Climate Interactive Database (CCID) Rainaldo F. Crosbourne, Michael A. Taylor, A. M. D. Amarakoon** CLIMATE STUDIES GROUP MONA Department.

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Presentation on theme: "Developing a Caribbean Climate Interactive Database (CCID) Rainaldo F. Crosbourne, Michael A. Taylor, A. M. D. Amarakoon** CLIMATE STUDIES GROUP MONA Department."— Presentation transcript:

1 Developing a Caribbean Climate Interactive Database (CCID) Rainaldo F. Crosbourne, Michael A. Taylor, A. M. D. Amarakoon** CLIMATE STUDIES GROUP MONA Department of Physics University of the West Indies JAMAICA [** SPEAKER]

2 INTRODUCTION AIACC (Assessment of Impacts and Adaptation to Climate Change) project SIS06. –Investigates the link between climate and dengue –Involves organizations – CSGM (Climate Studies Group Mona, CAREC (The Caribbean Epidemiology Center), CPACC (Caribbean Planning for Adaptation to Climate Change) etc. –Demands a lot of climate and dengue data, that need to be stored. –Requires that the climate data be accessible through a web interface. –All the climate data be converted to one common comprehensive form –Caribbean data isn’t easily available –If it is available, it isn’t easily accessible. –AIACC-SIS06 researchers, in dengue and climate, need specific climate variables and in specific format. The above problems were acknowledged and the need for a Caribbean Climate Interactive Database arose. CCID will attempt to solve all those problems

3 Methodology Gridded data –Interpolation of data to a regular grid. Oftentimes this involves a synthesis of station data, satellite data, data from ocean sensors and ship data. It has the structure shown. Acquiring the data Climate data is available in two forms Station data: Time series of a particular variable recorded at a particular location in a territory. Station data are usually recorded by the national meteorological stations, water resource authorities and agriculture research stations. Station Data are identified by parameters such as: Country, Station name, ID, Latitude, Longitude, Elevation, Time Series, Variable

4 The planned data base will cover the domain 0 ⁰ - 30 ⁰N and 110⁰ - 50⁰W. This includes 21 Caribbean countries. Costa Rica Jamaica

5 Data Sources and Types Dataset Data SourceData TypeVariables GHCN Global Historical Climate Network (GHCN) National Climate Data Center, (USA). Station Monthly Mean Temperature, Maximum Temperature, Minimum Temperature and Precipitation. UWI University of the West Indies (UWI) Climate Studies Group Mons (Chen and Taylor, 2002) Gridded (R40), monthly Precipitation Workshop Workshop on Climate Data Collection and Dissemination, Mona, Jamaica, (Peterson et al 2002) Station daily Mean Temperature, Maximum Temperature, Minimum Temperature and Precipitation. Magaña Magaña – Magana et al (1999) Taylor et al (2002) Gridded (0.5 o x0.5 o ) Monthly Precipitation Reanalysis National Center for Atmospheric Research (NCAR) (Kalaney et al, 1996 ) Gridded (2.5 o x2.5 o ). Monthly Geopotential height, relative humidity, specific humidity, temperature, pressure vertical velocity, u wind v wind

6 Methodology……. Design Of The Database Issues influencing the design CCID needs to fulfill the following criteria: Store large quantities of historical climate data on a variety of temporal and spatial scales. Store both gridded and station data with time resolution ranging from daily to yearly. The need for easy and quick retrieval of subsets of the database as specified by the user. The need to compute context specific statistical analysis of the data. Easy update of the database as new data become available. Easy update of the structure of the database, so as to facilitate changes in representation, that can be made to new data being stored.

7 Structural Modules of the Database and their Functions MODULE NAMEFUNCTION Data Storage And Retrieval Handles the way climate data is stored. Creates suitable directory structure to facilitate fast and easy access of data Statistics Handles all the statistical calculations that are needed. Data Update Handles the data updates. Visualizations Handles all the visualizations necessary for data analysis. Can take information from the statistics and the Data Storage and retrieval modules, and present suitable visualizations to the user interface The User Interface Allows the user to interact with all the other modules without knowing how each module is implemented.

8 Schematic Diagram of the Database

9 SCREENSHOT OF USER INTERFACE MODULE

10 Significance/Contributions of the CCID Once CCID is fully developed, it will provide a wealth of Climate Data that can easily be accessed and spanning a wider region. Under one roof, it enables: The study of the climate variability/change on a regional/country/parish(county) basis, on different time scales. Information on the frequency of droughts or floods The study of precipitation climatology Statistical and time series analysis of climate variables and also cross correlations together with visualizations Quick output of results

11 Significance…………. Thus, CCID, shall be an invaluable data depository for the SIS06 project as it is concerned with climate impacts on dengue epidemic. In relation to the National Communications under the UNFCCC, CCID is again of immense practical value, as: Climate/drought/flood impacts on the Health, Agriculture, and hence on the Economic Sector are some main components dealt in National Communications

12 Recent analysis of Caribbean Temperature by Peterson and Taylor et al (2002). Show increasing trend TYPICAL EXAMPLES OF SUCH CONTRIBUTIONS Caribbean Warming Trend

13 Peterson and Taylor et al Show decreasing “linear trend”. But dominated by variability on the annual to decadal scales. Precipitation Decreasing Trend

14 Mean Precipitation Climatology of the Caribbean Bimodal Nature of the Precipitation Chen et al. 1997; 2002

15 A Time Series of Jamaica Rainfall Ref: Jamaica’s First National Communication to UNFCCC National Meteorological Service, Jamaica

16 CONSTRAINTS Lack of digitized daily data. Digitization was time and labour consuming Incomplete data records and poor quality of some records. Needed quality control Unwillingness to share data, RED TAPES! Lack of spatial variability in station data. A limitation to the dengue project. Mismatch of climate and dengue data formats (reporting periods). Impact may not be severe.

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