Download Developing a Caribbean climate interactive data base

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]
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
Methodology
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
•
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.
The planned data base will cover the domain 0⁰ 30⁰N and 110⁰ - 50⁰W. This includes 21
Caribbean countries.
Jamaica
Costa Rica
Data Sources and Types
Dataset
GHCN
Data Source
Global Historical Climate
Network (GHCN) National
Climate Data Center, (USA).
Data Type
Station
Monthly
Variables
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
Workshop
Workshop on Climate Data
Collection and Dissemination,
Mona, Jamaica, 2001.
(Peterson et al 2002)
Station
daily
Magaña
Magaña – Magana et al (1999)
Taylor et al (2002)
Gridded
(0.5o x0.5o)
Monthly
Precipitation
National Center for
Atmospheric Research
(NCAR) (Kalaney et al, 1996 )
Gridded
(2.5o x2.5o).
Monthly
Geopotential height, relative
humidity, specific humidity,
temperature, pressure vertical
velocity, u wind v wind
Reanalysis
Precipitation
Mean Temperature, Maximum
Temperature, Minimum
Temperature and
Precipitation.
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.
Structural Modules of the Database and their Functions
MODULE NAME
FUNCTION
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.
Schematic Diagram of the Database
SCREENSHOT OF USER INTERFACE MODULE
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
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
TYPICAL EXAMPLES OF SUCH CONTRIBUTIONS
Caribbean Warming Trend
Recent analysis of Caribbean
Temperature by Peterson and
Taylor et al (2002).
Show increasing trend
Precipitation Decreasing Trend
Peterson and Taylor et al. 2002
Show decreasing “linear trend”. But dominated by variability
on the annual to decadal scales.
Mean Precipitation Climatology
of the Caribbean
Bimodal Nature of the Precipitation
Chen et al. 1997; 2002
A Time Series of Jamaica
Rainfall
Ref: Jamaica’s First National Communication to UNFCCC
National Meteorological Service, Jamaica
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.