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Seasonal Changes

Future changes in seasonal climate with reference to a historical climatological period. Climatological period is user defined and is same in both historical and future periods. Future projections are based on the representative concentration pathways (RCPs).

Many options can be specified to produce yearly time series of a chosen seasonal diagnostic of the daily precipitation data. The user can choose between three parameters and choose different GCM-RCM combinations to assess future seasonal changes over the area of interest. Clicking on the map will then produce a local yearly seasonal time series, frequency distribution and trend of the chosen parameter.

Years, Season and climatology period: Specify the start years in the future and history as well as the climatology period which will automatically define the end years in both history and future. The season can then be specified by choosing the start and end months. Finally, specify the model and parameter for which to perform the analysis.
Historical Start Year: This is defined as the start of the climatological period in history.

Future Start Year: This is defined as the start of the climatological perion in future.
Period: This is the climatological period over which the assessment is to be made, the default value is (30 years). Once this is defined, it will automatically calculate the end years for the climatological period both in history and future. For consistency, this period is same in both time periods.
Distribution Range: This is used for scaling the x-axis of the distribution plot. Precipitation as well as maximum and minimum temperature will have different scales and this parameter should be used to scale the x-axis appropriately.
Models: This defines the combination of GCM-RCM used
Season: is defined by the start month (abbriviated) and end month. A user can specify any number of months to describe their season as is applicable in their region.
Seasonal Changes: The change statistic is calculated by taking the climatological mean of the parameter in both periods and then subtracting the historical climatological mean from the future climatological mean (Future Changes = Mean_Fut - Mean_Hist).

Spatial Resolution: The analysis can performed and map at each 0.44 resolution grid point. Additionally it is possible to average the results of the analysis over the 0.44 grid points falling within administrative boundaries for the time series graph.

Dataset Documentation

Climate projection dataset from the Coordinated Regional Downscaling Experiemnt (CORDEX). This dataset is available for download at any of the ESGF data nodes upon registration.

We acknowledge the World Climate Research Programme's Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. We also thank the climate modelling groups (listed in the model options of this page) for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure an international effort led by the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP).

How to use this interactive map


Contact with any technical questions or problems with this Map Room.