This plot shows the time series of a country’s 12-month Weighted Anomaly Standardization Precipitation (WASP) index relative to a baseline period. The purpose of this tool is to provide a simple visual means of relating country-averaged precipitation to a reference period of interest.
To compute the WASP index, monthly precipitation departures from the long-term (30-year) average are obtained and then standardized by dividing by the standard deviation of monthly precipitation. The standardized monthly anomalies are then weighted by multiplying by the fraction of the average annual precipitation for the given month. These weighted anomalies are then summed over a 12-month time period.
Precipitation, especially in dry lands (warm semi-arid and desert fringe areas), is one of the factors responsible for creating the conditions which lead to the formation of sufficient surface water and moisture for mosquito breeding sites.
For WASP index values above (below) the baseline, the area between the index and the baseline value is shaded in green (brown). A baseline above (below) 0 indicates the selected year or period recorded precipitation above (below) the long-term average.
WASP index values are derived from precipitation estimates from the Merged Analysis of Precipitation from the Climate Prediction Center (CMAP).
Lyon, B., and A. G. Barnston. ENSO and the spatial extent of interannual precipitation extremes in tropical land areas. Journal of Climate, 2005, 18:5095-5109.
Lyon, B. The strength of El Niño and the spatial extent of tropical drought. Geophys. Res. Lett., 31, 2004, L21204.
Contact help@iri.columbia.edu with any technical questions or problems with this Map Room, for example, the forecasts not displaying or updating properly.
The default plot on this page displays the WASP values spatially averaged over a country (Algeria) against a base period (1979). Users can select a country and baseline year by using the menu at the top of the page. As the user moves the cursor over the map, a tool bar will appear on top that will allow for the baseline period to begin at different months.
For example, selecting “Mali”, “1985” and “March” will produce a time series with WASP values averaged over Mali relative to a baseline corresponding to the March 1985-February 1986 average.
The baseline can be a single year or consist of a range of years. For multiple years, enter the 4 digits of the desired years separated by one blank. For instance the entry 1985 1990 2004 will select those 3 single-year baselines and average them to form a new baseline. For a range of years, enter the 4 digits of the first and the last year (inclusive) separated by a "-". For instance 1990-1999 will select the 10 single-year baselines of the 90s and average them to form a new baseline.