Each week, ISciences processes an ensemble of 28 seasonal temperature and precipitation forecasts issued by the National Oceanic and Atmospheric Administration's Climate Forecast System Version 2 (CFSv2). The maps that follow depict global temperature and precipitation forecasts maps for June 2015 and are based on CFSv2 forecasts issued May 15 through May 21, 2015. The full report contains monthly temperature and precipitation forecasts for June 2015 through February 2016.
Most of the world's land surface is forecast to have above normal temperatures in June 2015. Extreme warm anomalies are forecast for the west coasts of Central and South America and portions of the Sahel and Egypt. Cool anomalies are forecast for Texas, central Mexico. Cool extremes are forecast for central Africa.
Wet anomalies are forecast for Southwest United States, Northwest Mexico, Western and Southern Brazil, Turkey, and portions of Western Australia. Dry anomalies are forecast for Northern South America, Northern India, Southeast Asia, and the Philippines.
This blog post presents results from our "WSIM Precipitation and Temperature Forecasts" report issued on May 25, 2015. This report includes forecasts for June 2015 through February 2016 based on NOAA CFSv2 forecasts issued May 15 through May 21, 2015.
Technical details:
- Forecasts are based on an ensemble of 28 forecasts issued by the National Oceanic and Atmospheric Administration's Climate Forecast System Version 2 (CFSv2).
- Each CFSv2 forecast is bias corrected by:
- Constructing probability density functions from CFSv2 hindcasts.
- Fitting the hindcast probability distribution functions to a generalized extreme value distribution.
- Using an inverse lookup to an extreme value distribution fitted to the observed temperature and precipitation record (Fan & vanden Dool 2008, Chen et al. 2002).
- The maps colors depict the return period of the median forecast anomaly.
- Regions where the interquartile range of the enemble spans both above normal and below normal conditions are hashed as having uncertain direction.
- Regions where the interquartile range of the ensemble divided by the median forecast is large (>0.4) are hashed as having uncertain magnitude.