A Probabilistic Statistical Climatological Relationship between Precipitable Water Vapor and Precipitation for Near-Real Time Forecasting Applications

The IPCC 5th Assessment found that the warming of the climate system is unequivocal and the probability of extreme events such as heat waves, droughts, and floods will increase. Society is highly vulnerable to these extreme weather events, through impacts such as disruption of food production, water supply, health, and damage of infrastructure. Forecasting and monitoring of extreme weather events is essential for mitigation of societal impacts.

The Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite was launched in 2002 and provided the capability to retrieve water vapor profiles at high vertical resolution and good absolute accuracy over the ocean and land using the same algorithm. Currently, there is over 10 years of global gridded daily precipitable water vapor (PWV) data from the AIRS instrument. The NASA Tropical Rainfall Measuring Mission (TRMM) was launched in 1997 and provided nearly global precipitation observations over both land and ocean. Similarly, there is over a decade of global gridded daily precipitation data available from this mission. This paper utilizes the length and quality of these two datasets to derive a 10-year statistical climatological relationship between PWV and precipitation. Conditional probabilities and joint probabilities will be used to showcase the relationship. The potential application of the derived climatological relation for near-real time warning of extreme precipitation and flash flood events will be discussed.