Disasters Program Highlights week of 4/29/19

AIRS Images Cyclone Fani Before Landfall to Analyze Atmospheric Conditions

Temperatures within tropical Cyclone Fani off the coast of India, imaged by NASA's AIRS on May 2, 2019.

Temperatures within tropical Cyclone Fani off the coast of India, imaged by NASA's AIRS on May 2, 2019. Purple indicates cold clouds carried high into the air by thunderstorms. Blue areas, including the cyclone's eye, are warmer. Green is shallow rainclouds; orange is cloud free. Credit: NASA/JPL-Caltech 

This image shows Tropical Cyclone Fani just off the east coast of India in the Bay of Bengal. NASA's Atmospheric Infrared Sounder (AIRS) collected the image at about 1 p.m. PDT (4 p.m. EDT) today, May 2. At the time, the cyclone's wind speeds were equivalent to a Category 4 hurricane, with maximum sustained winds of 155 mph (249 kph) and gusts of up to 190 mph (306 kph), according to the Joint Typhoon Warning Center.  

The infrared image shows temperatures of the clouds or surface. The large purple area indicates very cold clouds carried high into the atmosphere by deep thunderstorms. Warmer areas, including the eye of the cyclone, are shown in blue. Shallower rain clouds appear green, while the orange areas represent mostly cloud-free air moving away from the storm.

AIRS brightness temperatures like those in the above image can be used to measure various atmospheric phenomena such as precipitation, relative humidity, and air temperature, which helps researchers and disaster response agencies to bettter quantify the impact of storm systems.

GPM IMERG Adds up Rainfall from Cyclone Fani

Cyclone Fani brought heavy rainfall and destructive winds to the east coast of India, causing mass evacuations. This GPM IMERG animation shows total rainfall accumulation from May 1st to 4th, 2019, compared with 3 hour accumulations as the storm made its way up the Bay of Bengal. 

IMERG is a multi-satellite precipitation product combining microwave and infrared measurements from a constellation of NASA and partner satellites united by the GPM Core Observatory. Rainfall accumulation analysis such as this are used by researchers to model and predict the occurrence of landslide and flood hazards on the ground. GPM data is also fed into Numerical Weather Predication models to improve the accuracy and precision of storm track predications and provide people on the ground with advanced warning of impending hazards.