Home » malar arulraj

Tag: malar arulraj

Figure: Precipitation system observed at 0725 UTC 11 Aug 2020, over the U.S. Midwest. MRMS surface precipitation product (observations) on the left and U-Net output on the right.

Optimal Summertime Precipitation Data from GEO and LEO Observations 

ESSIC/CISESS Scientists Veljko Petković, Malarvizhi Arulraj, and CISESS Summer Intern Vesta Gorooh (UCI PhD student) have a new article in the November issue of the Journal of Hydrometeorology. The article describes the use of machine learning techniques to improve the retrieval of surface precipitation from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites.

Read More »
Figure: (Top panel) Rain-Rate predicted by eTRaP and observed by MRMS. (Bottom panel) Scatter plot and estimation metrics for Tropical Storm Fiona between September 18, 2022 12 UTC to September 19, 2022 12 UTC.

NPreciSe Evaluation of eTRaP during Tropical Storm Fiona

Tropical Storm Fiona struck Puerto Rico on September 17-18, 2022 causing catastrophic floods and leaving most of the island with a major power outage. Fiona is the first Atlantic storm this season to cause a major disaster. NPreciSe (NOAA Satellite Precipitation Validation System) led by the CISESS science team (Malar Arulraj, Veljko Petkovic, Ralph Ferraro, and Huan Meng), evaluated the performance of the Ensemble Tropical Rainfall Potential (eTRaP) forecasts during this event, using a recently added Multi-Radar/Multi-Sensor (MRMS) observation product over Caribbean Islands.

Read More »
A NOAA visualization of Tropical Storm Fred's path up the East Coast, which spreads from Alabama and Mississippi to northern New York and western Massachussets

Performance of NOAA Satellite-based Precipitation Products During Tropical Storm Fred

On August 18, 2021, the western part of North Carolina suffered a catastrophic flash flood caused by Tropical Storm Fred. As part of a NOAA/STAR precipitation validation project, CISESS science team Malar Arulraj, Veljko Petković, Ralph Ferraro, and Huan Meng evaluated the performance of different satellite-based precipitation products during this event using Multi-Radar/Multi-Sensor (MRMS) observations.

Read More »