Introduction to CHRS CONNECT - a global extreme precipitation event database using object-oriented approach

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Phu Nguyen1, Andrea R Thorstensen1, Hao Liu2, Scott L Sellars3, Hamed Ashouri2, Phat Huynh4, Thanh Palacios4, Pengyu Li4, Hoang Tran4, Dan Braithwaite5, Kuolin Hsu1, Xiaogang Gao6, Soroosh Sorooshian2 and CHRS CONNECT, (1)University of California Irvine, Civil and Environmental Engineering, Irvine, CA, United States, (2)University of California Irvine, Irvine, CA, United States, (3)University of California Irvine, Earth System Science, Irvine, CA, United States, (4)UC Irvine, Irvine, CA, United States, (5)Univ California Irvine, Irvine, CA, United States, (6)Univ California, Irvine, Irvine, CA, United States
Extreme precipitation events cause natural disasters that impact many parts of the world. Understanding how these events vary in space and time is a key goal in climatology research. The recently developed CHRS CONNECT (Center for Hydrometeorology & Remote Sensing CONNected precipitation objECT) system is a global extreme precipitation event database derived from CHRS’s satellite precipitation data products, including PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and PERSIANN-CDR (Climate Data Record). Precipitation data from PERSIANN is hourly, 0.25ox0.25o grid, 60oS – 60oN, from 2000 to 2015, and data from PERSIANN-CDR is daily, 0.25ox0.25o grid, 60oS – 60oN, from 1983 to 2015. We used an advanced method in computer science which represents a data point on a three dimensional grid (longitude, latitude and time) called volumetric pixel or voxel. An object segmentation algorithm was developed to derive precipitation events as objects. In each object, voxels are connected to each other through the 26 connectivity faces (a voxel is connected to a neighboring voxel if they share a common face). The object-oriented algorithm was designed to provide a unique means in which extreme precipitation events and their attributes can be stored in a searchable database. This database is accessible through a user-friendly interface (connect.eng.uci.edu), allowing the user to retrieve events that fit specific criteria of interest such as spatiotemporal domain, maximum intensity, minimum duration and climatology indices. The interface includes several modes for visualization such as total precipitation, event tracking, and event evolution animation. The CHRS CONNECT tool is designed to be used for climatology research related to extreme precipitation events as well as for water resources management applications.