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Tools
0.04° Realtime Precipitation Server
G-Wadi GeoServer for High Resolution Precipitation
tutorials for G-Wadi
View G-WADI Realtime Global Precipitation on Google Earth
G-WADI Heavy Precipitation (Flood Potential)

PERSIANN-CONNECT

Drought Visualization
GIDMaPS Drought Tool

0.25° Precipitation Server
Hydis link
Global Latest Rainfall Animation
48-hour Global Animation PERSIANN-CCS
Access to PERSIANN 0.25° 3 and 6 hourly Archives
Direct Access to PERSIANN Archive (2000-Current)
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Recent flash flooding in Arizona (Sept 8, 2014) captured by PERSIANN-CCS near real-time

Extreme rain and flood events in Arizona were accurately represented by PERSIANN-CCS near real-time data and could be seen via the CHRS G-Wadi GeoServer: http://persiann.eng.uci.edu/gwadi/

Comparing PERSIANN-CCS data with the radar for 24 hours (00:00 UTC through 23:59 UTC) Monday Sept 8, 2014 for the area shows:

The majority of rain fell in just 3-5 hours in each event. As can be seen in the hourly animation of the event
NOTE: maximum mm/day of about 115mm (or 4.5 inches) in both datasets for the Phoenix area.

The remnants of Hurricane Norbert caused flash flooding in Phoenix and Tucson Arizona Monday Sept 8, 2014.
A 75-year old mark for wettest day in Phoenix was topped when over 3 inches fell in a short period of time, killing at least 2 people and threatening homes near retention basins and channels as capacity levels were exceeded.
Even heavier rainfall was recorded in nearby Chandler (5.63 inches) and Mesa (4.41 inches).
Tucson, Az received 2 inches of rain in mere hours causing washes to run flash flood feet deep, killing 2 people.


30+ year PERSIANN-CDR dataset



A near-global 30+ year high-resolution precipitation dataset for long-term studies is now available. PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record) provides daily rainfall estimates at 0.25 deg for the latitude band 60N-60S over the period of 01/01/1983 to 03/31/2014 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data and adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5 deg monthly scale throughout the entire record.

The PERSIANN-CDR product is available to the public as an operational climate data record via the NOAA NCDC CDR Program website under the Atmospheric CDRs category.


For assistance with the data, please contact Dan Braithwaite (dbraithw@uci.edu) and/or Hamed Ashouri (h.ashouri@uci.edu).

RainMapper Smart Phone app


Near real-time global precipitation imagery on-the-go now available with the RainMapper app developed at the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California Irvine (UCI). RainMapper provides access to PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System) a real-time global high-resolution (~4km) satellite precipitation product.


Evolution of Typhoon Rammasun using RainMapper app: Rain totals of 3, 6, 12, 24, 48 and 72 hours

RainMapper is available for iOS devices (iPhones 4x, 5x; iPad, iPad Mini, iPods) and Android devices (Android phones and tablets). RainMapper is compatible with iOS 6 or later.
RainMapper can be downloaded (free) from App Store and Google Play.

Super Typhoon Haiyan

Total accumulated precipitation (mm) of Typhoon Haiyan (11-03-2013 00:00 to 11-11-2013 24:00 UTC) estimated by PERSIANN-CCS

Tracking Haiyan's centroid each day from its formation on November 3rd to its dissipation on November 11th, 2013. The sizes of the circles are proportional to the amount of precipitation as estimated by PERSIANN-CCS. The maximum accumulated precipitation shown is 615 mm.

CHRS Mission Statement

Building Global Capacity for Forecast and Mitigation of Hydrologic Disasters through the development of means to extend the benefits of space and weather agencies' vast technological resources, which are untapped, into applications that can assist hydrologists and water resource managers worldwide and through equitable access to relevant nformation

Objectives

  • Improve hydrologic prediction through development and refinement of hydrologic models and use of advanced observations, particularly from remote sensing sources
  • Develop mathematical algorithms capable of estimating precipitation both from space-based and in-situ observations at spatial and temporal resolutions relevant to hydrologic applications, particularly in the semi arid environments
  • Develop decision support tools for generating and evaluating a variety of hydro-meteorologic and hydro-climatologic information required by the water resources management community
  • Contribute to the education of well trained hydrologists and water resources engineers responsive to the growing needs of public and private sectors at the state, national and international levels.

CHRS will pursue its mission through interdisciplinary research and education involving faculty and students from Engineering, Physical Sciences, and Social Ecology as well as cooperation with a number of other universities and national laboratories.


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