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Climate Monitoring Panel. Paul D. Try, Moderator Sr. V.P. Science and Technology Corporation Director, International GEWEX Project Office. Thomas R. Karl Director, National Climatic Data Center, NOAA Editor, Journal of Climate, Climatic Change & IPCC. William B. Rossow
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Climate Monitoring Panel Paul D. Try, Moderator Sr. V.P. Science and Technology Corporation Director, International GEWEX Project Office Thomas R. Karl Director, National Climatic Data Center, NOAA Editor, Journal of Climate, Climatic Change & IPCC William B. Rossow Goddard Institute for Space Studies, NASA Chairman, GEWEX Radiation Panel, WCRP Director, International Satellite Cloud Climatology Project Stanley Q. Kidder Cooperative Institute for Research in the Atmosphere, CSU Numerous Publications & Books on Meteorological Satellites & Sensors [ “Satellite Meteorology: An Introduction” Kidder and VonderHaar ]
Models Observations Products Global Energy and Water Cycle Experiment GOES Users Conference Climate Monitoring Panel Dr. Paul D. Try, Director International GEWEX Project Office
WV Flux Precipitation Evaporation Runoff Storage Energy and Water Cycle OBJECTIVES Determine the Hydrological Cycle by Global Measurements Model the Hydrological Cycle and its Effects Predict Response to Environmental Change Improve Observing Techniques and Data Assimilation Systems
Data SetProgress (10-23yrs 2002) ISCCP (Clouds) GPCP (Precipitation) Satellite Lifetimes GACP (Aerosols) GVaP (Water Vapour)
PREDICTED OBSERVED Climate Model vs Observed Precipitation Global Intensification of the hydrological cycle? Models indicate trend -- observations don’t confirm Errors don’t allow proof
GPCP New 20+ yr Monthly Product GPCP 1979 - Present shows interannual variability in tropical regions -- El Nino Events
GPCP New 20+ yr Pentad (5dy) Product Monthly Pentad GPCP Pentad data in tropical regions -- shows Madden-Julian Oscillation (MJO) Events [ Ref: P. Xie, NWS/NCEP/CPC ]
PERSIANN System for Hydrological Applications [ U of AZ ] Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks [ Rainfall accumulation for 6 hrly, daily, 5 day and monthly ] Monthly 1x1 degree from 30 min 0.25 degree GOES-IR data
PERSIANN System PERSIANN: Medium Spatial and Temporal Global Gridded Coverage Estimation GOES High Temporal, Low Spatial TRMM Training IR: Comparable but low temporal Radar: High Spatial, low temporal, Narrow Swath Pan American NEXRAD & Gauges SW U.S Africa Radar: High Spatial + Temporal Mountain Blockage Gauges: Spotty Coverage Global-tropical
Local time: 00-02 hr Local time: 12-14 hr Local time: 03-05 hr Local time: 15-17 hr Local time: 06-08 hr Local time: 18-20 hr Local time: 09-11 hr Local time: 21-23 hr Data Resolution at 1o x 1o Lat/Lon PERSIANN: Capturing the diurnal cycle December, January, and February (DJF)
GPCP Results Support IPCC “... climate change will lead to an intensification of the global hydrological cycle and can have major impacts on regional water resources”. ‘95 IPCC -- Global Distribution of Observed Moisture Recycling Using GPCP & TOVS Pathfinder (also GVaP) data sets! [Ref: Chahine et al , 1997] Zonal Average Recycling Rate per Month