CPC Unified Precipitation Project Pingping Xie, Wei Shi, Mingyue Chen and Sid Katz NOAA’s Climate Prediction Center 2011.11.09.

Slides:



Advertisements
Similar presentations
Precipitation in IGWCO The objectives of IGWCO require time series of accurate gridded precipitation fields with fine spatial and temporal resolution for.
Advertisements

COMPARISON OF MEAN AREAL PRECIPITATION ESTIMATES FROM WSR-88D AND HISTORICAL GAGE NETWORKS OVER CHEAT RIVER BASIN, WV David Wang, Michael Smith, D.J. Seo.
Weather Station Data Quality and Interpolation Issues in Modeling Joe Russo International Workshop on Plant Epidemiology Surveillance for the Pest Forecasting.
B E T HE W EATHER G UY A guide to accessing and using public domain weather information via the world wide web by Dick Westergard Certified Consulting.
Development of Bias-Corrected Precipitation Database and Climatology for the Arctic Regions Daqing Yang, Principal Investigator Douglas L. Kane, Co-Investigator.
National Climatic Data Center Status of Continental Indicators for NADM Richard R. Heim Jr. NOAA/NESDIS/National Climatic Data Center Asheville, North.
A Global Daily Gauge-based Precipitation Analysis, Part I: Assessing Objective Techniques Mingyue Chen & CPC Precipitation Working Group CPC/NCEP/NOAA.
Characteristics of High-Resolution Satellite Precipitation Products in Spring and Summer over China Yan Shen 1, A.-Y. Xiong 1 Pingping Xie 2 1. National.
1 Fischer-Porter Retrofit Workshop Sterling, Virginia Nov , 2008 Hourly Precipitation Data Processing System at NCDC Stuart Hinson Meteorologist.
The Climate Prediction Center Rainfall Estimation Algorithm Version 2 Tim Love -- RSIS/CPC.
ETA and GFS Validation (Southeastern Mexico) John M. Dickens RSIS/CPC.
Report from the GCOS Archive/Analysis Center Matthew Menne NOAA/National Centers for Environmental Information Center for Weather and Climate (NCEI-Asheville)
Further Development of GPCC products Global Precipitation Climatology Centre T. Fuchs, U. Schneider, A. Meyer-Christoffer, and B. Rudolf.
Northeast Regional Climate Center
1 NOAA’s National Climatic Data Center April 2005 Climate Observation Program Blended SST Analysis Changes and Implications for the Buoy Network 1.Plans.
Temperature and Precipitation Data CBRFC Stakeholder Forum July 31, 2012.
Infusing Information from SNPP and GOES-R Observations for Improved Monitoring of Weather, Water and Climate Pingping Xie, Robert Joyce, Shaorong Wu and.
Automated Real-Time Operational Rain Gauge Quality-Control Tools in NWS Hydrologic Operations Chandra R. Kondragunta 1 and Kiran Shrestha 2 1 Hydrology.
CARPE DIEM Centre for Water Resources Research NUID-UCD Contribution to Area-3 Dusseldorf meeting 26th to 28th May 2003.
SST Diurnal Cycle over the Western Hemisphere: Preliminary Results from the New High-Resolution MPM Analysis Wanqiu Wang, Pingping Xie, and Chenjie Huang.
1 GOES-R AWG Hydrology Algorithm Team: Rainfall Probability June 14, 2011 Presented By: Bob Kuligowski NOAA/NESDIS/STAR.
The Evaluation of a Passive Microwave-Based Satellite Rainfall Estimation Algorithm with an IR-Based Algorithm at Short time Scales Robert Joyce RS Information.
John Janowiak Climate Prediction Center/NCEP/NWS Jianyin Liang China Meteorological Agency Pingping Xie Climate Prediction Center/NCEP/NWS Robert Joyce.
CPC Unified Gauge – Satellite Merged Precipitation Analysis for Improved Monitoring and Assessments of Global Climate Pingping Xie, Soo-Hyun Yoo,
GPCC Global Precipitation Climatology Centre Calculation Of Gridded Precipitation Data for Global Land-Surface Using In Situ Gauge Observations IPWG, Monterey,
June 12, 2009F. Iturbide-Sanchez MIRS F16 Rainfall Rate Overview and Validation F. Iturbide-Sanchez, K. Garrett, C. Grassotti, W. Chen, and S.-A. Boukabara.
Wayne Faas Chief, NOAA National Climatic Data Center Data Operations Division December 3, 2003.
April nd IBTrACS Workshop 1 Operational Procedures How can we build consistent, homogeneous, well- documented climate quality data?
Southern Hemisphere: Weather & Climate over Major Crops Areas Update prepared by Climate Prediction Center / NCEP 23 May 2011 For Real-time information:
Center for Hydrometeorology and Remote Sensing, University of California, Irvine Basin Scale Precipitation Data Merging Using Markov Chain Monte Carlo.
June 19, 2007 GRIDDED MOS STARTS WITH POINT (STATION) MOS STARTS WITH POINT (STATION) MOS –Essentially the same MOS that is in text bulletins –Number and.
Climate Monitoring of Precipitation: The GPCC - Status and plans Global Precipitation Climatology Centre U. Schneider, A. Meyer-Christoffer, B. Rudolf.
Michael A. Palecki USCRN Science Project Manager National Climatic Data Center DOC/NOAA/NESDIS USCRN PROGRAM STATUS MARCH 3, United States Climate.
Cooperative Institute of Climate Studies University of Maryland 2207 Computer & Spaces Sciences Bldg. College Park, MD Tel: (301) Fax:
Multi-Sensor Precipitation Estimation Presented by D.-J. Seo 1 Hydrologic Science and Modeling Branch Hydrology Laboratory National Weather Service Presented.
USGS Overview Workshop on Improved Quality of Data and Data Exchange for Climate Research and Analysis NOAA National Climatic Data Center Bill Hazell,
Gridded Rainfall Estimation for Distributed Modeling in Western Mountainous Areas 1. Introduction Estimation of precipitation in mountainous areas continues.
Overview of the Colorado Basin River Forecast Center Lisa Holts.
Precipitation Analyses for Climate Applications Pingping Xie
Combining CMORPH with Gauge Analysis over
Quality control of daily data on example of Central European series of air temperature, relative humidity and precipitation P. Štěpánek (1), P. Zahradníček.
Operational Issues from NCDC Perspective Steve Del Greco, Brian Nelson, Dongsoo Kim NOAA/NESDIS/NCDC Dongjun Seo – NOAA/NWS/OHD 1 st Q2 Workshop Archive,
Real-time Verification of Operational Precipitation Forecasts using Hourly Gauge Data Andrew Loughe Judy Henderson Jennifer MahoneyEdward Tollerud Real-time.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 In Situ SST for Satellite Cal/Val and Quality Control Alexander Ignatov.
1 Motivation Motivation SST analysis products at NCDC SST analysis products at NCDC  Extended Reconstruction SST (ERSST) v.3b  Daily Optimum Interpolation.
Stage IV Multi-sensor Mosaic Development, production and Application at NCEP/EMC Ying Lin NOAA/NWS/NCEP/EMC Jan 2011.
Status and Plans of the Global Precipitation Climatology Centre (GPCC) Bruno Rudolf, Tobias Fuchs and Udo Schneider (GPCC) Overview: Introduction to the.
July 31, 2012 Kevin Werner NWS Colorado Basin River Forecast Center Tim Bardsley Western Water Assessment 1 Future Colorado Basin Observing System.
© Crown copyright Met Office The EN4 dataset of quality controlled ocean temperature and salinity profiles and monthly objective analyses Simon Good.
Spatial interpolation of Daily temperatures using an advection scheme Kwang Soo Kim.
Central Region Snowfall Analysis Brian P. Walawender NWS Central Region Headquarters Matt W. Davis NWS WFO La Crosse, WI 5/26/2011.
NOAA’s National Climatic Data Center Climate Service Partnership Activities At NOAA’s National Climatic Data Center Tim Owen Climate Prediction Applications.
Robert Grumbine National Weather Service RA-IV WIGOS Implementation Workshop (English), December, Willemstad Curaçao United.
1 NOHRSC Challenges of using Snow Data Carrie Olheiser Office of Hydrologic Development National Weather Service, NOAA U.S. Department of Commerce National.
Examining Fresh Water Flux over Global Oceans in the NCEP GDAS, CDAS, CDAS2, GFS, and CFS P. Xie 1), M. Chen 1), J.E. Janowiak 1), W. Wang 1), C. Huang.
NCEP Dropout Team Briefing JAG/ODAA Meeting OFCM October 2008 “Where America’s Climate, Weather and Ocean Prediction Services Begin” Jordan Alpert, Bradley.
Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 1 1 Reconstruction of Near-Global Precipitation Variations Based on Gauges.
88 th Annual American Meteorological Society Meeting New Orleans, LA January 20-25, The Integrated Surface Database: Partnerships and Progress Neal.
Application of Probability Density Function - Optimal Interpolation in Hourly Gauge-Satellite Merged Precipitation Analysis over China Yan Shen, Yang Pan,
NWS Precipitation Analysis Product Victor Murphy NWS Southern Region Climate Service Program Mgr. 5 th US Drought Monitor Forum Portland, OR October 11,
An Examination of the Diurnal Cycle in the NCEP GFS (and Eta) Model Precipitation Forecasts (during NAME) John Janowiak, Valery Dagostaro*, Vern Kousky,
High Resolution Gauge – Satellite Merged Analyses of Precipitation: A 15-Year Record Pingping Xie, Soo-Hyun Yoo, Robert Joyce, Yelena Yarosh, Shaorong.
Latin American and Caribbean Flood and Drought Monitor – What it does and does not do Figure showing current system Coarse resolution 25km, daily Satellite.
A Prototype Algorithm for Gauge – Satellite Merged Analysis of Daily Precipitation over Land
Jay Lawrimore, Matt Menne
Dan Zarrow Northeast Regional Climate Center Fall 2010
Bruno Rudolf, Andreas Becker, Udo Schneider,
Soo-Hyun Yoo and Pingping Xie
Rain Gauge Data Merged with CMORPH* Yields: RMORPH
NOAA Objective Sea Surface Salinity Analysis P. Xie, Y. Xue, and A
Presentation transcript:

CPC Unified Precipitation Project Pingping Xie, Wei Shi, Mingyue Chen and Sid Katz NOAA’s Climate Prediction Center

Background Multiple precipitation analyses generated at CPC over the past ~20 years to satisfy various requirements Inconsistencies exist among the various CPC precipitation products due to: Differences in input data sources; and Differing objective algorithms

Overall Goal of The Project To consolidate and unify the various CPC precipitation products by creating a suite of unified products of global / regional precipitation The new products will have better quality present close quantitative consistency replace the existing products

Components of the Unified Products Station reports Unified, quality controlled Satellite estimates Multiple satellites / multiple instruments Analyses Global / regional ; Daily / Pentad / Monthly / hourly; Retrospective / Real-time

A Database of Gauge Reports Monthly and daily reports from over 32,000 stations GTS, NCDC archives (GHCN/GDCN..), COOP, RFC, Mexico, Brazil, Australia, China…; Quality Control with historical records, buddy check, satellite data and model forecasts

Distribution of Reporting Stations for July 1, 2003

Data Source for the US Historical NCDC COOP; SNOTEL; HADS; GTS (near) Realtime 24-hr "first order" WMO GTS sites; 24-hr SHEF-encoded precipitation reports received via AWIP from the River Forecast Centers (NWS data stream). * No MADIS data stream or CoCoRaHS data * We tend to only use data with stable and long history in the analysis

[1] Overall QC of Daily Reports over the U.S. [1] Overall  Developed ~15 years ago at CPC;  Performed on an operational basis for daily reports from the US;  QC’ed station data used to create analyzed fields of daily precipitation over the CONUS.

[2] Procedures QC of Daily Reports over the US [2] Procedures Four types: 1.Duplicate Station Check (eliminates duplicates; key punch errors) 2. Buddy Check (check for extreme values)  Examine the absolute value of the difference between the current station and all other stations within a one-degree box centered on the current station. If all of the stations exceed a specified threshold, then the current station is flagged and removed from the analysis.

[3] QC procedures (continued) QC of Daily Reports over the US [3] QC procedures (continued) 3.Standard Deviation Check  Apply a daily climatology (gridded) obtained from the unified gauge data base for the base period 1971 – 2000 (WMO standard). Compare each station observation to the nearest grid point value (from the climatology). The station value must be within 5 standard deviations of the daily climatology. During hurricane days, this check is turned off for affected areas. 4.Radar QC (Eliminate spurious zeros from the rain gauge data)  Systematically compare all daily rain-gauge reports against the nearest grid points in the 24-hr radar estimate of precipitation (Similar to procedures in standard deviation check). Flag and eliminate rain gauge zero reports if the radar estimates ≥ 1.0 mm/day.

Gauge-Based Analysis of Global Daily Precipitation >30K station reports Optimal Interpolation (OI) with orographic consideration 0.5 o lat/lon grid over global land 0.25 o lat/lon grid over the CONUS Daily fields from 1979 (1948 for CONUS) to present Real-time operations

Example of Gauge-based Analysis for July 1, 2003