GAUGES – RADAR – SATELLITE COMBINATION Prof. Eng. Ezio TODINI

Slides:

Advertisements

Similar presentations

Operational information FAO RFE for Sudan FAO & Sudan Meteorology Authority Mauro Evangelisti &Stefano Alessandrini (FAO Consultant)

Advertisements

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

Multiple Sensor Precipitation Estimation over Complex Terrain AGENDA I. Paperwork A. Committee member signatures B. Advisory conference requirements II.

Gage R&R Estimating measurement components

1 The relation between rainfall and area-time Integrals At the transition from and arid to an equatorial Climate: application to rainfall estimation by.

Poster template by ResearchPosters.co.za Effect of Topography in Satellite Rainfall Estimation Errors: Observational Evidence across Contrasting Elevation.

Multi-sensor and multi-scale data assimilation of remotely sensed snow observations Konstantinos Andreadis 1, Dennis Lettenmaier 1, and Dennis McLaughlin.

A Framework for Integrating Remote Sensing, Soil Sampling, and Models for Monitoring Soil Carbon Sequestration J. W. Jones, S. Traore, J. Koo, M. Bostick,

W. McNair Bostick, Oumarou Badini, James W. Jones, Russell S. Yost, Claudio O. Stockle, and Amadou Kodio Ensemble Kalman Filter Estimation of Soil Carbon.

The Climate Prediction Center Rainfall Estimation Algorithm Version 2 Tim Love -- RSIS/CPC.

State space model of precipitation rate (Tamre Cardoso, PhD UW 2004) Updating wave height forecasts using satellite data (Anders Malmberg, PhD U. Lund.

Towards an Hydrological Qualification of the Simulated Rainfall in Mountainous Areas Eddy Yates, Sandrine Anquetin, Jean-Dominique Creutin Laboratoire.

PROVIDING DISTRIBUTED FORECASTS OF PRECIPITATION USING A STATISTICAL NOWCAST SCHEME Neil I. Fox and Chris K. Wikle University of Missouri- Columbia.

Hierarchical models STAT 518 Sp 08. Rainfall measurement Rain gauge (1 hr) High wind, low rain rate (evaporation) Spatially localized, temporally moderate.

3. Jahrestreffen LandCaRe 2020, Tharandt – 30. November 2009 TP 2.3 Bonn Temporal downscaling of heavy precipitation Ralf Lindau.

CARPE DIEM 7 th (Final) meeting – Bologna Critical Assessment of available Radar Precipitation Estimation techniques and Development of Innovative approaches.

Statistics, data, and deterministic models NRCSE.

Diplomanden-Doktoranden-Seminar Bonn – 18. Mai 2008 LandCaRe 2020 Temporal downscaling of heavy precipitation and some general thoughts about downscaling.

Activity of SMHI (Swedish Meteorological and Hydrological Institute) Presentation for CARPE DIEM kick-off meeting, DLR-GERMANY, January Contact.

WORKSHOP ON PRECIPITATION MEASUREMENTS MADRID SEPTEMBER 2002 AN INTERCOMPARISON OF GAUGE, RADAR AND SATELLITE RAINFALL IN THE TROPICS A. J. Pereira.

Geo479/579: Geostatistics Ch13. Block Kriging. Block Estimate  Requirements An estimate of the average value of a variable within a prescribed local.

CARPE DIEM Centre for Water Resources Research NUID-UCD Contribution to Area-3 Dusseldorf meeting 26th to 28th May 2003.

A Kalman Filter Approach to Blend Various Satellite Rainfall Estimates in CMORPH Robert Joyce NOAA/NCEP/CPC Wyle Information Systems Pingping Xie NOAA/NCEP/CPC.

Ethiopia Improving Availability, Access and Use of Climate Information in Ethiopia Tufa Dinku 1, Kinfe Hilemariam 2, David Grimes 3, and Stephen Connor.

1 GOES-R AWG Hydrology Algorithm Team: Rainfall Probability June 14, 2011 Presented By: Bob Kuligowski NOAA/NESDIS/STAR.

Spatial Interpolation of monthly precipitation by Kriging method

Geostatistical approach to Estimating Rainfall over Mauritius Mphil/PhD Student: Mr.Dhurmea K. Ram Supervisors: Prof. SDDV Rughooputh Dr. R Boojhawon Estimating.

ANALYSIS OF ESTIMATED RAINFALL DATA USING SPATIAL INTERPOLATION. Preethi Raj GEOG 5650 (Environmental Applications of GIS)

Time Series Databases (TSDBs) A new tool for storing time series data within InfoWorks ICM and ICMLive Provides intermediate storage between external data.

LMD/IPSL 1 Ahmedabad Megha-Tropique Meeting October 2005 Combination of MSG and TRMM for precipitation estimation over Africa (AMMA project experience)

Anthony DeAngelis. Abstract Estimation of precipitation provides useful climatological data for researchers; as well as invaluable guidance for forecasters.

Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss High-resolution data assimilation in COSMO: Status and.

1 GOES-R AWG Hydrology Algorithm Team: Rainfall Potential June 14, 2011 Presented By: Bob Kuligowski NOAA/NESDIS/STAR.

Rationale The occurrence of multiple catastrophic events within a given time span affecting the same portfolio of insured properties may induce enhanced.

MULTI-SOURCES PRECIPITATION ESTIMATION K. Tesfagiorgis, S. E. Mahani, R. Khanbilvardi (NOAA-CREST, CCNY, CUNY, NY-10031) David Kitzmiller (NOAA-NWS Collaborator)

Center for Hydrometeorology and Remote Sensing, University of California, Irvine Basin Scale Precipitation Data Merging Using Markov Chain Monte Carlo.

STEPS: An empirical treatment of forecast uncertainty Alan Seed BMRC Weather Forecasting Group.

Multi-Sensor Precipitation Estimation Presented by D.-J. Seo 1 Hydrologic Science and Modeling Branch Hydrology Laboratory National Weather Service Presented.

Combining CMORPH with Gauge Analysis over

VALIDATION OF HIGH RESOLUTION PRECIPITATION PRODUCTS IN THE SOUTH OF BRAZIL WITH A DENSE GAUGE NETWORK AND WEATHER RADARS – FIRST RESULTS Cesar Beneti,

Maximum Likelihood Estimation and Simplified Kalman Filter tecniques for real time Data Assimilation.

The NOAA Hydrology Program and its requirements for GOES-R Pedro J. Restrepo Senior Scientist Office of Hydrologic Development NOAA’s National Weather.

THE MULTI-SENSOR BAYESIAN COMBINATIONS

CARPE DIEM 6 th meeting – Helsinki Critical Assessment of available Radar Precipitation Estimation techniques and Development of Innovative approaches.

Distributed Hydrologic Modeling-- Jodi Eshelman Analysis of the Number of Rain Gages Required to Calibrate Radar Rainfall for the Illinois River Basin.

Application of a Combined Daily Rain Gauges and Rainfall Satellite Estimates Scheme for Basin Management Daniel Vila Cesar.

Flash Flood Monitoring and Prediction Current Operational Capabilities, Issues and Perspectives Britt Westergard, Service Hydrologist WFO Jackson, KY Q2.

Generate ξ m,i for each direction i given H, σ 1 and m (Eq. 2) calculate X’ m,i for each direction i (Eq. 1) given ξ m,i and X m, which corresponds for.

National Weather Service Hydrologic Forecasting Course Agenda 14 October – 7 November 2003.

Barcelona Toward an error model for radar quantitative precipitation estimation in the Cévennes- Vivarais region, France Pierre-Emmanuel Kirstetter, Guy.

Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Ground.

Microclimates Fieldwork Revision of fieldwork techniques.

INTEGRATING SATELLITE AND MONITORING DATA TO RETROSPECTIVELY ESTIMATE MONTHLY PM 2.5 CONCENTRATIONS IN THE EASTERN U.S. Christopher J. Paciorek 1 and Yang.

Sarah Callaghan British Atmospheric Data Centre, UK, The effects of climate change on rain The consensus in the climate change.

DOWNSCALING GLOBAL MEDIUM RANGE METEOROLOGICAL PREDICTIONS FOR FLOOD PREDICTION Nathalie Voisin, Andy W. Wood, Dennis P. Lettenmaier University of Washington,

EVALUATION OF A GLOBAL PREDICTION SYSTEM: THE MISSISSIPPI RIVER BASIN AS A TEST CASE Nathalie Voisin, Andy W. Wood and Dennis P. Lettenmaier Civil and.

ENVI 412 Hydrologic Losses and Radar Measurement Dr. Philip B. Bedient Rice University.

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Characterizing Radar Raingauge Errors.

HYDROCARE meeting; Bratislava, June INTERREG IIIB CADSES HYDROCARE Project Partner 5 Servizio Opere Idrauliche, Provincia Autonoma di Trento (Service.

CARPE DIEM 4 th meeting Critical Assessment of available Radar Precipitation Estimation techniques and Development of Innovative approaches for Environmental.

Application of Probability Density Function - Optimal Interpolation in Hourly Gauge-Satellite Merged Precipitation Analysis over China Yan Shen, Yang Pan,

Precipitation Research at UMN: Multiscale variability and Uncertainty in Rainfall Estimation and Retrieval (1) Merging multiscale observations, (2) Verification.

The Convective Rainfall Rate in the NWCSAF

INTERREG IIIB CADSES HYDROCARE

Multi-Sensor Precipitation Estimation

Verifying Precipitation Events Using Composite Statistics

Using Quantitative Precipitation Estimates in Flash Flood Forecasting

TOWARDS HIGH-RESOLUTION GLOBAL SATELLITE PRECIPITATION ESTIMATION

Hydrologically Relevant Error Metrics for PEHRPP

Discussion Questions to all Questions to SRNWP consortia

Presentation transcript:

GAUGES – RADAR – SATELLITE COMBINATION Prof. Eng. Ezio TODINI

Improvements in Rainfall Estimates are obtained by combining together the different available Rainfall Measurement Sources RAIN GAUGES Reliable but point measures

Improvements in Rainfall Estimates are obtained by combining together the different available Rainfall Measurement Sources RADAR Spatial but less reliable

Improvements in Rainfall Estimates are obtained by combining together the different available Rainfall Measurement Sources METEOSAT Spatial but too coarse resolution

The MUSIC Prototype Integrates: Hydrologic & Hydraulic models GIS and Advanced Visual User Interface THE MUSIC INTEGRATED SYSTEM PROTOTYPE RAINFALL INPUTS CAN BE FROM: Gauges, Radar, Satellite and Meteorological Models Forecasts

Rain-gauge measurements KRIGED measurements from gauges Radar measurements, A PRIORI estimates Combination of radar estimates and gauges measurements, A POSTERIORI estimate BLOCK KRIGING KALMAN FILTER SPATIAL MEASUREMENTS over the radar pixels Eliminating the BIAS and producing MINIMUM VARIANCE precipitation estimates on pixels ORIGINAL TECHNIQUE TO COMBINE, IN A BAYESIAN SENSE, AREAL PRECIPITATION FIELDS (RADAR) TO POINT MEASUREMENTS OF PRECIPITATION (RAIN-GAUGES) GROUND BASED TELE- METERING RAIN- GAUGE MEASUREMENTS - accurate in a point - spatial significance decays with the distance and with the area BLOCK KRIGING estimating the average field over the radar pixels and its Variance from the point rain-gauge measurements SPATIAL MEASUREMENTS POINT MEASUREMENTS RADAR MEASUREMENTS - good spatial representation - poor quantitative estimates - biased measurements SPATIAL MEASUREMENTS KALMAN FILTER finding the a posteriori estimates by combining the a priori estimates provided by the radar with the block Kriged measurements provided by the gauges, in a Bayesian framework 1

RAIN-GAUGES Meteorological RADAR Meteorological SATELLITE Measurements of the rainfall field at different scales. combine measurements at multiple resolution. MODEL: UP-SCALING: disaggregated estimate at the RADAR scale (from the Bayesian combination) covariance of the estimation errors at the RADAR scale aggregated RADAR estimate variance of the estimation errors of the aggregated RADAR estimate RAIN-GAUGES, RADAR AND SATELLITE COMBINATION The true rainfall at the upper scale can be obtained simply by summing the true rainfall at the lower scale RAD Scale SAT Scale x y DOWNSCALING RAD Scale SAT Scale x y UPSCALING

BAYESIAN APPROACH at SATELLITE Scale TRUEBK-RADSATBK-RAD- SAT

BAYEISAN APPROACH at RADAR scale TRUEBKRADBK-RADBK-RAD-SAT

RESULTS (1000 time-steps) BIASVARIANCE RADAR RADAR BLOCK KRIGING BLOCK KRIGING BLOCK KRIGING + RADAR (RADAR scale) BLOCK KRIGING + RADAR (RADAR scale) SATELLITE SATELLITE BK+RADAR AGGREGATED BK+RADAR AGGREGATED (SATELLITE scale) (SATELLITE scale) BK+RADAR + SATELLITE (SATELLITE scale) BK+RADAR + SATELLITE (SATELLITE scale) BK+RADAR + SATELLITE (RADAR scale) BK+RADAR + SATELLITE (RADAR scale)

BLOCK KRIGING RADARSATELLITE BK+RADARBK+RADAR+SATELLITEBK+SATELLITE 6.5 mm 0.0 mm 2.2 mm 4.4 mm

The present status: - Block-Kriging software package Completed(*) - Raingauge – Radar combination Completed - Raingauge – Satellite combination Completed - Raingauge-Radar-Satellite comb. Completed - Coupling with TOPKAPICompleted (*) Under revision