Science Plan for Radar Observations During NAME NSF S-Pol Radar SMN C-Band Doppler Radars Shipborne Radar P-3 Aircraft Radar Steve Rutledge Timothy Lang.

Slides:



Advertisements
Similar presentations
DS-01 Disaster Risk Reduction and Early Warning Definition
Advertisements

Calibration of GOES-R ABI cloud products and TRMM/GPM observations to ground-based radar rainfall estimates for the MRMS system – Status and future plans.
Terry Schuur Weather Radar Research Meteorological Observations in Support of Dual Polarization Research.
“OLYMPEX” Physical validation Precipitation estimation Hydrological applications Field Experiment Proposed for November-December th International.
Radar-Derived Rainfall Estimation Presented by D.-J. Seo 1 Hydrologic Science and Modeling Branch Hydrology Laboratory National Weather Service Presented.
THE USE OF DUAL-POLARIMETRIC RADAR DATA TO IMPROVE RAINFALL ESTIMATION ACROSS THE TENNESSEE RIVER VALLEY W.A. Petersen NASA – Marshall Space Flight Center,
Review of the current and likely future global NWP requirements for Weather Radar data Enrico Fucile (ECMWF) Eric WATTRELOT & Jean-François MAHFOUF (Météo-France/CNRM/GMAP)
DYNAMO Cruise Info TOGA Radar Scanning Timothy Lang.
Precipitation in the Olympic Peninsula of Washington State Robert Houze and Socorro Medina Department of Atmospheric Sciences University of Washington.
Cabo Guasave S-Pol NAME Radar Data - Product Description & Quality Control.
Radar-Observed Characteristics of the Diurnal Cycle of Precipitation during NAME 2004 Timothy Lang, Steve Nesbitt, Rob Cifelli, and Steve Rutledge Colorado.
Continuing research on radar-observed precipitation systems during NAME 2004 Timothy J. Lang, Stephen W. Nesbitt, Steven A. Rutledge, Robert Cifelli, David.
Radar Discussion Report Review of radar systems Locations of radars at supersite Scanning strategies Data formats and displays Real time data transmission.
Elevation-dependent Trends in Precipitation during NAME Angela K. Rowe, Steven A. Rutledge, and Timothy J. Lang Colorado State University, Fort Collins,
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar by S. A. Rutledge, R. Cifelli, T. Lang and S. W. Nesbitt EGU 2009.
Lessons learned in field studies about weather radar observations in the western US and other mountainous regions Socorro Medina and Robert Houze Department.
Institut für Physik der Atmosphäre Status of working group Precipitation Processes and Live cycle Martin Hagen DLR Oberpfaffenhofen.
Radar Operations during AMMA SOP Alain Protat  Benin mesosite : Scanning Polarimetric Doppler X-band radar (X-Port) + Scanning Polarimetric Doppler C-band.
WHAT IS Z?  Radar reflectivity (dBZ)  Microwave energy reflects off objects (e.g. hydrometeors) and the return is reflectivity WHAT IS R?  Rainfall.
Request to embed a DOW in NASA’s OLYMPEX validation campaign for GPM (Houze) OLYMPEX is a NASA ground validation campaign for the recently launched GPM.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State.
RADAR OBSERVATIONS DURING NAME 2004 PART I: DATA PRODUCTS AND QUALITY CONTROL Timothy J. Lang, Rob Cifelli, Lee Nelson, Stephen W. Nesbitt, Gustavo Pereira,
Surveillance Weather Radar 2000 AD. Weather Radar Technology- Merits in Chronological Order WSR-57 WSR-88D WSR-07PD.
NOAA P-3 activities during NAME Michael Douglas, NSSL Co-PI’s: Bill Cotton CSU Joe Zehnder, ASU G.V. Rao, SLU.
March 14, 2006Intl FFF Workshop, Costa Rica Weather Decision Technologies, Inc. Hydro-Meteorological Decision Support System Bill Conway, Vice President.
Scott W. Powell and Stacy R. Brodzik University of Washington, Seattle, WA An Improved Algorithm for Radar-derived Classification of Convective and Stratiform.
Similar in concept to JDOP, except with the goal to operationally demonstrate the value of the polarimetric upgrade of the 88D. Multi-seasonal to study.
Radar Observations During NAME 2004 EOP Timothy Lang Steve Rutledge Steve Nesbitt Rob Cifelli Lee Nelson Dave Lerach Gustavo Pereira Dave Ahijevych Rit.
Rainfall Runoff Prediction Designed and presented by George Limpert in association with CARES and Chris Barnett Mentor: Dr. Neil Fox.
NREPS Applications for Water Supply and Management in California and Tennessee. Patrick Gatlin 1, Mariana Felix Scott 1, Lawrence D. Carey 1, and Walter.
CARPE-DIEM 13/6/02, slide 1German Aerospace Center Microwaves and Radar Institute CARPE-DIEM Besprechung Helsinki, June 2004 Ewan.
S-Pol NAME Radar Network NAME radar network will allow characterization of gulf surge precipitation along coast and over Gulf of California Selected sectors.
The Role of Polarimetric Radar for Validating Cloud Models Robert Cifelli 1, Timothy Lang 1, Stephen Nesbitt 1, S.A. Rutledge 1 S. Lang 2, and W.K. Tao.
The IEM-KCCI-NWS Partnership: Working Together to Save Lives and Increase Weather Data Distribution.
Approaches/associated tools fall in three broad categories: 1)Quick-look applications SOLO/P3tv - Review of raw single-Doppler data in native polar coordinates.
Real-time Verification of Operational Precipitation Forecasts using Hourly Gauge Data Andrew Loughe Judy Henderson Jennifer MahoneyEdward Tollerud Real-time.
Monthly Precipitation Rate in July 2006 TRMM MMF DIFF RH84 New Scheme 3.3 Evaluate MMF Results with TRMM Data Zonal Mean Hydrometeor Profile TRMM TMI CONTROL.
The NOAA Hydrology Program and its requirements for GOES-R Pedro J. Restrepo Senior Scientist Office of Hydrologic Development NOAA’s National Weather.
CARPE DIEM 6 th meeting – Helsinki Critical Assessment of available Radar Precipitation Estimation techniques and Development of Innovative approaches.
NORTH AMERICAN MONSOON EXPERIMENT (NAME) An internationally coordinated, joint US-Mexico process study aimed at improving warm season precipitation prediction.
Polarimetric radar analysis of convection in northwestern Mexico Timothy J. Lang, Angela Rowe, Steve Rutledge, Rob Cifelli Steve Nesbitt.
Wayne G. Leslie 13 November 2002 Harvard Ocean Prediction System (HOPS) Operational Forecasting and Adaptive Sampling.
Alexander Ryzhkov Weather Radar Research Meteorological Applications of Dual-polarization Radar.
Topographic Dependency of Rainfall Characteristics from the Sierra Madre Occidental in Northwest Mexico NERN Project Team: NCAR, U. Arizona, U. Sonora,
NAME Enhanced Observation Period 5 th NAME Science Working Group Meeting November 5-7, 2003 NAME Homepage:
SST and vegetation in modulating the diurnal cycle forcing of convection during the warm season Michael Douglas, NSSL Co-PI’s: Christopher Watts, Univ.
NAME Upper-Air Gridded Datasets: Description and Some Preliminary Results Paul E. Ciesielski Richard H. Johnson, Peter J.
An Outline for Global Precipitation Mission Ground Validation: Building on Lessons Learned from TRMM Sandra Yuter and Robert Houze University of Washington.
05/03/2016FINNISH METEOROLOGICAL INSTITUTE Jarmo Koistinen, Heikki Pohjola Finnish Meteorological Institute CARPE DIEM FMI (Partner 5) progress report.
RICO DATA MANAGEMENT Steve Williams and Scot Loehrer UCAR/Joint Office for Science Support (JOSS) Boulder, Colorado RICO Workshop Boulder, CO February.
Diurnal Cycle of Precipitation Based on CMORPH Vernon E. Kousky, John E. Janowiak and Robert Joyce Climate Prediction Center, NOAA.
NAME SWG th Annual NOAA Climate Diagnostics and Prediction Workshop State College, Pennsylvania Oct. 28, 2005.
The National Weather Service Goes Geospatial – Serving Weather Data on the Web Ken Waters Regional Scientist National Weather Service Pacific Region HQ.
Warm Season Precipitation Analyses from the NAME Event Raingauge Network (NERN) '02-'03 NERN Project Team: NCAR, U. Arizona, U. Sonora, IMADES, ITSON April,
CARPE DIEM 4 th meeting Critical Assessment of available Radar Precipitation Estimation techniques and Development of Innovative approaches for Environmental.
NWS Precipitation Analysis Product Victor Murphy NWS Southern Region Climate Service Program Mgr. 5 th US Drought Monitor Forum Portland, OR October 11,
Observations of Specific Differential Phase, KDP Chris Collier Acknowledgements: Lindsay Bennett, Alan Blyth and David Dufton.
The three-dimensional structure of convective storms Robin Hogan John Nicol Robert Plant Peter Clark Kirsty Hanley Carol Halliwell Humphrey Lean Thorwald.
Statistical Analysis of S-Pol Polarimetric Radar Data from NAME 2004 Timothy J. Lang, Robert Cifelli, Steven A. Rutledge, Angela Rowe, and Lee Nelson Colorado.
Travis Smith U. Of Oklahoma & National Severe Storms Laboratory Severe Convection and Climate Workshop 14 Mar 2013 The Multi-Year Reanalysis of Remotely.
NPOL Olympex Located N/ W, 157 m ASL
A dual-polarization QPE method based on the NCAR Particle ID algorithm Description and preliminary results Michael J. Dixon1, J. W. Wilson1, T. M. Weckwerth1,
Radar/Surface Quantitative Precipitation Estimation
NSF Briefing 28 February 2003 Rit Carbone Issues and Opportunities.
Polarimetric radar analysis of convection in the complex topography
Richard H. Johnson, Paul E. Ciesielski, Brian D
Group interests RICO data required
Polarimetric radar analysis of convection in northwestern Mexico
NAME Tier 1 Atmospheric/Ocean Process and Budget Studies
Group interests RICO data in support of studies
Presentation transcript:

Science Plan for Radar Observations During NAME NSF S-Pol Radar SMN C-Band Doppler Radars Shipborne Radar P-3 Aircraft Radar Steve Rutledge Timothy Lang Robert Cifelli Steve Nesbitt Rit Carbone Arturo Valdez-Manzanilla plus colleagues

Basic Science Objectives of Radar Observations Document horizontal distribution of rainfall amount and intensity Document storm morphology Document the diurnal cycle of rainfall and convection Identify 2-D airflow features such as gust fronts, sea breezes, etc. Hydrometeor identification to aid verification of models What are the (thermo)dynamical and microphysical characteristics of convection? What is the diurnal behavior of convection within the monsoon regime? What are the physical processes controlling the diurnal cycle over land and ocean? How well do models simulate convection in complex terrain? What is the connection between synoptic variability and Gulf surges? What are the characteristics of Gulf surges? What are the links between monsoon strength and precipitation over the central US? Science Questions Addressed by Radar Network

Platform Descriptions NCAR/NSF S-Pol Radar S-Band, Dual-Linearly Polarized, Doppler Provides superior rain estimates to conventional radars Can distinguish between hydrometeor types SMN C-Band Doppler Radars Four locations extend coverage region over much of Tier I Run remotely, data saved via planned digitization upgrades S-Pol radar, gauges can be used to help improve rain estimates Provide important data to address storm structure, climatology, hydrological applications

Platform Descriptions Shipborne C-Band Doppler Radar Radar unlikely to be deployed due to lack of radar-capable ship Puma ship can be used for sounding, flux, and profiler measurements in the mouth of the GoC Aircraft X-Band Doppler Radar On NOAA P-3; Obtain additional flight hours if no ship radar Dual-Doppler coverage, in situ microphysical measurements No 24-hour coverage; Event-based flights over GoC, elsewhere

Measurement Protocols S-Pol Radar 24-hour/day ops for 6 weeks 15-minute cycle w/ 360° vol, PPI, and RHI sectors Staffed by NCAR and CSU SMN Radars 24-hour/15-minute cycle matched w/ S-Pol Pre-programmed 360° volumes w/ 7.5-min period Elevation angles, etc., unique to each site (blockage,etc.) Oversight by Arturo Valdez-Manzanilla & NCAR Shipborne Radar Unlikely to be available; Would be continuous 360° vol Staffed by CSU, others Still place Puma and launch 6 soundings/day for ~42 days on station (three 14-day IOPs); Continuous profiler & flux

Aircraft Radar Add ~60 flight hours (7-8 research flights) to the NOAA P-3 to provide radar coverage of convective systems over the GoC and SMO Collect dual-Doppler (and in situ microphysical data) in these systems Non-continuous coverage CSU personnel oversee in-flight radar dataacquisition Measurement Protocols

Possible Flight Patterns for P-3 Track evolving MCSs as they move into Gulf from SMO Or track already developed GoC systems

Data will be disseminated in a delayed fashion due to high QC requirements of radar data Raw data can be provided in standard DORADE/UF formats quickly; Same with aircraft or shipborne radar data Radar data will require extensive QC due to anticipated blockage, clutter, and attenuation Individual radar data is not anticipated to be the most useful format to most NAME users Therefore, combine QC’d S-Pol, SMN, and other radar data into a merged, regional product - CSU student under NCAR supervision Data Dissemination

NAME objectives focus on regional-scale processes, therefore a regional-scale radar product is required Create regional composites of rainfall maps and gridded volumes of convective echo; Include time-cumulative, averaged, and time-progressive composites Available at intervals of 15-minutes or less; Nested, telescoping grids Created after QC through NCAR gridding and analysis software; Anticipated format would be NetCDF or variant thereof Input from other NAME PIs will be used to determine gridding and filtering options (e.g., grid spacing) that best meet NAME objectives Details of Merged Radar Product

24-hour rainfall accumulation from gridded hourly NEXRAD Level-II low-elevation data, 27 May 1998 Example Data Product

Gridded S-Pol hydrometeor identification, for model verification; Available for most radar volumes In addition, S-Pol & gauges will be used to help correct attenuation and to improve Z-R estimates from SMN and other radars Kinematic analyses of selected events (from P-3) Rain rate/accumulation product over radar-covered, gauged watersheds Anticipate quick delivery of raw data (DORADE, UF) for individual radars, but creation of regional composites, and other processed analyses could take 12+ months for full datasets Can fast-track high-priority cases! Other Radar Products

S-Pol will be base of radar observations - extensive coordination will be required with aircraft, in order to provide flight guidance and target selection during radar-oriented flights Radar scientists will need to be involved in determination of radar-oriented P-3 flights if they are made available; CSU will provide staff for those flights SMN radars cannot be adjusted for individual events; Scan strategy will be set prior to project S-Pol will adjust PPI and RHI sectors depending on evolving situation; However, there will be 360° volumes available every 15-min for rain maps, etc. Field Coordination Requirements

Coordination with Other NAME Researchers We anticipate extensive contact and collaboration with NAME data assimilation and modeling researchers Coordinate the QC and processing of radar data to create the merged regional, microphysical, and kinematic products that meet NAME science objectives and researcher requirements Collaborate with the NAME hydrological community through radar/gauge comparisons, rain maps