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Status and Update of Quantitative Precipitation Estimates from Satellites: the International Precipitation Working Group Activities
Daniel Alejandro Vila
CPTEC/INPE, Cachoeira Paulista, Brazil
SCOPE-Nowcasting Ad-hoc Steering Group, First MeetingGeneva, Switzerland, 19-22 November 2013
Outline
IPWG History and Objectives
Recent Accomplishments
IPWG Datasets
IPWG Validation Sites and Strategies
Recommendations and Future Direction
IPWG History
Formation Meeting: June 2001, Fort Collins, USEndorsed by the Coordinating Group on Meteorological Satellites (CGMS) 29th session (July 2001)
IPWG‐1: September 2002, INM, Madrid, SpainIPWG‐2: October 2004, NRL, Monterey, USIPWG‐3: October 2006, BoM, Melbourne, AustraliaIPWG‐4: October 2008, NSMC; Beijing, ChinaIPWG‐5: October 2010, KC, MPI‐M, Hamburg, GermanyIPWG‐6: October 2012, INPE, Sao Jose dos Campos, Brazil
IPWG was established under CGMS to:
Promote standard operational procedures and common software for deriving precipitation estimates from satellitesEstablish standards for validation and independent verification of precipitation estimatesFoster the exchange of data on inter-comparisons of operational precipitation estimates from satellitesStimulate increased international scientific research and development in this fieldProvide recommendations to national and international agencies regarding the utilization of current and future satellite instruments on both polar and geostationary platformsEncourage regular education and training activities
IPWG Objectives
IPWG Membership• There are about 279 participants from 39 countries and agencies
• Every year new members are joining IPWG.
0
20
40
60
80
100
120
140
Argentina
Australia
Austria
Bangladesh
Brasil
Bulgaria
Canada
China
Cyprus
ECMWF
EUMETSA
TFinland
France
Germany
Greece
Hun
gary
India
Indo
nesia
Italy
Japan
Korea
Latvia
Moldo
vaMozam
biqu
eNep
alNigeria
Poland
Portugal
Slovenia
South Africa
Spain
Sweden
Taiwan
Thailand
Turkey
Ukraine
United Kingdom
USA
WMO
Africa, 5
Asia, 31
Australia, 5
ECMWF, 5
EUMETSAT, 7
Europe, 91
North America,
121
South America,
11
WMO, 3
We want to get better at turning this
TRMM Sat-Gauge (mm/h) 00Z 01 March 2000
into this
Satellite‐based rainfall estimation methods
• Satellite rainfall retrievals are generally categorized into LEO and GEO. • Retrieval algorithms are typically classified on their observing spectrum (VIS, IR, PMW, AMW) or “multi‐spectral” (i.e., use of one or more of these individual spectrums). • If the methodology uses multiple satellites or other information such as radar or gauges is classified as a “blended” technique.
A diverse, changing, uncoordinated set of input precip estimates, with various
• periods of record
• regions of coverage
• sensor‐specific strengths and
limitations
infrared microwave
latency 15‐60 min 3‐4 hr
footprint 4‐8 km 5‐30+ km
interval 15‐30 min 12‐24 hr(up to 3 hr) (~3 hr)
“physics” cloud top hydrometeorsweak strong
• additional microwave issues over land include• scattering channels only• issues with orographic precip• no estimates over snow
IPWG Recent Accomplishments
Developed a IPWG web page the lists of publicly available, quasi‐operational and quasi‐global precipitation data sets
Conducted a survey and developed a list of different sources of validation precipitation databases
Conducted a survey on applications of satellite‐derived precipitation products and published the list of applications on the IPWG website
Leadership of Group on Earth Observations (GEO) precipitation subtask
Interactions with Working Group on Numerical Experimentation (WGNE) on satellite precipitation validation using NWP generated precipitation estimates
IPWG Recent Accomplishments
Developed a IPWG web page the lists of publicly available, quasi‐operational and quasi‐global precipitation data sets
Conducted a survey and developed a list of different sources of validation precipitation databases
Conducted a survey on applications of satellite‐derived precipitation products and published the list of applications on the IPWG website
Leadership of Group on Earth Observations (GEO) precipitation subtask
Interactions with Working Group on Numerical Experimentation (WGNE) on satellite precipitation validation using NWP generated precipitation estimates
Introduction to Global Precipitation Data Sets
The focus here is on data sets that provide:global (or nearly global) coverage, with
multi‐year periods of record, that are
publicly available.
Four tiers of algorithmsSingle‐source datasets → data sets from a single satellite sensor type.
Satellite combination datasets → data sets that are produced by combining input data from several satellite sensor types (LEO & GEO).
Combination datasets with gauge data → data sets that are produced by combining input data from several sensor types, including satellite sensors and precipitation gauges.
Precipitation gauge analyses → data sets from precipitation gauge data.
Introduction to Global Precipitation Data SetsSingle‐source datasets → http://www.isac.cnr.it/~ipwg/data/datasets3.html
Introduction to Global Precipitation Data SetsSatellite combination datasets → http://www.isac.cnr.it/~ipwg/data/datasets2.html
Near real‐time intercomparison of model & satellite estimates vs radar/gauge
Validation / intercomparison of daily satellite precipitation estimates ‐‐ An IPWG project
Validation / intercomparison of daily satellite precipitation estimates ‐‐ An IPWG project
24‐hour precipitation rate mm day‐1 during 2008‐2010 period
Percent bias calculated during 2008‐2010period for the different algorithms
Percent bias calculated during 2008‐2010period for the different algorithms for South America (upper panel) and southern Brasil (bottom panel)
Global precipitation measurement uncertainty estimated from an ensemble of six different datasets, for winter (DJF) and summer (JJA). Large uncertainties can be seen at higher latitudes, over winter U.S. and Europe, and over summer Himalayas (Tian and Peters‐Lidard, 2010).
Applications of Satellite‐derived Precipitation Datasets • A survey of the IPWG community was conducted• A BAMS publication is being drafted that summarizes the wide‐range of applications
• Kucera, P. A., E. E. Ebert, F. J. Turk, V. Levizzani, D. Kirschbaum, F. J. Tapiador, P. Xian, A. Loew, and M. Borsche, 2013: Precipitation from Space: Advancing Earth System Science. Bull. Amer. Meteor. Soc., DOI: BAMS‐D‐11‐00171.1.
• A few examples shown below:
Drought Monitoringhttp://www.emc.ncep.noaa.gov/mmb
/nldas/drought/
Floods/Landslideshttp://trmm.gsfc.nasa.gov/publications_dir/
potential_flood_hydro.html
Disease Monitoringhttp://appliedsciences.nasa.gov/pdf/Project1P/08-Malaria.pdf
http://www.isac.cnr.it/~ipwg/applications.html
IPWG6 RecommendationsCritical validation sites/networks should be sustained, particularly over data sparse regions (e.g., Africa, South America) where validation has been particularly challenging The long-term continuity of conically-scanning microwave imagers as well as space based radars should be maintained, especially for future operational NOAA / DoD polar platformsThe coordination of satellite overpass times has to be ensured including non-sun-synchronous platforms with a minimum temporal resolution of 3 hThe release of precipitation relevant information from research missions in a timely manner. In particular, the critical importance of data from the Megha-Tropiques MADRAS sensor
IPWG6 RecommendationsThe implementation of new technology, such as geostationary microwave and advanced radar instrumentationA database of existing precipitation products be archived for at least two years to facilitate intercomparison and graceful user transitions with new algorithms and satellite productsFor quasi-operational satellite algorithms based on multiple platforms and channels (VIS, IR, WV), an archive of historical data should be made available to provide access to channels from GEO and LEO satellitesThe support of the constellation of PMW imagers, consistent with the CGMS baseline and the WMO Vision for the Global Observing System in 2025
IPWG Future Direction
To continue and expand validation activites:
Foster improved availability of validation data from data sparse regions: Africa, South America, etc.
Prepare guidance document on precipitation validation techniques and issues
Encourage validation of precipitation datasets in hydrological models
Collect datasets for snow validation
Expand training activities and provide training resources on the IPWG web site
To establish an ad‐hoc Special Interest Group to share information, processing concepts, and best practices in an effort provide precipitation data products in GIS‐standard format
IPWG Future DirectionNew IPWG co‐chairs have been nominated for 2013‐2014: ‐Kazumasa Aonashi (JMA/Meteorological Research Institute)‐Nai‐Yu Wang (ESSIC/University of Maryland)
IPWG7: Next meeting is tentatively planned for Tsukuba Space Center, Tsukuba, Ibaraki, Japan, Oct. 21‐25, 2014
IPWG is a community effort. We welcome anyone that has interestin precipitation research to join and contribute to the future direction of IPWGPlease visit the IPWG website for more information: http://www.isac.cnr.it/~ipwg/
Thank you
http://www.isac.cnr.it/~ipwg/