Status and Update of Quantitative Precipitation Estimates from Satellites: the International Precipitation Working Group Activities

Transcription

1 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 Meeting Geneva, Switzerland, November 2013

2 Outline IPWG History and Objectives Recent Accomplishments IPWG Datasets IPWG Validation Sites and Strategies Recommendations and Future Direction

3 IPWG History Formation Meeting: June 2001, Fort Collins, US Endorsed by the Coordinating Group on Meteorological Satellites (CGMS) 29th session (July 2001) IPWG 1: September 2002, INM, Madrid, Spain IPWG 2: October 2004, NRL, Monterey, US IPWG 3: October 2006, BoM, Melbourne, Australia IPWG 4: October 2008, NSMC; Beijing, China IPWG 5: October 2010, KC, MPI M, Hamburg, Germany IPWG 6: October 2012, INPE, Sao Jose dos Campos, Brazil

4 IPWG Objectives IPWG was established under CGMS to: Promote standard operational procedures and common software for deriving precipitation estimates from satellites Establish standards for validation and independent verification of precipitation estimates Foster the exchange of data on inter-comparisons of operational precipitation estimates from satellites Stimulate increased international scientific research and development in this field Provide recommendations to national and international agencies regarding the utilization of current and future satellite instruments on both polar and geostationary platforms Encourage regular education and training activities

5 IPWG Membership There are about 279 participants from 39 countries and agencies Every year new members are joining IPWG South America, 11 North America, 121 WMO, 3 Africa, 5 Asia, 31 Europe, 91 Australia, 5 ECMWF, 5 EUMETSAT, Argentina Australia Austria Bangladesh Brasil Bulgaria Canada China Cyprus ECMWF EUMETSAT Finland France Germany Greece Hungary India Indonesia Italy Japan Korea Latvia Moldova Mozambique Nepal Nigeria Poland Portugal Slovenia South Africa Spain Sweden Taiwan Thailand Turkey Ukraine United Kingdom USA WMO

6 We want to get better at turning this into this TRMM Sat-Gauge (mm/h) 00Z 01 March 2000

7 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.

8 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 min 3 4 hr footprint 4 8 km km interval min hr (up to 3 hr) (~3 hr) physics cloud top hydrometeors weak strong additional microwave issues over land include scattering channels only issues with orographic precip no estimates over snow

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10 IPWG Recent Accomplishments Developed a IPWG web page the lists of publicly available, quasioperational 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

11 IPWG Recent Accomplishments Developed a IPWG web page the lists of publicly available, quasioperational 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

12 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 algorithms Single 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.

13 Introduction to Global Precipitation Data Sets Single source datasets

14 Introduction to Global Precipitation Data Sets Satellite combination datasets

15 Near real time intercomparison of model & satellite estimates vs radar/gauge

16 Validation / intercomparison of daily satellite precipitation estimates An IPWG project

17 Validation / intercomparison of daily satellite precipitation estimates An IPWG project

18 24 hour precipitation rate mm day 1 during period

19 Percent bias calculated during period for the different algorithms

20 Percent bias calculated during period for the different algorithms for South America (upper panel) and southern Brasil (bottom panel)

21 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).

22 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 A few examples shown below: Floods/Landslides potential_flood_hydro.html Disease Monitoring /pdf/project1p/08-malaria.pdf Drought Monitoring /nldas/drought/

23 IPWG6 Recommendations Critical 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 platforms The coordination of satellite overpass times has to be ensured including non-sun-synchronous platforms with a minimum temporal resolution of 3 h The 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

24 IPWG6 Recommendations The implementation of new technology, such as geostationary microwave and advanced radar instrumentation A database of existing precipitation products be archived for at least two years to facilitate intercomparison and graceful user transitions with new algorithms and satellite products For 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 satellites The support of the constellation of PMW imagers, consistent with the CGMS baseline and the WMO Vision for the Global Observing System in 2025

25 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

26 IPWG Future Direction New IPWG co chairs have been nominated for : 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 , 2014 IPWG is a community effort. We welcome anyone that has interest in precipitation research to join and contribute to the future direction of IPWG Please visit the IPWG website for more information:

27 Thank you