WMO 2016 Survey on the Use of Satellite Data

Transcription

1 WMO 2016 Survey on the Use of Satellite Data World Meteorological Organization (WMO) Space Programme 5 th Meeting of the Coordinating Group for the RA II WIGOS Project to Develop Support for NMHSs in Satellite Data, Products and Training Vladivostok, Russia 21 Oct 2017

2 Outline Motivation The Survey Regional Distribution of Responses GEO: Region-specific Analysis RAII: GEO Data Access and Processing RAII: GEO Visualization Tools and Training Needs RAII: Next-generation GEO satellites Readiness Level LEO: Region-specific Analysis RAII: LEO Data Access, Data Processing and Training Needs RAII: Next-generation LEO satellites Readiness Level Conclusions

3 Motivation WMO carries out a global user survey every 4 years. Users worldwide need to prepare for newgeneration satellites gaps and issues? Need a dialogue between users and satellite operators. Satellite data are increasing in importance (nowcasting, NWP, marine services, climate monitoring, etc.)

4 The Survey Online questionnaire, developed by WMO CBS IPET-SUP Four languages (E, F, S, R) Three major topics: accessing and using geostationary satellite data, accessing and using low-earth orbiting satellite data, satellite applications and training

5 The Survey: RAII March-May responses globally 38 from RA II, from 16 Members 66% NMHS 8% Other gov t agency 24% Research, Academia Bangladesh China Hong Kong, China Macao, China India Iran Japan Kazakhstan Kyrgyzstan Oman Pakistan Republic of Korea Russian Federation Thailand United Arab Emirates Uzbekistan

6 The Survey: Regional Distribution of Responses WMO Region Number of Members Number of Members with at least one response (rate in %) Total number of responses Comparison to 2012 Survey I (Africa) (63%) (30%) 37 II (Asia) (45%) (54%) 34 III (S America) 13 8 (62%) 21 5 (38%) 14 IV (N&C America &C) (44%) 40 8 (31%) 44 V (SW Pacific) 23 6 (26%) (55%) 17 VI (Europe) (56%) (68%) 72 All (55%) (50%) 218

7 RAII: GEO Data Use

8 RA II: GEO Data Access and Processing Access to GEO data good Some challenges in GEO data processing and visualization (mostly minor) We have little experience in processsing Himawari-8 into high level secondary products. e.g. RDT products for severe storm detection (Hong Kong, China)

9 RA II: GEO Data Training Needs

10 Meteosat Meteosat Himawari GOES-East GOES-East Himawari Meteosat Meteosat Meteosat Himawari GOES-East GOES-East Himawari Meteosat RAII: GEO Data Processing - Regional Analysis Training Needs Visualization Tools Met Partially Met Not Met 60% 48% 48% 45% Met Partially Met Not Met 48% 40% 38% 39% 26% 21% 21% 24% 38% 24% 18% 18% 32% 29% 24% 18% 30% 20% 32% 26% 5% 10% 10% 10% 3% 0 0 8% 5% 3% 10% 4% RAI RAII RAIII RAIV RAV RAVI RAI RAII RAIII RAIV RAV RAVI Unmet needs require attention, but Challenges in RA II no larger than elsewhere despite ongoing transition to new-generation Himawari-8 and FY-4A

11 MTG-I (2020) FY-4A (2016) GOES-R (2016) GOES-R (2016) GEO-KOMPSAT-2A (2018) MTG-I (2020) RAII: Next-generation GEO - Readiness Level Regional Analysis 40% 35% 30% 25% 20% 15% 10% We are aware of the mission but have not acted We have started the planning process We have plans to upgrade our systems We are implementing plans to upgrade our systems 5% 0% RAI RAII RAIII RAIV RAV RAVI Little awareness to prepare for FY-4A despite significant use of current FY-2!

12 RA II: LEO Data Use

13 RA II: LEO Data Access and Processing No issues with access (for those who access); Needs for pre-processing packages (Metop, POES, S-NPP, Aqua/Terra, FY-3) and related training SOFT W ARE N EED S Answe r Op tio ns No e xtra so ftwa re ne e d e d L0-L1 p ro c e sso r ne e d e d L1-L2 p ro c e sso r ne e d e d Bo th L0-L1 & L1-L2 ne e d e d R e s p o ns e Co unt METOP A-B GCOM-W S-NPP NOAA DMSP F16-F FY 3A-3C Meteor-M Oceansat Landsat AQUA/TERRA Cloudsat/Calipso Part of AOMSUC-8 training course on Oct 2017

14 MetOP AB NOAA NOAA NOAA Aqua/Terra NOAA MetOp AB Aqua/Terra RAII: LEO Data Processing Training Needs Regional Analysis Met Partially Met Not Met 50% 34% 20% 16% 16% 23% 15% 24% 11% 10% 10% 4% 5% 0 0 3% 0 2% RAI RAII RAIII RAIV RAV RAVI Missions with highest response rate per RA

15 FY 3D-3E ( ) FT 3D-3E ( ) JPSS-1 (2017) JPAA-1 (2017) FY 3D-3E ( ) JPSS-1 (2017) Sentinel-3 (2016) RAII: Next-generation LEO - Readiness Level Regional Analysis 20% 18% 16% 14% 12% 10% 8% 6% We are aware of the mission but have not acted We have started the planning process We have plans to upgrade our systems We are implementing plans to upgrade our systems 4% 2% 0% RAI RAII RAIII RAIV RAV RAVI Missions with highest response rate per RA

16 Conclusion Good response rate in RA II Processing and visualization software needs (GEO and LEO) and related training Transition to Himawari-8 largely under control Transition to FY-4A requires attention Preparation to FY-3D/E under way by many Members

17 Thank you for your attention Stephan Bojinski