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NOAA, version 1.0, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS El Nino Rapid Response Presented to CGMS-44, Working Group 2, agenda.

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Presentation on theme: "NOAA, version 1.0, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS El Nino Rapid Response Presented to CGMS-44, Working Group 2, agenda."— Presentation transcript:

1 NOAA, version 1.0, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS El Nino Rapid Response Presented to CGMS-44, Working Group 2, agenda item 5 Presented by Mitch Goldberg Major Content from: Gilbert P. Compo (OAR/CIRESI)Chris Barnet (NOAA/STC)

2 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Introduction & Key Points This presentation provides to the CGMS community an overview of how satellites supported the NOAA El Nino Rapid Response Campaign and some early results from the campaign. The El Nino rapid response field campaign is a NOAA/OAR-led multi-agency mission, see link for details: http://www.esrl.noaa.gov/psd/enso/rapid_response/ Goal of this campaign is to monitor this extreme El Nino event and improve weather forecasting with targeted observations in the Intertropic Convergence Zone (ITCZ) JPSS scientists provided real time S-NPP soundings from CrIS and ATMS using direct broadcast assets from Corvallis Oregon and Honolulu Hawaii. 22 flights were supported Jan. 21 through Mar. 10, 2016, Over 500 dropsondes deployed Significance: Real time JPSS data was used as guidance for aircraft flights and the JPSS soundings was used to characterize the thermodynamic field in regions that could not be measured with in-situ observations. Data collected from the campaign provided opportunities for unique datasets for validating satellite products

3 NOAA, version 1.0, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Slide: 3 Coordination Group for Meteorological Satellites - CGMS  Response to special topic on El Nino as recommended by David Halpern for working group 2.  Reference to HLPP 3.3 Foster the continuous improvement of products through validation and inter-comparison through international working groups and SCOPE-type mechanisms;  Satellite community involvement in campaigns for various objectives benefit from opportunities to obtain unique data that can be used in validating satellite products. Key issues of relevance to CGMS:

4 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS °C Maps from the NOAA-CIRES 20 th Century Reanalysis version 2c (Compo et al. 2011, go.usa.gov/XTd). ACRE, NOAA’s NCEI, and 65 organizations are key partners providing historical observations to 20CR. HadISST1.1 By Fall 2015, NOAA expected a significant El Niño and anticipated effects comparable to historical large events such as 1877-78, 1982-83, 1997-98 20CR Precipitation20CR 200 hPa Zonal Wind 20CR SST and Land surface T °C Select 9 largest JFM warm events and average

5 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS

6 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS ENRR data fill a void in the conventional sounding network G-IV Dropsondes Kirimati Island (CXENRR) Soundings NOAA R/V R. H. Brown (WTEC) soundings All Soundings from Radiosondes and Dropsondes on 19 February 2016 within ~6 hours of 00 UTC

7 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Dr. Chris Barnet of STC & NOAA /NESDIS prepared morning and afternoon overpasses from Suomi-NPP Microwave-only and combined Infrared and Microwave sounding retrievals and compared with G-IV dropsondes and NCEP’s Global Forecast System 3-9 hour forecasts. Morning overpass helped guide the ENRR daily mission planning. Colors: Total precipitable water from NOAA S-NPP Satellite Sounding algorithm (NUCAPS) Boxes: location of dropsondes from NOAA G-IV. (time offset from overpass) Sonde 4 ENRR science team was often able to adjust flight plans to maximize overlap of G-IV dropsonde deployment with the NPP afternoon overpass swath geometry. Afternoon Overpass NUCAPS total precipitable water retrieval Sonde MW-only IR+MW GFS

8 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Feb. 17, Sonde #1: 2.5 hours before overpass time IR+MW tends to capture vertical T(p) and q(p) structure better than MW 8

9 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Feb. 17, Sonde #5: 0.8 hours before overpass time But obviously doesn’t have the vertical resolution of a sonde or GFS 9

10 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Feb. 17, Sonde #8: near overpass time NUCAPS is capturing large scale vertical structures 10

11 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Feb. 17, Sonde #28: 2.3 hours after overpass time thin layers can be used to estimate vertical response 11

12 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Feb. 17, Sonde #30: 3 hours after overpass time Again, vertical resolution of IR+MW tends to be better than MW-only 12

13 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Feb. 17, Sonde #31: 3.2 hours after overpass time But why did this case do so much better? 13

14 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS http://gmao.gsfc.nasa.gov/forecasts/systems/fp/obs_impact/ All Tropical dropsondes in this period are from ENRR. Given all observations around the world, of those taken from 20N to 20S: ENRR dropsondes have the greatest contribution to reduction of error on a “per observation” basis, and substantially reduce the total global error, comparable to GPS Radio Occultation and CrIS. Implies a large local reduction in the tropical central Pacific. Impact of observations on reducing 24 hour forecast error as measured by global total moist energy. Negative value represents improvement in this measure. 20N-20S Courtesy R. Gelaro, NASA/GMAO

15 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS NOAA G-IV dropsonde obs reduce 24 hour Global Forecast Error (implies Large local effect). Obs tracking courtesy of NCEP

16 Agency NOAA, version 1.0, Date 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Conclusions 1.El Niño Rapid Response organized important study of tropical convection and links to extratropical impacts of historic 2015-16 El Niño with a combination of deployed aircraft and dropsondes, in-situ and ship released radiosondes, ground met stations, radar, and focused satellite retrievals. 2.Surprising result: NOAA G-IV dropsondes had a beneficial impact on 24 hour forecasts of NASA GEOS-5. a.“Per observation”, no other part of the tropical observing system contributed more, on average, to a reduction of 24 hour forecast error in the global moist energy during 25 January to 24 February 2016. b.G-IV dropsondes in a void of tropical radiosonde observations are comparable to major satellite systems even in total impact. c.Impact needs to be assessed in NOAA Global Forecasting System.

17 NOAA, version 1.0, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS Slide: 17 Coordination Group for Meteorological Satellites - CGMS  Recommend CGMS agencies to report on campaigns at CGMS working group 2 and CGMS science working groups to enable cross cutting benefits.  CGMS agencies should consider support of multipurpose campaigns to enable cross cutting benefits (science understanding, validation, etc.) To be considered by CGMS:


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