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Measuring High-Latitude Precipitation from Space Ralf Bennartz SSEC University of Wisconsin – Madison EES – Vanderbilt University.

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Presentation on theme: "Measuring High-Latitude Precipitation from Space Ralf Bennartz SSEC University of Wisconsin – Madison EES – Vanderbilt University."— Presentation transcript:

1 Measuring High-Latitude Precipitation from Space Ralf Bennartz SSEC University of Wisconsin – Madison EES – Vanderbilt University

2 Outline What can we do now?What can we do now? Connecting to the surfaceConnecting to the surface Greenland mass balanceGreenland mass balance ValidationValidation Clouds and the surface energy balanceClouds and the surface energy balance Way forwardWay forward

3 Contributions IWSSM-4 participants, in particular:IWSSM-4 participants, in particular: Tristan L’EcuyerTristan L’Ecuyer Mark KulieMark Kulie Gail Skofronick-JacksonGail Skofronick-Jackson Karen BoeningKaren Boening Anne WalkerAnne Walker Deb VaneDeb Vane

4 IWSSM-4 Fourth International Workshop on Space-based Snowfall Measurement Held March 2013, MammothHeld March 2013, Mammoth 50 participants50 participants Reports back to IPWG, CGMS, WMOReports back to IPWG, CGMS, WMO Detailed recommendations from four working groups:Detailed recommendations from four working groups: 1.Applications & Validation 2.Radiative Properties 3.Global & Regional Detection/Estimation 4.Missions & Concepts Ralf Bennartz, University of Wisconsin Robin Hogan, University of Reading Paul Joe, Environment Canada Gail Skofronick Jackson, NASA GSFC Graeme Stephens, JPL Deb Vane, JPL Jeff Dozier, UCSB

5 Phase C. Kidd

6 NEXRAD 1638Z Terra MODIS 1635Z Type

7 Observing Snow with CloudSat  Active sensor  Excellent sensitivity  Near-global coverage  Coincident measurements from other A-Train sensors Strengths of CloudSat:  Complex relationship between reflectivity and snowfall rate/IWC  Rain/snow discrimination  Sampling  Ground Clutter Challenges: T. L’Ecuyer

8 Global Precipitation Measurement (GPM) Joint NASA/JAXA missionJoint NASA/JAXA mission 2013: As soon as NASA find a launch vehicle…2013: As soon as NASA find a launch vehicle… Active: Dual- frequency Precipitation Radar (DPR) 12/17 dBZ MDSActive: Dual- frequency Precipitation Radar (DPR) 12/17 dBZ MDS Passive: Multi- frequency GPM Microwave Imager (GMI): 13 channels ( GHz)Passive: Multi- frequency GPM Microwave Imager (GMI): 13 channels ( GHz) GPM - Courtesy of NASA GSFC

9 Global Precipitation Measurement (GPM) GPM-DPRGPM-DPR “It is estimated that due to its higher detectability threshold, only about 7%/1% of the near-surface radar reflectivity values and about 17%/4% of the total accumulation associated with global dry snowfall would be detected by a DPR-like instrument” (Kulie & Bennartz 2009, from global CloudSat observations)“It is estimated that due to its higher detectability threshold, only about 7%/1% of the near-surface radar reflectivity values and about 17%/4% of the total accumulation associated with global dry snowfall would be detected by a DPR-like instrument” (Kulie & Bennartz 2009, from global CloudSat observations)

10 10 Earth Explorer User Consultation Meeting 19 and 20 April 2004EarthCARE10 EarthCARE FOUR INSTRUMENTS: DOPPLER CLOUD RADAR HIGH SPECTRAL RESOLUTION LIDAR MULTI SPECTRAL IMAGER BROAD BAND RADIOMETER A. Illingworth

11 Greenland Ice Sheet: Surface Mass Balance M. van den Broeke et al. 2009

12 CloudSat data density Even nadir-only sensors (CloudSat) provide decent coverage at higher latitudesEven nadir-only sensors (CloudSat) provide decent coverage at higher latitudes About 7000 obs per year per 1x2 deg box at 70 N.About 7000 obs per year per 1x2 deg box at 70 N.

13 CloudSat: 2006 – 2010 Mean

14 Greenland Ice Sheet: Surface Mass Balance Cloudsat derived annual mean precipitation accumulation GIS 6/2006:Cloudsat derived annual mean precipitation accumulation GIS 6/2006: 650 Gt/yr650 Gt/yr

15 GPCC: 2006 – 2010

16

17 Snowflakes Summit Observatory – Greenland Shupe et al. (2012) Vermont – Bentley (ca. 1902)

18 Modeling Non-spherical Particles In the last 5 years significant progress has been made in modeling non-spherical ice optical propertiesIn the last 5 years significant progress has been made in modeling non-spherical ice optical properties What did we learn?What did we learn? How can we constrain them?How can we constrain them?

19 Uncertainty due to habit Hiley, Kulie, Bennartz (JAMC, 2011)

20 Comparison to Canadian Surface Observations

21 Jet Propulsion Laboratory California Institute of Technology Workshop on Space-based Snowfall Measurement (4th IWSSM), May 6-8, 2013 Boening et al.: SNOWFALL-DRIVEN MASS CHANGE ON THE EAST ANTARCTIC ICE SHEET Ice Mass Increase and Antarctic Precipitation CloudSat CloudSat observes snowfall Accumulated snow from CloudSat agrees well with GRACE’s observed mass Sublimation plays minor role CloudSat observes snowfall Accumulated snow from CloudSat agrees well with GRACE’s observed mass Sublimation plays minor role This slide from Boening et al.

22 Clouds and surface melting ICECAPS observations and models show that clouds were “just right” for enhanced ice surface melt in July Thin liquid water clouds trap infrared radiation while still permitting enough solar radiation to lead to maximum surface heating.

23 Polar precipitation is a major gap with current satellite missions. Given the changes that are being observed in the Arctic due to climate change, a future satellite mission must focus on the capability to address polar precipitation and clouds synergistically in order to address climate and water cycle science/prediction priorities. There is much to gained by the precipitation and snow on the ground communities working together to outline priorities for future missions and address retrieval issues. If we want to observe climate signals, we need to have long- term records. Need for stable, well-calibrated long-term satellite datasets. Conclusions


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