IGARSS July 2011 1 Thresholds of Detection for Falling Snow from Satellite-Borne Active and Passive Sensors IGARSS 2011 Vancouver, Canada Gail Skofronick.

Slides:

Advertisements

Similar presentations

Robin Hogan, Richard Allan, Nicky Chalmers, Thorwald Stein, Julien Delanoë University of Reading How accurate are the radiative properties of ice clouds.

Advertisements

Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,

The Aquarius Salinity Retrieval Algorithm Frank J. Wentz and Thomas Meissner, Remote Sensing Systems Gary S. Lagerloef, Earth and Space Research David.

All-Weather Wind Vector Measurements from Intercalibrated Active and Passive Microwave Satellite Sensors Thomas Meissner Lucrezia Ricciardulli Frank Wentz.

Passive Measurements of Rain Rate in Hurricanes Ruba A.Amarin CFRSL December 10, 2005.

Analysis of ARM cirrus data and the incorporation of Doppler Fall-velocity measurements in lidar/radar retrievals Outline of lidar/radar procedure. Problem.

The ASCII 2012 campaign: overview and early results AgI Seeding Cloud Impact Investigation Bart Geerts presented by: Xia Chu contributions by: Katja Friedrich,

Equation for the microwave backscatter cross section of aggregate snowflakes using the Self-Similar Rayleigh- Gans Approximation Robin Hogan ECMWF and.

Retrieval of smoke aerosol loading from remote sensing data Sean Raffuse and Rudolf Husar Center for Air Pollution Impact and Trends Analysis Washington.

Atmospheric structure from lidar and radar Jens Bösenberg 1.Motivation 2.Layer structure 3.Water vapour profiling 4.Turbulence structure 5.Cloud profiling.

Figure 2.10 IPCC Working Group I (2007) Clouds and Radiation Through a Soda Straw.

1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.

Surface Reflectivity from OMI using MODIS to Eliminate Clouds: Effects of Snow on UV-Vis Trace Gas Retrievals Gray O’Byrne, 1 Randall V. Martin, 1,2 Aaron.

Photo courtesy of Paul Lawson/J.H. Bain An Overview of Cirrus Cloud Thinning and Determining Its Scientific Feasibility David L. Mitchell Desert Research.

1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.

Improving the AMSR-E snow depth product: recent developments Richard Kelly University of Waterloo, Canada.

NARVAL South Lutz Hirsch, Friedhelm Jansen Sensor Synergy While Radars and Lidars provide excellent spatial resolution but only ambiguous information on.

WATER LEVEL MONITORING USING THE INTERFERENCE PATTERN GNSS-R TECHNIQUE § Remote Sensing Lab, Dept. TSC, Building D3, Universitat Politècnica de Catalunya,

Retrieving Snowpack Properties From Land Surface Microwave Emissivities Based on Artificial Neural Network Techniques Narges Shahroudi William Rossow NOAA-CREST.

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 1 M. Brogioni 1, S. Pettinato 1, E. Santi 1, S. Paloscia 1, P. Pampaloni 1,

Precipitation Retrievals Over Land Using SSMIS Nai-Yu Wang 1 and Ralph R. Ferraro 2 1 University of Maryland/ESSIC/CICS 2 NOAA/NESDIS/STAR.

A Combined Radar/Radiometer Retrieval for Precipitation IGARSS – Session 1.1 Vancouver, Canada 26 July, 2011 Christian Kummerow 1, S. Joseph Munchak 1,2.

William Crosson, Ashutosh Limaye, Charles Laymon National Space Science and Technology Center Huntsville, Alabama, USA Soil Moisture Retrievals Using C-

A Simple Model of the Mm-wave Scattering Parameters of Randomly Oriented Aggregates of Finite Cylindrical Ice Hydrometeors : An End-Run Around the Snow.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 POES Microwave Products Presented.

Estimation of Cloud and Precipitation From Warm Clouds in Support of the ABI: A Pre-launch Study with A-Train Zhanqing Li, R. Chen, R. Kuligowski, R. Ferraro,

BIOPHYS: A Physically-based Algorithm for Inferring Continuous Fields of Vegetative Biophysical and Structural Parameters Forrest Hall 1, Fred Huemmrich.

DMRT-ML Studies on Remote Sensing of Ice Sheet Subsurface Temperatures Mustafa Aksoy and Joel T. Johnson 02/25/2014.

Frank J. LaFontaine 1, Robbie E. Hood 2, Courtney D. Radley 3, Daniel J. Cecil 4, and Gerald Heymsfield 5 1 Raytheon Information Solutions, Huntsville,

First Tropical Cyclone Overflights by the Hurricane Imaging Radiometer (HIRAD) Chris Ruf 1, Sayak Biswas 2, Mark James 3, Linwood Jones 2, Tim Miller 3.

Evaluating Cloud Microphysics Schemes in the WRF Model Fifth Meeting of the Science Advisory Committee November, 2009 Andrew Molthan transitioning.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Infrared Temperature and.

WATER VAPOR RETRIEVAL OVER CLOUD COVER AREA ON LAND Dabin Ji, Jiancheng Shi, Shenglei Zhang Institute for Remote Sensing Applications Chinese Academy of.

Second International Workshop on Space-based Snowfall Measurement 31 March - 4 April 2008 Steamboat Ski Village, Colorado Organizing Committee Ralf Bennartz.

Characterization of Aerosols using Airborne Lidar, MODIS, and GOCART Data during the TRACE-P (2001) Mission Rich Ferrare 1, Ed Browell 1, Syed Ismail 1,

Matthew Shupe Ola Persson Paul Johnston Duane Hazen Clouds during ASCOS U. of Colorado and NOAA.

MULTI-FREQUENCY, MULTI-POLARIZATION AND ANGULAR MEASUREMENTS OF BARE SOIL, SNOW AND WATER ICE MICROWAVE REFLECTION AND EMISSION BY C-, Ku-, AND Ka-BAND,

Evaluation of Passive Microwave Rainfall Estimates Using TRMM PR and Ground Measurements as References Xin Lin and Arthur Y. Hou NASA Goddard Space Flight.

A review on different methodologies employed in current SWE products from spaceborne passive microwave observations Nastaran Saberi, Richard Kelly Interdisciplinary.

Improvement of Cold Season Land Precipitation Retrievals Through The Use of Field Campaign Data and High Frequency Microwave Radiative Transfer Model IPWG.

A Global Rainfall Validation Strategy Wesley Berg, Christian Kummerow, and Tristan L’Ecuyer Colorado State University.

Ice-Phase Precipitation Remote Sensing Using Combined Passive and Active Microwave Observations Benjamin T. Johnson UMBC/JCET & NASA/GSFC (Code 613.1)

Retrieval of Vertical Columns of Sulfur Dioxide from SCIAMACHY and OMI: Air Mass Factor Algorithm Development, Validation, and Error Analysis Chulkyu Lee.

GPM Planning Mtg Aug 2001Skofronick-Jackson, Weinman, Wang, Chang High Frequency Microwave Observations of Frozen Hydrometeors Gail Skofronick Jackson.

Retrieval of Cloud Phase and Ice Crystal Habit From Satellite Data Sally McFarlane, Roger Marchand*, and Thomas Ackerman Pacific Northwest National Laboratory.

Challenges and Strategies for Combined Active/Passive Precipitation Retrievals S. Joseph Munchak 1, W. S. Olson 1,2, M. Grecu 1,3 1: NASA Goddard Space.

Instrument location ceilo pyro radar 10m Ground-based remote sensing instruments of clouds and precip at Princess Elisabeth.

Initial Analysis of the Pixel-Level Uncertainties in Global MODIS Cloud Optical Thickness and Effective Particle Size Retrievals Steven Platnick 1, Robert.

Ocean and Land Surface Characterization in the GPM Radar-Radiometer Combined Algorithm S. Joseph Munchak 1,2 *, William S. Olson 1,3, Mircea Grecu 1,4,

The Inter-Calibration of AMSR-E with WindSat, F13 SSM/I, and F17 SSM/IS Frank J. Wentz Remote Sensing Systems 1 Presented to the AMSR-E Science Team June.

Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.

Geophysical Ocean Products from AMSR-E & WindSAT Chelle L. Gentemann, Frank Wentz, Thomas Meissner, Kyle Hilburn, Deborah Smith, and Marty Brewer

Basis of GV for Japan’s Hydro-Meteorological Process Modelling Research GPM Workshop Sep. 27 to 30, Taipei, Taiwan Toshio Koike, Tobias Graf, Mirza Cyrus.

A step toward operational use of AMSR-E horizontal polarized radiance in JMA global data assimilation system Masahiro Kazumori Numerical Prediction Division.

A Combined Radar-Radiometer Approach to Estimate Rain Rate Profile and Underlying Surface Wind Speed over the Ocean Shannon Brown and Christopher Ruf University.

SeaWiFS Views Equatorial Pacific Waves Gene Feldman NASA Goddard Space Flight Center, Lab. For Hydrospheric Processes, This.

BACKSCATTERING FROM SEA SURFACE WITH PRECIPITATION

Active and passive microwave remote sensing of precipitation at high latitudes R. Bennartz - M. Kulie - C. O’Dell (1) S. Pinori – A. Mugnai (2) (1) University.

- 1 - Satellite Remote Sensing of Small Ice Crystal Concentrations in Cirrus Clouds David L. Mitchell Desert Research Institute, Reno, Nevada Robert P.

Shaima Nasiri University of Wisconsin-Madison Bryan Baum NASA - Langley Research Center Detection of Overlapping Clouds with MODIS: TX-2002 MODIS Atmospheres.

SCM x330 Ocean Discovery through Technology Area F GE.

Microwave Emission Signature of Snow-Covered Lake Ice Martti Hallikainen (1), Pauli Sievinen (1), Jaakko Seppänen (1), Matti Vaaja (1), Annakaisa von Lerber.

Developing Winter Precipitation Algorithm over Land from Satellite Microwave and C3VP Field Campaign Observations Fifth Workshop of the International Precipitation.

What Are the Implications of Optical Closure Using Measurements from the Two Column Aerosol Project? J.D. Fast 1, L.K. Berg 1, E. Kassianov 1, D. Chand.

Passive Microwave Remote Sensing

Microwave Assimilation in Tropical Cyclones

NPOESS Airborne Sounder Testbed (NAST)

Microwave Remote Sensing

Wei Huang Class project presentation for ECE539

Fourth International Workshop on Space-based Snowfall Measurement

Presentation transcript:

IGARSS July Thresholds of Detection for Falling Snow from Satellite-Borne Active and Passive Sensors IGARSS 2011 Vancouver, Canada Gail Skofronick Jackson Benjamin Johnson Joe Munchak NASA Goddard Space Flight Center, Greenbelt, Maryland

IGARSS July Presentation Outline (1)Contributions to Brightness Temperatures (2)Falling Snow Detection Thresholds Analysis framework Active thresholds based on instrument sensitivity Passive thresholds Comparison between active and passive Future improvements (3)Snow Field Campaign (Jan – Feb 2012) (4)Summary

IGARSS July Percentages from Surface, Snow, & Water Vapor Lake Effect 2-3km tops (0.5 to 1.0 IWP) Synoptic 5-7km tops (0.5 to 1.0 IWP) Blizzard ~10km tops (0.5 to 1.0 IWP) Blizzard ~10km tops (9 to 10 IWP) “Surface and Atmospheric Contributions to Microwave Brightness Temperatures for Falling Snow Events,” by Gail Skofronick-Jackson and Benjamin Johnson, JGR-Atmos, published Jan (a) (b) (a) (b) Macro and microphysical cloud characteristics affect TB signal These use dendrite snowflakes

IGARSS July Falling Snow Detection Thresholds What are the thresholds of detection in terms of IWP or IWC of falling snow? Analysis Approach: Use WRF models of Lake Effect and Synoptic snow Vertical profiles: IWC, temperature, water vapor profiles Surface: temperature, land classification, snow depth Joint active and passive computations of Z and TB Use Liu’s 2004 DDA tables for abs, scat, asymmetry, & backscatter 11 non-spherical snowflake shapes Adjust N0 to integrate Liu’s min-max DDA sizes to ensure WRF IWC is preserved

IGARSS July (1) Surface Emissivity Part 1 Urban crop land deciduous evergreen/mixed water Surface Temperature Vegetation Type Snow Depth WRF Simulations Courtesy of W.-K. Tao & team IWP (Jan UTC) IWP (Jan UTC) Lake Effect CaseSynoptic Snow Case

IGARSS July Radar Calculations W-Band (-26dBZ) Ka-Band (12dBZ)Ku-Band (18dBZ) Thresholds of Detection for Falling Snow from Satellite-borne Active and Passive Sensors by G. Skofronick-Jackson, et al., IEEE TGRS, submit 9/11 These use 3-bullet rosette snowflakes

IGARSS July Reflectivities Depend on Particle Shape W-Band Ka-Band Ku-Band

IGARSS July Reflectivities Depend on Particle Shape W-Band Ka-Band Ku-Band Ka

IGARSS July Z-Thresholds Depend on Particle Shape Average IWC Detected at Surface Assumed minimum instrument Z: Ku: 18 dBZ Ka: 12 dBZ W: -15 dBZ ±One std dev of variability over 11 shapes is plotted Snowflake Shape (#)Ku-BandKa-BandW-Band Long Hex Col. (0) Short Hex Col. (1) Block Hexag. Col. (2) Thick Hex Plate (3) Thin Hex Plate (4) Bullet Rosette (5) Bullet Rosette (6) Bullet Rosette (7) Six Bullet Rosette (8) Sector Snowflake (9) Dendrite Snow (10)

IGARSS July Radiometer Threshold Procedure Y-Axis: TBhydr – TBclearair (with perfect surface, etc knowledge) X-Axis: IWP (max of 6 kg/m 2 ) 3-Bullet Rosette Shape: Red Line = Land surfaces, Blue line = Water Surfaces 10V 183±3V 166V 89V37V 183±7V These use 3-bullet rosette snowflakes

IGARSS July Radiometer Thresholds Depend on Shape 89V 166V 166H 183±3V 183±7V 166V 22 Jan

IGARSS July Radiometer Thresholds Depend on Snow Vertical Structure and Surface Type Channel (GHz) Total Threshold Cutoff (rounded up) (in K) From 0.05 error in emissivity From 10 o C error in surface T From 10% change in Tprofile From 10% change in RHprof ± ±

IGARSS July Radiometer Thresholds Depend on Snow Vertical Structure and Surface Type Channel (GHz) Total Threshold Cutoff Average Detected IWP Lake Effect over Land Detected IWP Lake Effect over Lakes V-pol Detected IWP Lake Effect over Lakes H-pol Detected IWP Synoptic over Land Detected IWP Synoptic over Lakes V-pol Detected IWP Synoptic over Lakes H-pol na ±351.8 na1.1 na 183± na0.6 na

IGARSS July Active Versus Passive Snow Detection Thresholds of Detection for Falling Snow from Satellite-borne Active and Passive Sensors by G. Skofronick-Jackson, et al., IEEE TGRS, submit 9/11 Active Avg. Surface IWC Detected: Ku Ka W Units g m -3 Simple falling snow conversion (melted snow rate) mm hr -1 Passive over land Avg. Columnar IWP Detected: ±3 183±7Units Land V-Pol Lake Effect kg m -2 Land V-Pol Synoptic kg m -2 Simple IWC conversion (correct assumption????) Lake Effect (3 km clouds) g m -3 Synoptic (6 km clouds) g m -3 Simple falling snow conversion (melted snow rate) Lake Effect (3 km clouds) mm hr -1 Synoptic (6 km clouds) mm hr -1 Thresholds for passive could be improved with additional information

IGARSS July RGB Composite AMSU-B Emissivity Map Three Color Emissivity Map by Joe Munchak 89 GHz (red), 150 GHz (green), 183 GHz (blue) Darker colors indicate lower emissivities (more reflective) Missing data (black).

16 IWSSM March 2011 GCPEx Snowfall Campaign (Near Toronto, Canada Jan.-Feb. 2012) GV Science 1.Radiometer/DPR Snowfall measurement sensitivities to snow type, rate, surface and tropospheric characteristics 2.Physics of snowfall in the column and relation to extinction characteristics 3.Model databases for forward modeling and retrieval development. Approach: DFIR instrument clusters (account for measurement uncertainty, mitigate wind, complimentary physics) centered around X/W/Ka-KU/MRR radars and a ground-staring radiometer at CARE site. Clusters located under C-band/D3R multi-freq/dual-pol radar umbrella; D3R V-point with W and X- bands or cover clusters in scanning/RHI/spectral sampling modes. Overfly in-situ aircraft in coordination with DC-8 (APR-2 and CoSMIR radiometer); Pre and post land surface radiative measurements by Ka-Ku and radiometers. O (60 km) O (10 km) 7-8 km km Ht. King City C-band Dual-pol DFIR Clusters x Georgian Bay CARE D3R PSD: 2DVD, Parsivel, POSS,SVI Radar: Ka/Ku,X,W(2),MRR SWER: Pluvio, Hot Plate SWE/Depth L-Band +  -sensor  (Land/Snow) GHz Radiometer Aircraft: DC-8, Citation x

IGARSS July Today’s Messages (1)Falling snow retrievals are complex Challenges being addressed: non-spherical particles surface emissivity (2) Thresholds of Detection Theoretical thresholds of detection are promising Differences between active and passive detection thresholds Thresholds for passive could be improved with additional constraints (3) What matters? IWP, cloud thickness, surface underneath, snow particle shapes and PSD limits, and more (4) The GCPEx Field Campaign in 2012 will provide data to help address challenges and finalize algorithms.

IGARSS July Questions? IEEE Geoscience and Remote Sensing Society Administrative Committee (AdCom) Member Voting is open All GRSS members can vote for new AdCom members Please vote this week at the GRSS booth or online by Sept. 16, 2011