A Comparison of Passive Microwave Derive Melt Extent to Melt Intensity Estimated from Combined Optical and Thermal Satellite Signatures Over the Greenland.

Slides:



Advertisements
Similar presentations
Enhancement of Satellite-based Precipitation Estimates using the Information from the Proposed Advanced Baseline Imager (ABI) Part II: Drizzle Detection.
Advertisements

Communicating Uncertainties for Microwave-Based ESDRs Frank J. Wentz, Carl A. Mears, and Deborah K. Smith Remote Sensing Systems, Santa Rosa CA Supported.
Using CReSIS airborne RADAR to constrain ice-volume influx across the lateral margins of the Northeast Greenland Ice Stream.
Resolution Resolving power Measuring of the ability of a sensor to distinguish between signals that are spatially near or spectrally similar.
TRMM Tropical Rainfall Measurement (Mission). Why TRMM? n Tropical Rainfall Measuring Mission (TRMM) is a joint US-Japan study initiated in 1997 to study.
SEAT Traverse The Satellite Era Accumulation Traverse (SEAT) collected near-surface firn cores and Ultra High Frequency (UHF) Frequency Modulated.
David B. Reusch (New Mexico Tech) Derrick Lampkin (Penn State) David Schneider (NCAR) Funded by the Office of Polar Programs, National Science Foundation.
Modeling Digital Remote Sensing Presented by Rob Snyder.
ATS 351 Lecture 8 Satellites
Karthaus, September 2005 Wouter Greuell IMAU, Utrecht, NL -Why? -Cloud masking -Retrieval method -An application: estimate surface mass balance from satellite.
Monitoring the Arctic and Antarctic By: Amanda Kamenitz.
Surface Skin Temperatures Observed from IR and Microwave Satellite Measurements Catherine Prigent, CNRS, LERMA, Observatoire de Paris, France Filipe Aires,
Detecting SWE peak time from passive microwave data Naoki Mizukami GEOG6130 Advanced Remote Sensing.
Recent results from GRACE in Greenland and Antarctica Isabella Velicogna* and John Wahr** * ESS, University of California Irvine, Irvine CA ** Dept Of.
Temporal and Spatial Variations of Sea Surface Temperature and Chlorophyll a in Coastal Waters of North Carolina Team Members: Brittany Maybin Yao Messan.
Interannual and Regional Variability of Southern Ocean Snow on Sea Ice Thorsten Markus and Donald J. Cavalieri Goal: To investigate the regional and interannual.
Quick Review of Remote Sensing Basic Theory Paolo Antonelli CIMSS University of Wisconsin-Madison Benevento, June 2007.
POSTER TEMPLATE BY: A Comparison of Passive Microwave Derive Melt extent to Melt intensity Estimated from Combined Optical.
Satellite Imagery and Remote Sensing NC Climate Fellows June 2012 DeeDee Whitaker SW Guilford High Earth/Environmental Science & Chemistry.
The Impact of CReSIS Summer Research Programs that Influence Students’ Choice of a STEM Related Major in College By: Alica Reynolds, Jessica.
Retrieval of Snow Water Equivalent Using Passive Microwave Brightness Temperature Data By: Purushottam Raj Singh & Thian Yew Gan Dept. of Civil & Environmental.
Improving the AMSR-E snow depth product: recent developments Richard Kelly University of Waterloo, Canada.
Comparison of SSM/I Sea Ice Concentration with Kompsat-1 EOC Images of the Arctic and Antarctic Hyangsun Han and Hoonyol Lee Department of Geophysics,
Earth Observation from Satellites GEOF 334 MICROWAVE REMOTE SENSING A brief introduction.
Technical Seminar Presentation-2004 MICROWAVE REMOTE SENSING Kishore Kumar ParidaEC [1] Microwave Remote Sensing (MRS) Presented by Kishore Kumar.
Retrieving Snowpack Properties From Land Surface Microwave Emissivities Based on Artificial Neural Network Techniques Narges Shahroudi William Rossow NOAA-CREST.
Passive Microwave Remote Sensing
Connecting Sensors: SSM/I and QuikSCAT -- the Polar A Train.
Development and evaluation of Passive Microwave SWE retrieval equations for mountainous area Naoki Mizukami.
GRSS Technical Committees and Chapter Meeting IGARSS 2007 Dr. Linda Bailey Hayden
The Center for Remote Sensing of Ice Sheets (CReSIS) at OSU.
Satellite-derived Sea Surface Temperatures Corey Farley Remote Sensing May 8, 2002.
Melting trends over the Greenland ice sheet ( ) from spaceborne microwave data and regional climate models Kelsey Simmons Atmospheric Science Major.
ANALISIS OF OBSERVED GLOBAL AND REGIONAL CLIMATE CHANGE Konstantin Vinnikov Department Atmospheric and Oceanic Science College of Computer, Mathematical.
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
5. Accumulation Rate Over Antarctica The combination of the space-borne passive microwave brightness temperature dataset and the AVHRR surface temperature.
NASA Snow and Ice Products NASA Remote Sensing Training Geo Latin America and Caribbean Water Cycle capacity Building Workshop Colombia, November 28-December.
WATER VAPOR RETRIEVAL OVER CLOUD COVER AREA ON LAND Dabin Ji, Jiancheng Shi, Shenglei Zhang Institute for Remote Sensing Applications Chinese Academy of.
A New Inter-Comparison of Three Global Monthly SSM/I Precipitation Datasets Matt Sapiano, Phil Arkin and Tom Smith Earth Systems Science Interdisciplinary.
Kaiem L. Frink Lecture Series Elizabeth City State University Department of Mathematics and Computer Science Adjunct Professor/Graduate Student Major Applied.
The rise of the planet’s temperature has a very negative impact on the subsurface dynamics of Earth’s Polar Regions. Analyzing the polar subsurface is.
Cryospheric Community Contribution to Decadal Survey Compiled from correspondence (about 50 participants) WAIS Meeting Presentation.
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.
An Overview of Satellite Rainfall Estimation for Flash Flood Monitoring Timothy Love NOAA Climate Prediction Center with USAID- FEWS-NET, MFEWS, AFN Presented.
SeaWiFS Views Equatorial Pacific Waves Gene Feldman NASA Goddard Space Flight Center, Lab. For Hydrospheric Processes, This.
Malvinas Current Blooms - 23 Dec 04 Gene Feldman NASA GSFC, Laboratory for Hydrospheric Processes, SeaWiFS Project Office The.
Remote Sensing C 2013 Anand Gnanadesikan Johns Hopkins University
Dr. Linda Hayden, Box 672 Elizabeth City State University Elizabeth City, NC Cyberinfrastructure for Remote Sensing.
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.
Global Ice Coverage Claire L. Parkinson NASA Goddard Space Flight Center Presentation to the Earth Ambassador program, meeting at NASA Goddard Space Flight.
AMSR-E and WindSAT Version 7 Microwave SSTs C. Gentemann, F. Wentz, T. Meissner, & L.Riccardulli Remote Sensing Systems NASA SST ST October.
TS 15 The Great Salt Lake System ASLO 2005 Aquatic Sciences Meeting Climatology and Variability of Satellite-derived Temperature of the Great Salt Lake.
SCM x330 Ocean Discovery through Technology Area F GE.
Ice Loss Signs of Change. The Cryosphere  Earth has many frozen features including – sea, lake, and river ice; – snow cover; – glaciers, – ice caps;
The Derivation of Snow-Cover "Normals" Over the Canadian Prairies from Passive Microwave Satellite Imagery Joseph M. Piwowar Laura E. Chasmer Waterloo.
In order to accurately estimate polar air/sea fluxes, sea ice drift and then ocean circulation, global ocean models should make use of ice edge, sea ice.
AOL Confidential Sea Ice Concentration Retrievals from Variationally Retrieved Microwave Surface Emissivities Cezar Kongoli, Sid-Ahmed Boukabara, Banghua.
Passive Microwave Remote Sensing
Presented by Beth Caissie
NSIDC’s Passive Microwave Sensor Transition for Polar Data
Ice sheets and their relation to sea level
Finding Fish Using Satellites
USGS Status Frank Kelly, USGS EROS CEOS Plenary 2017 Agenda Item #4.14
Project Title Watershed Watch 2007 Elizabeth City State University
Improved Forward Models for Retrievals of Snow Properties
Watershed Watch 2007 :: Elizabeth City State University
Undergraduate Research Experience with African Nation Component
Project Title Watershed Watch 2013 Elizabeth City State University
Project Title Watershed Watch 2009 Elizabeth City State University
Presentation transcript:

A Comparison of Passive Microwave Derive Melt Extent to Melt Intensity Estimated from Combined Optical and Thermal Satellite Signatures Over the Greenland Ice Sheet from Unquiea Wade Mentor: Dr. Derrick Lampkin

The Center for Remote Sensing of Ice Sheets The Center for Remote Sensing of Ice Sheets (CReSIS) is a Science and Technology Center established by the National Science Foundation (NSF) in 2005 The mission of CReSIS is to develop new technologies and computer models to measure and predict the response of sea level change to the mass balance of ice sheets in Greenland and Antarctica. NSF’s Science and Technology Center (STC) program combines the efforts of scientists and engineers to respond to problems of global significance, supporting the intense, sustained, collaborative work that is required to achieve progress in these areas.

The earth is a system Which is effected by processes that occur Responds to these processes and changes These changes are then study and monitored

Data  Special Sensor Microwave/ Imager brightness temperature grids were downloaded from National Snow and Ice Data Center. (NDIDC)  SSMI files were collected for three different channels  Satellite Ascending/Descending: 19H.GHZ,37V.GHZ, /37V.GHZ

Brightness Temperature This distinct change is observed in the brightness temperature (Tb) signal according to the Rayleigh Jeans approximation: where Tb refers to the microwave brightness temperature at a particular wavelength (λ or frequency υ ), ε is the microwave emissivity, and Tp is the effective physical temperature of the snow (Zwally, 1977)

Melt Occurrence and Extent Retrival Techniques  Technique 1:Cross Polarization Gradient Ratio (XPGR ) [Abdalati and Steffen [1995, 1997]  Technique 2: Dirnual Ampltiude Variation (DAV) [Ramage and Isacks [2002]

XPGR Derived Melt Occurrence (Day 161, Year 2000) Blue: Melt Occurrence White: No Melt Occurrence

DAV Derived Melt Occurrence (Day 161, Year 2000) Blue: Melt Occurrence White: No Melt Occurrence

Melt Magnitude Retrieval Liquid Water Fraction

Results

Results Contd..

Results Contd…

Conclusions  Results indicate that DAV show a much more proportional relationship to melt magnitude than XPGR consistently during the analysis period. Both techniques show a scaled increase in melt occurrence with melt magnitude from the early part of the melt season (Day 145- May 25) than later in the melt season (Day 193-July 12).  Difference in the comparison of XPGR and DAV to E-melt may be due to the ability of DAV to track more night time persistent melt, producing higher occurrences of melt. E- melt values derived from surface reflectance and temperature may be sensitive the diurnal effects as well resulting in a stronger relationship to DAV than XPGR. Further work is necessary to explain these trends.

Questions

Acknowledgements  Center for Remote Sensing of Ice Sheets  Center of Excellence in Remote Sensing Education and Research  College of Earth and Mineral Sciences  Peter Burkett  Dr. Derrick Lampkin  Dr. Linda Hayden