Magdalena D. Anguelova Michael H. Bettenhausen William F. Johnston* Peter W. Gaiser Novel Applications of Remote Sensing for Improved Quantification of.

Slides:



Advertisements
Similar presentations
Radar/lidar observations of boundary layer clouds
Advertisements

Whitecaps, sea-salt aerosols, and climate Magdalena D. Anguelova Physical Oceanography Dissertation Symposium College of Marine Studies, University of.
Sea salt aerosols: Their generation and role in the climate system Ph. D. Dissertation Proposal Magdalena D. Anguelova November 12, 1999 College of Marine.
Upgrades to the MODIS near-IR Water Vapor Algorithm and Cirrus Reflectance Algorithm For Collection 6 Bo-Cai Gao & Rong-Rong Li Remote Sensing Division,
A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.
(Mt/Ag/EnSc/EnSt 404/504 - Global Change) Climate Models (from IPCC WG-I, Chapter 8) Climate Models Primary Source: IPCC WG-I Chapter 8 - Climate Models.
Allison Parker Remote Sensing of the Oceans and Atmosphere.
3D Radiative Transfer in Cloudy Atmospheres: Diffusion Approximation and Monte Carlo Simulation for Thermal Emission K. N. Liou, Y. Chen, and Y. Gu Department.
Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.
TRMM Tropical Rainfall Measurement (Mission). Why TRMM? n Tropical Rainfall Measuring Mission (TRMM) is a joint US-Japan study initiated in 1997 to study.
Complex dielectric constant of sea foam for microwave remote sensing Magdalena D. Anguelova Peter W. Gaiser Naval Research Laboratory, Washington, DC 15th.
NRL09/21/2004_Davis.1 GOES-R HES-CW Atmospheric Correction Curtiss O. Davis Code 7203 Naval Research Laboratory Washington, DC 20375
Aerosol radiative effects from satellites Gareth Thomas Nicky Chalmers, Caroline Poulsen, Ellie Highwood, Don Grainger Gareth Thomas - NCEO/CEOI-ST Joint.
The Radiative Budget of an Atmospheric Column in Tropical Western Pacific Zheng Liu Department of Atmospheric Science University of Washington.
ATS 351 Lecture 8 Satellites
Using Scatterometers and Radiometers to Estimate Ocean Wind Speeds and Latent Heat Flux Presented by: Brad Matichak April 30, 2008 Based on an article.
Millimeter and sub-millimeter observations for Earth cloud hunting Catherine Prigent, LERMA, Observatoire de Paris.
Radiative Properties of Clouds ENVI3410 : Lecture 9 Ken Carslaw Lecture 3 of a series of 5 on clouds and climate Properties and distribution of clouds.
The Radiative Budget of an Atmospheric Column in Tropical Western Pacific Zheng Liu 1 Thomas Ackerman 1,2, Sally McFarlane 2, Jim Mather 2, University.
Single Column Experiments with a Microwave Radiative Transfer Model Henning Wilker, Meteorological Institute of the University of Bonn (MIUB) Gisela Seuffert,
Magdalena D. Anguelova, Ferris Webster, Peter Gaiser 12 May, 2004 Effects of Environmental Variables in Sea Spray Generation Function via Whitecap Coverage.
Graduate Course: Advanced Remote Sensing Data Analysis and Application SURFACE HEAT BUDGETS IN THE PACIFIC WARM POOL DURING TOGA COARE Shu-Hsien Chou Dept.
Magdalena D. Anguelova, Justin P. Bobak, William E. Asher, David J. Dowgiallo, Ben I. Moat, Robin W. Pascal, Margaret J. Yelland 16th Conference on Air-Sea.
CALWATER2 Field Study of Air-Sea Interaction and AR dynamics in Midlatitude Pacific Storms Ship (NOAA Brown) Ship Field Duration – 30 days Time Window.
Applications and Limitations of Satellite Data Professor Ming-Dah Chou January 3, 2005 Department of Atmospheric Sciences National Taiwan University.
Retrieving Snowpack Properties From Land Surface Microwave Emissivities Based on Artificial Neural Network Techniques Narges Shahroudi William Rossow NOAA-CREST.
Passive Microwave Remote Sensing
William Crosson, Ashutosh Limaye, Charles Laymon National Space Science and Technology Center Huntsville, Alabama, USA Soil Moisture Retrievals Using C-
Introduction Invisible clouds in this study mean super-thin clouds which cannot be detected by MODIS but are classified as clouds by CALIPSO. These sub-visual.
AGU 2002 Fall Meeting NASA Langley Research Center / Atmospheric Sciences Validation of GOES-8 Derived Cloud Properties Over the Southeastern Pacific J.
Generation of Sea-Salt Aerosols Magdalena Anguelova Bridging the Gap October , 1999.
CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements Vijay Natraj, Damien Lafont, John Worden, Annmarie Eldering Jet Propulsion.
Dependence of SMOS/MIRAS brightness temperatures on wind speed and foam model Xiaobin Yin, Jacqueline Boutin LOCEAN & ARGANS.
Magdalena D. Anguelova, Justin P. Bobak, William E. Asher, David J. Dowgiallo, Ben I. Moat, Robin W. Pascal, Margaret J. Yelland 16th Conference on Air-Sea.
Oceanic Whitecaps: Good or Bad? Magdalena Anguelova Bridging the Gap October , 2000.
Optimization of L-band sea surface emissivity models deduced from SMOS data X. Yin (1), J. Boutin (1), N. Martin (1), P. Spurgeon (2) (1) LOCEAN, Paris,
Introduction Martin et al. JGR, 2014 CAROLS airborne Tbs indicate slightly lower wind influence than predicted by model 1 at high WS In model 1 previous.
Whitecaps, sea-salt aerosols, and climate Magdalena D. Anguelova Oceans and Ice Branch Seminar College of Marine Studies University of Delaware18 October,
GE0-CAPE Workshop University of North Carolina-Chapel Hill August 2008 Aerosols: What is measurable and by what remote sensing technique? Omar Torres.
Representation of Sea Salt Aerosol in CAM coupled with a Sectional Aerosol Microphysical Model CARMA Tianyi Fan, Owen Brian Toon LASP/ATOC, University.
Synthesis NOAA Webinar Chris Fairall Yuqing Wang Simon de Szoeke X.P. Xie "Evaluation and Improvement of Climate GCM Air-Sea Interaction Physics: An EPIC/VOCALS.
Optical properties Satellite observation ? T,H 2 O… From dust microphysical properties to dust hyperspectral infrared remote sensing Clémence Pierangelo.
USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH Joel Susskind University of Maryland May 12, 2005.
Testing LW fingerprinting with simulated spectra using MERRA Seiji Kato 1, Fred G. Rose 2, Xu Liu 1, Martin Mlynczak 1, and Bruce A. Wielicki 1 1 NASA.
Trends & Variability of Liquid Water Clouds from Eighteen Years of Microwave Satellite Data: Initial Results 6 July 2006 Chris O’Dell & Ralf Bennartz University.
Robert Wood, Atmospheric Sciences, University of Washington The importance of precipitation in marine boundary layer cloud.
The use of satellite data in marine aerosol studies: future perspectives, challenges, development needs Gerrit de Leeuw Finnish Meteorological Institute.
Clouds & Radiation: Climate data vs. model results A tribute to ISCCP Ehrhard Raschke, University of Hamburg Stefan Kinne, MPI-Meteorology Hamburg 25 years.
Graduate Course: Advanced Remote Sensing Data Analysis and Application RETRIEVAL OF SURFACE AIR HUMIDITY FROM SSM/I Shu-Hsien Chou Dept. of Atmospheric.
Remote Sensing Division Naval Research Lab, Washington, DC Separating Whitecap Fraction of Active Wave Breaking From Satellite Estimates of Total.
An evaluation of a hybrid satellite and NWP- based turbulent fluxes with TAO buoys ChuanLi Jiang, Kathryn A. Kelly, and LuAnne Thompson University of Washington.
ISCCP SO FAR (at 30) GOALS ►Facilitate "climate" research ►Determine cloud effects on radiation exchanges ►Determine cloud role in global water cycle ▬
Daily observation of dust aerosols infrared optical depth and altitude from IASI and AIRS and comparison with other satellite instruments Christoforos.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
AEROCOM AODs are systematically smaller than MODIS, with slightly larger/smaller differences in winter/summer. Aerosol optical properties are difficult.
A step toward operational use of AMSR-E horizontal polarized radiance in JMA global data assimilation system Masahiro Kazumori Numerical Prediction Division.
Infrared and Microwave Remote Sensing of Sea Surface Temperature Gary A. Wick NOAA Environmental Technology Laboratory January 14, 2004.
CLAWATER2 Ship-based Field Study of Air-Sea Interaction in Midlatitude Pacific Storms One ships (Brown? Or UNOLS Class I) Aircraft (NOAA P-3, NASA Global.
Magdalena D. Anguelova Michael H. Bettenhausen Michael H. Bettenhausen William F. Johnston William F. Johnston Peter W. Gaiser Peter W. Gaiser Oceanic.
November 28, 2006 Representation of Skin Layer and Diurnal Warming Effects Gary Wick 1 and Sandra Castro 2 1 NOAA Earth System Research Laboratory 2 CCAR,
Evaluation of Satellite-Derived Air-Sea Flux Products Using Dropsonde Data Gary A. Wick 1 and Darren L. Jackson 2 1 NOAA ESRL, Physical Sciences Division.
Radiometric Measurements of Whitecaps and Surface Fluxes Magdalena D. Anguelova Remote Sensing Division Naval Research Laboratory Washington, DC, USA In.
Mayurakshi Dutta Department of Atmospheric Sciences March 20, 2003
Magdalena D. Anguelova Michael H. Bettenhausen Michael H. Bettenhausen William F. Johnston William F. Johnston Peter W. Gaiser Peter W. Gaiser Whitecap.
Passive Microwave Remote Sensing
Whitecaps, sea-salt aerosols, and climate
What are the causes of GCM biases in cloud, aerosol, and radiative properties over the Southern Ocean? How can the representation of different processes.
Microwave Emissivity of a Vertically Inhomogeneous Sea-Foam Layer: Application to the WindSat Retrieval Algorithm Magdalena D. Anguelova, Karen St.
FOAM EMISSIVITY MODELS FOR MICROWAVE OBSERVATIONS OF OCEANS FROM SPACE
Why do satellite-based estimates of whitecap fraction depend on
Presentation transcript:

Magdalena D. Anguelova Michael H. Bettenhausen William F. Johnston* Peter W. Gaiser Novel Applications of Remote Sensing for Improved Quantification of Sea Spray Source Function Remote Sensing Division, Naval Research Laboratory, Washington, DC * Computational Physics, Inc., Springfield, VA

Motivation  Sea spray aerosols  Direct effect – cooling  Indirect effect  Dominate the activation of CCN  Compete with SO 4 2- aerosols  Halogen chemistry  Reactive Cl and Br  Tropospheric O 3  Sink of S  Sea spray droplets  Heat exchange  Tropical storm intensification  Whitecaps  Gas exchange  Ocean albedo & roughness  Geophysical retrievals  Surface wind  Ocean color  Salinity Photo courtesy of C. Fairall 6 Dec, 20112Whitecaps and sea spray, Anguelova et al., NRL

Sea spray source function Rate of production of sea spray per unit area per increment of droplet radius, r (s -1 m -2  m -1 ). )f() rU   dr bardF,...,, From photographic measurements (Monahan and O’Muircheartaigh, 1980) From measurements using various methods )()(fUUWU    log f )(f rd r d r  6 Dec, 20113Whitecaps and sea spray, Anguelova et al., NRL Size distributionScaling factor ShapeMagnitude

Possible improvements  For the size distribution f(r)  Extend the size range, large and small ends  Recognize and include the effect of organics  Introduce ambient factors  For the scaling factor f(U)  Less uncertainty in measuring W  Introduce ambient factors  Remote sensing: method, results, implications de Leeuw et al. O’Dowd et al. Keene et al. Quinn & Bates et al. Meskhidze & Peters et al. μm25μm1 80  r μm250μm  r...),,(f )( f bar r ,,()( baUWU W  6 Dec, 20114Whitecaps and sea spray, Anguelova et al., NRL (de Leeuw et al., 2011) Ernie Lewis poster Sofiev et al., 2011

Objective  Measure W globally  Compile database  Model the high variability of whitecap fraction U – wind speed (U 10 or u * )  T – atmospheric stability (= T air – T sea ) X – wind fetch d – wind duration U cur – water currents T s – sea surface temperature S – salinity C k – concentration, type (k) of surface active materials  CSTUdXTUW scur,,,,,,,    UW 6 Dec, 20115Whitecaps and sea spray, Anguelova et al., NRL

Whitecaps signature High Reflectivity High Emissivity Reflectivity Emissivity Vis IRmW 6 Dec, 20116Whitecaps and sea spray, Anguelova et al., NRL

Remote sensing of sea foam  Microwave region  Advantages  Transparent (almost) atmosphere  “...4% problem...at 5 GHz,..., 90% problem at IR” (Swift, 1990)  Tractable atmospheric correction  Clouds penetration  Drawback  Low resolution  Smoother geophysical variability  Trade-off: global coverage  More data  Various conditions   sB fr T e T eWeWe   1 6 Dec, 20117Whitecaps and sea spray, Anguelova et al., NRL

Models  Rough sea surface model  2-scale  Wave spectrum  Durden/Vesecky/Yueh  Tuned for roughness only  Using WindSat code (v )  Foam emissivity model  RT model  Layer with vertically non-uniform properties  Distribution of thicknesses © P.R.Hemington z = 0 z = -d Air, ε 0 =1 Water, ε Foam, ε (z) Courtesy of Prof. Cilliers   fr eWeWe  1 6 Dec, 20118Whitecaps and sea spray, Anguelova et al., NRL Anguelova and Webster, 2006 Anguelova et al., 2006

Data  Independent sources  T B from WindSat  V, L from SSM/I or TMI  U 10 and  from QuikSCAT or GDAS  T s from GDAS  S = 34 psu  Trade-off:  Sampling issues  Use long-term data Sample count 6 Dec, 20119Whitecaps and sea spray, Anguelova et al., NRL

Estimates of W  Improvements over the feasibility study (Anguelova and Webster, 2006) :  More physical models  Independence of the variables 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Compare to photographic data 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Further development  Models  Higher resolution  Improved wave spectrum in 2-scale model  Comparisons/Validation  More points for direct comparisons  Indirect comparisons in terms of other variables  CO2 fluxes from ship cruises o and COARE CO2 parameterization  AOD from AERONET o and AOD from microphysical aerosol model  Uncertainty characterization  Currently uncertainty minimization  Evaluate the remaining using global geophysical model 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Whitecaps data base  All available orbits for  Resolution 50×70 km 2  Time period  Entire 2006  Months of 2003, 2007 and 2008  Gridded data  With 0.5  x 0.5  grid box  Any other N  x N  possible  Time periods:  Daily  Monthly  Weekly (7 days)  3-days 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Geographic characteristics of W March,  x 0.5  Wind speed formula Satellite, 10.7 GHz, H pol. 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Geographic characteristics of W March,  x 0.5  Wind speed formula 18.7 Satellite, 18.7 GHz, H pol. 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Develop parameterization(s)  Relative importance of the variables  Correlation analysis  CSTUdXTUW scur,,,,,,,    UW 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL Fetch SST Stability Wave height Wave period Wind

New sea spray source function  Include wave-field characteristics and one more factor  Improve/choose size distribution  Include organics    ss s THUW HUW,,, 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL )f() rU   dr bardF,...,, Size distributionScaling factor ShapeMagnitude

Sea-salt flux  Solar irradiance at TOA (W/m 2 ) : GCM – ERBE  NO aerosols;  Max difference over the oceans. 2         10 5 Number flux, dF (s -1 m -2 ) Annual sea-salt flux (1998) 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL Haywood et al., Science, 1999 Anguelova and Webster, 2006

Sea foam definition  Oceanographic definition  Whitecaps on the surface  Bubble plumes below  Passive remote sensing  Radiometers detect only the surface foam layers  Skin depth  At microwave frequencies  a few mm to a few cm 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL

Photographic measurements  High uncertainty: up to 30% or more  Intensity threshold  A and B stages under oblique angle  Patchy coverage  Open ocean  Southern ocean! 6 Dec, 2011Whitecaps and sea spray, Anguelova et al., NRL20 Stramska and Petelski, 2003

Improvements and restrictions 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL (de Leeuw et al., 2011) Whitecap fraction, W (%)

Modeling whitecap fraction 6 Dec, Whitecaps and sea spray, Anguelova et al., NRL