The study of cloud and aerosol properties during CalNex using newly developed spectral methods Patrick J. McBride, Samuel LeBlanc, K. Sebastian Schmidt,

Slides:



Advertisements
Similar presentations
Proposed new uses for the Ceilometer Network
Advertisements

UPRM Lidar lab for atmospheric research 1- Cross validation of solar radiation using remote sensing equipment & GOES Lidar and Ceilometer validation.
Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.
3D Radiative Transfer in Cloudy Atmospheres: Diffusion Approximation and Monte Carlo Simulation for Thermal Emission K. N. Liou, Y. Chen, and Y. Gu Department.
Proposed participation of the MODIS Aerosol team and Si-Chee in the Dry/wet AMC + SMOCC campaign in Amazonia August-November 2002 (There are question marks.
May 10, 2004Aeronet workshop Can AERONET help with monitoring clouds? Alexander Marshak NASA/GSFC Thanks to: Y. Knyazikhin, K. Evans, W. Wiscombe, I. Slutsker.
Constraining aerosol sources using MODIS backscattered radiances Easan Drury - G2
A 21 F A 21 F Parameterization of Aerosol and Cirrus Cloud Effects on Reflected Sunlight Spectra Measured From Space: Application of the.
1 Cloud Droplet Size Retrievals from AERONET Cloud Mode Observations Christine Chiu Stefani Huang, Alexander Marshak, Tamas Várnai, Brent Holben, Warren.
TReSS (Transportable Remote Sensing Station) in Tamanrasset Overview of TReSS Status of implementation on April 1 st 2006 Operations in the framework of.
Overview The path to Skywatch Video tour of the facility Brief rooftop instrument overview Description of real-time and.
ESTEC July 2000 Estimation of Aerosol Properties from CHRIS-PROBA Data Jeff Settle Environmental Systems Science Centre University of Reading.
METO 621 Lesson 27. Albedo 200 – 400 nm Solar Backscatter Ultraviolet (SBUV) The previous slide shows the albedo of the earth viewed from the nadir.
Profiling Clouds with Satellite Imager Data and Potential Applications William L. Smith Jr. 1, Douglas A. Spangenberg 2, Cecilia Fleeger 2, Patrick Minnis.
Direct Radiative Effect of aerosols over clouds and clear skies determined using CALIPSO and the A-Train Robert Wood with Duli Chand, Tad Anderson, Bob.
Direct aerosol radiative forcing based on combined A-Train observations – challenges in deriving all-sky estimates Jens Redemann, Y. Shinozuka, M.Kacenelenbogen,
MAGIC hyperspectral observations for studying cloud properties A.Marshak (NASA GSFC), P. McBride (GESTAR/ASTRA), C. Chiu (University of Reading) W. Wiscombe.
EARLINET and Satellites: Partners for Aerosol Observations Matthias Wiegner Universität München Meteorologisches Institut (Satellites: spaceborne passive.
Characterization of Arctic Mixed-Phase Cloudy Boundary Layers with the Adiabatic Assumption Paquita Zuidema*, Janet Intrieri, Sergey Matrosov, Matthew.
Determination of the optical thickness and effective radius from reflected solar radiation measurements David Painemal MPO531.
Page 1© Crown copyright 2004 Cirrus Measurements during the EAQUATE Campaign C. Lee, A.J. Baran, P.N. Francis, M.D. Glew, S.M. Newman and J.P. Taylor.
Chemical and Aerosol Data Assimilation Activities during CalNex R. Bradley Pierce NOAA/NESDIS/STAR Allen Lenzen 1, Todd Schaack 1, Tom Ryerson 2, John.
AO: Areas solicited for contribution Validation using other satellite, airborne, or ground- based experiments providing independent measurements of wind.
Trace gas and AOD retrievals from a newly deployed hyper-spectral airborne sun/sky photometer (4STAR) M. Segal-Rosenheimer, C.J. Flynn, J. Redemann, B.
Aerosol Optical Depths from Airborne Sunphotometry in INTEX-B/MILAGRO as a Validation Tool for the Ozone Monitoring Instrument (OMI) on Aura J. Livingston.
Linking the Radiative Energy Budget and Remote Sensing of Complex Cloud and Aerosol Fields S. Song, K. S. Schmidt, P. Pilewskie (University of Colorado)
AGU 2002 Fall Meeting NASA Langley Research Center / Atmospheric Sciences Validation of GOES-8 Derived Cloud Properties Over the Southeastern Pacific J.
The combined use of MODIS, CALIPSO and OMI level 2 aerosol products for calculating direct aerosol radiative effects Jens Redemann, M. Vaughan, Y. Shinozuka,
GSFC. Glaciation Level and Vertical Profile of Droplet Size Associated with Cloud-Aerosol Interactions (D. Rosenfeld) Clean Polluted.
Studies of Emissions & Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS) Brian Toon Department of Atmospheric and Oceanic.
4STAR: Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research Development and Results from First Test-flights A collaboration involving: PNNL:
ARM Data Overview Chuck Long Jim Mather Tom Ackerman.
Jetstream 31 (J31) at Mid-Campaign in INTEX-B/MILAGRO: Science Goals, Payload, Example Results, Assessment Phil Russell, Jens Redemann, Brian Cairns, Charles.
Aerosol-Cloud Interactions and Radiative Forcing: Modeling and Observations Graham Feingold 1, K. S. Schmidt 2, H. Jiang 3, P. Zuidema 4, H. Xue 5, P.
LASE Measurements During IHOP Edward V. Browell, Syed Ismail, Richard A. Ferrare, Susan A Kooi, Anthony Notari, and Carolyn F. Butler NASA Langley Research.
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,
4STAR: Spectrometer for Sky-Scanning, Sun- Tracking Atmospheric Research Results from Test-flight Series PNNLNASA AmesNASA GSFC B. SchmidS. DunaganS. Sinyuk.
Redemann, ICARTT workshop, Durham, NH, Aug.9-12, 2005 Airborne measurements of spectral direct aerosol radiative forcing - a new aerosol gradient method.
INFRARED-DERIVED ATMOSPHERIC PROPERTY VALIDATION W. Feltz, T. Schmit, J. Nelson, S. Wetzel-Seeman, J. Mecikalski and J. Hawkinson 3 rd Annual MURI Workshop.
Summary of ARCTAS P-3 Data Flight #21 Flown 7 Jul 2008 Phil Russell, NASA Ames with contributions from many, many experimenters, modelers, forecasters,
For INTEX-B/MILAGRO the J31 was equipped to measure solar energy and how that energy is affected by atmospheric constituents and Earth's surfaces. Because.
Retrieval of Cloud Phase and Ice Crystal Habit From Satellite Data Sally McFarlane, Roger Marchand*, and Thomas Ackerman Pacific Northwest National Laboratory.
SATELLITE REMOTE SENSING OF TERRESTRIAL CLOUDS Alexander A. Kokhanovsky Institute of Remote Sensing, Bremen University P. O. Box Bremen, Germany.
ACKNOWLEDGEMENTS: Rob Albee, Jim Wendell, Stan Unander, NOAA Climate Forcing program, DOE ARM program, NASA, Met. Service Canada, Chinese Met. Agency,
Vertically resolved aerosol optical properties over the ARM SGP site B. Schmid, H. Jonsson, A. Strawa, B. Provencal, K. Ricci, D. Covert, R. Elleman, W.
4STAR Instrument Technology Development Dunagan, 1/13 4STAR: Spectrometer for Sky-Scanning, Sun- Tracking Atmospheric Research Instrument Design, Development.
Developement of exact radiative transfer methods Andreas Macke, Lüder von Bremen, Mario Schewski Institut für Meereskunde, Uni Kiel.
Jetstream 31 (J31) in INTEX-B/MILAGRO. Campaign Context: In March 2006, INTEX-B/MILAGRO studied pollution from Mexico City and regional biomass burning,
Within dr, L changes (dL) from… sources due to scattering & emission losses due to scattering & absorption Spectral Radiance, L(, ,  ) - W m -2 sr -1.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
Aerosol optical properties measured from aircraft, satellites and the ground during ARCTAS - their relationship to aerosol chemistry and smoke type Yohei.
Airborne Sunphotometry and Closure Studies during the SAFARI-2000 Dry Season Campaign B. Schmid BAER/NASA Ames Research Center, Moffett Field, CA, USA.
Airborne Sunphotometry and Closure Studies in the SAFARI-2000 Dry Season Campaign B. Schmid 1, P.B. Russell 2, P.Pilewskie 2, J. Redemann 1, P.V. Hobbs.
ACE - Aerosol Working Group Science Traceability Matrix Category 1: Aerosols, Clouds and Climate Category 2: Aerosols, Clouds and Precipitation.
UCLA Vector Radiative Transfer Models for Application to Satellite Data Assimilation K. N. Liou, S. C. Ou, Y. Takano and Q. Yue Department of Atmospheric.
Jetstream-31 (J31) in ITCT-INTEX (Intercontinental Transport and Chemical Transformation- Intercontinental Chemical Transport Experiment) J31 GOALS in.
The Use of Spectral and Angular Information In Remote Sensing
UNIVERSITY OF BASILICATA CNR-IMAA (Consiglio Nazionale delle Ricerche Istituto di Metodologie per l’Analisi Ambientale) Tito Scalo (PZ) Analysis and interpretation.
Measurements and modeling of water vapor from solar spectral irradiance during ATTREX Bruce Kindel, Peter Pilewskie, Sebastian Schmidt, Troy Thornberry,
J. Redemann 1, B. Schmid 1, J.A. Eilers 2, R. Kahn 3, R.C. Levy 4,5, P.B. Russell 2, J.M. Livingston 6, P.V. Hobbs 7, W.L. Smith Jr. 8, B.N. Holben 4 1.
Studying the radiative environment of individual biomass burning fire plumes using multi-platform observations: an example ARCTAS case study on June 30,
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.
Motivation: Help satellite studies of aerosol-cloud interactions Aerosol remote sensing near clouds is challenging Excluding areas near-cloud risks biases.
Remote sensing of snow in visible and near-infrared wavelengths
Vertically resolved CALIPSO-CloudSat aerosol extinction coefficient in the marine boundary layer and its co-variability with MODIS cloud retrievals David.
Near UV aerosol products
An overview of J-31 measurements during the INTEX-B/MILAGRO campaign
Robert Wood, Duli Chand, Tad Anderson University of Washington
Robert Wood, Duli Chand, Tad Anderson University of Washington
Robert Wood, Duli Chand, Tad Anderson University of Washington
Presentation transcript:

The study of cloud and aerosol properties during CalNex using newly developed spectral methods Patrick J. McBride, Samuel LeBlanc, K. Sebastian Schmidt, Peter Pilewskie University of Colorado, ATOC/LASP Warren Gore, Jens Redemann, Philip B. Russell NASA Ames, CA Chris Fairall, Dan Wolfe, Sara Lance NOAA/ESRL, Boulder, CO Patrick Minnis, Kristopher M. Bedka, Chris Hostetler, Rich Ferrare NASA Langley, Hampton, VA CalNex data workshop, Sacramento, CA

P3 Instrumentation Solar Spectral Flux Radiometer Zenith and nadir viewing spectral irradiance at 411 wavelengths Sampling frequency of 1 Hz Spectral range: nm In-situ Cloud microphysics Aerosol optical properties NOAA P3 SSFR

Atlantis Instrumentation clouds “clear” SSFR Zenith viewing irradiance and radiance reported at 313 wavelengths Sampling frequency of 1 Hz Spectral range: nm Microwave radiometer (MWR) Retrieves column integrated liquid water and water vapor Cloud Radar Provides profiles of backscatter from cloud NOAA R/V Atlantis

Other data sources GOES NASA King Air Geostationary Operational Environmental Satellites (GOES) Provides cloud optical thickness and effective radius over 4 km. High Spectral Resolution Lidar (HSRL) Profiles aerosol extinction coefficients at 532 nm

τ, r eff, LWP Cloud remote sensing Satellite validation Can derive radiative forcing NOAA P3 GOES NOAA R/V Atlantis Atlantis cloud retrievals Cloud property ( τ, r eff, LWP) retrievals performed for the first time on the SSFR and derived from transmitted spectral radiance. Near real-time cloud retrieval. (See McBride et al., A spectral method for retrieving cloud optical thickness and effective radius from surface-based transmittance measurements, ACPD, 2011a.

MODIS cloud image

Microwave radiometer comparison Broken cloud McBride et al. 2011b, In preparation

Comparing multiple platforms McBride et al. 2011b, In preparation GEOS-NESDIS data provided by Andy Heidinger and Andi Walther

Atlantis LWP statistical comparison Histogram for all times where LWP > 30 gm -2 (1 minute averages) Histogram filtered for overcast cases Factors still to be explored: Cloud inhomogeneities Cloud phase Number of cloud layers Precipitation Polluted cloud Still to do: Statistical analysis with GOES cloud properties

Collaborative cloud observations Overcast cases Broken cloud cases

Aerosol remote sensing g, ϖ, τ NOAA R/V Atlantis NOAA P3 NASA King Air

Aerosol optical property retrievals 19 May 2010 In situ Cavity Ring Down (CRD) Retrieved aerosol properties for this aerosol layer HSRL 30 min. between HSRL and CRD data CRD data provided by Justin Langridge, NOAA

Aerosol retrieval results Optical depth Surface Albedo Asymmetry parameter Single Scattering Albedo LeBlanc et al. 2011, In preparation Relative forcing efficiency = Inputs to the retrieval: SSFR irradiance Aeronet Angstrom parameter HSRL extinction

Relative forcing efficiency comparison Relative forcing efficiency Spectral shape of relative forcing efficiency comparable to within 15% of previous results LeBlanc et al. 2011, In preparation

Capabilities  Ability to retrieve cloud properties ( τ, r eff, LWP) from transmitted spectral radiance  Studying cloud optical properties from above and below using statistical methods  Aerosol optical property retrieval (g, ϖ, τ) without simultaneous optical thickness observation  Relative forcing efficiency is within 15% of previous experiments

Future work  Statistical comparison of different viewing geometries Using in-situ observations, cloud radar, microwave radiometer, satellite data  Aerosol-cloud interaction study  Ship-based aerosol property retrievals  Simultaneous retrieval of aerosol and cloud properties under overcast and broken cloud fields

SSFR data information NOAA P3 30 flights 151 hours of data collected Over 543,000 spectral collected Spectra reported at 411 wavelengths over the range 350 to 2150 nm Data archive location R/V Atlantis 273 hours of data collected Over 983,000 spectra collected Spectra reported at 313 wavelengths over the range 350 to 1700 nm Data archive location ftp://laspftp.colorado.edu/pub/schmidt/calnex/atlantis/