Status of requirements definition for the ACE multiangle, multispectral, polarimetric imager David J. Diner ACE workshop Salt Lake City, UT 6-7 November.

Slides:

Advertisements

Similar presentations

 nm)  nm) PurposeSpatial Resolution (km) Ozone, SO 2, UV8 3251Ozone8 3403Aerosols, UV, and Volcanic Ash8 3883Aerosols, Clouds, UV and Volcanic.

Advertisements

CHRIS (Compact High Resolution Imaging Spectrometer) sira group sira electro-optics Dr Mike Cutter EO & Technology Business Manager.

Polarization measurements for CLARREO

AMwww.Remote-Sensing.info Ch.2 Remote Sensing Data Collection

Preliminary management plan for PACE SDT What are the Goals of PACE? The goals of the PACE mission are: 1-Extend key climate data records on ocean color.

PACE SDT Polarimeter Characteristic Discussion Hal Maring, NASA Headquarters Steve Platnick, NASA GSFC PACE SDT Meeting November 2011.

TRMM Tropical Rainfall Measurement (Mission). Why TRMM? n Tropical Rainfall Measuring Mission (TRMM) is a joint US-Japan study initiated in 1997 to study.

Multispectral Remote Sensing Systems

Remote sensing in meteorology

Quantifying aerosol direct radiative effect with MISR observations Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory California Institute of Technology,

A 21 F A 21 F Parameterization of Aerosol and Cirrus Cloud Effects on Reflected Sunlight Spectra Measured From Space: Application of the.

Polarization Surface-State Retrieval in the Presence of Atmospheric Perturbations Mentor: Dr. Carol Bruegge (JPL) By: Victor Chu.

64 or 128 Columns 2°2° 2.5° Depiction of Multi-scale Modeling Framework (MMF) A Cloud Resolving Model with an Adaptive Vertical Grid Roger Marchand and.

ESTEC July 2000 Estimation of Aerosol Properties from CHRIS-PROBA Data Jeff Settle Environmental Systems Science Centre University of Reading.

Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute.

An Introduction to Using Angular Information in Aerosol Remote Sensing Richard Kleidman SSAI/NASA Goddard Lorraine Remer UMBC / JCET Robert C. Levy NASA.

Fundamentals of Satellite Remote Sensing NASA ARSET- AQ Introduction to Remote Sensing and Air Quality Applications Winter 2014 Webinar Series ARSET -

PACE AEROSOL CAL/VAL Cameron McNaughton Golder Associates Ltd.

Km’s; hours to weeks 100-km; years 1000-km, decades Two-Way Interactions Global ocean and climate dynamics strongly influence processes at local scales.

EARLINET and Satellites: Partners for Aerosol Observations Matthias Wiegner Universität München Meteorologisches Institut (Satellites: spaceborne passive.

1 Remote Sensing and Image Processing: 7 Dr. Mathias (Mat) Disney UCL Geography Office: 301, 3rd Floor, Chandler House Tel: (x24290)

Stereoscopic cloud imaging for future 3-D wind constellation Dong L. Wu Climate and Radiation Laboratory (613) NASA Goddard Space Flight Center Working.

MT Workshop October 2005 JUNE 2004 DECEMBER 2004 End of OCTOBER 2005 ? MAY 2002 ? Capabilities of multi-angle polarization cloud measurements from.

DOCUMENT OVERVIEW Title: Fully Polarimetric Airborne SAR and ERS SAR Observations of Snow: Implications For Selection of ENVISAT ASAR Modes Journal: International.

Orbit Characteristics and View Angle Effects on the Global Cloud Field

Earth Observation Science Recent and potential scientific achievements of the (A)ATSR Series - and some possibilities for synergy with MERIS David Llewellyn-Jones.

Remote Sensing and Image Processing: 7 Dr. Hassan J. Eghbali.

OpenDAP Server-side Functions for Multi-Instrument Aggregation ESIP Session: Advancing the Power and Utility of Server-side Aggregation Jon C. Currey (NASA),

Rutherford Appleton Laboratory Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: FP, 25 April 2014, ESTEC.

1 Applications of Remote Sensing: SeaWiFS and MODIS Ocean Color Outline  Physical principles behind the remote sensing of ocean color parameters  Satellite.

Maria Val Martin and J. Logan (Harvard Univ., USA) D. Nelson, C. Ichoku, R. Kahn and D. Diner (NASA, USA) S. Freitas (INPE, Brazil) F.-Y. Leung (Washington.

GSFC. Glaciation Level and Vertical Profile of Droplet Size Associated with Cloud-Aerosol Interactions (D. Rosenfeld) Clean Polluted.

Wildfire Plume Injection Heights Over North America: An Analysis of MISR Observations Maria Val Martin and Jennifer A. Logan (Harvard Univ., USA) Fok-Yan.

Aerosol-Cloud Ocean Biology Mission (ACOB)

NASA GISS 21-Nov-15 Carbonaceous Aerosol Workshop Page 1 How can satellites help define the history of carbonaceous aerosols in the industrial era. Acknowledgements:

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,

NASA ESTO ATIP Laser Sounder for Remotely Measuring Atmospheric CO 2 Concentrations 12/12/01 NASA Goddard - Laser Remote Sensing Branch 1 James B. Abshire,

2009 CLARREO Meeting at LaRC 1 Information content of satellite remote-sensing measurements: photopolarimetric vs intensity-only.

As components of the GOES-R ABI Air Quality products, a multi-channel algorithm similar to MODIS/VIIRS for NOAA’s next generation geostationary satellite.

Synergy of MODIS Deep Blue and Operational Aerosol Products with MISR and SeaWiFS N. Christina Hsu and S.-C. Tsay, M. D. King, M.-J. Jeong NASA Goddard.

Use of Solar Reflectance Hyperspectral Data for Cloud Base Retrieval Andrew Heidinger, NOAA/NESDIS/ORA Washington D.C, USA Outline " Physical basis for.

Studies of Advanced Baseline Sounder (ABS) for Future GOES Jun Li + Timothy J. Allen Huang+ W. +CIMSS, UW-Madison.

(to optimize its vertical sampling)

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

Validation strategy for aerosol retrievals of the future Lorraine Remer and J. Vanderlei Martins Dec

What science questions address PACE goals? How would PACE address the science questions? Instrument requirements Mission requirements Strawman instrument.

Spaceborne Underwater Imaging 1 David J. Diner (JPL/CALTECH) John Martonchik (JPL/CALTECH) Yoav Y. Schechner (Technion, Israel) c Copyright All rights.

The Orbiting Carbon Observatory (OCO) Mission: Retrieval Characterisation and Error Analysis H. Bösch 1, B. Connor 2, B. Sen 1, G. C. Toon 1 1 Jet Propulsion.

GEWEX Aerosol Assessment Panel members Sundar Christopher, Rich Ferrare, Paul Ginoux, Stefan Kinne, Jeff Reid, Paul Stackhouse Program Lead : Hal Maring,

1 Xiong Liu Harvard-Smithsonian Center for Astrophysics K.V. Chance, C.E. Sioris, R.J.D. Spurr, T.P. Kurosu, R.V. Martin, M.J. Newchurch,

ACE - Aerosol Working Group Science Traceability Matrix Category 1: Aerosols, Clouds and Climate Category 2: Aerosols, Clouds and Precipitation.

Data acquisition From satellites with the MODIS instrument.

Potential for estimation of river discharge through assimilation of wide swath satellite altimetry into a river hydrodynamics model Kostas Andreadis 1,

Barbuda Antigua MISR 250 m The Climatology of Small Tropical Oceanic Cumuli New Findings to Old Problems (Analysis of EOS-Terra data) Larry Di Girolamo,

Rutherford Appleton Laboratory Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: Initial trade-off: Height-resolved.

MODIS Atmosphere Products: The Importance of Record Quality and Length in Quantifying Trends and Correlations S. Platnick 1, N. Amarasinghe 1,2, P. Hubanks.

NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS LIMB CORRECTION OF POLAR- ORBITING IMAGERY FOR THE IMPROVED INTERPRETATION.

Electro-optical systems Sensor Resolution

Cloud Detection: Optical Depth Thresholds and FOV Considerations Steven A. Ackerman, Richard A. Frey, Edwin Eloranta, and Robert Holz Cloud Detection Issues.

Rutherford Appleton Laboratory Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: FP, 25 April 2014, ESTEC.

The Lodore Falls Hotel, Borrowdale

AVIRIS By: Evan, Mike, Ana Belen ER-2 Twin Otter.

Cloud Trends and Anomalies Observed by MISR

Hyperspectral Sensing – Imaging Spectroscopy

GEO-CAPE to TEMPO GEO-CAPE mission defined in 2007 Earth Science Decadal Survey Provide high temporal & spatial resolution observations from geostationary.

Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: FP, 25 April 2014, ESTEC Height-resolved aerosol R.Siddans.

Need for TEMPO-ABI Synergy

The GIFTS Fast Model: Clouds, Aerosols, Surface Emissivity

Retrieval of SO2 Vertical Columns from SCIAMACHY and OMI: Air Mass Factor Algorithm Development and Validation Chulkyu Lee, Aaron van Dokelaar, Gray O’Byrne:

MODIS Airborne Simulator (MAS),

Presentation transcript:

Status of requirements definition for the ACE multiangle, multispectral, polarimetric imager David J. Diner ACE workshop Salt Lake City, UT 6-7 November 2008

Top level requirements Specification Horizontal spatial resolution Swath width Number of angles and angular range Spectral bands, spectral range, and number with polarization capability Polarization uncertainty A systems view is necessary, as certain capabilites cannot be established without impacting others.

SpecificationRationaleSource 3 kmAerosol measurements away from cloud edges ACOB white paper, §4.1 1 kmNot providedDecadal Survey 500 mImproved cloud edge discrimination and resolution of scene variability ACOB white paper, §1.2, mStereo cloud-top and aerosol injection heights MISR experience 100 mCloud spatial heterogeneityACOB white paper, §2.2 SufficientRetrieve aerosols in heterogeneous conditions ACE STM, v3a Range of opinions on horizontal spatial resolution Comments: Different channels may have different requirements. Cloud 3D effects on aerosol retrievals need to be addressed.

SpecificationRationaleSource 1500 km2-day coverage to overlap ocean color spectrometer ACE STM, v3a 400 kmFocus on process studiesACOB white paper, §2.2 SufficientCapture aerosol events in monthly mean statistics at global model grid resolutions ACE STM, v3a Range of opinions on swath width Comments: Capabilities overlapping the lidar/radar views may differ from those within the broader swath. Establishing role of atmospheric instruments in ocean color measurement will help resolve swath requirement.

SpecificationConsensusNo consensus yet AnglesRange: Nadir to oblique (60º-70º) along-track Number: <10 to capture general scattering/polarization phase function shape; separate aerosol from surface; stereo; vs. >15 to do above plus >60 to resolve detailed angular features (e.g., cloudbow) BandsUV-VNIR-SWIR coverageWavelength of shortest band (355 vs. 380 nm) Number and spectral range of polarization bands Polarization uncertainty Better than 2% required for aerosols 0.1% vs. 0.5% vs. 1.0% Range of opinions on other requirements

Paths to resolving requirements An airborne ACE simulator capability is critical RSP, AirMSPI, HSRL collocated on ER-2 for aerosols PACS on ER-2 if possible, or WB-57 (easier accommodation) Additional synergistic instruments must be identified Simultaneous ground and in situ data required Radiative transfer simulations are also critical Documentation of sensitivity studies (along with key assumptions) needed These activities require substantive funding by NASA HQ Need to identify, capture results of, and possibly repurpose already funded efforts New efforts specifically targeted at resolving areas of disagreement on instrument requirements are essential