'Cloud clearing' diaporamas de présentation

Anomaly Compensation and Cloud Clearing of AIRS Hyperspectral Data

Presented at IEEE GRSS Boston Section Meeting August 24, 2005 Choongyeun (Chuck) Cho. Anomaly Compensation and Cloud Clearing of AIRS Hyperspectral Data. Overview I. Problem statement Definition of anomaly Background

751 views • 61 slides

Anomaly Compensation and Cloud Clearing of AIRS Hyperspectral Data

Presented at IEEE GRSS Boston Section Meeting August 24, 2005 Choongyeun (Chuck) Cho. Anomaly Compensation and Cloud Clearing of AIRS Hyperspectral Data. Overview I. Problem statement Definition of anomaly Background

615 views • 61 slides

Hyperspectral Cloud-Clearing

Hyperspectral Cloud-Clearing Allen Huang, Jun Li, Chian-Yi Liu, Kevin Baggett, Li Guan, & Xuebao Wu SSEC/CIMSS, University of Wisconsin-Madison. AIRS/AMSU V3.5 &V4.0 Cloud-Clearing Characteristic AIRS/AMSU Additional C.C. QC Using MODIS AIRS/MODIS Over Sampling Single-FOV N* C.C.

595 views • 46 slides

USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH Joel Susskind University of Maryland

USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH Joel Susskind University of Maryland May 12, 2005. USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH. AIRS/AMSU/HSB launched on EOS Aqua May 5, 2002 AIRS is a multi-detector array grating spectrometer

536 views • 43 slides

Regression Upgrades

Regression Upgrades. M. Goldberg(1), Chris Barnet(1), W. Wolf(2), L. Zhou(2), M. Divakarla(3), and A. Frolov(3) (1) NOAA-NESDIS, Camp Springs, MD, USA (2) QSS Group Inc, Lanham, MD, USA (3) DSTI Group, Rockville, MD, USA. Outline. Update on Data Distribution

403 views • 40 slides

Combining Observations

Comparison of MODIS radiances and atmosphere products with AIRS, MISR and ground based measurements Steve Ackerman Jun Li, Paul Menzel, Dave Tobin, and others at CIMSS/UW-Madison. Combining Observations. WHY?. Radiance Comparisons Product Comparisons Combined Retrievals Science Insights.

334 views • 33 slides

Retrieval of cloud parameters from the new sensor generation satellite multispectral measurement

Retrieval of cloud parameters from the new sensor generation satellite multispectral measurement F. ROMANO and V. CUOMO. ITSC-XII Lorne, Victoria, Australia. Main Object: Improvement using AMSU data and high spectral resolution data (IASI and IMG) in

332 views • 24 slides

Can we improve our first guess estimate of clear?

252 views • 24 slides

Joanna Joiner Donald Frank, Paul Poli, Arlindo da Silva

Assimilation of satellite data at DAO: cloud- and land-affected sounding data, kilo-channel sounders, and other new data types. Joanna Joiner Donald Frank, Paul Poli, Arlindo da Silva. Outline. Introduction

304 views • 18 slides

CrIMSS EDR Algorithm Improvements beyond Provisional Maturity

CrIMSS EDR Algorithm Improvements beyond Provisional Maturity.

271 views • 17 slides

Cloud Clearing Round Robin

348 views • 15 slides

Harmful Algal Blooms and GOES-R

Harmful Algal Blooms and GOES-R. 49. 48. SeaWiFS data from OrbImage, Inc. 47. 46. -127. -126. -125. -124. -123. Richard P. Stumpf NOAA National Ocean Service Maryland, USA. WA. SST. GOES-R Users Conference, 2004.

278 views • 9 slides