Blue Sky group presentation

Slides:



Advertisements
Similar presentations
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,
Advertisements

 nm)  nm) PurposeSpatial Resolution (km) Ozone, SO 2, UV8 3251Ozone8 3403Aerosols, UV, and Volcanic Ash8 3883Aerosols, Clouds, UV and Volcanic.
1 Satellite Imagery Interpretation. 2 The SKY Biggest lab in the world. Available to everyone. We view from below. Satellite views from above.
AIRS (Atmospheric Infrared Sounder) Level 1B data.
Visible and Infrared (IR) Weather Satellite Interpretation 1. Visible satellite images are coded from black to white according to the amount of reflected.
Satellite Haze Detection on July July 16-18,1999 Rudolf B. Husar CAPITA, Washington University October 1999.
Cloud Masking and Cloud Products MODIS Operational Algorithm MOD35 Paul Menzel, Steve Ackerman, Richard Frey, Kathy Strabala, Chris Moeller, Liam Gumley,
CLOUD DETECTION WITH OPERATIONAL IMAGERS
Satellites and Radar – A primer ATMO 203. Satellites Two main types of satellite orbits – Geostationary Earth Orbiting Satellite is 35,786 km (22,236.
Surface Skin Temperatures Observed from IR and Microwave Satellite Measurements Catherine Prigent, CNRS, LERMA, Observatoire de Paris, France Filipe Aires,
Millimeter and sub-millimeter observations for Earth cloud hunting Catherine Prigent, LERMA, Observatoire de Paris.
Climate, Meteorology and Atmospheric Chemistry.
Quick Review of Remote Sensing Basic Theory Paolo Antonelli CIMSS University of Wisconsin-Madison Benevento, June 2007.
Remote Sensing Allie Marquardt Collow Met Analysis – December 3, 2012.
Version 1.0, 30 June 2004 APPLICATIONS OF METEOSAT SECOND GENERATION (MSG) RGB IMAGES: PART 1 OVERVIEW MSG SEVIRI CHANNELS Author:Jochen Kerkmann (EUMETSAT)
Meteorolojik Uzaktan Algılamaya Giriş Erdem Erdi Uzaktan Algılama Şube Müdürlüğü 7-8 Mayıs 2012, İzmir.
Extending HIRS High Cloud Trends with MODIS Donald P. Wylie Richard Frey Hong Zhang W. Paul Menzel 12 year trends Effects of orbit drift and ancillary.
Applications and Limitations of Satellite Data Professor Ming-Dah Chou January 3, 2005 Department of Atmospheric Sciences National Taiwan University.
Radiation in the Atmosphere (Cont.). Cloud Effects (2) Cloud effects – occur only when clouds are present. (a) Absorption of the radiant energy by the.
Hyperspectral Infrared Alone Cloudy Sounding Algorithm Development Objective and Summary To prepare for the synergistic use of data from the high-temporal.
Cloud Mask: Results, Frequency, Bit Mapping, and Validation UW Cloud Mask Working Group.
High impact weather studies with advanced IR sounder data Jun Li Cooperative Institute for Meteorological Satellite Studies (CIMSS),
Preparing for GOES-R: old tools with new perspectives Bernadette Connell, CIRA CSU, Fort Collins, Colorado, USA ABSTRACT Creating.
METEOSAT SECOND GENERATION FROM FIRST TO SECOND GENERATION METEOSAT
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
Developing a Dust Retrieval Algorithm Jeff Massey aka “El Jeffe”
Unit 4 Lesson 2 Clouds and Cloud Formation
GOES-R ABI and Himawari-8 AHI Training using SIFT
Objective: 2/26/2013 List three types of cloud forms. Intro
The Eight Planets (13.14).
Microwave Assimilation in Tropical Cyclones
Unit 4 Lesson 2 Clouds and Cloud Formation
Weather The condition of the atmosphere at a given place
GOES-R ABI and Himawari-8 AHI Training using SIFT
Extinction measurements
CMa & CT Cloud mask and type
Dust detection methods applied to MODIS and VIIRS
Surface Energy Budget, Part I
Best practices for RGB compositing of multi-spectral imagery
Example for a Satellite: Meteosat Second Generation
In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven.
NASA Aqua.
GOES-8 thru GOES-15 NPP VIIRS MSG SEVIRI AVHRR GOES Sounder MTG FCI
METEOSAT SECOND GENERATION (MSG)
Unit 4 Lesson 2 Clouds and Cloud Formation
In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven.
GOES visible (or “sun-lit”) image
Winds in the Polar Regions from MODIS: Atmospheric Considerations
ABI Visible/Near-IR Bands
Geostationary Sounders
Unit 4 Lesson 2 Clouds and Cloud Formation
In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven.
Cristina Lupu, Niels Bormann, Reima Eresmaa
Monitoring Earth’s Climate System
Remote Sensing Seminar
Remote Sensing Seminar
In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven.
In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven.
CH=20km; CPS=12.5 microns; COT=1.6 Cloud Spectral Signature
WEATHER What is it?. To Review: Fronts Fronts are the line boundary lines where two chunks (masses) of cold and warm air meet. Storms often occur at.
Image Interpretation for Weather Analysis
Satellite Foundational Course for JPSS (SatFC-J)
Energy Budgets Some parts of the earth receive a lot of solar energy (surplus), some receive less (deficit). In order to transfer this energy around, to.
Water and Wind in Earth’s Atmosphere
Front page of the realtime GOES-12 site, showing all of the latest Sounder spectral bands (18 infrared and 1 visible) over the central and Eastern US All.
AIRS (Atmospheric Infrared Sounder) Level 1B data
CALIPSO Total Attenuated Backscatter 532 nm 7 June 2006 Volcanic plume
METEOSAT SECOND GENERATION (MSG) OVERVIEW MSG SEVIRI CHANNELS
Representing Climate Data II
Water Cycle and Weather
Presentation transcript:

Blue Sky group presentation Spectra features Francesca, Francesco, Igor, Piotr, Raffaella

Italian: Ecco a voi la stupefacente, meravigliosa e sconvolgente presentazione del famoso gruppo “Cielo Azzurro” German: Wunderbarer Blauhimmelgruppenvortrag French: Maintenant on y va avec l`une des meilleures présentations du fameux grouppe “Ciel Bleu” Hungarian: A „Kek Eg” csoport csodalatos eloadasa Polish: Zaskakująca i zachwycająca prezentacja grupy “Błękitne Niebo”

? ? ?

Snow Cloud-day Etna Plume Clear Sky Ocean Tunisia desert AIRS

Investigated areas desert snow cloud

AIRS Spectra from around the Globe 20-July-2002 Ascending LW_Window This shows the ascending data (day-time) for the current AIRS “focus day” of 20 July 2002. The image is of a longwave window channel brightness temperature (using a GOES colormap), along with various sample spectra. We’ve had global observations of high spectral resolution before (IRIS and IMG), but they were not really atmospheric profile sounders. The AIRS data is very clean, and the applications are numerous. This is what many of us have been waiting for, and working towards for many years. There are many un-tapped opportunities: SO2 detection from volcanoes, the blue-spike fire detection, new cloud detection techniques, low level inversion detection for severe weather, new spectroscopy investigations, climate change signatures, …

Day? Night? Desert? Ice/Snow? Here the temperature is lower in the window than in the H2O band: Signature of cold surface and dry atmosphere Here the flatness indicates that it could be either snow /ice, or night Low BT points to snow/ice Here two windows channel at similar level exclude desert land Low surface temp. 31 29 23 Very dry atmosphere

Polar ice, very low temperature Polar coastline

Comparison with modis ice/snow pseudochannels 31-23: Snow surfaces have small negative difference of Tb 31-29: snow surfaces have same Tb

Our conclusion Probably ice/snow, clear, very cold, hard to say day/night. (Polar bear chattering with teeth)

be due to bare soil (desert): see picture Land? Ocean? This BT difference may be due to bare soil (desert): see picture Night or lack of clouds (water clouds) Relatively low surface temperature 31 29 32

Tunisia desert - AIRS spectra Daytime No clouds

11 m - 12 m 11m - 8.6 m 31-29 over desert (red surfaces) Sea, land with vegetation (blue surfaces) 31-32: difference over desert is close to 0 Thin clouds (cirrus) brighter 11 m - 12 m 11m - 8.6 m

Our conclusion Probably night, desert, and presence of cirrus clouds. (Muffled sounds of camel hoofs coming from a distance)

Daytime, due to the steep slope from reflected sun radiation: this is very high, so it could be thick clouds, or clouds composed by small droplets (high reflectivity). Presence of clouds: we see that it is ice clouds, because otherwise it would not be so steep 23 31 29 32

AIRS spectra over cloudy area Sun reflection Low temperature

23-31 29-31 31-32 High cloud with ice particles on the top well presented Broken clouds and low water clouds better detected Thin clouds well detected Thick high clouds not detected

Our conclusion High cirrus over a low cloud at the daytime Daytime, probably two layers of clouds, or broken clouds (where we have both ice and water droplet) Final decision High cirrus over a low cloud at the daytime

Clear sky over the sea - AIRS spectra High temperature, similar in all windows

SO2 plume from Etna - AIRS spectra Etna plume: Brightness Temperature Spectra Characteristic slopes of window channels