Suomi NPP VIIRS Day Night Band (DNB)

Slides:

Advertisements

Similar presentations

VIIRS Data Evaluation Over Thailand and Japan February 13, 2012 Chair, Chris Elvidge NOAA-NGDC 1.

Advertisements

SPoRT Activities in Support of the GOES-R and JPSS Proving Grounds Andrew L. Molthan, Kevin K. Fuell, and Geoffrey T. Stano NASA Short-term Prediction.

10 November 2014 Colorado Dust Storm Matched to Aircraft Photo Steve Miller Colorado State University Cooperative Institute for Research in the Atmosphere.

Overview of GOES and MTSAT Platforms: Fire Monitoring Characteristics

Tommy Jasmin1, Dan Lindsey2, Steve Miller3, Thomas Rink1, Don Hillger2

Developing the VIIRS/DNB Lunar Reflectance Product Steve Miller Updated: 27 July 2012.

Transitioning research data to the operational weather community Use of VIIRS DNB Data to Monitor Power Outages and Restoration for Significant Weather.

Fusion of SeaWIFS and TOMS Satellite Data with Surface Observations and Topographic Data During Extreme Aerosol Events Stefan Falke and Rudolf Husar Center.

Steven Miller Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Ft. Collins, CO Jeremy Solbrig, Mindy Surratt, Kim.

Satellite Imagery Meteorology 101 Lab 9 December 1, 2009.

Meteorological satellites – National Oceanographic and Atmospheric Administration (NOAA)-Polar Orbiting Environmental Satellite (POES) Orbital characteristics.

Satelite Training in Latin America Vilma Castro, Professor at the School of Physics, University of Costa Rica WMO Regional Meteorological Training Center.

Analysis of High Resolution Infrared Images of Hurricanes from Polar Satellites as a Proxy for GOES-R INTRODUCTION GOES-R will include the Advanced Baseline.

An Update of CIRA’s GOES-R and JPSS Proving Ground Activities Ed Szoke 1,2, Dan Bikos 1, Renate Brummer 1, Hiro Gosden 1, Steve Miller 1, Curtis Seaman.

Estimation of poverty rates based on satellite observed nighttime lights Chris Elvidge, NOAA National Geophysical Data Center (NGDC) Boulder, Colorado.

Improved Scaling for DNB Imagery in the Alaska Region Curtis Seaman CIRA/Colorado State University.

Evidence of Strong Updrafts in Tropical Cyclones using Combined Satellite, Lightning, and High-Altitude Aircraft Observations Christopher S. Velden*, Sarah.

Prospects for Improved Global Mapping of Development Using VIIRS Data Chris Elvidge Earth Observation Group NOAA-NESDIS National Geophysical Data Center.

18 October 2012 IMAP/VISI (ISS) Suomi NPP VIIRS Day/Night Band Steven D. Miller Colorado State University / CIRA 13 Nov 2013.

TC Intensity Estimation: SATellite CONsensus (SATCON) Derrick Herndon, Chris Velden, Tony Wimmers, Tim Olander International Workshop on Tropical Cyclone.

High Resolution MODIS Ocean Color Fred Patt 1, Bryan Franz 1, Gerhard Meister 2, P. Jeremy Werdell 3 NASA Ocean Biology Processing Group 1 Science Applications.

Poster 1.66 An Update on CIRA’s GOES-R Proving Ground Activities Ed Szoke 1,2, Renate Brummer 1, Hiro Gosden 1, Steve Miller 1, Mark DeMaria 3, Dan Lindsey.

GOES-R ABI Synthetic Imagery at 3.9 and 2.25 µm 24Feb2015 Poster 2 Louie Grasso, Yoo-Jeong Noh CIRA/Colorado State University, Fort Collins, CO

GOES-R/JPSS PG User Readiness Meeting WFO Honolulu & Central Pacific Hurricane Center Robert Ballard, SOO June 2, 2014.

Not-So Silent Night: Suomi NPP’s Day/Night Band Makes Waves as a Disruptive Technology to Characterization of the Nocturnal Environment Steven D. Miller.

Andrew Heidinger and Michael Pavolonis

Status of improving the use of MODIS, AVHRR, and VIIRS polar winds in the GDAS/GFS David Santek, Brett Hoover, Sharon Nebuda, James Jung Cooperative Institute.

20 April 2009 Boulder WFO Spring Workshop Talk GOES-R Proving Ground WFO Interaction Activities – An Update Presentation at Boulder Spring Workshop – Ed.

Using the Next Generation Satellite (NexSat) Webpage to Demonstrate and Apply NPP Sensor Products During the NPP/JPSS Missions September 2012 – June 30,

Importance of Low Light Sensing Lunar reflection-based features: Terrestrial/atmospheric emission-based features:

High impact weather studies with advanced IR sounder data Jun Li Cooperative Institute for Meteorological Satellite Studies (CIMSS),

The NRL Tropical Cyclone Web Resource Jeff Hawkins, Kim Richardson, Tom Lee, Buck Sampson, Arunas Kuciauskas 1, Joe Turk 2, Steve Miller 3, and John Kent.

Preparing for GOES-R: old tools with new perspectives Bernadette Connell, CIRA CSU, Fort Collins, Colorado, USA ABSTRACT Creating.

Consistency of reflected moonlight based nighttime precipitation product with its daytime equivalent. Andi Walther 1, Steven Miller 3, Denis Botambekov.

N-AWIPS Product Dissemination by SPoRT, CIRA, and CIMAS.

Introduction to NCC in AWIPS VISIT Satellite Chat (18 Dec 2015)

SANDY SUPPLEMENTAL PROJECT: NEW AWIPS DATA FOR ALASKA Carl Dierking, Tom Heinrichs, Gwen Bryson, Jay Cable, Scott Macfarlane, Jessie Cherry, Eric Stevens.

1 GLIMPSING THE FIRST PRODUCTS FROM VIIRS Dr. Wayne Esaias NASA GSFC Thomas F. Lee Jeffrey Hawkins Arunas Kuciauskas Kim Richardson Jeremy Solbrig Naval.

Applications of the NPOESS Imagers Thomas F. Lee, Jeffrey Hawkins, F. Joseph Turk, Peter Gaiser, Mike Bettenhausen Naval Research Laboratory Monterey CA.

True-Color Imagery for GOES-R: Creating a Green Band for ABI

Example from 9 January 2015 cont’d Display of Near Real-Time Data

GOES-R Resources from NOAA, NASA & CIMSS

VIIRS and the Fort McMurray Fire VISIT Satellite Chat (18 May 2016)

A Probabilistic Nighttime Fog/Low Stratus Detection Algorithm

GOES-8 thru GOES-15 NPP VIIRS MSG SEVIRI AVHRR GOES Sounder MTG FCI

USING GOES-R TO HELP MONITOR UPPER LEVEL SO2

GOES-R Risk Reduction Research on Satellite-Derived Overshooting Tops

TIROS-1: The First Weather Satellite

GOES visible (or “sun-lit”) image

Preparation for use of the GOES-R Advanced Baseline Imager (ABI)

Operational Use of the Day-Night Band in Alaska

Who We Are SSEC (Space Science and Engineering Center) is part of the Graduate School of the University of Wisconsin-Madison (UW). SSEC hosts CIMSS (Cooperative.

Geostationary Sounders

Night time sea ice motion East Central Greenland

Sea of Japan Full moon depiction at night using VIIRS Day Night Band (DNB) with Enhanced IR along with an application of the Lunar reflection model developed.

Digital Numbers The Remote Sensing world calls cell values are also called a digital number or DN. In most of the imagery we work with the DN represents.

NOAA Agency Update Steve Volz, SIT Vice Chair

An Update of CIRA’s GOES-R and JPSS Proving Ground Activities

DNB provides more low cloud structure City Lights

Oceanic Features via VIIRS

Monitoring the Growing Big Sur “Pfeiffer” Wildfire at Night

Matthew A. Lazzara1, Linda M

DMSP Daytime Visible: Z

AVHRR & VIIRS True Color Comparisons

Caribbean Institute for Meteorology and Hydrology

Suomi NPP VIIRS true color imagery illustrating dust event over Iraq and SW Asia from April 18-20, Data products are posted with 8-10 hour latency.

Status of recent/near future VISIT/SHyMet as it relates to the Satellite Foundational Course for GOES-R (SatFC-G) NOAA Satellite Proving Ground / User.

Atmospheric Sciences 101 Weather Satellite 2019

Oceanic Features via VIIRS

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.

Presentation transcript:

Suomi NPP VIIRS Day Night Band (DNB) Tropical Cyclone 10P Jasmine 02-07-12 1422Z 0122 (Local) Infrared Day Night Band Suomi NPP day night band (DNB) example for tropical cyclone (TC) 10P (Jasmine) on Feb 7, 2012 (1422Z, local time 0122) located in the south pacific near New Caledonia. VIIRS IR band image with color table illustrating cold cloud tops associated with the tropical cyclone, with coldest (highest) clouds within the eyewall and the main convective band spiraling into the storm center. (Note the flow is clockwise in TCs within the southern hemisphere). VIIRS day night band (DNB) image depicting the reflection of lunar illumination from the top most clouds. Note the local time is 0122, thus this nighttime image appears “day-like” due to the nearly full moon conditions. DNB products maintain their spatial resolution across the 3000 km swath (similar to DMSP OLS) but have 14-bit digitization instead of the 6-bit (64 gray shades) available for OLS. Note the ability to view the texture associated with the convective elements with the eyewall and strong rainband on the storm’s east side. A multi-spectral combination (IR+DNB) enables the user to readily distinguish the low clouds (yellow) and high clouds (light blue) while still retaining the texture in the eyewall associated with the DNB imagery. Note: No correction has been made yet for variable moon illumination (planned) to create a consistent DNB imagery data set that would be easier to analyze and utilize for quantitative applications. Acknowledgments: NPP VIIRS data provided via the U. of Wisconsin Cooperative Institute for Meteorological Studies (CIMSS, Madison, WI) which acquires the data from the NOAA CLASS servers. This product was created by the Naval Research Laboratory, Marine Meteorology Division, Monterey, CA (NRL-MRY) Satellite Meteorological Applications Section. Special thanks to Jeremy Solbrig, Kim Richardson, and Mindy Surratt (NRL-MRY) and Steve Miller (Cooperative Institute for Research in the Atmosphere (CIRA, Colorado State Univ, Ft. Collins, CO)) for making this capability possible. IR-DNB Multi-spectral Low-clouds: Yellow Cirrus: Light blue