Title: Applications of the AWG Cloud Height Algorithm (ACHA) Authors and AffiliationsAndrew Heidinger, NOAA/NESDIS/STAR Steve Wanzong, UW/CIMSS Topics:

Slides:



Advertisements
Similar presentations
Recent Advances in the Processing, Targeting and Data Assimilation Applications of Satellite-Derived Atmospheric Motion Vectors (AMVs) Howard Berger 1,
Advertisements

Slide 1 ECMWF Training Course - The Global Observing System - 06/2013 The Satellite Global Observing System Stephen English 1.A brief introduction to the.
The µm Band: A More Appropriate Window Band for the GOES-R ABI Than 11.2 µm? Daniel T. Lindsey, STAR/CoRP/RAMMB Wayne M. MacKenzie, Jr., Earth Resources.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 A Cloud Object Based Volcanic.
Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
Improved Automated Cloud Classification and Cloud Property Continuity Studies for the Visible/Infrared Imager/Radiometer Suite (VIIRS) Michael J. Pavolonis.
The Utility of GOES-R and LEO Soundings for Hurricane Data Assimilation and Forecasting Jun Timothy J. Schmit #, Hui Liu &, Jinlong and Jing.
1 GOES Users’ Conference October 1, 2002 GOES Users’ Conference October 1, 2002 John (Jack) J. Kelly, Jr. National Weather Service Infusion of Satellite.
1 High impact weather nowcasting and short- range forecasting with advanced IR soundings Jun Tim Schmit &, Hui Liu #, Jinlong Jing
VIIRS Cloud Products Andrew Heidinger, Michael Pavolonis Corey Calvert
Polar Atmospheric Composition: Some Measurements and Products A Report on Action item STG3-A11 Jeff Key NOAA/NESDIS.
GOES-R Risk Reduction Status Dan Lindsey and Andy Heidinger Cooperative Research Program (CoRP) NOAA/NESDIS/STAR NOAA SATELLITE SCIENCE WEEK, 2015 February.
Recent Progress on High Impact Weather Forecast with GOES ‐ R and Advanced IR Soundings Jun Li 1, Jinlong Li 1, Jing Zheng 1, Tim Schmit 2, and Hui Liu.
Joe Sienkiewicz 1, Michael Folmer 2 and Hugh Cobb 3 1 NOAA/NWS/NCEP/OPC 2 University of Maryland/ESSIC/CICS 3 NOAA/NWS/NCEP/NHC/ Tropical Analysis and.
1 Andrew Heidinger, Michael Pavolonis NOAA/NESDIS Steve Wanzong, Andi Walther, Pat Heck, William Straka, Marek Rogal UW/CIMSS Patrick Minnis NASA/LaRC.
Motivation Many GOES products are not directly used in NWP but may help in diagnosing problems in forecasted fields. One example is the GOES cloud classification.
A New Cloud Cover Layers Application Andrew Heidinger and Dan Lindsey NOAA/NESDIS Andi Walther, Steve Wanzong UW/CIMSS Steve Miller, YJ Noh, Curtis Seaman.
GOES-R Synthetic Imagery over Alaska Dan Lindsey NOAA/NESDIS, SaTellite Applications and Research (STAR) Regional And Mesoscale Meteorology Branch (RAMMB)
1 Tropical cyclone (TC) trajectory and storm precipitation forecast improvement using SFOV AIRS soundings Jun Tim Schmit &, Hui Liu #, Jinlong Li.
1 CIMSS Participation in the Development of a GOES-R Proving Ground Timothy J. Schmit NOAA/NESDIS/Satellite Applications and Research Advanced Satellite.
A43D-0138 Towards a New AVHRR High Cloud Climatology from PATMOS-x Andrew K Heidinger, Michael J Pavolonis, Aleksandar Jelenak* and William Straka III.
Régis Borde Polar Winds EUMETRAIN Polar satellite week 2012 Régis Borde
Towards Operational Satellite-based Detection and Short Term Nowcasting of Volcanic Ash* *There are research applications as well. Michael Pavolonis*,
1 GOES-R AWG Product Validation Tool Development Aviation Application Team – Volcanic Ash Mike Pavolonis (STAR)
1 GOES-R AWG Product Validation Tool Development Aviation Application Team – Volcanic Ash Mike Pavolonis (STAR)
1 Center for S a t ellite A pplications and R esearch (STAR) Applicability of GOES-R AWG Cloud Algorithms for JPSS/VIIRS AMS Annual Meeting Future Operational.
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
Advanced Baseline Imager (ABI) will be flown on the next generation of NOAA Geostationary Operational Environmental Satellite (GOES)-R platform. The sensor.
Initial Trends in Cloud Amount from the AVHRR Pathfinder Atmospheres Extended (PATMOS-x) Data Set Andrew K Heidinger, Michael J Pavolonis**, Aleksandar.
Hurricane Intensity Estimation from GOES-R Hyperspectral Environmental Suite Eye Sounding Fourth GOES-R Users’ Conference Mark DeMaria NESDIS/ORA-STAR,
US BENEFITS. It Addresses Priorities The US and Canada have common scientific, economic and strategic interests in arctic observing: marine and air transportation.
RGB Activities for the GOES-R Proving Ground Gary Jedlovec, NASA / MSFC / SPoRT Mark DeMaria NOAA / NESDIS / STAR Tim Schmit NOAA / NESDIS / CIMSS and.
P1.85 DEVELOPMENT OF SIMULATED GOES PRODUCTS FOR GFS AND NAM Hui-Ya Chuang and Brad Ferrier Environmental Modeling Center, NCEP, Washington DC Introduction.
Towards Operational Satellite-based Detection and Short Term Nowcasting of Volcanic Ash* *There are research applications as well. Michael Pavolonis*,
Active Projects for FY04 Clouds from AVHRR – technical support for OSDPD transition to operations, validation of products and development of better algorithms.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Infrared Temperature and.
1 Using water vapor measurements from hyperspectral advanced IR sounder (AIRS) for tropical cyclone forecast Jun Hui Liu #, Jinlong and Tim.
Andrew Heidinger and Michael Pavolonis
Hyperspectral Infrared Alone Cloudy Sounding Algorithm Development Objective and Summary To prepare for the synergistic use of data from the high-temporal.
GOES-R Recommendations from past GOES Users’ Conference: Jim Gurka Tim Schmit Tom Renkevens NOAA/ NESDIS Tony Mostek NOAA/ NWS Dick Reynolds Short and.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Using CALIPSO to Explore the Sensitivity to Cirrus Height in the Infrared.
High impact weather studies with advanced IR sounder data Jun Li Cooperative Institute for Meteorological Satellite Studies (CIMSS),
Summary of GOES-R Activities at CIMSS/ASPB and Recommendations for the Future Steven Ackerman, Tom Achtor GOES-R Algorithm Working Group GOES-R Algorithm.
Developing Assimilation Techniques for Atmospheric Motion Vectors Derived via a New Nested Tracking Algorithm Derived for the GOES-R Advanced Baseline.
Cloud Products and Applications: moving from POES to NPOESS (A VIIRS/NOAA-biased perspective) Andrew Heidinger, Fuzhong Weng NOAA/NESDIS Office of Research.
The Hyperspectral Environmental Suite (HES) and Advanced Baseline Imager (ABI) will be flown on the next generation of NOAA Geostationary Operational Environmental.
1 Recommendations from the 2 nd GOES-R Users’ Conference: Jim Gurka Tim Schmit NOAA/ NESDIS Dick Reynolds Short and Associates.
Cirrus Cloud Boundaries from the Moisture Profile Hyperspectral (i.e., Ultraspectral) IR Sounders W. L. Smith 1,2, Jun-Li 2, and E, Weisz 2 1 Hampton University.
4. GLM Algorithm Latency Testing 2. GLM Proxy Datasets Steve Goodman + others Burst Test 3. Data Error Handling Geostationary Lightning Mapper (GLM) Lightning.
A. FY12-13 GIMPAP Project Proposal Title Page version 04 August 2011 Title: Fusing Goes Observations and RUC/RR Model Output for Improved Cloud Remote.
Preliminary results from the new AVHRR Pathfinder Atmospheres Extended (PATMOS-x) Data Set Andrew Heidinger a, Michael Pavolonis b and Mitch Goldberg a.
High impact weather nowcasting and short-range forecasting using advanced IR soundings Jun Li Cooperative Institute for Meteorological.
Overview of JPSS and GOES-R Data Assimilation in Global Numerical Weather Prediction Models Presented by Jim Yoe NWS National Centers for Environmental.
CLAVR-x in CSPP Andrew Heidinger, NOAA/NESDIS/STAR, Madison WI
NOAA Report on Ocean Parameters - SST Presented to CGMS-43 Working Group 2 session, agenda item 9 Author: Sasha Ignatov.
GOES-R AIT: Updating the Data Processing System with data from the Himawari-8 Geostationary Satellite Jonathan Wrotny1, A. Li1, A. Ken1, H. Xie1, M. Fan1,
PATMOS-x Reflectance Calibration and Reflectance Time-Series
USING GOES-R TO HELP MONITOR UPPER LEVEL SO2
GOES-R Risk Reduction Research on Satellite-Derived Overshooting Tops
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.
EG2234 Earth Observation Weather Forecasting.
RECENT INNOVATIONS IN DERIVING ATMOSPHERIC MOTION VECTORS AT CIMSS
Geostationary Sounders
Hyperspectral Wind Retrievals Dave Santek Chris Velden CIMSS Madison, Wisconsin 5th Workshop on Hyperspectral Science 8 June 2005.
Advanced Satellite Products Branch at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) University of Wisconsin-Madison The Advanced.
AVHRR Pathfinder Atmospheres Extended (PATMOS-x)
Generation of Cloud Products from NOAA’s Operational Satellite Imagers
Andrew Heidinger and Michael Pavolonis
Satellite Wind Vectors from GOES Sounder Moisture Fields
Advanced Satellite Products Branch at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) University of Wisconsin-Madison The Advanced.
Presentation transcript:

Title: Applications of the AWG Cloud Height Algorithm (ACHA) Authors and AffiliationsAndrew Heidinger, NOAA/NESDIS/STAR Steve Wanzong, UW/CIMSS Topics: Tropical Cyclones, Non-convective Forecasts, Satellite use in data sparse regions Program: AWG, Proving Ground, JPSS Risk Reduction 1

2. Introduction The GOES-R AWG funded the development of a cloud height algorithm to exploit the advanced capabilities of the ABI. The AWG Cloud Height Algorithm (ACHA) has evolved into a multi-sensor approach. ACHA products have found application in AMV estimation, PG experiments and field campaign support. ACHA is implemented into NESDIS Ops. This Poster highlights these applications and the lessons learned. 2

3. Methodology/Expected Outcomes The original ABI ACHA operated on the 11, 12 and 13.3  m observations and therefore operated on MODIS and SEVIRI. ACHA was modified to operate on the IR channel sets offered by AVHRR, GOES, MTSAT, COMS and VIIRS. The ability to run on current sensors gives us an opportunity to engage users and applications now. 3

Demonstration of Global ACHA 4 Image below demonstrates ACHA products from GOES-15, GOES-13, MET- 10 and MTSAT-2 at 18Z on February Global coverage is achieved with inclusion of AVHRR, MODIS and VIIRS. CIMSS creates global-geo composites of ACHA for Aviation Support.

ACHA Comparison to NWP 5 Image on right demonstrates ACHA products from GOES-15, GOES-13, MET-10 and MTSAT-2 at 18Z on February 15, 2013 Image on left is the derived cloud-top pressure from the NCEP GFS 12hr Forecast. Cloud-top pressure derived from cloud liquid water profiles. ACHA being sent to Rapid Refresh Group at NOAA/OAR/ESRL. Being testing for improving cloud building in the RAP model. NCEP/GFS group also using ACHA and other products for model verification.

ACHA Support for Field Campaigns 6 ACHA and other AWG cloud products have found use in Field Campaigns. Data is available in field catalogs of the 2012 TORERO and DC3 campaigns. ACHA results used in flight planning where cirrus altitudes were needed. ACHA also used in the Hurricane and Severe Storm Sentinel (HS3) experiment. ACHA cloud heights used to help estimate if a storm’s maximum cloud height exceeded the altitude range of the instrument drone aircraft. Image on right is from HS3 Image courtesy of S. Monette (CIMSS)

ABI ACHA Cloud Top Pressure (CTP) Product from WRF-CHEM/CRTM simulated ABI data (CIMSS) Cloud Top Pressure January 29-30, 2013 Tornado Outbreak GOES-East Sounder (Not ACHA) ACHA CTP From ABI Proxy Data ACHA Generated using Simulated ABI Radiances for GOES-R PG. Images courtesy of T. Schmit (NOAA)

hPa CALIPSO validation of ACHA heights used in SEVIRI Wind Products. Location shown on bottom right image. CALIPSO PATH WITH AMV Points AMV Results for SEVIRI using ACHA AMV Application of ACHA AWG Atmospheric Motion Vector (AMV) algorithm uses pixel-level cloud height products from ACHA. This application provides additional insight into ACHA’s performance. Overall, use of pixel-level height has shown benefits to AMV generation.

5. Possible Path to Operations ACHA is already operational in NESDIS. ACHA runs operationally on the GOES- Imager via the GOES Surface & Insolation Project (GSIP) and on the AVHRR in Cloud from AVHRR Extended Project (CLAVR-x) Real-time data is served also from CIMSS Climate data is generated with the Pathfinder Atmospheres Extended Project (PATMOS-x) and hosted at NCDC. 9

6. Future Plans To better support the AWG mission, we intend to implement ACHA on simulated ABI data and the GOES Sounder. In the presence of complex vertical structures, cloud profile information from NWP appears capable of improving ACHA and we are collaborating with Stan Benjamin on this (GIMPAP funded). VIIRS lacks any IR absorption channels. Work being done at CIMSS will allow CrIS data to provide MODIS- like channels in real-time and allow for more consistent VIIRS/GOES-R products. 10

7. Publication List Heidinger, A. K.; Pavolonis, M. J.; Holz, R. E.; Baum, Bryan A. and Berthier, S. Using CALIPSO to explore the sensitivity to cirrus height in the infrared observations from NPOESS/VIIRS and GOES-R/ABI. Journal of Geophysical Research, Volume 115, 2010, doi: /2009JD Heidinger, Andrew K. and Pavolonis, Michael J. Gazing at cirrus clouds for 25 years through a split window, part 1: Methodology. Journal of Applied Meteorology and Climatology, Volume 48, Issue 6, 2009, pp