Sub-Working Groups & Topical Groups (2016-2018)
From CrewWiki
Contents |
Introduction
The ICWG created semi-permanent Sub-Working Groups (SWGs) that provide the focus and continuity necessary for addressing past and future recommendations and key research topics:
- Algorithms
- Assessments
- Climate Applications
- Weather Applications
Each Sub-Working Group is led by a chair and a rapporteur. At each biennial meeting, the Sub-Working Group chairs present their results, discuss the focal points to be addressed in breakout sessions, and report on these focal points at the plenary final discussion. The Sub-Working Groups may address different topics at each workshop. The Sub-Working Groups encapsulate Topical Groups (TGs) that are established at the ICWG meetings. The Topical Groups that were active during the period 2014-2016 and presented their progress at ICWG-1 can be found under: ICWG-1: List of Topical Groups (2014-2016). The list of semi-permanent Sub-Working Groups, and their current Topical Groups are given below.
Sub Working Group - Algorithms
TG - Cloud Detection, including detection of Arctic/Antarctic clouds
Lead: Karl-Goran Karlsson (SMHI)
Participants: Anke Thoss, Adam Dybbroe, Andi Walther, Andrew Heidinger
Link:
Summary and Scope
Cloud masking is still a crucial operation performed prior to the retrieval of many atmospheric, cloud or surface properties from satellite imagery. Inaccurate cloud masking might ruin or at least seriously bias various parameter retrievals. This topical group will discuss the latest achievements in cloud masking methods for various sensors and satellites. Three groups of methods can be identified at present:
1. Traditional multispectral thresholding methods
2. Bayesian methods (probabilistic cloud masking)
3. Artificial Neural Network-based cloud masking.
The pros and cons of the three groups will be discussed and illustrated with the latest achievements in the respective fields. A particular focus will also be put on improving the definition and knowledge of what clouds are being detected or not being detected. In other words: What do we mean by a cloud for a specific cloud mask or cloud masking method? This information will, e.g., be based on high-sensitive reference data from active lidar instruments and, in particular, data from the CALIOP lidar on the CALIPSO satellite. The prospect of defining standard cloud mask validation methods will also be covered. The use of standard methods could facilitate the inter-comparison of results from different methods.
TG - Use of Combined Sensors for Cloud Retrievals
Lead: Bryan Baum (University of Wisconsin–Madison)
Participants: Elisabeth Weisz, W. Paul Menzel, Andrew Heidinger
Link:
Summary and Scope
Since the advent of the NOAA polar-orbiting operational weather satellites, each platform has carried a high spatial resolution imager (AVHRR) and a lower spatial resolution sounder (HIRS). The Metop-A/B platforms carry both an AVHRR and a HIRS, and additionally a Michelson interferometer called IASI. The primary imager on the NASA Terra and Aqua platforms is MODIS, a 36-band imager, while on the Suomi-NPP platform, the imager/sounder combination is VIIRS and CrIS. Of all these platforms, the only imager that has infrared (IR) absorption channels is MODIS; the others have at most three IR window bands. The bands of interest are in the broad 4.5-µm CO2, 6.7- µm H2O, and 15-µm CO2 absorption bands. In recent work, we developed a method to construct high spatial resolution infrared (IR) absorption band radiances for an imager based on a fusion of imager and sounder data on polar-orbiting weather satellite platforms. More specifically, high spatial resolution IR absorption band radiances were constructed for VIIRS moderate-resolution bands (750 m spatial resolution at nadir) based on data from both VIIRS and CrIS (15 km spatial resolution at nadir). We note that the MODIS+AIRS combination on the NASA Aqua platform provides a unique platform to test the data fusion method since MODIS takes measurements at both the HIRS and AVHRR wavelengths of interest to cloud top property retrievals.
The goal of this topical group is to discuss the formation of a new fundamental climate data record (FCDR) in which similar IR absorption band radiances are constructed for AVHRR+IASI and AVHRR+HIRS. The benefit to merging the imager and sounder measurements is that the sounder measurements are useful for the analysis of optically thin high clouds, can help to improve cloud retrievals in polar regions, and also benefit IR phase determination, among others.
TG - Microwave Cloud Remote Sensing
Lead: Ralf Bennartz (Vanderblidt Univeristy)
Participants: Anke Thoss, Adam Dybbroe, Andi Walther, Andrew Heidinger
Link:
Summary and Scope
Cloud detection (update will follow soon) ...
Sub Working Group - Assessments
Chair: Andi Walther (CIMMS), Rapporteur: ...
TG - Assessment of level-2 Passive Imager Cloud Parameter Retrievals
Lead: Yong-SangChoi (Ewha Womans University)
Participants: Andi Walther ...
Link:
Summary and Scope
The ICWG will continue inter-comparing cloud property retrievals derived from both polar-orbiting and geostationary passive imagers. Comparisons with the CALIPSO/CALIOP and CPR/CloudSat sensors have proven to be very useful in the previous CREW workshops. These comparisons aim at identifying current capacity of retrieving the cloud parameters based on unified reference data.
The providers of cloud parameter retrievals_ are invited to provide instantaneous (level-2) cloud property retrievals, either new datasets or updates of existing datasets, for the golden days (13, 17, 18, and 22 June 2008, 3 July 2008, and 8 October 2014). These datasets will be included in the Common Database of cloud property retrievals. This database currently includes cloud property retrievals from 15 different algorithms. The providers of cloud property datasets have the option to:
- Update their algorithm descriptions;
- Update of their cloud property dataset for the golden days;
- Submit new cloud property datasets for the golden days;
The goal is to use the level-2 datasets for an inter-comparison of cloud property retrievals (and their error estimates) from both polar and geostationary passive imagers (e.g., SEVIRI observing Europe and Africa, AHI/Himawari8 observing Asia and Tropical Western Pacific, AVHRR onboard NOAA 18 and MODIS). As reference datasets, the main sources of information will be the cloud properties obtained from CLOUDSAT and/or CALIPSO observations and Cloud Liquid Water Path observations from passive microwave instruments (e.g. AMSR).
Sub Working Group - Climate Applications
TG - Assessment of Cloud Parameter Data Records for Climate Studies
Lead: Martin Stengel (Deutscher Wetterdienst)
Participants: Mike Foster, Ralf Bennartz, Jan Fokke Meirink
Link:
Summary and Scope
This Topical Group has the following mission statements:
- Focus on passive imagers , thus mainly AVHRR and MODIS cloud property records
- Potentially considered datasets: NASA MODIS coll. 6 (2000-today), Patmos-X (AVHRR, 1982-today), CLARA-A2 (AVHRR, 1982-2014), Cloud_cci (AVHRR, 1982-2014), ISCCP (AVHRR+GEOs, 1983-2009)
- Focus on following cloud variables: cloud fraction, cloud top pressure, optical thickness, thermodynamic phase
- Focus on monthly means in the beginning (later also considering monthly histograms)
- Discuss impact of L1 data quality on climate quality of the cloud records
- Investigate stability of existing datasets and their maturity in terms of trend detection
- Assess impact of orbital drift and possible methods to correct for this
Note: The group interacts with climate group of ITSC (which focuses on TOVS/ATOVS sensors)
Sub Working Group - Weather Applications
TG - Severe Weather Applications
Lead: Mike Pavolonis (NOAA STAR)
Participants: Bryan Baum, Anke Thoss, Adam Dybbroe, Daniel Rosenfeld, Ulrich Hamann
Link:
Summary and Scope
Severe weather applications illustrate the importance of developing sophisticated, scientific, computer algorithms to convert extremely large volumes of satellite data knowledge. The need for science based computer algorithms has never been greater as data volumes and information content will increase significantly with the next generation of operational satellites. Thunderstorms that produce large hail, damaging winds, and tornadoes are often difficult to forecast due to their rapid evolution and complex interactions with environmental features that are challenging to directly observe. Satellite data, in combination with other data sets, can be used to increase the timeliness and accuracy of severe weather warnings and the understanding of the convective life cycle. This topical group will focus on research aimed at using satellite data, perhaps in combination with other data sources, to improve severe weather forecasting and knowledge.
TG - Cloud Height for Wind Applications
Lead: Andrew Heidinger (NOAA STAR)
Participants: Phil Watts, Regis Borde
Link:
Summary and Scope
Many current Atmospheric Motion Vector (AMV) algorithms are relying on objectively derived cloud heights to assign the vertical position of their AMV tracers. In recognition of this evolution, The International Winds Working Group (IWWG) has expressed a desire to collaborate with the International Cloud Working Group. This ICWG Topical Group will focus on this collaboration. The AMV algorithms predominately use results at the edges of clouds to derive AMVs. Much of the technical discussions in this topical group will focus on the performance of the cloud height algorithms at cloud edges. Another important topic is the comparison of the methods and metrics used to report cloud height uncertainties and other diagnostic parameters for use in AMV applications.
