A new Atmospheric Motion Vector (AMV) nested tracking algorithm has been developed for the Advanced Baseline Imager (ABI) to be flown on NOAA's future GOES-R satellite [Bresky et al., 2012]. This algorithm is very different from the AMV algorithm used operationally at NOAA/NESDIS today. The new AMV algorithm was designed to capture the dominant motion in each target scene from a family of local motion vectors derived for each target scene. Capturing this dominant motion is achieved through use of a two-dimensional clustering algorithm that segregates local displacements into clusters. The dominant motion is taken to be the average of the local displacements of points belonging to the largest cluster. This approach prevents excessive averaging of motion that may be occurring at multiple levels or at different scales which may lead to a slow speed bias and a poor quality AMV. A representative height is assigned to the dominant motion vector through exclusive use of cloud heights [Heidinger & Pavolonis, 2009 and Heidinger et al., 2010] from pixels belonging to the largest cluster. This algorithm has been demonstrated to significantly reduce the slow speed bias associated with winds at upper levels, something that is commonly observed in AMVs derived from satellite imagery.
About 70 scientists from the Joint Center and its academic and private
sector partners, including principal investigators, program managers
and JCSDA management/staff, participated in the 11th Annual JCSDA
Workshop on Satellite Data Assimilation, June 5-7, 2013, at NOAA's
Center for Weather and Climate Prediction on the research campus
of the University of Maryland in College Park.
The Workshop was opened by greetings from representatives of the JCSDA's
Management Oversight Board. Simon Chang, Naval Research Laboratory,
pointed out that there is much work to be done, no one agency can do it,
and the Joint Center was needed to facilitate progress. Colonel Daniel
Edwards, USAF, highlighted the DoD?s analysis of alternatives for a
follow-on to the terminating Defense Meteorological Satellite Program,
and the need for the Joint Center to quantify the benefits of proposed
alternatives. Bill Lapenta, NOAA/National Weather Service (NWS),
expressed appreciation for the Center?s contributions to improving
forecast model guidance and urged investigators to focus on how
their work can be integrated into operations. Stan Benjamin,
NOAA/Oceanic and Atmospheric Research (OAR), lauded the Center for
its assistance in making the Gridpoint Statistical Interpolation
assimilation system into a truly community model.
The Joint Center has agreed with the American Meteorological Society to
arrange a "Second Symposium on the Joint Center for Satellite Data Assimilation"
as part of the "10th Annual Symposium on New Generation Operational
Environmental Satellite Systems" during the 2014 AMS Annual Meeting in Atlanta.
The JCSDA Symposium will take place on Thursday, February 6,
and this year the primary focus will be on the scientific and
technical activities of JCSDA and its partners. In particular
we solicit contributions in the following areas:
The 2013 Joint Developmental Testbed Center (DTC) - Environmental Modeling Center (EMC) - JCSDA Community Gridpoint Statistical Interpolation (GSI) Tutorial and GSI Workshop will be held at the National Oceanic and Atmospheric Administration (NOAA) Center for Weather and Climate Prediction (NCWCP), College Park, Maryland, August 5-8. GSI is a variational data assimilation system used in a variety of forecast models, including the Global Forecast System, North American Mesoscale model, Real-Time Mesoscale Analysis, Hurricane Weather Research and Forecasting model, and NASA?s Goddard Earth Observing System model. It is also a community model used by a number of research groups.
The GSI Tutorial will be held on August 5-7, 2013, and includes both lectures and hands-on practical sessions. The Tutorial is designed to train participants in the use of the GSI: how to run and develop the system. The invited speakers are from the primary GSI development teams, including the data assimilation experts working at and with NOAA/EMC, NOAA/Earth System Research Laboratory, JCSDA, NASA/Global Modeling and Assimilation Office, National Center for Atmospheric Research, and the DTC.