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Director's Message

Brant Foote
RAL Director, Brant Foote

Welcome to the Research Applications Laboratory's Annual Report for FY2007.  Our mission is to conduct directed research that contributes to the depth of fundamental scientific understanding, to foster the transfer of knowledge and technology for the betterment of life on earth, and to support technology transfer that expands the reach of atmospheric science.  We are, at present, an organization with an annual budget of more than $30M and a staff comprised of nearly 200 scientists, software engineers, and management/administration personnel. Although NCAR as a whole is largely funded by the National Science Foundation, RAL receives the vast majority of its funding from other sources such as domestic and international government agencies and private companies interested in exploiting the latest advanced weather technologies. 

In 2005 we reorganized the Laboratory into five programs dealing with research and applications in topics related to aviation, homeland security, hydrometeorology, weather systems and assessments, and numerical testbeds. The activities within each of these programs are detailed on the RAL website. In this Annual Report, however, we take the opportunity to present our program in a different way, highlighting the many areas in which our work supports and advances the NCAR Strategic Plan.

Given our focus on applied atmospheric research and technology transfer, it is natural that much of our work contributes to Strategic Goal 2, Priority 2:  "Building capacity for coping with weather and climate hazards."  It is also important to note, though, that many parts of our program map easily into other goals and priorities of NCAR’s Strategic Plan.  RAL scientists are engaged in fundamental investigations of earth-atmosphere interactions, in improving community models, in connecting science to decision making and public policy, in building scientific and technical capacity in developing countries, in creating new mathematical and statistical tools, and in improving instruments used to observe the atmosphere.  In each of these activities, RAL works to bring science and technology to bear on problems that affect society. 

Highlights

This Annual Report provides short narratives on nearly 40 programs conducted at RAL.  Here I highlight five programs that significantly advance NCAR's strategic priorities.

Improving prediction of weather, climate and other atmospheric phenomenon

Highlight:  Climate Forecasting Applications for Bangladesh

A RAL/ASP post-doc, Thomas Hopson, has worked with Peter Webster and colleagues at the Georgia Institute of Technology and researchers at the Asian Disaster Preparedness Centre to improve flood forecasts for Bangladesh. Using ECMWF forecast products and NASA and NOAA precipitation estimates to produce short-range (1- to 10-day) and long-range (1- to 6-month) forecasts--as well as a statistical model to create 20-25 day forecasts--the team is now issuing operational forecasts designed to provide extended-lead-time to those most likely to be affected by flooding of the Ganges and Bramaputhra Rivers.  Good forecasts alone, however, don’t necessarily save lives.   Dissemination of forecasts to a largely rural population lacking access to electricity, as well as advanced communication technologies, has long been a problem. To address this challenge, the Asian Disaster Preparedness Centre staff teamed with local organizations and the country’s Flood Forecasting and Warning Centre to establish a pilot dissemination network in 2006.  A series of training workshops was conducted for the people within the pilot regions so they could effectively utilize the CFAB probabilistic discharge forecast information.  Improved flood forecasts effectively communicated are credited with saving thousands of lives during the severe floods of July and September 2007.

Investigating weather and climate information needs and decision making

Highlight:  Societal Impacts Program

societal impacts program

In 2007 the Societal Impacts Program, a collaborative effort with ISSE, completed an “Overall U.S. Sector Sensitivity Assessment” which examined the sensitivity and vulnerability of state-level economic productivity to weather across 11 economic “super” sectors.  Results indicate that U.S. sensitivity to weather variability is estimated to be about 3.4% of gross domestic product or $260 billion annually. This is the first study of its kind to combine economic and weather data using valid economic methods to assess sector, state, and national economic sensitivity weather variability. Building on this work, SIP staff will focus on specific sectors of the economy to assess the use and value of current and improved weather forecasts. 

SIP staff continue to develop and implement the Weather and Society*Integrated Studies (WAS*IS) workshops. This effort trains and empowers practitioners, researchers, and stakeholders to forge new relationships and to use new tools for more effective socio-economic applications and evaluations of weather products. A total of 145 WAS*IS graduates now comprise a growing community of researchers, operational forecasters, academics, and private sector individuals working to infuse social science research and understanding into the weather enterprise

Community Modeling

Highlight: Developmental Testbed Center (DTC)

DTC
3-h total precipitation (shaded), mean sea level pressure, and 1000-500 mb thickness fields for 60-h forecasts valid at 12 UTC on 3 May 2006. Right panel shows the ARW forecast and left panel shows the NMM forecast. Both WRF configurations used NAM initial and lateral boundary conditions and the same suite of physics parameterizations. For this particular forecast cycle, the ARW and NMM forecasts show rather different evolutions of the cyclone for this extended lead time.

The effort to develop the new Weather Research and Forecasting (WRF) model for the atmospheric community has long been an NCAR priority.  While the development effort largely resides in ESSL, the effort to test and evaluate model configurations resides with the DTC.  The DTC works primarily to facilitate the transfer of new numerical weather prediction (NWP) technologies from research to operations, thereby accelerating the improvement of numerical weather prediction for the nation. This past year, the DTC conducted an extended core test of WRF’s two dynamic solvers: the Advanced Research WRF (ARW) developed by NCAR/MMM, and the Nonhydrostatic Mesoscale Model (NMM) developed by NCEP, to determine whether the small differences in forecast skill between the two dynamic cores for a 24-hour lead time also pertain to longer lead times (i.e., 60 hours).  In addition to extending the forecasts out to 60 hours, the DTC is working to determine whether forecast skill is dependent on the computing platform used to generate the forecasts.  The DTC remains very focused on serving the community by hosting an active visitor program, conducting WRF tutorials, and providing a support system to aid users in accessing and using WRF codes.

Conducting computer science, computational science, applied mathematics, statistics, and numerical methods research and development

Highlight: Verification research and development

verifciation research and development
Example of an application of the MODE, a tool included in MET, as an advanced verification technique provided to the NWP community. By comparing the locations of objects identified using the MODE technique between the forecast (left) and analysis (right) fields, one may identify errors that are difficult or impossible to detect using traditional verification metrics.

Much of the work we do at RAL is focused on improving weather forecasts.  But how do we know if a new forecast is better than an existing one? Forecast verification by nature is a mathematical activity, and development of improved verification methods requires the application of advanced mathematical, statistical, and computational approaches.  To develop and disseminate new forecast verification approaches, RAL scientists conduct research in several areas, including statistical methods, exploratory data analysis, statistical inference, pattern recognition, and evaluation of user needs. Their goal is to produce statistically-valid approaches (e.g., object-based evaluation of precipitation and convective forecasts, distribution-based schemes, etc.) that can provide more meaningful and relevant information about forecast performance, both for those who develop forecasts and for the decision makers who use them.  This past year the Verification Group implemented its Method for Object-based Diagnostic Evaluation (MODE) tool within a new verification toolkit it developed for the DTC and the broader NWP community.  It also launched an intercomparison project (ICP) for spatial forecast verification methods, involving scientists from around the world who are developing new methods for evaluation of spatial forecasts.  A workshop to discuss initial results of the project is planned for Spring 2008.

Provide world-class ground, airborne, and space-borne observational facilities and services

Highlight:  The NEXRAD Turbulence Detection Algorithm (NTDA)

NTDA

RAL scientists have worked for more than 15 years to improve the detection of turbulence.  Over the past several years they have developed the NEXRAD Turbulence Detection Algorithm (NTDA), a new approach to processing data from the National Weather Service’s network of Next Generation Radars (NEXRADs). While aviation users commonly use reflectivity from onboard radars or ground-based radar mosaics to gauge the intensity of a storm, the NTDA detects the wind variations that can shake an aircraft.  By directly measuring the in-cloud turbulence intensity, the NTDA will provide airline dispatchers, air traffic managers, and pilots an important new source of information for tactical turbulence avoidance. NTDA has won final approval from the NEXRAD Technical Advisory Committee (TAC) and the NEXRAD Software Recommendation and Evaluation Committee, and the software package has been delivered to the NEXRAD Radar Operations Center.  Final testing and deployment of the algorithm on the nation’s radars is expected to occur in Summer 2008.



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