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FAA tactical weather forecasting in the United States National Airspace
September 5, 2005
Conference Paper
Published in:
World Weather Research Program Symp. on Nowcasting and Very Short Term Forecasts, 5-9 September 2005.
Summary
This paper describes the Tactical 0-2 hour Convective Weather Forecast (CWF) algorithm developed by the MIT LL for the FAA. We will address the algorithm and focus on the key scientific developments. Future directions will also be discussed.
Summary
This paper describes the Tactical 0-2 hour Convective Weather Forecast (CWF) algorithm developed by the MIT LL for the FAA. We will address the algorithm and focus on the key scientific developments. Future directions will also be discussed.
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Automated extraction of weather variables from camera imagery
August 18, 2005
Conference Paper
Published in:
Proc. of 2005 Mid-Continent Transportation Research Symp., 18-19 August 2005.
Summary
Thousands of traffic and safety monitoring cameras are deployed or are being deployed all across the country and throughout the world. These cameras serve a wide range of uses from monitoring building access to adjusting timing cycles of traffic lights at clogged intersections. Currently, these images are typically viewed on a wall of monitors in a traffic operations or security center where observers manually monitor potentially hazardous or congested conditions and notify the appropriate authorities. However, the proliferation of camera imagery taxes the ability of the manual observer to track and respond to all incidents. In addition, the images contain a wealth of information, including visibility, precipitation type, road conditions, camera outages, etc., that often goes unreported because these variables are not always critical or go undetected. Camera deployments continue to expand and the corresponding rapid increases in both the volume and complexity of camera imagery demand that automated algorithms be developed to condense the discernable information into a form that can be easily used operationally by users. MIT Lincoln Laboratory (MIT/LL) under funding from the Federal Highway Administration (FHWA) is investigating new techniques to extract weather and road condition parameters from standard traffic camera imagery. To date, work has focused on developing an algorithm to measure atmospheric visibility and prove the algorithm concept. The initial algorithm examines the natural edges within the image (the horizon, tree lines, roadways, permanent buildings, etc) and performs a comparison of each image with a historical composite image. This comparison enables the system to determine the visibility in the direction of the sensor by detecting which edges are visible and which are not. A primary goal of the automated camera imagery feature extraction system is to ingest digital imagery with limited specific site information such as location, height, angle, and visual extent, thereby making the system easier for users to implement. There are, of course, many challenges in providing a reliable automated estimate of the visibility under all conditions (camera blockage/movement, dirt/raindrops on lens, etc) and the system attempts to compensate for these situations. This paper details the work-to-date on the visibility algorithm and defines a path for further development of the overall system.
Summary
Thousands of traffic and safety monitoring cameras are deployed or are being deployed all across the country and throughout the world. These cameras serve a wide range of uses from monitoring building access to adjusting timing cycles of traffic lights at clogged intersections. Currently, these images are typically viewed on...
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Description of the Corridor Integrated Weather System (CIWS) weather products
August 1, 2005
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-317
Summary
Improved handling of severe en route and terminal convective weather has been identified by the FAA in both the Operational Evolution Plan (OEP) (FAA, 2002) and the Flight Plan for 2004-2008 (FAA, 2003) as a major thrust over the coming decade for the National Airspace System (NAS) modernization. Achieving such improved capabilities is particularly important in highly congested corridors where there is both a high density of over flights and major terminals. Delay increases during thunderstorm season have been the principal cause of the dramatic delay growth in the US aviation system. When major terminals also underlie the en route airspace, convective weather has even greater adverse impacts, especially if the convective weather occurs frequently. In response to the need to enhance both safety and capacity during adverse weather, the FAA is exploring the concept of a Corridor Integrated Weather System (CIWS). CIWS is designed to improve convective weather decision support for congested en route airspace (and the terminals that lie under that airspace) by automatically generating graphical depictions of the current severe weather situation and providing frequently updated forecasts of the future weather locations for forecast times from zero to two hours. An operational demonstration of the CIWS was conducted during the summer of 2003. This document provides a detailed description of each CIWS weather information product as it was demonstrated in 2003, including a general description of the product, what data sources are used by the product, how the product is generated from the input data, and what caveats in the technical performance apply. A discussion of how the products might be used to enhance safety and support decision-making for traffic management is also included. Detailed information on the operational benefits of the CIWS products demonstrated in 2003 is provided in a companion report (Robinson et al., 2004). Improvements made to the products for the 2004 and 2005 CIWS operational demonstrations are briefly discussed in the final chapter.
Summary
Improved handling of severe en route and terminal convective weather has been identified by the FAA in both the Operational Evolution Plan (OEP) (FAA, 2002) and the Flight Plan for 2004-2008 (FAA, 2003) as a major thrust over the coming decade for the National Airspace System (NAS) modernization. Achieving such...
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Operational benefits of the Integrated Terminal Weather System (ITWS) at Atlanta
July 15, 2005
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-320
Summary
This report summarizes the results of an initial study to estimate the yearly delay reduction provided by the initial operational capability (IOC) Integrated Terminal Weather System (ITWS) at Hartsfield-Jackson Atlanta International Airport (ATL). Specific objectives of this initial study were to: (1) analyze convective weather operations at ATL to determine major causes of convective weather delay and how those might be modeled quantitatively. (2) provide estimates of the ATL ITWS delay reduction based on the "Decision/Modeling" method using questionnaires and interviews with Atlanta Terminal Radar Approach Control (TRACON) and Air Route Traffic Control Center (ARTCC) operational ITWS users. (3)assess the "reasonableness" of the model-based delay reduction estimates by comparing those savings with estimates of the actual weather-related arrival delays at ATL. In addition, the reasonableness of model-based delay reduction estimates was assessed by determining the average delay savings per ATL flight during times when adverse convective weather is within the coverage of the ATL ITWS. (4)conduct an exploratory study confirming the ATL ITWS delay savings by comparing Aviation System Performance Metrics (ASPM) database delays pre- and post-ITWS at ATL. (5) assess the accuracy of the "downstream" delay model employed in this study by analyzing ASPM data from a major US airline, and (6) make recommendations for follow-on studies of the ITWS delay reduction at Atlanta and other IOC ITWS facilities. [not complete]
Summary
This report summarizes the results of an initial study to estimate the yearly delay reduction provided by the initial operational capability (IOC) Integrated Terminal Weather System (ITWS) at Hartsfield-Jackson Atlanta International Airport (ATL). Specific objectives of this initial study were to: (1) analyze convective weather operations at ATL to determine...
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Multi-PRI signal processing for the terminal Doppler weather radar, part I: clutter filtering
May 1, 2005
Journal Article
Published in:
J. Atmos. Ocean. Technol., Vol. 22, May 2005, pp. 575-582.
Topic:
R&D area:
Summary
Multiple pulse repetition interval (multi-PRI) transmission is part of an adaptive signal transmission and processing algorithm being developed to aggressively combat range-velocity ambiguity in weather radars. In the past, operational use of multi-PRI pulse trains has been hampered due to the difficulty in clutter filtering. This paper presents finite impulse response clutter filter designs for multi-PRI signals with excellent magnitude and phase responses. These filters provide strong suppression for use on low-elevation scans and yield low biases of velocity estimates so that accurate velocity dealiasing is possible. Specifically, the filters are designed for use in the Terminal Doppler Weather Radar (TDWR) and are shown to meet base data bias requirements equivalent to the Federal Aviation Administration's specifications for the current TDWR clutter filters. Also an adaptive filter selection algorithm is proposed that bases its decision on clutter power estimated during an initial long-PRI surveillance scan. Simulations show that this adaptive algorithm yields satisfactory biases for reflectivity, velocity, and spectral width. Implementation of such a scheme would enable automatic elimination of anomalous propagation signals and constant adjustment to evolving ground clutter conditions, an improvement over the current TDWR clutter filtering system.
Summary
Multiple pulse repetition interval (multi-PRI) transmission is part of an adaptive signal transmission and processing algorithm being developed to aggressively combat range-velocity ambiguity in weather radars. In the past, operational use of multi-PRI pulse trains has been hampered due to the difficulty in clutter filtering. This paper presents finite impulse...
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Improved range-velocity ambiguity mitigation for the Terminal Doppler Weather Radar
October 4, 2004
Conference Paper
Published in:
11th Conf. on Aviation, Range and Aerospace Meteorology, 4-8 October 2004.
Summary
The Terminal Doppler Weather Radar (TDWR) radar data acquisition (RDA) subsystem is being replaced as part of a broader FAA program to improve the supportability of the system. An engineering prototype RDA has been developed with a scalable, open-systems hardware platform. With the dramatically increased computing power and more flexible transmitter control, modern signal processing algorithms can be implemented to improve the quality of the base data. Nation-wide, the most serious data quality challenge is range-velocity (RV) ambiguity. In a previous study (Cho et al., 2003) we showed that multiple pulse repetition interval (PRI) and constant-PRI phase-code processing have complementary strengths with respect to range-fold protection, and pro-posed an adaptive waveform and processing selection scheme on a radial-by-radial basis. Here we describe the scheme and give more details about the clutter filtering and velocity dealiasing algorithms to be used on the two types of signals.
Summary
The Terminal Doppler Weather Radar (TDWR) radar data acquisition (RDA) subsystem is being replaced as part of a broader FAA program to improve the supportability of the system. An engineering prototype RDA has been developed with a scalable, open-systems hardware platform. With the dramatically increased computing power and more flexible...
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Corridor integrated weather system operation benefits 2002-2003 : initial estimates of convective weather delay reduction : executive summary
May 19, 2004
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-313-1
Summary
The Corridor Integrated Weather System (CIWS) seeks to improve safety and reduce delay by providing accurate, automated, rapidly updated information on storm locations and echo tops along with two-hour high-resolution animated growth and decay convective storm forecasts. An operational benefits assessment was conducted using on-site observations of CIWS usage at major en route control centers in the Northeast and Great Lakes corridors and the Air Traffic Control Systems Command Center (ATCSCC) during six multi-day periods in 2003. (Not complete).
Summary
The Corridor Integrated Weather System (CIWS) seeks to improve safety and reduce delay by providing accurate, automated, rapidly updated information on storm locations and echo tops along with two-hour high-resolution animated growth and decay convective storm forecasts. An operational benefits assessment was conducted using on-site observations of CIWS usage at...
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Corridor Integrated Weather System operation benefits 2002-2003 : initial estimates of convective weather delay reduction
April 9, 2004
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-313
Summary
The Corridor Integrated Weather System (CIWS) seeks to improve safety and reduce delay by providing accurate, automated, rapidly updated information on storm locations and echo tops along with two-hour high-resolution animated growth and decay convective storm forecasts. An operational benefits assessment was conducted using on-site observations of CIWS usage at major en route control centers in the Northeast and Great Lakes corridors and the Air Traffic Control Systems Command Center (ATCSCC) during six multi-day periods in 2003. This first phase of the benefit assessment characterizes major safety and delay reduction benefits and quantifies the delay reduction benefits for two key Traffic Flow Management (TFM) user benefits: "keeping air routes open longer/reopening closed routes soon" and "proactive, efficient reroutes of traffic around storm cells." The overall CIWS delay reduction for these two benefits is 40,000 to 69,000 hours annually with an equivalent monetary value ot $127M to $26M annually. Convective weather delays at most of the major airports in the test domain, normalized by thunderstorm frequency, decreased after new CIWS echo tops and forecast products were introduced. Recommendations are made for near-term, low-cost improvements to the CIWS demonstration system to further increase the operational benefits.
Summary
The Corridor Integrated Weather System (CIWS) seeks to improve safety and reduce delay by providing accurate, automated, rapidly updated information on storm locations and echo tops along with two-hour high-resolution animated growth and decay convective storm forecasts. An operational benefits assessment was conducted using on-site observations of CIWS usage at...
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Utilizing local terrain to determine targeted weather observation locations
September 9, 2003
Conference Paper
Published in:
Conf. on Battlespace Atmospheric and Cloud Impacts on Military Operations, BACIMO, 9-11 September 2003.
Summary
Many of the recent conflicts where the United States (US) military forces have been deployed are regions that contain complex terrain (i.e. Korea, Kosovo, Afghanistan, and northern Iraq). Accurate weather forecasts are critical to the success of operations in these regions and are typically supplied by numerical weather prediction (NWP) models like the US Navy NOGAPS, CAOMPS, and US Airforce MM5. Unfortunately the weather observations required to generate accurate initial conditions needed by these models are often not available. In these cases it is desirable to deploy additional weather sensors. The question then becomes: Where should the military planners deploy their sensor resources? This study demonstrates that knowledge of just the terrain within the model domain may be a useful factor for military planners to consider. For NWP, model forecast errors in mountainous areas are typically thought to be due to poorly resolved terrain, or model physics not suited for use in a complex terrain environment. Recent advances in computational technology are making it possible to run these models at resolutions where many of the significant terrain features are now being well resolved. While terrain can be accurately specified, often the gradients in wind, temperature, and moisture fields associated with the higher resolution terrain are not. As a result, initial conditions in complex terrain environments are not be adequately specified. Since not all initial condition errors contribute significantly to model forecast error, knowledge of terrain induced NWP model forecast sensitivity may be important when developing and deploying a weather sensor network to support a regional scale NWP model. The terrain induced model sensitivity can provide an indication of which variables in the initial conditions have a significant influence on the forecast and where initial conditions need to be most accurate to minimize model forecast error. A sensor network can then be designed to minimize these errors by deploying critical sensors in sensitive locations, thereby reducing relevant initial condition error without the costly deployment of a high-density sensor network. This is similar to the targeted observation technique first suggested by Emanuel et al. (1995), except that in this example the targeted observations would be designed to reduce initial condition error associated with poorly resolved atmospheric features created by the terrain. This paper is organized as follows. Section 2 contains a brief description of the data collection effort designed to support this study. The experimental design and the specifics of the case used in this study are described in section 3. The analysis and results from both the forward and adjoint simulations are presented in section 4. Section 5 contains a summary of the results, and a brief discussion of their implications.
Summary
Many of the recent conflicts where the United States (US) military forces have been deployed are regions that contain complex terrain (i.e. Korea, Kosovo, Afghanistan, and northern Iraq). Accurate weather forecasts are critical to the success of operations in these regions and are typically supplied by numerical weather prediction (NWP)...
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The effect of topography on the initial condition sensitivity of a mesoscale model
June 23, 2003
Conference Paper
Published in:
10th Conf. on Mesoscale Processes, 23-27 June 2003.
Summary
Errors in NWP model forecasts are typically due to deficiencies in the model formulation, inaccuracies associated with the numerical integration techniques, and errors in the specification of initial conditions. This study investigates the latter of these three issues and, in particular, elucidates the errors in the initial conditions due to inadequate data resolution. In a basic sense, for the atmosphere to be adequately sampled at a given length scale, it is not always necessary to increase the number of samples throughout the entire domain. Increased sampling resolution has the greatest benefit in the regions where gradients in the atmospheric conditions exist. Targeted observation techniques attempt to take advantage of this fact by using additional observations to improve the initial analysis in the regions that will have the most impact on forecast accuracy (Emanuel et al. 1995). The result is an economical means to reduce initial condition error and improve forecast accuracy. It is well known that terrain can serve as a localized forcing mechanism in high-resolution models. In addition to acting as a forcing mechanism, variations in terrain can also create strong gradients in the atmospheric fields of models using terrain following vertical coordinates. It is reasonable to assume that if these gradients were better represented in the initial conditions, forecasts accuracies could improve. The present study examines the relationship between terrain variability and the sensitivity of a high-resolution wind forecast to errors in the initial conditions in these areas. The background behind this study and a brief description of the terrain and atmospheric characteristics of the cases used in the experiments are presented in section 2. Initial condition sensitivity analysis results from the fifth generation Pennsylvania State University (PSU), National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) adjoint and forward models are contained in sections 3 and 4. A summary of the results and conclusions are found in section 5.
Summary
Errors in NWP model forecasts are typically due to deficiencies in the model formulation, inaccuracies associated with the numerical integration techniques, and errors in the specification of initial conditions. This study investigates the latter of these three issues and, in particular, elucidates the errors in the initial conditions due to...
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