Publications

In this work, machine learning and image processing methods are used to estimate radar-like precipitation intensity and echo top heights beyond the range of weather radar. The technology, called the Offshore Precipitation Capability (OPC), combines global lightning data with existing radar mosaics, five Geostationary Operational Environmental Satellite (GOES) channels, and several fields from the Rapid Refresh (RAP) 13 km numerical weather prediction model to create precipitation and echo top fields similar to those provided by existing Federal Aviation Administration (FAA) weather systems. Preprocessing and feature extraction methods are described to construct inputs for model training. A variety of machine learning algorithms are investigated to identify which provides the most accuracy. Output from the machine learning model is blended with existing radar mosaics to create weather radar-like analyses that extend into offshore regions. The resulting fields are validated using land radars and satellite precipitation measurements provided by the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement Mission (GPM) core observatory satellite. This capability is initially being developed for the Miami Oceanic airspace with the goal of providing improved situational awareness for offshore air traffic control.

This report evaluates the incremental operational benefits of a proposed Lightning Mapping Sensor (LMS) for NOAA's Geostationary Operational Environmental Satellites (GOES). If deployed, LMS would provide continuous, real-time surveillance of total lightning activity over large portions of the North and South American continents and surrounding oceans. In contrast to the current National Lightning Detection Network, LMS would monitor total lightning activity, including the dominant intracloud component which is estimated to occur with order of magnitude greater frequency than cloud-to-ground lightning and may occur ten minutes or more in advance of a storm's first ground flash.

Air traffic congestion in the United States (US) is a serious national problem resulting in a critical need for timely, reliable and high quality forecasts of precipitation and echo tops with forecast time horizons of up to 8 hours. In order to address the short-term needs of the Federal Aviation Administration (FAA) as well as the long-term goals of the US's Next Generation Airspace System (NextGen), MIT Lincoln Laboratory, NCAR Research Applications Laboratory and NOAA Earth Systems Research Laboratory (ESRL) Global Systems Division (GSD) are collaborating on developing a forecast system under funding from the FAA's Aviation Weather Research Program (AWRP). The CoSPA system combines the latest technologies in heuristic nowcasting, extrapolation, statistical techniques and numerical weather prediction to produce rapidly updating (15 min) 0-8 hour forecasts of storm locations, echo tops and intensities. The system blends highly-skillful heuristic nowcasts with output from NOAA's High Resolution Rapid Refresh (HRRR) using phase correction and statistical weighting functions. The CoSPA 0-8 hour forecasts are accessible to the aviation community via an operational situation display and a website that builds upon the FAA's Corridor Integrated Weather System (CIWS) and shows current time situational awareness products including: VIL, echo tops, lightning, growth and decay, forecasts and verification contours, as well as an animation of the weather from 8 hours in the past to 8 hours into the future. This presentation will include a brief description of the CoSPA forecast system and display, examples of forecast performance, and provide an overview of recent enhancements to CoSPA as well as ongoing research.

As new observation systems are developed and deployed, new and presumably more precise information is becoming available for weather forecasting and climate monitoring. To take advantage of these new observations, it is desirable to have schemes to accurately retrieve the information before statistical analyses are performed so that statistical computation can be more effectively used where it is needed most. The authors propose a sequential variational approach that possesses advantages of both a standard statistical analysis [such as with a three-dimensional variational data assimilation (3DVAR) or Kalman filter] and a traditional objective analysis (such as the Barnes analysis). The sequential variational analysis is multiscale, inhomogeneous, anisotropic, and temporally consistent, as shown by an idealized test case and observational datasets in this study. The real data cases include applications in two-dimensional and three-dimensional space and time for storm outflow boundary detection (surface application) and hurricane data assimilation (three-dimensional space application). Implemented using a multigrid technique, this sequential variational approach is a very efficient data assimilation method.

The long-term objectives for the NextGen Weather Processor (NWP) include consolidation of today's multiple weather systems, incorporation of recent and emerging Federal Aviation Administration (FAA) infrastructure (Federal Telecommunications Infrastructure (FTI), System Wide Information Management (SWIM), NextGen Network-Enabled Weather (NNEW)), leveraging National Oceanic and Atmospheric Administraiton (NOAA) and/or commercial weather resources, and providing a solid development and runn-time platform for advanced aviation weather capabilities. These objectives are to be achieved in a staged fashion, ideally with new components coming on-line in time to replace existing capabilities prior to their end-of-life dates. As part of NWP Segment 1, a number of alternative implementations for the NWP as it might exist in the 2013 time frame have been proposed. This report examines the alternatives form a top-down technical perspective, assessing how well each maps to a high-level NWP architecture consistent with the long-term NextGen information sharing vision. Tehcnical challenges and opportunities for weather product improvements associated with each alternative are discussed. Additional alternatives consistent with the high-level NWP architecture, as well as a number of suggested follow-on analysis efforts are also presented.

Convective storms are responsible for causing a predominant number of delays in the summer when air traffic peaks. Several studies have shown that there is a critical need for timely, reliable, and high-quality forecasts of precipitation and echo tops with forecast time horizons of up to 12 hours in order to predict airspace capacity (Robinson et al. 2008; Evans et al. 2006; FAA 2007). While a variety of convective weather forecast systems are available to strategic planners of the National Airspace System (NAS), these products don't meet Air Traffic Management (ATM) needs fully. In addition, a multitude of forecast products increases the potential of having conflicting information available in the planning process, which can cause situational awareness problems between the operational facilities, ultimately leading to more potential delays and perhaps safety problems.

This report provides recommendations for aligning new Collaborative Air Traffic Management Technologies (CATM-T) with evolving aviation weather products to improve NAS efficiency during adverse (especially severe) weather conditions. Key gaps identified include 1. Improving or developing pilot convective storm avoidance models as well as models for route blockage and capacity in severe weather is necessary for automated congestion prediction and resolution. 2. Forecasts need to characterize uncertainty that can be used by CATM tools and, explicitly forecast key parameters needed for translation of weather products to capacity impacts. 3. Time based flow management will require substantial progress in both the translation modeling and in predicting appropriate storm avoidance trajectories. Near term efforts should focus on integration of the Traffic Management Advisor (TMA) with contemporary severe weather products such as the Corridor Integrated Weather System (CIWS). 4. Human factors studies on product design to improve individual decision making, improved collaborative decision making in "difficult" situations, and the use of probabilistic products are also essential. 5. Studies need to be carried out to determine how well en route and terminal capacity currently is being utilized during adverse weather events so as to identify the highest priority areas for integrated weather-CATM system development.

Air traffic congestion caused by convective weather in the US has become a serious national problem. Several studies have shown that there is a critical need for timely, reliable and high quality forecasts of precipitation and echo tops with forecast time horizons of up to 12 hours in order to predict airspace capacity (Robinson et al. 2008, Evans et al. 2006 and FAA REDAC Report 2007). Yet, there are currently several forecast systems available to strategic planners across the National Airspace System (NAS) that are not fully meeting Air Traffic Management (ATM) needs. Furthermore, the use of many forecasting systems increases the potential for conflicting information in the planning process, which can cause situational awareness problems between operational facilities. One of the goals of the Next Generation Air Transportation System (NextGen) is to consolidate these redundant and sometimes conflicting forecast systems into a Single Authoritative Source (SAS) for aviation uses. The FAA initiated an effort to begin consolidating these systems in 2006, which led to the establishment of a collaboration between MIT Lincoln Laboratory (MIT LL), the National Center for Atmospheric Research (NCAR) Research Applications Laboratory (RAL), the NOAA Earth Systems Research Laboratory (ESRL) Global Systems Division (GSD) and NASA, called the Consolidated Storm Prediction for Aviation (CoSPA; Wolfson et al. 2008). The on-going collaboration is structured to leverage the expertise and technologies of each laboratory to build a CoSPA forecast capability that not only exceeds all current operational forecast capabilities and skill, but that provides enough resolution and skill to meet the demands of the envisioned NextGen decision support technology. The current CoSPA prototype for 0-6 hour forecasts is planned for operation as part of the NextGen Initial Operational Capability (IOC) in 2013. CoSPA is funded under the FAA's Aviation Weather Research Program (AWRP). The first CoSPA research prototype demonstration was conducted during the summer of 2008. Technologies from the Corridor Integrated Weather System (CIWS; Evans and Ducot 2006), National Convective Weather Forecast (NCWF; Megenhardt et al. 2004), and NOAA’s Rapid Update Cycle (RUC; Benjamin et al. 2004) and High Resolution Rapid Refresh (HRRR; Benjamin et al. 2009) models were consolidated along with new technologies into a single high-resolution forecast and display system. Historically, forecasts based on heuristics and extrapolation have performed well in the 0-2 hour window, whereas forecasts based on Numerical Weather Prediction (NWP) models have shown better performance than heuristics past 3-4 hours (Figure 1). One of the goals of CoSPA is to optimally blend heuristics and NWP models into a unified set of aviation-specific storm forecast products with the best overall performance possible. The CoSPA prototype demonstration began in July 2008 with 2-6 hr forecasts of Vertically-Integrated Liquid water (VIL) that seamlessly matched with the 0-2 hr VIL forecasts available in CIWS. These real-time forecasts have been made available to the research team and FAA management only through a web-based interface. This paper discusses the system infrastructure, the forecast display, the forecast technology and performance of the 2-6 hr VIL forecast. Our early assessment based on the 2008 demonstration is that CoSPA is showing tremendous promise for greatly improving strategic storm forecasts for the NAS. Early user feedback during CoSPA briefings suggested that the 6 hr forecast time horizon be extended to 8 hours to better meet their planning functions, and that forecasts of Echo Tops must also be included.

In this paper, we develop a novel way to measure the accuracy of weather forecasts based upon the impact on air traffic flows. This method uses new techniques developed as part of the CWAM that consider the complicated interaction between pilots, air traffic controllers and weather. This technique, known as the blockage model (Martin et al., 2006), differentiates between minor deviations performed by pilots around convective weather and their larger deviations due to fully blocked air routes that require air traffic control interaction. This blockage model is being used by the automated Route Availability Planning Tool (RAPT) to predict route blockage for NYC departures. RAPT integrates the Corridor Integrated Weather Systems (CIWS) deterministic 0-2 hour forecasts of precipitation and echo tops into route specific forecasts of impact on air traffic in the congested east coast corridor. Applying the blockage model to the entire CIWS weather domain as a metric for scoring the performance of the forecast algorithms is shown to be an excellent approach for measuring the adequacy of the forecast in predicting the impact of the convective weather on air traffic operations.

Research over the last 10 years primarily funded by the FAA Aviation Weather Research Program (AWRP) has led to very successful development of forecasts of both convective and winter storms, using heuristic and numerical models, for aviation applications. We have reached a point where there are several overlapping capabilities, and the smorgasbord of choices has become confusing. Moreover, aviation-impacting winter and summer conditions can exist simultaneously - even within a single terminal area - so a consolidated forecast must work equally well for all storm conditions. Advances in computing and communications allow incorporation of new observing systems and scientific advancements in data assimilation and modeling toward large-scale, very high resolution forecast systems that were prohibitive just 10 years ago. Other government agencies, in addition to FAA, have needs for aviation-oriented forecasts, including at least the National Weather Service, NASA, Homeland Defense, Air Force and other DoD agencies. Further efficiencies will be realized by consolidating such efforts as well. These goals are well-aligned with the goals of the Next Generation Air Transportation System and its Joint Program and Development Office. The FAA Aviation Weather Research Program is leading development of the new Consolidated Storm Prediction for Aviation (CoSPA) effort, which will combine aviation-oriented storm research in a coordinated fashion, with the goal of eventually replacing operational legacy storm diagnostic and forecast products, as appropriate, that are also geared toward aviation (see Appendix A). While many of the current storm prediction products are derived using NOAA model forecast data, especially from the hourly updated 13-km Rapid Update Cycle (RUC) model over CONUS, CoSPA products will be related to a new generation of NOAA models now assimilating radar reflectivity and lightning, including the Rapid Refresh, its proposed nest - the High-Resolution Rapid Refresh (HRRR), and ensemble-based products from both. A kick-off meeting was held in June 2006 to discuss AWRP?s concepts for a consolidated aviation forecast, and to understand unmet user needs, major scientific development issues, and also to begin to explore issues associated with production and dissemination of a consolidated forecast. These findings are summarized below.