Publications

The Next Generation Weather Radar (NEXRAD) dual polarization upgrade has begun adding a functional enhancement to classify hydrometeors. MIT Lincoln Laboratory (LL) develops NEXRAD-based weather radar products for Federal Aviation Administration (FAA) weather systems such as Corridor Integrated Weather System (CIWS), Integrated Terminal Weather System (ITWS), and Weather and Radar Processor (WARP). Without dual polarization, those products are limited to providing information on precipitation location and intensity. With dual polarization, LL is now developing new aviation weather products to determine locations of hydrometeor-based hazards. A product for Icing Hazards Level (IHL) is expected to benefit the FAA. LL has partnered with Valparaiso University (VU) in northern Indiana near Chicago since 2008 to study the evolution of winter storms prior to the NEXRAD dual polarization upgrade. VU contributes to the study a C-band dual polarization weather radar, an on-demand local sounding capability, and a surface winter weather verification team. Additionally, the Wolcott, IN wind profiler is about 70 km south within viewing range of the VU radar, and provides information on the fall speeds of the hydrometeors of interest. This resource-rich location has allowed for substantive study of many winter storm types: synoptic, lake effect, and frontal passages. A key to development of the IHL product is the ability to interpret dual polarization radar signatures from the winter microphysical states and precipitation structures. Evolution of the structures is a response to the microphysical water and ice saturation (sub or super) states. The magnitude of the vertical lift may affect the saturation states. Methods to segregate the radar signatures will be important regarding the inferred presence of a supercooled water icing hazard. The blizzard of Feb. 1 and 2, 2011 produced four distinct precipitation periods (snow, sleet, freezing drizzle, and lake effect snow), all of which will be discussed. The paper and presentation will also detail findings from the study of multiple winter storms and how they inform the development of the IHL product.

Weather radar products from the United States' NEXRAD network are used as key components in FAA weather systems such as CIWS, ITWS, and WARP. The key products, High Resolution VIL (HRVIL) and High Resolution Enhanced Echo Tops (HREET), provide primary information about precipitation location and intensity. The NEXRAD network will become dual polarization capable beginning in late 2010 adding the ability to classify hydrometeors. This new aspect from radar remote sensing of the weather offers opportunity to provide new aviation weather products and augment existing ones. This paper will detail the dual polarization product development program at MIT Lincoln Laboratory (LL) in support of FAA system needs. Current development efforts focus on four products. Two new products will provide volumetric analysis seeking aviation hazards (icing and hail). Two existing products, HRVIL and HREET, will be invigorated by dual polarization data to yield improved data quality and mitigation of partial beam blockage. The LL program has partnered with NCAR and NSSL subject matter experts to bring their most advanced research results into these new and improved products. The LL program also has partnered with Valparaiso University for them to provide dual polarization and local sonde sounding data especially during suspected icing conditions. The new Icing Hazards Level (IHL) product is expected to provide the most benefit to the FAA. Its development also poses the greatest challenge both in scope and in the ability of S-band radar to sense the phenomena of interest. Icing phenomena include supercooled drops/droplets and ice crystals and the associated aviation hazard could be aloft or near/at the surface. Graupel is an indication that supercooled water has accreted to ice particles. The initial NEXRAD hydrometeor classifier will not have an explicit supercooled water class or the benefit of supporting data. It will have ice crystal and graupel classes. The LL approach will utilize at least some additional data (vertical thermodynamic profiles). Techniques applied to the development of IHL will likely have applicability to the other products as well. Aspects of the IHL development will also be discussed in the paper.

A fundamental function of any aviation weather system is to provide accurate and timely weather information tailored to the specific air traffic situations for which a system is designed. Weather location and intensity are of prime importance to such systems. Knowledge of the weather provides "nowcasting" functionality in the terminal and en route air spaces. It also is used as input into aviation weather forecasting applications for purposes such as storm tracking, storm growth and decay trends, and convective initiation. Weather radar products are the primary source of the weather location and intensity information used by the aviation weather systems. In the United States, the primary radar sources are the Terminal Doppler Weather Radar (TDWR) and the Weather Surveillance Radar 1988 Doppler (WSR-88D, known as NEXRAD). Additional weather radar products from the Canadian network are used by some of the aviation weather systems. Product quality from all these radars directly impacts the quality of the down stream products created by the aviation weather systems and their utility to air traffic controllers. Four FAA weather systems use some combination of products from the aforementioned radars. They are the Corridor Integrated Weather System (CIWS), the Integrated Terminal Weather System (ITWS), the Weather and Radar Processor (WARP), and the Medium Intensity Airport Weather System (MIAWS). This paper focuses on the improvement of weather radar data quality specific to CIWS. The other mentioned FAA aviation weather systems also benefit either directly or indirectly from the improvements noted in this paper. For CIWS, the legacy data quality practices involve two steps. Step one is the creation of weather radar products of highest possible fidelity. The second step involves creating a mosaic from these products. The mosaic creation process takes advantage of inter-radar product comparisons to interject a further level of improved data quality. The new CIWS data quality plan will use a mounting evidence data quality classifier technique currently being developed. The technique applies a multi-tiered approach to weather radar data quality. Its premise is that no single data quality improvement technique is as effective as a collaboration of many. The evidence will be expanded to include data and products from the radars along with data from additional sensing platforms. The mosaic creation process will correspondingly expand to take advantage of the additional evidence. Section 2 covers data quality of products from the single radar perspective. Section 3 focuses on the use of satellite data as the first additional sensing platform to augment removal of problematic radar contamination. Section 4 describes the data quality procedures associated with creation of mosaics from the single radar products augmented with new satellite masking information. Last, Section 5 discusses future plans for the mounting evidence data quality improvement technique.

The NEXRAD program will begin fielding a dual polarization capability in 2009. Three additional base data parameters and two additional derived parameters from the dual polarization capability will be produced to complement the traditional three radar moments. The initial use of the added data is to provide a dual-polarization-based quantitative precipitation estimate (QPE) algorithm. Other NEXRAD algorithms will have access to the new dual polarization parameters as well as the derived products. The National Severe Storms Laboratory coordinated a dual polarization product evaluation to solicit NEXRAD agency participant feedback regarding potential dual polarization products. The evaluation consisted of analyzing dual polarization data from seven weather cases. MIT Lincoln Laboratory participated in the evaluation. The evaluation opportunity was used to have early access to prototypical dual polarization data to consider the potential benefit to FAA weather systems. This report introduces the new dual polarization pararmeters, presents some of the relevant weather cases, and provides recommendations regarding use of the dual polarization parameters.

Over a decade ago the FAA identified a need to detect and forecast movement of wind shear hazards such as gust fronts that impact the terminal air space. The Machine Intelligent Gust Front Algorithm (MIGFA) was developed to address this need (Delanoy and Troxel, 1993). The MIGFA product provides the position, the forecasted positions, and the strength of each wind shear detection to support air traffic control safety and planning functions. MIGFA will realize a new capability for NEXRAD but was originated for use with the FAA's Airport Surveillance Radar Model 9 (ASR-9) Weather Systems Processor (WSP) as described in Troxel and Pughe (2002). Subsequently, a second version was developed for the FAA's Terminal Doppler Weather Radar (TDWR) and is a component of the FAA's Integrated Terminal Weather System (ITWS). Most of the larger U.S. airports have ITWS installations. The ASR-9s are associated with medium-sized airports. MIGFA in NEXRAD is intended to further expand MIGFA support of air traffic control functions. There are significant algorithmic differences between the ASR-9 WSP and TDWR versions of MIGFA, primarily because of the different beam types of the two radars. Physically, the TDWR's pencil beam allows for good vertical resolution in a spatial volume of data. The ASR-9's vertical fan beam results in poor vertical resolution. Nonetheless, a key tenet in developing these two versions of MIGFA was to use the same core image processing analysis techniques (Morgan and Troxel, 2002) central to the MIGFA functionality. This same core is also central to MIGFA in NEXRAD. The Massachusetts Institute of Technology's Lincoln Laboratory (LL) has been tasked by the FAA to transfer MIGFA technology to NEXRAD. The goal is to enable a NEXRAD MIGFA capability at airports within about 70 km of any NEXRAD. LL has been developing NEXRAD algorithms to address the FAA's weather systems' needs since the Open Radar Product Generator (ORPG) was fielded in 2001. FAA sponsored, LL-developed NEXRAD algorithms generate the following products: the Data Quality Assurance (DQA), the High Resolution VIL (HRVIL), and the High Resolution Enhanced Echo Tops (HREET) (Smalley et al., 2003). These algorithms have proven useful to non-FAA users of NEXRAD products such as the National Weather Service (NWS) and the Department of Defense (DoD). Similarly, the NWS and DoD are developing plans to use MIGFA. MIGFA is slated to be included in the ORPG Build 9 baseline that is scheduled to be released in the Spring of 2007. In the following sections, we will discuss the salient features of MIGFA; the tuning of MIGFA to NEXRAD data; a comparison of detection performance of the TDWR and NEXRAD MIGFA versions; and some examples of MIGFA in operation.

A radar data quality control (QC) system is being developed for the real-time, continuously updateable NOWCAST system at the Naval Research Laboratory (NRL-NOWCAST) in Monterey, California. NRL has developed its own new radar QC algorithms, and is also working with the MIT Lincoln Laboratory (MIT LL), the National Center for Atmospheric Research (NCAR), the National Severe Storms Laboratory and the Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma (NSSL-OU) to obtain, adapt, integrate, test and install various types of recently-developed radar QC algorithms for use with NRL-NOWCAST. These algorithms work with volume scans of full-resolution Doppler radar data. Radar data QC can be divided into two categories: echo classification (EC) and calibration. New EC algorithms have recently demonstrated substantial success at separating the radar echoes of precipitation from other echo types, such as noise, normal propagation (NP) and anomalous propagation (AP) ground clutter, sea clutter, insects/clear-air, birds, second-trip echoes, and constant power function (CPF) artifacts. Radar data calibration methods assess the accuracy of both the data values and data coordinates. One calibration issue is aliased radial velocity data from precipitation and insect/clear-air returns, which if correctly de-aliased, afford the opportunity to estimate winds. Another calibration issue of concern to NRL is the processing of radar data from mobile platforms, such as US Navy ships. This processing requires corrections to the radial velocity data and the data-coordinates for the motion of the platform, as well as corrections for the altitude of the data coordinates due to the AP of the radar beam that frequently occurs within surface and evaporation ducts of the marine atmosphere. The goal of this work is to test the performance of the most current and promising radar data QC algorithms on archived data sets, both from ground- and sea-based radars, in order to determine the optimal combination for future real-time use within NRL-NOWCAST. NRL-NOWCAST currently ingests full-resolution Doppler radar data from both the Weather Surveillance Radar-1988 Doppler (WSR-88D) network and the US Department of Defense (DoD) Supplemental Weather Radar (SWR) at the Naval Air Station (NAS) in Fallon, NV. Various products are then created from these data for NRL-NOWCAST display. The radar data are also ingested into the COAMPS-0S (R) (Geiszler et al. 2004) data assimilation system at NRL. Figure 1 shows a flow chart that summarizes the processing stages and uses of radar data at NRL. Figure 2 shows an example of the NRL-NOWCAST demonstration site currently set up at Fallon, where the specific products displayed are only a few from a large list that may be chosen by the forecasters at the NAS. This paper presents a brief overview of the concepts behind the various EC and radial velocity de-aliasing algorithms under consideration. Test results from an NRL algorithm-testing platform will also be presented along with some previously published test results from the authors. Additional test results from the platform will be presented at the conference. Methods to address data-value and data coordinate calibration problems associated with Doppler radars onboard US Navy ships are currently being studied; a discussion on future work in this area will be outlined.

In this paper, we describe a major new FAA initiative, the Corridor Integrated Weather System (CIWS), to improve convective weather decision support for congested en route airspace and the terminals within that airspace through use of a large, heterogeneous network of weather sensing radars as well as many additional sensors. The objective of the CIWS concept exploration is to determine the improvements in NAS performance that could be achieved by providing en route controllers, en route and major terminal traffic flow managers, and airline dispatch with accurate, fully automated high update-rate information on current and near term (0-2 hour) storm locations, severity and vertical structure so that they can achieve more efficient tactical use of the airspace. These "tactical" traffic flow management products will complement the longer-term (2-6 hr) forecasts that are also needed for flight planning and strategic traffic flow management. Since balancing the en route traffic flows in the presence of time varying impacts on sector capacities by convective weather is essential if delays are to be reduced, an important element of the CIWS initiative is interfacing to and, in some cases providing, air traffic flow management (TFM) and airline dispatch decision support tools (DSTs)

The initial release of a new operational open architecture is currently being phased into the national WSR-88D (NEXRAD) radar network. This new Common Operations and Development Environment (CODE) includes the Open Radar Product Generator (ORPG) that replaces the existing NEXRAD Radar Product Generator. The new ORPG includes all the algorithms of the RPG it replaces. Future algorithms designed for use within NEXRAD also will be processed by the ORPG. CODE can also be used in a research capacity to significantly enhance the process of ORPG meteorological algorithm development. When used independently of a NEXRAD installation, CODE/ORPG provides multiple playback options for accessing real-time base data streams. This allows development and testing of new algorithms under the same environment an algorithm would encounter in an operational setting. This establishes a flow relationship from algorithm development through operational implementation within the common environment of CODE/ORPG. A six-month Build cycle for future CODE/ORPG releases has been established. An algorithm developed in a research CODE/ORPG capacity has an opportunity, at six-month intervals, to garner agency approval and undergo final preparation for operational release. The NEXRAD Radar Operations Center (ROC) needs about eight months preparation time from algorithm submission until release of the next CODE/ORPG version. For instance. Build 2 is to be released September 30. 2002. Algorithms for Build 2 inclusion had to be submitted by January 31, 2002. It will take about three months after the release for the entire NEXRAD network to be updated. The deadline for Build 3 submission is in July 2002 with a release date set in March 2003. Multiple Federal Aviation Administration (FAA) critical systems rely on products from NEXRAD algorithms. These projects include ITWS (Integrated Airport Weather System), WARP (Weather and Radar Processing), and ClWS (Corridor Integrated Weather System). Some of the NEXRAD products used include severe storm information, composite reflectivity factor depictions, and velocity data. In this paper, we discuss new algorithms and modifications to existing algorithms earmarked for the first few releases of the CODE/ORPG that produce products of importance to these FAA systems. They include modifications to the existing Anomalous Propagation Edited Composite Reflectivity algorithm released during Build 1 upgrades, a new high resolution, digital VIL (Vertically Integrated Liquid) algorithm slated for Build 2, and a Data Quality Assurance algorithm anticipated for Build 3.

A number of Federal Aviation Administration (FAA) critical systems rely on products from the NEXRAD (WSR-88D) suite of algorithms. These systems include MIAWS (Medium Intensity Airport Weather System), ITWS (Integrated Terminal Weather System), CIWS (Corridor Integrated Weather System), and WARP (Weather and Radar Processing). With the advent of the NEXRAD Open Radar Product Generator (ORPG), a six-month build cycle has been established for the incorporation of new or improved algorithms. This build cycle provides the mechanism for the integration of new products into the algorithm suite tailored to the needs of these FAA systems now and into the future. Figure 1 is useful for visualizing the MIT/LL ORPGnet. Four of the ORPGnet systems are located at MIT/LL headquartered in Lexington, MA. These four systems form the core of the development center where algorithms are developed for and implemented into the ORPG environment. Part of the development process includes examination of algorithm products created from past weather. A number of utilities are available for playback of various versions of NEXRAD Archive II base data: from tape or disk files in standard or LDM formats. Additionally, MIT/LL operates the CIWS demonstation project for the FAA. The ORPG clones at the development center have access to base data from 26 NEXRAD radars from the Midwest to the East Coast of the United States ingested for CIWS. The FAA has tasked the Massachusetts Institute of Technology's Lincoln Laboratory (MIT/LL) with developing algorithms for the ORPG to address their systems' needs. Many of these algorithms will also prove useful to other users of NEXRAD products such as the National Weather Service and the Department of Defense. MIT/LL has created a network of ten ORPGs, or an ORPGnet, to use for the purpose of developing, testing, and implementing new algorithms targeted to specific builds. The benefits of the ORPGnet will be discussed in more detail later in this paper. MIT/LL has provided improvements to existing algorithms or developed new algorithms for the first three build cycles of the ORPG (Istok et al., 2002; Smalley and Bennett, 2002). Development of more algorithms is currently in progress for upcoming build cycles. In addition to describing ORPGnet, this paper will focus on its use in the development of a new Data Quality Assurance (DQA) algorithm, an improved High Resolution VIL (HRVIL) algorithm, and progress on the development of the enhanced Echo Tops (EET) algorithm; as well as the symbiotic relationship of these algorithms to the FAA critical systems.