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At least 703 records · Page 39

Operational Concept for the Smart Landing Facility (SLF)

The purpose of this document is to describe an operational concept for the Smart Landing Facility (SLF). The SLF is proposed as a component of the Small Aircraft Transportation System (SATS) and is envisioned to utilize Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM) technologies to support higher-volume air traffic operations in a wider variety of weather conditions than are currently possible at airports without an Air Traffic Control Tower (ATCT) or Terminal Radar Approach Control (TRACON). In order to accomplish this, the SLF will provide aircraft sequencing and separation within its terminal airspace (the SLF traffic area) and on the airport surface. The approach taken in this report is to first define and describe the SLF environment and the type of operations and aircraft that must be supported. Services currently provided by an ATCT and TRACON are reviewed and assembled into a set of high-level operational functions. A description of the applicable CNS/ATM technologies that have been deployed in the NAS (National Airspace System) or have been demonstrated to be operationally feasible is presented. A candidate SLF system concept that employs the CNS/ATM technologies is described. This is followed by SLF operational scenarios for minimally-equipped aircraft and for aircraft fully-equipped to make full use of SLF services. An assessment is made of the SLF technology and key research issues are identified.

Thompson, S. D.↗

Assessments of Total Lightning Data Utility in Weather Forecasting

National Weather Service forecasters in Huntsville, Alabama have had access to total lightning data from the North Alabama Lightning Mapping Array (LMA) since 2003. Forecasters can monitor real-time total lightning observations on their AWIPS (Advanced Weather Interactive Processing System (AWIPS) workstations. The lightning data is used to supplement other observations such as radar and satellite data. The lightning data is updated every 2 min, providing more timely evidence of storm growth or decay than is available from 5 min radar scans. Total lightning observations have been used to positively impact warning decisions in a number of instances. A number of approaches are being pursued to assess the usefulness of total lightning measurements to the operational forecasting community in the warning decision process. These approaches, which include both qualitative and quantitative assessment methods, will be discussed. submitted to the American Meteorological Society (AMS) Conference on Meteorological Applications of Lightning Data to be held in San Diego, CA January 9-13,2005. This will be a presentation and an extended abstract will be published on a CD available from the AMS.

Buechler, Dennis E.↗

Ellicott City Disasters II - Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

Ellicott City Disasters III: Building a Real-Time Statistical Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

Recommendations for a wind profiling network to support Space Shuttle launches

The feasibility is examined of a network of clear air radar wind profilers to forecast wind conditions before Space Shuttle launches during winter. Currently, winds are measured only in the vicinity of the shuttle launch site and wind loads on the launch vehicle are estimated using these measurements. Wind conditions upstream of the Cape are not monitored. Since large changes in the wind shear profile can be associated with weather systems moving over the Cape, it may be possible to improve wind forecasts over the launch site if wind measurements are made upstream. A radar wind profiling system is in use at the Space Shuttle launch site. This system can monitor the wind profile continuously. The existing profiler could be combined with a number of radars located upstream of the launch site. Thus, continuous wind measurements would be available upstream and at the Cape. NASA-Marshall representatives have set the requirements for radar wind profiling network. The minimum vertical resolution of the network must be set so that the wind shears over the depths greater than or = 1 km will be detected. The network should allow scientists and engineers to predict the wind profile over the Cape 6 hours before a Space Shuttle launch.

Zamora, R. J.↗

GPM Microwave Imager Engineering Model Results

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dualfrequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element ofGPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

Newell, David↗

Virtual Environment Design for Low/Zero Visibility Tower Tools

This paper describes prototype software for three-dimensional display of aircraft movement based on realtime radar and other Air Traffic Control (ATC) information. This prototype can be used to develop operational tools for controllers in ATC Towers who cannot view aircraft in low or zero visibility (LZV) weather conditions. The controller could also use the software to arbitrarily reposition his virtual eyepoint to overcome physical obstructions or increase situation awareness. The LZV Tower tool prototype consists of server and client components. The server interfaces to operational ATC radar and communications systems, sending processed data to a client process written in java. This client process runs under Netscape Communicator to provide an interactive perspective display of aircraft in the airport environment. Prototype VRML airport models were derived from 3-D databases used in FAA-certified high fidelity flight-simulators. The web-based design offers potential efficiency increases and decreased costs in the development and deployment of operational LZV Tower tools.

Reisman, Ron↗

Unraveling the 2021 Central Tennessee flood event using a hierarchical multi-model inundation modeling framework

Flood prediction systems need hierarchical atmospheric, hydrologic, and hydraulic models to predict rainfall, runoff, streamflow, and floodplain inundation. The accuracy of such systems depends on the error propagation through the modeling chain, sensitivity to input data, and choice of models. In this study, we used multiple precipitation forcings (hindcast and forecast) to drive hydrologic and hydrodynamic models to analyze the impacts of various drivers on the estimates of flood inundation depth and extent. We implement this framework to unravel the August 2021 extreme flooding event that occurred in Central Tennessee, USA. We used two radar-based quantitative precipitation estimates (STAGE4 and MRMS) as well as quantitative precipitation forecasts (QPF) from the National Weather Service Weather Prediction Center (WPC) to drive a series of models in the hierarchical framework, including the Variable Infiltration Capacity (VIC) land surface model, the Routing Application for Parallel Computation of Discharge (RAPID) river routing model, and the AutoRoute and TRITON inundation models. An evaluation with observed high-water marks demonstrates that the framework can reasonably simulate flood inundation. Despite the complex error propagation mechanism of the modeling chain, we show that inundation estimates are most sensitive to rainfall estimates. Most notably, QPF significantly underestimates flood magnitudes and inundations leading to unanticipated severe flooding for all stakeholders involved in the event. Finally, we discuss the implications of the hydrodynamic modeling framework for real-time flood forecasting.

54 ENVIRONMENTAL SCIENCES↗

Development and flight test of a helicopter, X-band, portable precision landing system concept

A beacon landing system (BLS) is being developed and flight tested as a part of NASA's Rotorcraft All-Weather Operations Research Program. The system is based on state-of-of-the-art X-band radar technology and digital processing techniques. The bLS airborne hardware consists of an X-band receiver and a small micropreocessor, installed in conjunction wht the aircraft instrument landing system (ILS) receiver. The microprocessor analyzes the X-band, BLS pulses and outputs ILS-compatible localizer and glide slope signals. Range information is obtained using an on-board weather/mapping radar in conjunction with the BLS. The ground station is an inexpensive, portable unit; it weighs less than 70 lb and can be quickly deployed at a landing site. Results from the flight-test program show that the BLS has a significant potential for providing rotorcaraft with low-cost, precision instrument approach capability in remote areas.

Davis, T. J.↗

System concepts for transmit arrays of parabolic antennas for deep space uplinks

Phased arrays of parabolic antennas are a potentially lower-cost way to provide uplink transmission to distant spacecraft, compared to the 34-m and 70-m antennas now used by the NASA Deep Space Network. A large transmit array could provide very high EIRP when needed for spacecraft emergencies, such as the equivalent of 1 MW radiated from a 70-m antenna. Cost-effectiveness is realized by dividing the array into smaller arrays to provide routine support to many spacecraft simultaneously. The antennas might be as small as 12-m in diameter, with as many as 100 antennas covering an area of 0.5 km to 1 km in extent. Such arrays present significant technical challenges in phase alignment, which must be maintained at close to 1 mm. The concept requires a very stable system with accurately known antenna phase center locations. The system is first calibrated by transmitting from all antennas, and observing the signals at a target located in the far fields of the individual antennas. The antennas are then pointed to the operational targets, with the signal phases and time delays set to reinforce in the target directions. This requires accurate knowledge of the target directions and calculation of the required phases. The system must be phase-stable for all directions and over the time between calibrations, which is desired to be at least one day. In this paper, a system concept is presented, the major error sources are identified, a rough error budget is established, and key elements of the system are discussed. A calibration method is recommended which uses satellites as radar targets. The performance goal is to achieve a combining loss of less than 0.2 dB in good weather, and of less than 1 dB in all but extremely bad weather.

Effective Isotropic Radiated Power (EIRP)↗

The Weekend Effect for Precipitation Over Eastern U.S.: Evidence for Midweek Storm Intensification by Pollution

Every week the U.S. population carries out a climate-change experiment by varying their activities with the day of the week. It is well documented that pollution levels vary on a weekly basis. Particulate aerosol pollution is generally a maximum in the middle of the week and a minimum on weekends. It is also well known that aerosols can affect precipitation, although whether they suppress or enhance storm development depends on many factors. The Tropical Rainfall Measuring Mission (TRMM) satellite has provided evidence that rain statistics change with the day of the week over the southeast U.S. and neighboring waters during the summer months (JJA) of 1998-2005. There is a midweek increase in both rain area and intensity over land, and a midweek decrease over the nearby Atlantic and perhaps the Gulf of Mexico. Statistical tests suggest that the weekly variations are very unlikely to be due to the random behavior of weather. We will discuss the TRMM evidence. Wind data from model reanalysis, rain-gauge data, and TRMM radar data all appear to be consistent with the picture that aerosols are causing summertime storms to grow more vigorously and to produce more rainfall.

Bell, Thomas↗

GPM Microwave Imager Design, Predicted Performance and Status

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (t.JASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dual-frequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element of GPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

Krimchansky, Sergey↗

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (≤1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Li, Xuanli↗

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (≤1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Li, Xuanli↗

Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle

A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.

Joseph, A.T.↗

Storm Chasing from Space: Detecting severe weather phenomena from satellite platforms

Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.

Sarah D. Bang↗

Storm Chasing from Space: Detecting Severe Weather Phenomena from Satellite Platforms

Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.

Sarah D Bang↗