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The First Seasat-A Industrial Users Workshop

The purpose of this workshop was to begin the process of definition and development of the SEASAT-A Demonstration Program, leading to the implementation of a set of experiments which would begin during the latter part of 1978 following the launch of SEASAT-A (now scheduled for May 1978). NASA through the SEASAT-A program, has encouraged the planning of cooperative experiments by industry and government agencies that operate in areas of ocean activity that could benefit from improved measurements and forecasts of weather and ocean conditions. The objectives of these experiments are to: (1) evaluate the significance of SEASAT-A data to commercial user organizations; (2) assist in identifying those characteristics of follow-on systems that are important to industrial users; (3) obtain experimental evidence that could be used to refine estimates of the economic potential of an operational system; and (4) begin the technology transfer process to the industrial users.

Hicks, K. W.↗

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗

Users Guide for the Anvil Threat Corridor Forecast Tool V1.7.0 for AWIPS

The Applied Meteorology Unit (AMU) originally developed the Anvil Threat Sector Tool for the Meteorological Interactive Data Display System (MIDDS) and delivered the capability in three phases beginning with a feasibility study in 2000 and delivering the operational final product in December 2003. This tool is currently used operationally by the 45th Weather Squadron (45 WS) Launch Weather Officers (LWO) and Spaceflight Meteorology Group (SMG) forecasters. Phase I of the task established the technical feasibility of developing an objective, observations-based tool for short-range anvil forecasting. The AMU was subsequently tasked to develop short-term anvil forecasting tools to improve predictions of the threat of triggered lightning to space launch and landing vehicles. Under the Phase II effort, the AMU developed a nowcasting anvil threat sector tool, which provided the user with a threat sector based on the most current radiosonde upper wind data from a co-located or upstream station. The Phase II Anvil Threat Sector Tool computes the average wind speed and direction in the layer between 300 and 150 mb from the latest radiosonde for a user-designated station. The following threat sector properties are consistent with the propagation and lifetime characteristics of thunderstorm anvil clouds observed over Florida and its coastal waters (Short et al. 2002): a) 20 n mi standoff circle, b) 30 degree sector width, c) Orientation given by 300 to 150 mb average wind direction, d) 1-, 2-, and 3- hour arcs in upwind direction, and e) Arc distances given by 300 to 150 mb average wind speed. Figure 1 is an example of the MIDDS Anvil Threat Sector tool overlaid on a visible satellite image at 2132 UTC 13 May 2001. Space Launch Complex 39A was selected as the center point and the Anvil Threat Sector was determined from upper-level wind data at 1500 UTC in the preconvective environment. Narrow thunderstorm anvil clouds extend from central Florida to the space launch and landing facilities at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) and beyond. The anvil clouds were generated around 1930 UTC (1430 EDT) by thunderstorm activity over central Florida and transported 90 n mi east-northeastward within 2 hours, as diagnosed by the anvil forecast tool. Phase III, delivered in February 2003, built upon the results of Phase II by enhancing the Anvil Threat Sector Tool with the capability to use national model forecast winds for depiction of potential anvil lengths and orientations over the KSC/CCAFS area with lead times from 3 through 168 hours (7 days). In September 2003, AMU customers requested the capability to use data from the KSC 50 MHz Doppler Radar Wind Profiler (DRWP) in the Anvil Threat Sector Tool and this capability was delivered by the AMU in December 2003. In March 2005, the AMU was tasked to migrate the MIDDS Anvil Threat Sector Tool capabilities onto the Advanced Weather Interactive Processing System (AWIPS) as the Anvil Threat Corridor Forecast Tool.

Bauman, William H., III↗

An Overview of ANN Application in the Power Industry

The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

artificial neural networks ANN electric power syst↗

Observing Fast Mesoscale Atmospheric Processes with a Geostationary Microwave Sounder

A geostationary microwave sounder, GeoSTAR, capable of providing continuous monitoring every 15 minutes of atmospheric temperature, water vapor, clouds, precipitation, and wind in the presence of clouds and precipitation, which will add tremendously to our ability to observe rapidly evolving dynamic atmospheric phenomena, such as hurricanes and severe storms, monsoonal moisture flow, and atmospheric rivers, has been developed at the Jet Propulsion Laboratory. GeoSTAR uses aperture synthesis to overcome the difficulty of attaining adequate spatial resolution from geostationary orbit. It is made possible with new technology that has now been developed and fully tested. Low-risk mission development can start as soon as funding becomes available. The sensor can be hosted on a commercial communications satellite, which could reduce the cost substantially. Plans have been developed at JPL for such a mission, called “GeoStorm”, focused on observing severe convective storms – tropical cyclones, mesoscale convective systems, and extratropical cyclones – with a goal of improving our understanding, modeling and prediction of these destructive phenomena. It can equally well be configured as an operational mission, where the goal is to collect data for immediate assimilation into regional forecast systems, provide “now-casting” as the storms unfold, and support post-disaster relief and recovery efforts. With key observables including vertical profiles of temperature, water vapor, wind and precipitation over a wide area, many focused applications are possible, particularly pertaining to aviation, transportation and marine operations, in both the civilian and defense domains.

Lambrigsten, Bjorn↗

NASA research programs responding to workshop recommendations

The atmospheric electricity and lightning committee forecasts lightning and dissemination of information on the probability of occurrence. A data source with the F-106 flight program was established. The objective is to improve the detectability of lightning and severe storms and help develop operational avoidance procedures and to study the use of satellite and Doppler radar to detect thunderstorms and forecast the probability of lightning. Three recommendations are made: (1) to establish a national flying lightning laboratory; (2) strike models are considered and to gather strike data; (3) to find the best way to apply electrical field data to operations.

Tobiason, A. R.↗

Recursive Blind Forecasting of Photovoltaic Generation and Consumer Load for Microgrids

Existing forecasting frameworks that predict time-series photovoltaic (PV) generation and consumer load for micro-grids' operation and control assume near-continuous availability of real-time predictors from the field. The incoming data are used to periodically re-train the models and update forecast snapshots over a moving horizon window. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. This paper bridges the shortcoming by leveraging a previously proposed forecasting framework that is resilient to abrupt changes in data quality caused by communication losses. Assuming no availability of real-time field system data, which is typical in extreme weather events such as hurricanes, the framework uses lightweight recursive time-series models to independently forecast solar irradiance, ambient temperature, PV power, and consumer load for three horizon windows: 24 hours, 12 hours, and 1 hour. Four types of ensemble-based regression trees-simple gradient boosted trees (GBR), GBR with an adaptive component (A-GBR), random forests (RF), and extra trees (ExTR)-are leveraged and their performances are compared against a simple historical weekly mean. Numerical results show that A-GBR performs better on average by 32% for 24-hour horizon and 39% for 12-hour horizon, whereas ExTR outdoes the other models on average by 10% for 1-hour horizon.

Sundararajan, Aditya↗

The Integrated Air Transportation System Evaluation Tool

Throughout U.S. history, our nation has generally enjoyed exceptional economic growth, driven in part by transportation advancements. Looking forward 25 years, when the national highway and skyway systems are saturated, the nation faces new challenges in creating transportation-driven economic growth and wealth. To meet the national requirement for an improved air traffic management system, NASA developed the goal of tripling throughput over the next 20 years, in all weather conditions while maintaining safety. Analysis of the throughput goal has primarily focused on major airline operations, primarily through the hub and spoke system.However, many suggested concepts to increase throughput may operate outside the hub and spoke system. Examples of such concepts include the Small Aircraft Transportation System, civil tiltrotor, and improved rotorcraft. Proper assessment of the potential contribution of these technologies to the domestic air transportation system requires a modeling capability that includes the country's numerous smaller airports, acting as a fundamental component of the National Air space System, and the demand for such concepts and technologies. Under this task for NASA, the Logistics Management Institute developed higher fidelity demand models that capture the interdependence of short-haul air travel with other transportation modes and explicitly consider the costs of commercial air and other transport modes. To accomplish this work, we generated forecasts of the distribution of general aviation based aircraft and GA itinerant operations at each of nearly 3.000 airport based on changes in economic conditions and demographic trends. We also built modules that estimate the demand for travel by different modes, particularly auto, commercial air, and GA. We examined GA demand from two perspectives: top-down and bottom-up, described in detail.

Wingrove, Earl R., III↗

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long‐lead‐time forecast of auroral activity. Aurora, as manifestations of solar wind−magnetosphere−ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Zheng, Yihua↗

Objective Lightning Forecasting at Kennedy Space Center/Cape Canaveral Air Force Station using Cloud-to-Ground Lightning Surveillance System Data

The 45th Weather Squadron (45 WS) forecasters at Cape Canaveral Air Force Station (CCAFS) in Florida include a probability of thunderstorm occurrence in their daily morning briefings. This information is used by personnel involved in determining the possibility of violating Launch Commit Criteria, evaluating Flight Rules for the Space Shuttle, and daily planning for ground operation activities on Kennedy Space Center (KSC)/CCAFS. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data. The forecasters requested that a lightning probability forecast tool based on statistical analysis of historical warm-season (May - September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The tool is a set of statistical lightning forecast equations that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season. This study used 15 years (1989-2003) of warm season data to develop the objective forecast equations. The local CCAFS 1000 UTC sounding was used to calculate stability parameters for equation predictors. The Cloud-to-Ground Lightning Surveillance System (CGLSS) data were used to determine lightning occurrence for each day. The CGLSS data have been found to be more reliable indicators of lightning in the area than surface observations through local informal analyses. This work was based on the results from two earlier research projects. Everitt (1999) used surface observations and rawinsonde data to develop logistic regression equations that forecast the daily thunderstorm probability at CCAFS. The Everitt (1999) equations showed an improvement in skill over the Neumann-Pfeffer thunderstorm index (Neumann 1971), which uses multiple linear regression, and also persistence and climatology forecasts. Lericos et al. (2002) developed lightning distributions over the Florida peninsula based on specific flow regimes. The flow regimes were inferred from the average wind direction in the 1000-700 mb layer at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), Florida, and the lightning data were from the National Lightning Detection Network. The results suggested that the daily flow regime may be an important predictor of lightning occurrence on KSC/CCAFS.

Lambert, Winifred↗

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long-lead- time forecast of auroral activity. Aurora, as manifestations of solar wind-magnetosphere-ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Zheng, Yihua↗

The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts

Price dynamics in wholesale electricity markets are driven by supply and demand. In markets with hydroelectric dams, the timing and amount of hydropower offered can influence prices in similar ways to wind and solar power. Unlike variable renewable energy, however, the supply of hydropower in wholesale markets is a function of both water availability and operational decisions at dams. Dam operators maximize revenues in wholesale markets by aligning generation with the periods of highest expected prices, and these scheduling decisions may in turn influence prices. Here, we examine the relative importance of two types of information in predicting forward electricity prices: a) water availability at dams, in the form of short-to-medium-range hydrological forecasts; and b) hourly scheduling decisions at dams. Using softly coupled hydrologic, hydropower scheduling, and power systems models spanning the U.S. Western Interconnection, we quantify the importance of hydrologic forecast accuracy in correctly predicting wholesale electricity prices and compare this with the influence of dam operators’ own hourly scheduling decisions on realized market prices. We find that aligning hydropower generation schedules with the periods of high forecasted prices causes larger, inadvertent price forecast errors than imperfect hydrologic forecasts. This suggests that knowledge of how water is managed by dam operators within the week is more important than weekly inflow forecast errors when predicting forward electricity prices. Our findings have implications for optimal hydropower scheduling by region. Specifically, accounting for price effects is critical in markets dominated by hydropower capacity.

Electricity markets↗

Dynamic Restoration Strategy for Distribution System Resilience Enhancement

In electric power distribution systems, distributed energy resources (DERs) can act as controllable power sources and support utility operators to minimize power outages after extreme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influences of extreme events and the capabilities of DERs are dynamic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/dis-turbance information and the availability of DERs. In this paper, we propose a new dynamic restoration strategy for distribution systems to enhance system resilience against potential hazards. An efficient reconfiguration algorithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER operation set points based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

distributed energy resources (DERs)↗

Aviation weather service requirements, 1980 - 1990

Future aviation weather needs are discussed. Priority weather requirements and deficiencies existing for weather observations and forecast services in terminal areas are presented. Needs in en route operations up to 30 km are addressed with emphasis on turbulence, presence of suspended ice and water particles, SST to supersonic speeds, solar radiation, ozone, and sonic booms. Some conclusions are drawn and recommendations are presented.

Lieurance, N. A.↗

Seasonal and daily snowmelt runoff estimates utilizing satellite data

Methods using snowcovered area to update seasonal forecasts as snowmelt progresses are also being used in quasi-operational situations. The input of snowcovered area to snowmelt models for short term perdictions was attempted in two ways; namely, the modification of existing hydrologic models and/or the use of models that were specifically designed to use snowcovered area. A daily snowmelt runoff model was used with LANDSAT data to simulate discharge on remote basins in the Wind River Mountains of Wyoming. Daily predicted and actual flows compare closely, and, summarized over the entire snowmelt season (April 1 - September 30), the average difference is only three percent. The model and snowcovered area data are currently being tested on additional watersheds to determine the method's transferability.

Source record↗

ACEE program rationale and implementation

The impact of the Aircraft Energy Efficiency program (ACEE) on commercial aviation is examined. In addition to the emphasis on air transport fuel efficiency, topics such as airline operating costs, air transport effects on U.S. trade, and fuel price forecasts are addressed. An overview of the program and its contribution to aviation technology is included.

Aiken, W. S., Jr.↗

Determining torques over the ocean and their role in the planetary momentum budget

The transfer of angular momentum between the atmosphere and oceans was examined using a surface wind data set. The data set combines special sensor microwave imager wind speed estimates and operational wind analyses from the European Centre for Medium Range Weather Forecasts for estimation of zonal torques over the global ocean from July 1987 to June 1989. An attempt was made to determine the global space-time structure of ocean torques. The wind data sets are described, the general statistics of local and global torques are presented, and their characteristics were evaluated. Consideration is given to the impact of satellite data on the calculation of local and global torques. The contribution of ocean torques to fluctuations in atmospheric angular momentum was analyzed as a function of time scale and geographical location.

Ponte, Rui M.↗