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Applied Meteorology Unit (AMU)

Develop climatologies of gridded CG lightning densities and frequencies of occurrence for the Melbourne, FL National Weather Service (NWS MLB) county warning area. These grids are used to create a first-guess field for the lightning threat index map that is available on the NWS MLB NASA KSCIKT website. Forecasters previously created this map from scratch. Having the climatologies as a background field will increase consistency between forecasters and decrease their workload. Delivered all files containing the lightning climatologies, the data, and the code used to create the climatologies to NWS MLB. Completed and distributed a final memorandum describing how the climatologies were created. All the files were installed on the NWS MLB computer system, and then the code was compiled and tested to ensure that it worked properly on their operating system. The climatologies and their descriptions are posted on the NWS MLB website. Forecasting Low-Level Convergent Bands Under Southeast Flow Provide guidance to operational personnel that will help improve their forecasts of cloud bands under large-scale southeast flow. When these bands occur, they can lead to cloud, rain, and thunderstorm occurrences that adversely affect launch, landing, and ground operations at Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Completed the first draft of the final report. The conclusions from this task indicated low-level wind speed and direction, low-level high pressure ridge position, east coast sea breeze front activity and upper-level jet streak position have the greatest influence on convergent band formation and movement during southeasterly flow.

Bauman, William↗

Addressing Market Issues in Electrical Power Systems with Large Shares of Variable Renewable Energy

This paper reports recent findings from IEA Wind TCP Task 25, which compiles international experiences and research related to large-scale integration of wind and other renewable energy. In the paper, we address the main challenges for market integration of variable renewable energy, relating to price formation, cost recovery, balancing and other grid services. The paper gives an overview of recent scenario studies on electricity price impacts of (1) various generation, energy storage and demand types in different markets, and (2) different market designs and energy/climate policies. Studying markets with very high shares of variable renewable energy requires an improved set of analysis tools for forecasting market outcomes, estimating flexibility needs and sources, and assessing resource adequacy. Key market features need to be investigated within these improved analytical capabilities for systems transitioning to high shares of variable renewable energy, storage and flexible demand. System services that can be supported by markets will likely need to be revisited. Finally, this paper identifies open questions and suggested future market design work for supporting systems with very high shares of variable renewable energy, which are to be addressed in follow-up work of Task 25 collaborative research.

cost recovery↗

STOCHASTIC OPTIMAL POWER FLOW FOR REAL-TIME MANAGEMENT OF DISTRIBUTED RENEWABLE GENERATION AND DEMAND RESPONSE (Final Report)

To meet the grand challenge of a sustainable energy future, there has been a surge of interest in renewable energy. Today, the uncertainty associated with renewable resources is handled by using operating reserves. The high penetration of renewable resources, however, introduces difficult-to-control dynamics and challenges for power system operation. Decision support tools are necessary at the bulk system operational level to recognize and efficiently utilize renewable resources and distributed demand response products in concert with traditional grid resources. It is envisaged that responsive load can potentially have very significant cost advantages over either spinning or non-spinning ramping reserve. Critical decisions are made during hour(s)-ahead and real-time power system operation regarding the commitment and dispatch of generators to ensure power delivery is both reliable and economic. These decisions are typically made by a security constrained optimal flow, which determines future generator commitments, dispatches, and ensures adequate reserves are available in the event of a contingency (unexpected outage) or if future system conditions deviate from forecasts. However, security has been always based on a pre-specified subset of contingency constraints whose enforcement does not guarantee security under all possible future possibilities while also giving little or no weight to the likelihood of each contingent event or the severity of its consequences. Existing tools, which are based exclusively on deterministic optimization models, do not yield optimal operational decisions to address these new challenges, in terms of both reliability and cost-effectiveness. This project has focused on developing a stochastic optimal power flow (SOPF) framework, which integrates renewable resource uncertainty, load uncertainty, distributed storage (DS), demand response (DR) products, in a holistic manner to address the uncertainty associated with ever-increasing renewable resources, along with the inclusion of distributed demand response products in future power systems. A proof-of-concept problem was created using the Pennsylvania-Jersey-Maryland (PJM) power system network. Synthetic wind generation was added to the system to simulate 50% wind penetration. A 1-hour test of SOPF operation indicated more than 6% operational cost savings. The project continued by adding the Midwestern Independent System Operator (MISO) as a partner, with focus shifting from SOPF to Stochastic Look-Ahead Unit Commitment (SLAC). Unlike PJM, MISO is faced with significant renewable energy resources within its footprint and is challenged with substantial uncertainty in its operations. The SLAC distinguishes itself from existing tools that operators use. At best, today’s tools solve two to three cases independently, where one or two system parameters, such as forecasted load level (e.g., a low, base, and high forecast), are varied and the resulting scenarios are analyzed independently. The stochastic-based optimization of SLAC leverages statistical information from an ensemble of potential operational scenarios and their respective likelihood. The SLAC output can be translated into valuable information to the operator such as suggested commitments, optimal scheduling and dispatch of resources, reserve requirements at both locational and zonal resolutions, ramping availability and requirements, availability of demand response including operational guidance concerning the near-term and real-time coordination between distributed energy resources, and utilization of distributed storage resources. The developed SOPF/SLAC tool, a stand-alone tool compatible with existing EMSs, will provide system operators with unprecedented visibility, flexibility and predictability to these resources and operational guidance concerning the real-time coordination between DERs and DR/DS products. The game changing and practical impact of this disruptive technology will be dramatic and will usher in a new era in the electric power industry, wherein green energy concepts are fully embraced, and electric power costs are lowered throughout the nation.

42 ENGINEERING↗

High-Resolution Large-Eddy Simulations of Historical U.S. Gulf Coast Hurricanes

This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the Large-Eddy simulations. The data will be divided according to the storm intensity level at the simulation time. Category 2: Harvey, Nate Category 3: Michael, Delta Category 4: Michael, Laura

17 WIND ENERGY↗

High-Resolution Mesoscale Simulations of Historical U.S. Gulf Coast Hurricanes

This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the mesoscale simulations, separated by each storm.

17 WIND ENERGY↗

Mapping ERS-1 wind fields over north west Atlantic using a variational objective analysis

A variational method is implemented to produce five day mean gridded ERS-1 analyzed wind fields in the north west Atlantic with the aim of providing for wind forcing of basin scale ocean models. The method consists of minimizing a cost functional, designed to measure misfits to prescribed weighted constraints which express a smoothed behavior and the proximity to input data vectors and curl. The weights are empirically determined by comparison with independent ship and buoy data over four five day periods. Root mean square differences between analyzed winds and independent data are thus further decreased: they range from 0.8 up to 1.8 m/s. Some problems present in the initial data remain; they are principally due to incomplete data coverage (instrumental problems), and possibly unresolved ambiguities. The resulting curl fields are smoothed and show coherent patterns. A comparison with the European Center for Medium range Weather Forecasting (ECMWF) analysis is encouraging.

Siefridt, L.↗

Forecasting of Clear Air Turbulence using a Diagnostic Richardson Number Tendency formulation

The results of several case studies of Clear Air Turbulence (CAT) using the Diagnostic Richardson Number Tendency (DRT) formulation are highlighted. The performance of this technique in resolving regions of documented CAT encounters is encouraging. Its operational adaptability seems particularly attractive in that the input data can be supplied by the currently operational Rawinsonde system. A CAT index is calculated deterministically, sensing synoptic-scale changes in static stability and vertical wind shear conducive for supporting meso-scale CAT layers. This index reveals volumes of the troposphere which act as 'source regions' of Kelvin-Helmholtz instabilities. The results suggest that these regions are particularly efficient with respect to the synoptic/meso-scale energetical coupling necessary for supporting significantly turbulent layers. The output highlights specific regions of the atmosphere which can be interpreted operationally in terms of CAT-encounter probabilities.

Keller, J. L.↗

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of Hurricane Katrina. SCREAMv1 demonstrated skill in simulating TC track, size, and intensity, while the model produced an excessive amount of precipitation. In comparison, WRF more accurately simulated TC precipitation and intensity, although the TC wind extent was smaller than the observations.

54 ENVIRONMENTAL SCIENCES↗

Variational optimization analysis of temperature and moisture advection in a severe storm environment

Horizontal wind components, potential temperature, and mixing ratio fields associated with a severe storm environment in the south central U.S. were analyzed from synoptic upper air observations with a nonhomogeneous, anisotropic weighting function. Each data field was filtered with variational optimization analysis techniques. Variational optimization analysis was also performed on the vertical motion field and was used to produce advective forecasts of the potential temperature and mixing ratio fields. Results show that the dry intrusion is characterized by warm air, the advection of which produces a well-defined upward motion pattern. A corresponding downward motion pattern comprising a deep vertical circulation in the warm air sector of the low pressure system was detected. The axes alignment of maximum dry and warm advection with the axis of the tornado-producing squall line also resulted.

Mcfarland, M. J.↗

Experimental forecasts of El Nino

A deterministic numerical model of the coupled evolution of the tropical ocean and atmosphere was used to forecast all El Nino/Southern Oscillation (ENSO) events from 1970 to 1986. More particularly, the model, originally developed for studying large-scale ocean-atmosphere interactions in the tropics, successfully predicted the characteristics of the spatial and temporal structure of ENSO observed in the study interval. The model indicated that rainfall moving eastward over the Pacific slackens the surface winds that would otherwise cool the eastern Pacific by drawing up cooler subsurface waters. The oceanic thermocline increases, a poleward flow of westerly flowing warn waters deplets the equatorial warm water reservoir, and sea surface temperatures decline. These ENSO conditions are statistically tractable with the model several months in advance, provided upper ocean layer thermal data are available.

Cane, M. A.↗

STS-48 case study, 17-18 September 1991

Weather conditions are documented prior to and during the STS-48 attempted landing at the Shuttle Landing Facility at KSC on 18 Sep. 1991. Trends in meteorological data during 17 and 18 Sep. are examined along with their relationship to the overall weather pattern observed over the KSC region. The primary weather problems during the landing were the formation of showers within 10 nautical miles of the SLF and any ceiling less than 10,000 ft. The controlling factor of the weather was a high pressure ridge that was gradually weakening and moving off the northeast. As this occurred, the low level flow was switching from a easterly to a southeasterly direction. This change in wind direction was reflected by shower movement on the McGill radar and by trends in rawinsondes launched from the Cape. These rawinsondes also indicated that the boundary layers was becoming slightly more unstable several hours prior to the attempted landing which may have aided in the development of clouds and small isolated showers. Also, analyses of Doppler wind profiler and rawinsondes indicated a possible midlevel disturbance in the easterly flow pattern near 700 mb. This weak disturbance may have made the atmosphere a little more unstable early on 18 Sep. Finally, embedded within the southeasterly flow were several bands of low clouds. These clouds were rather difficult to see in unenhanced IR satellite imagery available to forecasters in real time. However, post analyses using several different enhancement curves, adapted from NESDIS, clearly reveals the presence of these clouds.

Atchison, Michael K.↗

Relationship between Precipitating Convection and Easterly Wave Dynamics in the Western Central Pacific

The main proposed goal of this research was a synthesis of radiosonde and radar time series from the TRMM validation experiment KWAJEX (Jul. 23 - Sep. 14 1999) with satellite datasets and forecast model based analyses, in order to characterize synoptic-scale disturbances passing through the Kwajalein (9 deg N 168 deg W) region on the north edge of the central Pacific ITCZ. The Sobel et al. paper summarizes our methodology and findings. A classic paper of Reed and Recker had documented the steady pulse of easterly waves modulating meridional wind, clouds and precipitation in and west of this region in a set of observations in boreal fall. Our study found easterly waves were much less organized and intense during KWAJEX, and only weakly correlated with daily area-averaged radar-derived precipitation and IR brightness temperature. Instead, we focused on three disturbances associated with the highest daily-averaged rainfall amounts during the period. We found by looking at NCEP reanalyses that only one was an easterly wave, while the other two corresponded to an equatorial Kelvin wave and a mixed Rossby-gravity wave, respectively. The contrast with Reed and Recker may be sampling variability, but the timing of KWAJEX, earlier in the year, and during suppressed (weak La Nina) conditions may also contribute to our different conclusions.

Bretherton, Christopher S.↗

Design definition of the Laser Atmospheric Wind Sounder (LAWS), phase 2. Volume 2: Final report

Lockheed personnel, along with team member subcontractors and consultants, have performed a preliminary design for the LAWS Instrument. Breadboarding and testing of a LAWS class laser have also been performed. These efforts have demonstrated that LAWS is a feasible Instrument and can be developed with existing state-of-the-art technology. Only a commitment to fund the instrument development and deployment is required to place LAWS in orbit and obtain the anticipated science and operational forecasting benefits. The LAWS Science Team was selected in 1988-89 as were the competing LAWS phase 1/2 contractor teams. The LAWS Science Team developed requirements for the LAWS Instrument, and the NASA/LAWS project office defined launch vehicle and platform design constraints. From these requirements and constraints, the lockheed team developed LAWS Instrument concepts and configurations. A system designed to meet these requirements and constraints is outlined. The LAWS primary subsystem and interfaces - laser, optical, and receiver/processor - required to assemble a lidar are identified. Also identified are the support subsystems required for the lidar to function from space: structures and mechanical, thermal, electrical, and command and data management. The Lockheed team has developed a preliminary design of a LAWS Instrument System consisting of these subsystems and interfaces which will meet the requirements and objectives of the Science Team. This final report provides a summary of the systems engineering analyses and trades of the LAWS. Summaries of the configuration, preliminary designs of the subsystems, testing recommendations, and performance analysis are presented. Environmental considerations associated with deployment of LAWS are discussed. Finally, the successful LAWS laser breadboard effort is discussed along with the requirements and test results.

Wilson, D. J.↗

A 30-yr high-resolution weather research and forecasting model downscaling data over California and Nevada

This dataset presents a 30-year high resolution meteorological dataset obtained using the WRF model (Advanced version Research WRF version 4.4). We used WRF and European Centre for Medium-Range Weather Forecasts Reanalysis v5 as initial and boundary conditions to generate gridded meteorological variables. A large number of surface weather stations was used for model validation. A multi-physics analysis was first developed to identify a good physics suite extended from 6 November 00 UTC to 10 November 23 UTC, 2018, which included the Camp Fire in northern California. Based on the best physics suite, the downscaling dataset extends from 1 December to 28 February, 1990–2021 and the horizontal domain has 1.5 km grid spacing covering the entire states of California and Nevada in the United States. Comparisons between hourly surface observations and WRF simulations of air temperature, relative humidity and wind speeds show mean absolute errors on the order of (1.6-2.0 C), (10 %) and 1.2–1.5 m s -1 , respectively.

54 ENVIRONMENTAL SCIENCES↗

Robustness of Observing System Simulation Experiments

Observing System Simulation Experiments (OSSEs) are used to investigate the potential performance of proposed new instruments on numerical weather prediction (NWP). As OSSEs involve a framework in which the atmosphere and observations are all completely simulated, it is necessary to perform validation of the OSSE to ensure that it is sufficiently realistic to provide useful experimental results. A common issue that affects the forecast skill and observation impacts is the tendency of OSSEs to have insufficient model error compared to NWP in the real world. In this work, two versions of the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) NWP OSSE framework are compared, with the newer framework having more simulated forecast model error than the older framework due to changes to the NWP system. The performance of the updated OSSE is validated against corresponding behavior of the same NWP system in the real world in terms of the simulated observations, the analysis increments, forecast error, and observation impacts. OSSE results of analysis and forecast impacts for three proposed new observation systems are also compared between the older and newer frameworks to evaluate the robustness of the OSSE experiments and the role of model error in observation impacts. These three new instruments are the Geostationary eXtended Observations (GeoXO) hyperspectral infrared sounder (GXS), the Midwave Infrared Sounding of Temperature and humidity in a Constellation for Winds (MISTiC Winds) atmospheric motion vectors, and additional Global Navigation Satellite System Radio Occultations (GNSS-RO).

Observing System Simulation Experiments↗

Northwest National Marine Renewable Energy Center

In 2008, the US Department of Energy’s (DOE) Wind and Water Power Program issued a funding opportunity announcement to establish university-led National Marine Renewable Energy Centers. Oregon State University and the University of Washington combined their capabilities in wave and tidal energy to establish the Northwest National Marine Renewable Energy Center, or NNMREC. NNMREC’s scope included research and testing in the following topic areas: • Advanced Wave Forecasting Technologies; • Device and Array Optimization; • Integrated and Standardized Test Facility Development; • Investigate the Compatibility of Marine Energy Technologies with Environment, Fisheries and other Marine Resources; • Increased Reliability and Survivability of Marine Energy Systems; • Collaboration/Optimization with Marine Renewable and Other Renewable Energy Resources. To support the last topic, the National Renewable Energy Laboratory (NREL) was brought onto the team, particularly to assist with testing protocols, grid integration, and testing instrumentation. NNMREC’s mission is to facilitate the development of marine energy technology, to inform regulatory and policy decisions, and to close key gaps in scientific understanding with a focus on workforce development. In this, NNMREC achieves DOE’s goals and objectives and remains aligned with the research and educational mission of universities. In 2012, DOE provided NNMREC an opportunity to propose an additional effort to begin work on a utility scale, grid connected wave energy test facility. That project, initially referred to as the Pacific Marine Energy Center, is now referred to as the Pacific Marine Energy Center South Energy Test Site (PMEC-SETS) and involves work directly toward establishing the facility, which will be in Newport Oregon, as well as supporting instrumentation for wave energy converter testing. This report contains a breakdown per subtask of the funded project. Under each subtask, the following are presented and discussed where appropriate: the initial objective or hypothesis; an overview of accomplishments and approaches used; any problems encountered or departures from planned methodology over the life of the project; impacts of the problems or rescoping of the project; how accomplishments compared with original project goals; and deliverables under the subtasks. Products and models developed under the award are also included.

16 TIDAL AND WAVE POWER↗

Variational methods in simultaneous optimum interpolation and initialization

The duality between optimum interpolation and variational objective analysis, is reviewed. This duality is used to set up a variational approach to objective analysis which uses prior information concerning the atmospheric spectral energy distribution, in the variational problem. In the wind analysis example, the wind field is partitioned into divergent and nondivergent parts, and a control parameter governing the relative energy in the two parts is estimated from the observational data being analyzed by generalized cross validation, along with a bandwidth parameter. A variational approach to combining objective analysis and initialization in a single step is proposed. In a simple example of this approach, data, forecast, and prior information concerning atmospheric energy distribution is combined into a single variational problem. This problem has (at least) one bandwidth parameter, one partitioning parameter governing the relative energy in fast slow modes, and one parameter governing the relative weight to be given to observational and forecast data.

Wahba, G.↗

The Principle of Energetic Consistency: Application to the Shallow-Water Equations

If the complete state of the earth's atmosphere (e.g., pressure, temperature, winds and humidity, everywhere throughout the atmosphere) were known at any particular initial time, then solving the equations that govern the dynamical behavior of the atmosphere would give the complete state at all subsequent times. Part of the difficulty of weather prediction is that the governing equations can only be solved approximately, which is what weather prediction models do. But weather forecasts would still be far from perfect even if the equations could be solved exactly, because the atmospheric state is not and cannot be known completely at any initial forecast time. Rather, the initial state for a weather forecast can only be estimated from incomplete observations taken near the initial time, through a process known as data assimilation. Weather prediction models carry out their computations on a grid of points covering the earth's atmosphere. The formulation of these models is guided by a mathematical convergence theory which guarantees that, given the exact initial state, the model solution approaches the exact solution of the governing equations as the computational grid is made more fine. For the data assimilation process, however, there does not yet exist a convergence theory. This book chapter represents an effort to begin establishing a convergence theory for data assimilation methods. The main result, which is called the principle of energetic consistency, provides a necessary condition that a convergent method must satisfy. Current methods violate this principle, as shown in earlier work of the author, and therefore are not convergent. The principle is illustrated by showing how to apply it as a simple test of convergence for proposed methods.

Cohn, Stephen E.↗