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NASA NTRS2017

GRAIL Gravity Observations of the Transition from Complex Crater to Peak-Ring Basin on the Moon: Implications for Crustal Structure and Impact Basin Formation

High-resolution gravity data from the Gravity Recovery and Interior Laboratory (GRAIL) mission provide the opportunity to analyze the detailed gravity and crustal structure of impact features in the morphological transition from complex craters to peak-ring basins on the Moon. We calculate average radial profiles for free-air anomalies and Bouguer anomalies for peak-ring basins, proto-basins, and the largest complex craters. Complex craters and proto-basins have free-air anomalies that are positively correlated with surface topography, unlike the prominent lunar mascons (positive free-air anomalies in areas of low elevation) associated with large basins. The Bouguer gravity anomaly profiles of complex craters are highly irregular, with central positive anomalies that are generally absent or not clearly tied to interior morphology. In contrast, gravity profiles for peak-ring basins (approx. 200 km to 580 km) are much more regular and are highly correlated with surface morphology. A central positive Bouguer anomaly is confined within the peak ring and a negative Bouguer anomaly annulus extends from the edge of the positive anomaly outward to about the rim crest. A number of degraded basins lacking interior peak rings have diameters and gravity patterns similar to those of well-preserved peak-ring basins. If these structures represent degraded peak-ring basins, the number of peak-ring basins on the Moon would increase by more than a factor of two to 34. The gravity anomalies within basins are interpreted to be due to uplift of the mantle confined within the peak ring and an annulus of thickened crust between the peak ring and rim crest. We hypothesize that mantle uplift is influenced by interaction between the transient cavity and the mantle. Further, mascon formation is generally disconnected from the number of basin rings formed and occurs over a wide range of basin sizes. These observations have important implications for models of basin and mascon formation on the Moon and other planetary bodies.

Baker, David M. H.↗

NASA NTRS2024

Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification

Two phase-optimized multisine peak factor minimization algorithms are presented and evaluated. The first algorithm minimizes peak factor by iteratively clipping the peaks of generated multisine signals. The second algorithm optimizes peak factor indirectly through minimization of an approximation of the infinity norm of the multisine. Algorithm performance was evaluated as a function of different signal properties, including the number of harmonics, harmonic spacing, and number of snow harmonics (extra harmonics included for further reduction of the peak factor). The two algorithms are compared against results obtained by minimizing peak factor directly using a simplex algorithm, which has been a common approach when designing phase-optimized multisines for system identification flight tests. Sample results show that the clipping and infinity norm algorithms produced multisine signals with comparable peak factors that were lower than that of the simplex algorithm. However, the clipping algorithm runs an order of magnitude faster than the other two algorithms, which also makes it practical to repeat the algorithm multiple times to achieve even lower peak factors.

system identification↗

NASA NTRSDate not supplied

Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification(Presentation)

flight test↗

DOE OSTI2024

Multiple Peaks and a Long Precursor in the Type IIn Supernova 2021qqp: An Energetic Explosion in a Complex Circumstellar Environment

Abstract We present optical photometry and spectroscopy of the Type IIn supernova (SN) 2021qqp. Its unusual light curve is marked by a long precursor for ≈300 days, a rapid increase in brightness for ≈60 days, and then a sharp increase of ≈1.6 mag in only a few days to a first peak ofM r ≈ −19.5 mag. The light curve then declines rapidly until it rebrightens to a second distinct peak ofM r ≈ −17.3 mag centered at ≈335 days after the first peak. The spectra are dominated by Balmer lines with a complex morphology, including a narrow component with a width of ≈1300 km s −1 (first peak) and ≈2500 km s −1 (second peak) that we associate with the circumstellar medium (CSM) and a P Cygni component with an absorption velocity of ≈8500 km s −1 (first peak) and ≈5600 km s −1 (second peak) that we associate with the SN–CSM interaction shell. Using the luminosity and velocity evolution, we construct a flexible analytical model, finding two significant mass-loss episodes with peak mass loss rates of ≈10 and ≈5M ⊙ yr −1 about 0.8 and 2 yr before explosion, respectively, with a total CSM mass of ≈2–4M ⊙ . We show that the most recent mass-loss episode could explain the precursor for the year preceding the explosion. The SN ejecta mass is constrained to be ≈5–30M ⊙ for an explosion energy of ≈(3–10) × 10 51 erg. We discuss eruptive massive stars (luminous blue variable, pulsational pair instability) and an extreme stellar merger with a compact object as possible progenitor channels.

Astronomy & Astrophysics↗

NASA NTRS2003

Extended Statistical Short-Range Guidance for Peak Wind Speed Analyses at the Shuttle Landing Facility: Phase II Results

This report describes the results from Phase II of the AMU's Short-Range Statistical Forecasting task for peak winds at the Shuttle Landing Facility (SLF). The peak wind speeds are an important forecast element for the Space Shuttle and Expendable Launch Vehicle programs. The 45th Weather Squadron and the Spaceflight Meteorology Group indicate that peak winds are challenging to forecast. The Applied Meteorology Unit was tasked to develop tools that aid in short-range forecasts of peak winds at tower sites of operational interest. A seven year record of wind tower data was used in the analysis. Hourly and directional climatologies by tower and month were developed to determine the seasonal behavior of the average and peak winds. Probability density functions (PDF) of peak wind speed were calculated to determine the distribution of peak speed with average speed. These provide forecasters with a means of determining the probability of meeting or exceeding a certain peak wind given an observed or forecast average speed. A PC-based Graphical User Interface (GUI) tool was created to display the data quickly.

Lambert, Winifred C.↗

NASA NTRS2010

Statistical Short-Range Guidance for Peak Wind Forecasts on Kennedy Space Center/Cape Canaveral Air Force Station, Phase III

This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations.The tool includes climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗

NASA NTRS2011

Peak Wind Forecasts for the Launch-Critical Wind Towers on Kennedy Space Center/Cape Canaveral Air Force Station, Phase IV

This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds arc an important forecast clement for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to update the statistics in the current peak-wind forecast tool to assist in forecasting LCC violations. The tool includes onshore and offshore flow climatologies of the 5-minute mean and peak winds and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗

NASA NTRS2008

Forecasting Cool Season Daily Peak Winds at Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily 24-Hour and Weekly Planning Forecasts issued by the 45th Weather Squadron (45 WS) for planning operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The morning outlook for peak speeds also begins the warning decision process for gusts ^ 35 kt, ^ 50 kt, and ^ 60 kt from the surface to 300 ft. The 45 WS forecasters have indicated that peak wind speeds are a challenging parameter to forecast during the cool season (October-April). The 45 WS requested that the Applied Meteorology Unit (AMU) develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. The tool must only use data available by 1200 UTC to support the issue time of the Planning Forecasts. Based on observations from the KSC/CCAFS wind tower network, surface observations from the Shuttle Landing Facility (SLF), and CCAFS upper-air soundings from the cool season months of October 2002 to February 2007, the AMU created multiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence, the temperature inversion depth, strength, and wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft. Six synoptic patterns were identified: 1) surface high near or over FL, 2) surface high north or east of FL, 3) surface high south or west of FL, 4) surface front approaching FL, 5) surface front across central FL, and 6) surface front across south FL. The following six predictors were selected: 1) inversion depth, 2) inversion strength, 3) wind gust factor, 4) synoptic weather pattern, 5) occurrence of precipitation at the SLF, and 6) strongest wind in the lowest 3000 ft. The forecast tool was developed as a graphical user interface with Microsoft Excel to help the forecaster enter the variables, and run the appropriate regression equations. Based on the forecaster's input and regression equations, a forecast of the day's peak and average wind is generated and displayed. The application also outputs the probability that the peak wind speed will be ^ 35 kt, 50 kt, and 60 kt.

Barrett, Joe, III↗

NASA NTRS2008

A Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

This conference abstract describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violatioas.The tool will include climatologies of the 5-minute mean end peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗

NASA NTRS2007

Developing a Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

This conference presentation describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations. The tool will include climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Lambert, WInifred↗

NASA NTRS2020

SN2020bvc: A Broad-line Type Ic Supernova with a Double-peaked Optical Light Curve and a Luminous X-Ray and Radio Counterpart

We present optical, radio, and X-ray observations of SN 2020bvc (=ASASSN-20bs, ZTF 20aalxlis), a nearby (z = 0.0252; d = 114Mpc) broad-line (BL) Type Ic supernova (SN) and the first double-peaked Ic-BL discovered without a gamma-ray burst (GRB) trigger. Our observations show that SN 2020bvc shares several properties in common with the Ic-BL SN 2006aj, which was associated with the low-luminosity gamma-ray burst (LLGRB) 060218. First, the 10 GHz radio luminosity (L(radio) ≈ 10^(37) erg/s) is brighter than ordinary core-collapse SNe but fainter than LLGRB SNe such as SN 1998bw (associated with LLGRB 980425). We model our VLA observations (spanning 13–43 days) as synchrotron emission from a mildly relativistic (v ≳ 0.3c) forward shock. Second, with Swift and Chandra, we detect X-ray emission (L(X) ≈ 10^(41) erg/s) that is not naturally explained as inverse Compton emission or part of the same synchrotron spectrum as the radio emission. Third, high-cadence (6 × per night) data from the Zwicky Transient Facility (ZTF) show a double-peaked optical light curve, the first peak from shock cooling of extended low-mass material (mass Me < 10^(-2) Mꙩ at radius Re > 10^(12) cm) and the second peak from the radioactive decay of 56Ni. SN 2020bvc is the first double-peaked Ic-BL SN discovered without a GRB trigger, so it is noteworthy that it shows X-ray and radio emission similar to LLGRB SNe. For four of the five other nearby (z ≲ 0.05) Ic-BL SNe with ZTF high-cadence data, we rule out a first peak like that seen in SN 2006aj and SN 2020bvc, i.e., that lasts ≈1 day and reaches a peak luminosity M ≈ −18. Follow-up X-ray and radio observations of Ic-BL SNe with well-sampled early optical light curves will establish whether double-peaked optical light curves are indeed predictive of LLGRB-like X-ray and radio emission.

Anna Y. Q. Ho↗

DOE OSTI2024

High Performance Computing Peak Shaving for Microreactor Operation

There are multiple nuclear microreactors currently under development that are designed to provide autonomous power for as many as ten or more years without refueling and are designed to power high performance computing (HPC) datacenters. But the load-follow speeds for a nuclear microreactor will be much slower than grid power and slower than the power variance typical of a HPC system. HPC datacenters experience peak power load variance driven by several factors ranging from the operation of cooling systems to remove heat from the servers to supporting a wide range of user application workflows and architectures each with different power signatures. One mechanism to support the limited load-follow of a microreactor is peak shaving where an energy storage mechanism is used to shed peak load and reduce significant power variance. This work explores peak electrical load shaving using uninterruptible power supply (UPS) systems designed for HPC support in the context of peak shaving when operating using a nuclear microreactor with a load-follow limited to 10% of load per minute. Using a self contained HPC datacenter complete with stand-alone cooling system and provisioned with an x86 cluster, an ARM cluster, and a graphics processing unit (GPU) cluster, peak shaving for microreactor operation using the UPS battery backup is explored while running two classes of typical HPC user applications. HPC architecture suitability for microreactor operation under this type of peak shaving is examined.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

When to vaccinate for seasonal influenza: check the peak forecast

Background Seasonal influenza infects 5-20% of people every year in the United States, resulting in hospitalizations, deaths, and adverse economic impacts. To mitigate these impacts, influenza vaccines are developed and distributed annually; however, growing evidence suggests that vaccine effectiveness (VE) wanes over the course of a flu season. Delaying influenza vaccination for older adults has attracted attention as a potential public health strategy. However, given the uncertainties in seasonal peak, vaccine effectiveness, and waning rates, postponing vaccination could also lead to increased morbidity, motivating an evaluation of a range of potential scenarios. The aim of this study was to investigate favorable age group-specific vaccination schedules that could lead to the greatest disease burden reduction. Methods We systematically investigated a broad range of vaccination start times for five age groups under six combinations of initial effectiveness and waning rates, based on influenza cases and vaccine uptake data from 10 influenza seasons. We defined the most favorable vaccination schedule as the one that resulted in the greatest reduction in disease burden. Results In scenarios with fast waning, all age groups benefit from delaying vaccination regardless of initial VE and peak timing. In scenarios with slower waning, results are mixed. For the ≥65 group, high initial VE and slow waning suggests that in early-peaking seasons, early vaccination most effectively reduces disease burden, while in late-peaking seasons delaying vaccination is most effective. For the ≥65 group in medium and low initial VE, and slow waning scenarios, delaying vaccination appears to prevent the greatest number of cases, regardless of whether the season peaks early or late. Conclusion The most favorable vaccination schedule is sensitive to changes in initial VE, waning rate, and peak timing. Given estimates of these quantities from statistical and immunological models and observations, our methods can inform vaccination recommendations in order to most effectively reduce the annual disease burden caused by seasonal influenza. Specifically, accurate peak timing forecasts for the upcoming season have the potential to guide decisions on when to vaccinate.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1980

Orientations of central peaks in lunar craters - Implications for regional structural trends

Impact craters are dominant features on the lunar surface and all fresh craters with diameters greater than 35 km possess central peaks. Approximately half of these central peaks (54%) have either linear or arcuate geometry and display some preferential orientation. These orientations were measured for 200 lunar craters of Pre-Nectarian to Copernican age. A pervasive regional north-south trend is identified for central peak orientation, with secondary trends at + or - 20-30 deg from this axis. No evidence for regional east-west trends is found. These orientations are shown to persist in craters formed through the last 4 billion years of lunar history. A lack of coincidence between impact direction, as determined from ejecta asymmetries and peak orientation, argues for structural control by the target as a source of the linear peak morphology. This is supported by the regional and temporal persistence of preferred peak orientations. It is proposed that linear central peak orientations in lunar craters reflect a pervasive regional structural system which developed early in lunar history and has persisted through geologic time.

Hale, W.↗

NASA NTRS1982

Reduction in peak oxygen uptake after prolonged bed rest

The hypothesis that the magnitude of the reduction in peak oxygen uptake (VO2) after bed rest is directly proportional to the level of pre-bed rest peak VO2 is tested. Complete pre and post-bed rest working capacity and body weight data were obtained from studies involving 24 men (19-24 years old) and 8 women (23-34 years old) who underwent bed rest for 14-20 days with no remedial treatments. Results of regression analyses of the present change in post-bed rest peak VO2 on pre-bed rest peak VO2 with 32 subjects show correlation coefficients of -0.03 (NS) for data expressed in 1/min and -0.17 for data expressed in ml/min-kg. In addition, significant correlations are found that support the hypothesis only when peak VO2 data are analyzed separately from studies that utilized the cycle ergometer, particularly with subjects in the supine position, as opposed to data obtained from treadmill peak VO2 tests. It is concluded that orthostatic factors, associated with the upright body position and relatively high levels of physical fitness from endurance training, appear to increase the variability of pre and particularly post-bed rest peak VO2 data, which would lead to rejection of the hypothesis.

Greenleaf, J. E.↗

NASA NTRS2006

Confirmation of the E(sup src)(sub Peak)-E(sub iso) (Amati) relation from the x-ray flash XRF 050416A observed by the Swift burst alert telescope

We report Swift Burst Alert Telescope (BAT) observations of the X-ray flash (XRF) XRF 050416A. The fluence ratio between the 15-25 and 25-50 keV energy bands of this event is 1.5, thus making it the softest gamma-ray burst (GRB) observed by BAT so far. The spectrum is well fitted by a Band function with E(sup obs)(sub peak) of 15.0(sup +2.3)(sub -2.7) keV. Assuming the redshift of the host galaxy (z = 0.6535), the isotropic equivalent radiated energy E(sub iso) and the peak energy at the GRB rest frame (E(sup src)(sub peak)) of XRF 050416A are not only consistent with the correlation found by Amati et al. and extended to XRFs by Sakamoto et al. but also fill in the gap of this relation around the 30-80 keV range of E(sup src)(sub peak). This result tightens the validity of the E(sup src)(sub Peak)-E(sup src)(sub peak) relation from XRFs to GRBs. We also find that the jet break time estimated using the empirical relation between E(sup src)(sub peak) and the collimation corrected energy E(sub gamma), is inconsistent with the afterglow observation by the Swift X-Ray Telescope. This could be due to the extra external shock emission overlaid around the jet break time or to the nonexistence of a jet break feature for XRFs, which might be a further challenge for GRB jet emission models and XRF/GRB unification scenarios.

Sakamoti, T.↗

NASA NTRS2008

Reviewing E(sub peak) Relations with Swift and Suzaku Data

In recent years several authors have derived correlations between gamma-ray burst (GRB) spectral peak energy (E(sub peak)) and either isotropic-equivalent radiated energy (E(sub iso)) or peak luminosity (L(sub iso)). Since these relationships are controversial, but could provide redshift estimators, it is important to determine whether bursts detected by Swift exhibit the same correlations. Swift has greatly added to the number of GRBs for which redshifts are known and hence E(sub iso) and L(sub iso) could be calculated. However, for most bursts it is not possible to adequately constrain E(sub peak) with Swift data alone since most GRBs have E(sub peak) above the energy range (15-50 keV) of the Swift Burst Alert Telescope (BAT). Therefore we have analyzed the spectra of 78 bursts (31 with redshift) which were detected by both Swift/BAT and the Suzaku Wide-band All-sky Monitor (WAM), which covers the energy range 50-5000 keV. For most bursts in this sample we can precisely determine E(sub peak) and for bursts with known redshift we can compare how the E(sub peak) relations for the Swift/Suzaku sample compare to earlier published results. Keywords: gamma rays: bursts

Krimm, Hans A.↗

NASA NTRS2010

Peak Wind Tool for General Forecasting

The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded again by six years, from October 1996 to April 2002, by interpolating 1000-ft sounding data to 100-ft increments. The Phase II developmental data set included observations for the cool season months of October 1996 to February 2007. The AMU calculated 68 candidate predictors from the XMR soundings, to include 19 stability parameters, 48 wind speed parameters and one wind shear parameter. Each day in the data set was stratified by synoptic weather pattern, low-level wind direction, precipitation and Richardson Number, for a total of 60 stratification methods. Linear regression equations, using the 68 predictors and 60 stratification methods, were created for the tool's three forecast parameters: the highest peak wind speed of the day (PWSD), 5-minute average speed at the same time (A WSD), and timing of the PWSD. For PWSD and A WSD, 30 Phase II methods were selected for evaluation in the verification data set. For timing of the PWSD, 12 Phase\I methods were selected for evaluation. The verification data set contained observations for the cool season months of March 2007 to April 2009. The data set was used to compare the Phase I and II forecast methods to climatology, model forecast winds and wind advisories issued by the 45 WS. The model forecast winds were derived from the 0000 and 1200 UTC runs of the 12-km North American Mesoscale (MesoNAM) model. The forecast methods that performed the best in the verification data set were selected for the Phase II version of the tool. For PWSD and A WSD, linear regression equations based on MesoNAM forecasts performed significantly better than the Phase I and II methods. For timing of the PWSD, none of the methods performed significantly bener than climatology. The AMU then developed the Microsoft Excel and MIDDS GUls. The GUIs display the forecasts for PWSD, AWSD and the probability the PWSD will meet or exceed 25 kt, 35 kt and 50 kt. Since none of the prediction methods for timing of the PWSD performed significantly better thanlimatology, the tool no longer displays this predictand. The Excel and MIDDS GUIs display forecasts for Day-I to Day-3 and Day-I to Day-5, respectively. The Excel GUI uses MesoNAM forecasts as input, while the MIDDS GUI uses input from the MesoNAM and Global Forecast System model. Based on feedback from the 45 WS, the AMU added the daily average wind speed from 30 ft to 60 ft to the tool, which is one of the parameters in the 24-Hour and Weekly Planning Forecasts issued by the 45 WS. In addition, the AMU expanded the MIDDS GUI to include forecasts out to Day-7.

Barrett, Joe H., III↗