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At least 955 records · Page 53

Jet stream winds - Comparisons of analyses with independent aircraft data over Southwest Asia

Cruise-level wind data from commercial aircraft are obtained, and these data are compared with operational jet stream analyses over southwest Asia, an area of limited conventional data. Results from an ensemble of 11 cases during January 1989 and individual cases during December 1988-March 1989 are presented. The key results are: (1) European Centre for Medium-Range Weather Forecasts (ECMWF), National Meteorological Center, and United Kingdom Meteorological Office analyses of the subtropical jet in southwest Asia are 11 percent, 17 percent, and 17 percent weaker, respectively, than aircraft observations; (2) analyzed poleward shears range up to 1 f (0.00007/s) compared with up to 3 f (0.00021/s) in the aircraft observations where f is the local Coriolis parameters; (3) the ECMWF errors are largest at the base of the jet; (4) the mean ECMWF core location is latitudinally correct but has an rms latitude variance of 1.5 deg; (5) isolated erroneous radiosondes produce unmeteorological structures in the analyzed subtropical jet stream; and (6) the increased utilization of automated aircraft reports is likely to produce a spurious secular increase in the apparent strength of the jets. The magnitude and spatial extent of the errors seen are near limits of current GCM resolution (100 km) but should be resolvable. The results imply that studies of GCM systematic jet stream wind errors in weather and climate forecasts must be interpreted with caution in this region.

Tenenbaum, J.↗

Data Assimilation Cycling for Weather Analysis

This software package runs the atmospheric model MM5 in data assimilation cycling mode to produce an optimized weather analysis, including the ability to insert or adjust a hurricane vortex. The program runs MM5 through a cycle of short forecasts every three hours where the vortex is adjusted to match the observed hurricane location and storm intensity. This technique adjusts the surrounding environment so that the proper steering current and environmental shear are achieved. MM5cycle uses a Cressman analysis to blend observation into model fields to get a more accurate weather analysis. Quality control of observations is also done in every cycle to remove bad data that may contaminate the analysis. This technique can assimilate and propagate data in time from intermittent and infrequent observations while maintaining the atmospheric field in a dynamically balanced state. The software consists of a C-shell script (MM5cycle.driver) and three FORTRAN programs (splitMM5files.F, comRegrid.F, and insert_vortex.F), and are contained in the pre-processor component of MM5 called "Regridder." The model is first initialized with data from a global model such as the Global Forecast System (GFS), which also provides lateral boundary conditions. These data are separated into single-time files using splitMM5.F. The hurricane vortex is then bogussed in the correct location and with the correct wind field using insert_vortex.F. The modified initial and boundary conditions are then recombined into the model fields using comRegrid.F. The model then makes a three-hour forecast. The three-hour forecast data from MM5 now become the analysis for the next short forecast run, where the vortex will again be adjusted. The process repeats itself until the desired time of analysis is achieved. This code can also assimilate observations if desired.

Tran, Nam↗

THE SPACE WEATHER OF PROXIMA CENTAURI b

A planet orbiting in the “habitable zone” of our closest neighboring star, Proxima Centauri, has recently been discovered, and the next natural question is whether or not Proxima b is “habitable.” Stellar winds are likely a source of atmospheric erosion that could be particularly severe in the case of M dwarf habitable zone planets that reside close to their parent star. Here, we study the stellar wind conditions that Proxima b experiences over its orbit. We construct 3D MHD models of the wind and magnetic field around Proxima Centauri using a surface magnetic field map for a star of the same spectral type and scaled to match the observed ∼600 G surface magnetic field strength of Proxima. We examine the wind conditions and dynamic pressure over different plausible orbits that sample the constrained parameters of the orbit of Proxima b. For all the parameter space explored, the planet is subject to stellar wind pressures of more than 2000 times those experienced by Earth from the solar wind. During an orbit, Proxima b is also subject to pressure changes of 1–3 orders of magnitude on timescales of a day. Its magnetopause standoff distance consequently undergoes sudden and periodic changes by a factor of 2–5. Proxima b will traverse the interplanetary current sheet twice each orbit, and likely crosses into regions of subsonic wind quite frequently. These effects should be taken into account in any physically realistic assessment or prediction of its atmospheric reservoir, characteristics, and loss.

79 ASTRONOMY AND ASTROPHYSICS↗

Wave and Offshore Wind Resource in the U.S. Pacific Ocean Minor Outlying Islands

Coastal environments such as islands have unique opportunities for renewable energy resources. This work explores the wave and offshore wind energy potential for the U.S. Pacific Ocean Minor Outlying Islands, including Baker Island, Howland Island, Jarvis Island, Johnston Atoll, Kingman Reef, Palmyra Atoll, and Wake Island. A numerical wave model based on WAVEWATCH III and SWAN (both are NWS / NOAA models) was developed, validated, and executed to generate a 32-year hindcast dataset suitable for resource characterization for each island. A complementary offshore wind resource characterization is provided for the same time period based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5). Each island has five netcdf files: 1. wave_[island]_annual_J_map.nc: the data used to generate the map of annual averaged omnidirectional wave power (J [kW/m]) 2. wave_[island]_100m_IEC: six IEC parameters at 100m isobath from 1979/01/01 to 2020/12/31, output hourly 3. wave_[island]_5km_IEC: six IEC parameters at 5km from the shoreline 1979/01/01 to 2020/12/31, output hourly 4. wind_island_100mASL_windspeed_timeseries.nc: wind speed timeseries from ERA5 at 100 m above sea level within a 60 km radius of the island (m/s) 1979/01/01 to 2010/12/31, output hourly 5. wind_island_100mASL_winddirection_timeseries.nc: wind direction timeseries from ERA5 at 100 m above sea level within a 60 km radius of the island (degrees) 1979/01/01 to 2010/12/31, output hourly

16 TIDAL AND WAVE POWER↗

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗

Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds

Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Simulation of wind and solar energy generation over California with E3SM SCREAM regionally refined models at 3.25 km and 800 m resolutions

This study presents wind and solar power generation estimates derived from the US Department of Energy’s Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) Regionally Refined Models (RRM) over California at 3.25 km and 800 m horizontal resolutions, using the Python wrapper for the System Advisor Model (PySAM). The resulting wind and solar generation estimates are compared to monthly capacity factors reported to the Energy Information Administration (EIA), High-Resolution Rapid Refresh (HRRR, 3 km resolution) forecast model, and E3SM North American regionally refined model (NARRM, 25 km resolution). We systematically assess the impacts of generation modeling assumptions, meteorological models, and horizontal resolution. Results show that resolution plays a dominant role for wind energy: increasing from 25 to 3.25 km brings qualitative and quantitative improvements, most notably by resolving the phase error in the seasonal cycle found in coarser simulations. However, further refinement to 800 m offers minimal gains. SCREAM performs better than HRRR for solar power generation in single- and dual-axis tracking systems, likely due to more accurate surface radiation. The sensitivity of PySAM to system configuration, particularly for axis-tracking modeling in photovoltaics, is also highlighted. Overall, SCREAM-RRM shows strong potential for high-resolution energy assessments, with future progress depending on more in situ observations and clearer quantification of uncertainties in generation modeling.

Geosciences↗

Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production

Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects.

17 WIND ENERGY↗

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Atmospheric 3D winds in the horizontal and vertical directions are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we use a state-of-the-art convolutional neural network for optical flow (FlowNetS) in a physics-guided deep learning framework for predicting AMVs in the horizontal direction. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations (DYAMOND) for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

geostationary↗

The impact of tropical wind data on the analysis and forcasts of the GLA GCM for the global weather experiment

It is well-known that divergent wind estimates are much more dependent upon the analysis system than are estimates of the rotational wind. This conclusion is supported in recent analyses of FGGE SOP1 data produced by the Goddard Laboratory for Atmospheres (GLA), the Geophysical Fluid Dynamics Laboratory (GFDL) and the European Center for Medium Range Weather Forecasting (ECMWF). These analyses differ in the forecast models that are used for the four-dimensional assimilation, in the data rejection criteria, and, to a certain extent, in the data density. Because the final divergent wind is a product of both model constraints and observation, it is relevant to inquire how much of each goes into the final product. We presently investigate this question through a systematic analysis of tropical data that are sampled at different densities by the GLA GCM.

Paegle, Jan↗

Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model

Prediction of Saharan dust customarily requires complex aerosols models and observations. A previous study of the Miami, Florida dust record in conjunction to reanalysis data discovered a possible source of subseasonal predictability using a dust-transport-efficiency (DTE) index. Development of the Subseasonal Forecast Experiment (SubX) has expanded global forecast products; producing multi-model ensemble forecasts out to 45 days. Retrospective forecast data from the Community Climate System Model version 4.0 (CCSM4) is used in direct comparison to National Centers for Environmental Prediction (NCEP) reanalysis to evaluate the CCSM4 subseasonal forecast and DTE index prediction skill of weekly dust variability. Successful prediction of weekly dust transport using the DTE index is variable year-to-year. The DTE most successfully predicts dust when there is high variability in the tropical winds, likely due to a fluctuating subtropical high, and is not dependent on the overall mean flow or total dust mass transported. The CCSM4 SubX retrospective forecast well represents North Atlantic meteorology out to week-3 in both mean flow and variability. Dust transport can be predicted using the DTE index and CCSM4 SubX retrospective forecasts at week-1 leads to the same success as contemporaneous NCEP reanalysis.

54 ENVIRONMENTAL SCIENCES↗

Projecting Future Energy Production from Operating Wind Farms in North America. Part III: Variability

Abstract Daily expected wind power production from operating wind farms across North America are used to evaluate capacity factors (CF) computed using simulation output from the Weather Research and Forecasting (WRF) Model and to condition statistical models linking atmospheric conditions to electricity production. In Parts I and II of this work, we focus on making projections of annual energy production and the occurrence of electrical production drought. Here, we extend evaluation of the CF projections for sites in the Northeast, Midwest, southern Great Plains (SGP), and southwest U.S. coast (SWC) using statewide wind-generated electricity supply to the grid. We then quantify changes in the time scales of CF variability and the seasonality. Currently, wind-generated electricity is lowest in summer in each region except SWC, which causes a substantial mismatch with electricity demand. While electricity of residential heating may shift demand, research presented here suggests that summertime CF are likely to decline, potentially exacerbating the offset between seasonal peak power production and current load. The reduction in summertime CF is manifest for all regions except the SGP and appears to be linked to a reduction in synoptic-scale variability. Using fulfillment of 50% and 90% of annual energy production to quantify interannual variability, it is shown that wind power production exhibits higher (earlier fulfillment) or lower (later fulfillment) production for periods of over 10–30 years as a result of the action of internal climate modes. Significance Statement Electrical power system reassessment and redesign may be needed to aid efficient increased use of variable renewables in the generation of electricity. Currently wind-generated electricity in many regions of North America exhibits a minimum in summertime and hence is not well synchronized with electricity demand, which tends to be maximized in summer. Future projections indicate evidence of reductions in wind power during summer that would amplify this offset. However, electrification of heating may lead to increased wintertime demand, which would lead to greater synchronization.

Coburn, Jacob↗

Mass-loss Rates from Coronal Mass Ejections: A Predictive Theoretical Model for Solar-type Stars

Coronal mass ejections (CMEs) are eruptive events that cause a solar-type star to shed mass and magnetic flux. CMEs tend to occur together with flares, radio storms, and bursts of energetic particles. On the Sun, CME-related mass loss is roughly an order of magnitude less intense than that of the background solar wind. However, on other types of stars, CMEs have been proposed to carry away much more mass and energy than the time-steady wind. Earlier papers have used observed correlations between solar CMEs and flare energies, in combination with stellar flare observations, to estimate stellar CME rates. This paper sidesteps flares and attempts to calibrate a more fundamental correlation between surface-averaged magnetic fluxes and CME properties. For the Sun, there exists a power-law relationship between the magnetic filling factor and the CME kinetic energy flux, and it is generalized for use on other stars. An example prediction of the time evolution of wind/CME mass-loss rates for a solar-mass star is given. A key result is that for ages younger than about 1 Gyr (i.e., activity levels only slightly higher than the present-day Sun), the CME mass loss exceeds that of the time-steady wind. At younger ages, CMEs carry 10–100 times more mass than the wind, and such high rates may be powerful enough to dispel circumstellar disks and affect the habitability of nearby planets. The cumulative CME mass lost by the young Sun may have been as much as 1% of a solar mass.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulation of Wind Profile Perturbations for Launch Vehicle Ascent Flight Systems Design Assessments

Ideally, a statistically representative sample of measured high-resolution wind profiles with wavelengths as small as tens of meters is required for assessment of launch vehicle ascent flight systems component capability and vehicle operability for a selected launch site. At most potential launch sites a sample of high-resolution measured wind profiles may not exist. Representative samples of Rawinsonde wind profiles are more likely to be available because of the extensive network of measurement sites established for routine measurements at 12-hr intervals in support of national and international weather observing and forecasting activity. Such a sample, although large enough to statistically represent relatively large wavelength perturbations, would be inadequate for launch system design assessment applications because the Rawinsonde system can accurately measure wind perturbations with wavelengths no smaller than 2000m (1000m altitude increment). Wavelengths less than 2000m in the raw Rawinsonde data, which tend to be dominated by un-damped spurious balloon motion and radar tracking system noise, are filtered within the data processing scheme. The Kennedy Space Center (KSC) Jimsphere wind profiles (150/month and seasonal pairs) are the only adequate high resolution (approximately 150 to 300m effective resolution, but over-sampled at 25m intervals) data that have been used extensively in launch vehicle design, operability assessments and operational protection of vehicle systems for wind perturbation uncertainty. Jimsphere wind profiles have been measured at a few other potential launch sites but the number of profiles is relatively small and the samples are not statistically representative of the site dependent wind profile variability. A simulation process has been developed for enhancement of measured low-resolution Rawinsonde profiles that are more likely to be available in the vicinity of potential launch sites and are a statistically representative sample of wind profile perturbation wavelengths greater than 2000m. The enhancement produces perturbed wind profiles with wavelengths as small as desired for application in launch vehicle ascent flight simulations and design assessments.

Adelfang, S. I.↗

Electric-Field Instrument With Ac-Biased Corona Point

Measurements indicative of incipient lightning yield additional information. New instrument gives reliable readings. High-voltage ac bias applied to needle point through high-resistance capacitance network provides corona discharge at all times, enabling more-slowly-varying component of electrostatic potential of needle to come to equilibrium with surrounding air. High resistance of high-voltage coupling makes instrument insensitive to wind. Improved corona-point instrument expected to yield additional information assisting in safety-oriented forecasting of lighting.

Markson, R.↗

TAMDAR Capabilities Development

In this viewgraph presentation, information is provided on a collaboration between NASA, the FAA (Federal Aviation Administration), and NOAA (National Oceanographic and Atmospheric Association), particularly regarding the development of a TAMDAR Sensor system. TAMDAR is envisioned to downlink weather data such as icing, temperature, pressure altitude, humidity, magnetic heading, eddy dissipation rate, true airspeed, dew point, density altitude, and winds at altitude from non-jet aircraft. The weather data will be sent to FSL (Forecast Systems Laboratory), FSS (Flight Service Station), ATC (Air Traffic Control), AWC (Aviation Weather Center), and others via a ground-based infrastructure and to other aircraft. New weather products will be generated and uplinked to the cockpit.

Daniels, Taumi↗

Sensitivity of the Assimilated Ozone in the UTLS to Model and Data Selection Changes

This presentation will discuss the sensitivity of assimilated ozone fields in the upper troposphere and lower stratosphere (UTLS) to a number of factors, focusing mainly on aspects of data selection and the prediction model. This is important, because assimilation represents an attempt to construct our best estimates of the true ozone field; however, inaccuracies in the UTLS ozone distribution translate into an uncertainty in factors such as the calculated radiative forcing of climate or the inferred stratosphere-troposphere exchange (STE) of ozone. The 3D ozone data assimilation system, from NASA's Global Modeling and Assimilation Office (GMAO), combines observations of total ozone column and stratospheric profiles with predictions from an off-line, parameterized chemistry and transport model (pCTM) to produce six-hourly, global analyses. The first experiments discussed assimilate ozone retrievals from the Earth-Probe Total Ozone Mapping Spectrometer (EPTOMS) and stratospheric profiles from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument. The SBUV/2 ozone data have a coarse vertical resolution, with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone profiles in the UTLS region are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Sensitivity studies have been conducted to examine the responses to TOMS and SBUV/2 data selection, modifications of the forecast and observation error covariance models, and the model formulation (turning off chemistry or using different wind analyses in the pCTM). The second set of experiments includes an additional data type: ozone retrieved from infrared limb-emission by MIPAS on Envisat. These data offer not only improved vertical resolution in the stratosphere, but also give measurements in the polar night. Comparisons of the assimilated ozone fields from both sets of experiments with independent observations, primarily ozone sondes, are used to determine the impact of each of these changes. It is shown that many of the changes have a significant impact on the UTLS ozone estimates. Implications for interpretation of STE and radiative forcing of climate are discussed.

Pawson, Steven↗

Sun, the Earth, and Near-Earth Space: A Guide to the Sun-Earth System

In a world of warmth and light and living things we soon forget that we are surrounded by a vast universe that is cold and dark and deadly dangerous, just beyond our door. On a starry night, when we look out into the darkness that lies around us, the view can be misleading in yet another way: for the brightness and sheer number of stars, and their chance groupings into familiar constellations, make them seem much nearer to each other, and to us, that in truth they are. And every one of them--each twinkling, like a diamond in the sky--is a white-hot sun, much like our own. The nearest stars in our own galaxy--the Milky Way-- are more than a million times further away from us than our star, the Sun. We could make a telephone call to the Moon and expect to wait but a few seconds between pieces of a conversation, or but a few hours in calling any planet in our solar system.

Sun↗