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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. The LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Investigation of water vapor motion winds from geostationary satellites

Water vapor imagery from geostationary satellites has been available for over a decade. These data are used extensively by operational analysts and forecasters, mainly in a qualitative mode (Weldon and Holmes 1991). In addition to qualitative applications, motions deduced in animated water vapor imagery can be used to infer wind fields in cloudless regimes, thereby augmenting the information provided by cloud-drift wind vectors. Early attempts at quantifying the data by tracking features in water vapor imagery met with modest success (Stewart et al. 1985; Hayden and Stewart 1987). More recently, automated techniques have been developed and refined, and have resulted in upper-level wind observations comparable in quality to current operational cloud-tracked winds (Laurent 1993). In a recent study by Velden et al. (1993) it was demonstrated that wind sets derived from Meteosat-3 (M-3) water vapor imagery can provide important environmental wind information in data void areas surrounding tropical cyclones, and can positively impact objective track forecasts. M-3 was repositioned to 75W by the European Space Agency in 1992 in order to provide complete coverage of the Atlantic Ocean. Data from this satellite are being transmitted to the U.S. for operational use. Compared with the current GOES-7 (G-7) satellite (positioned near 112W), the M-3 water vapor channel contains a superior horizontal resolution (5 km vs. 16 km ). In this paper, we examine wind sets derived using automated procedures from both GOES-7 and Meteosat-3 full disk water vapor imagery in order to assess this data as a potentially important source of large-scale wind information. As part of a product demonstration wind sets were produced twice a day at CIMSS during a six-week period in March and April (1994). These data sets are assessed in terms of geographic coverage, statistical accuracy, and meteorological impact through preliminary results of numerical model forecast studies.

Velden, Christopher S.↗
DOE OSTI2022

Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain?

Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-the-art NWP model – the Weather Research and Forecasting (WRF) Model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-term Ensemble Dataset (WTK-LED) to those observed by lidars at a site in Oklahoma, United States, and in a United States Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (~-1ms-1) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a limited negative bias (~-0.5ms-1) offshore and a slight positive bias (~+0.5ms-1) at the land-based site. On the other hand, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED's higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle. At the land-based site, this is partially caused by wind plant wake effects not being accurately captured by WTK-LED.

17 WIND ENERGY↗
NASA NTRS1991

A Variational Assimilation Method for Satellite and Conventional Data: a Revised Basic Model 2B

A variational objective analysis technique that modifies observations of temperature, height, and wind on the cyclone scale to satisfy the five 'primitive' model forecast equations is presented. This analysis method overcomes all of the problems that hindered previous versions, such as over-determination, time consistency, solution method, and constraint decoupling. A preliminary evaluation of the method shows that it converges rapidly, the divergent part of the wind is strongly coupled in the solution, fields of height and temperature are well-preserved, and derivative quantities such as vorticity and divergence are improved. Problem areas are systematic increases in the horizontal velocity components, and large magnitudes of the local tendencies of the horizontal velocity components. The preliminary evaluation makes note of these problems but detailed evaluations required to determine the origin of these problems await future research.

Achtemeier, Gary L.↗
NASA NTRS2001

The Vertical Error Characteristics of GOES-derived Winds: Description and Impact on Numerical Weather Prediction

Errors in the height assignment of some satellite-derived winds exist because the satellites sense radiation emitted from a finite layer of the atmosphere rather than a specific level. Potential problems in data assimilation may arise because the motion of a measured layer is often represented by a single-level value. In this research, cloud and water vapor motion winds that are derived from the Geostationary Operational Environmental Satellites (GOES winds) are compared to collocated rawinsonde observations (RAOBs). An important aspect of this work is that in addition to comparisons at each assigned height, the GOES winds are compared to the entire profile of the collocated RAOB data to determine the vertical error characteristics of the GOES winds. The impact of these results on numerical weather prediction is then investigated. The comparisons at individual vector height assignments indicate that the error of the GOES winds range from approx. 3 to 10 m/s and generally increase with height. However, if taken as a percentage of the total wind speed, accuracy is better at upper levels. As expected, comparisons with the entire profile of the collocated RAOBs indicate that clear-air water vapor winds represent deeper layers than do either infrared or water vapor cloud-tracked winds. This is because in cloud-free regions the signal from water vapor features may result from emittance over a thicker layer. To further investigate characteristics of the clear-air water vapor winds, they are stratified into two categories that are dependent on the depth of the layer represented by the vector. It is found that if the vertical gradient of moisture is smooth and uniform from near the height assignment upwards, the clear-air water vapor wind tends to represent a relatively deep layer. The information from the comparisons is then used in numerical model simulations of two separate events to determine the forecast impacts. Four simulations are performed for each case: 1) A control simulation that assimilates no satellite wind data, 2) assimilation of all GOES winds according to their assigned single level height, 3) assimilation of all GOES winds spread over multiple levels, and 4) assimilation of all GOES winds spread over multiple levels, but with variations in the vertical influence of clear-air water vapor winds based on the moisture profile in the model. In the first case, a strong mid-latitude cyclone is present and the use of the satellite data results in improved storm tracks during the initial approx. 36 h forecast period. This is because the satellite data improves the analysis of the environment into which the storm progresses. Statistics for mean wind vector and height differences show that, with the exception of the height field at later times in the first case, the use of GOES winds improves the simulation with time. The simulation results suggest that it is beneficial to spread the GOES wind information over multiple levels, particularly when the moisture profile is used to define the vertical influence.

Rao, P. Anil↗
NASA NTRS2000

Evaluation of Bogus Vortex Techniques with Four-Dimensional Variational Data Assimilation

The effectiveness of techniques for creating "bogus" vortices in numerical simulations of hurricanes is examined by using the Penn State/NCAR nonhydrostatic mesoscale model (MM5) and its adjoint system. A series of four-dimensional variational data assimilation (4-D VAR) experiments is conducted to generate an initial vortex for Hurricane Georges (1998) in the Atlantic Ocean by assimilating bogus sea-level pressure and surface wind information into the mesoscale numerical model. Several different strategies are tested for improving the vortex representation. The initial vortices produced by the 4-D VAR technique are able to reproduce many of the structural features of mature hurricanes. The vortices also result in significant improvements to the hurricane forecasts in terms of both intensity and track. In particular, with assimilation of only bogus sea-level pressure information, the response in the wind field is contained largely within the divergent component, with strong convergence leading to strong upward motion near the center. Although the intensity of the initial vortex seems to be well represented, a dramatic spin down of the storm occurs within the first 6 h of the forecast. With assimilation of bogus surface wind data only, an expected dominance of the rotational component of the wind field is generated, but the minimum pressure is adjusted inadequately compared to the actual hurricane minimum pressure. Only when both the bogus surface pressure and wind information are assimilated together does the model produce a vortex that represents the actual intensity of the hurricane and results in significant improvements to forecasts of both hurricane intensity and track.

Pu, Zhao-Xia↗
NASA NTRS2014

Hurricane Imaging Radiometer Wind Speed and Rain Rate Retrievals during the 2010 GRIP Flight Experiment

Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes.

Sahawneh, Saleem↗
NASA NTRS2006

The Solar Wind and Geomagnetic Activity as a Function of Time Relative to Corotating Interaction Regions

Corotating interaction regions during the declining phase of the solar cycle are the cause of recurrent geomagnetic storms and are responsible for the generation of high fluxes of relativistic electrons. These regions are produced by the collision of a high-speed stream of solar wind with a slow-speed stream. The interface between the two streams is easily identified with plasma and field data from a solar wind monitor upstream of the Earth. The properties of the solar wind and interplanetary magnetic field are systematic functions of time relative to the stream interface. Consequently the coupling of the solar wind to the Earth's magnetosphere produces a predictable sequence of events. Because the streams persist for many solar rotations it should be possible to use terrestrial observations of past magnetic activity to predict future activity. Also the high-speed streams are produced by large unipolar magnetic regions on the Sun so that empirical models can be used to predict the velocity profile of a stream expected at the Earth. In either case knowledge of the statistical properties of the solar wind and geomagnetic activity as a function of time relative to a stream interface provides the basis for medium term forecasting of geomagnetic activity. In this report we use lists of stream interfaces identified in solar wind data during the years 1995 and 2004 to develop probability distribution functions for a variety of different variables as a function of time relative to the interface. The results are presented as temporal profiles of the quartiles of the cumulative probability distributions of these variables. We demonstrate that the storms produced by these interaction regions are generally very weak. Despite this the fluxes of relativistic electrons produced during those storms are the highest seen in the solar cycle. We attribute this to the specific sequence of events produced by the organization of the solar wind relative to the stream interfaces. We also show that there are large quantitative differences in various parameters between the two cycles.

McPherron, Robert L.↗
NASA NTRS2016

Forecasting the Northern African Dust Outbreak Towards Europe in April 2011: A Model Intercomparison

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 hours using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

dust storms↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
DOE OSTI2016

2015 Wind Technologies Market Report

Annual wind power capacity additions in the United States surged in 2015 and are projected to continue at a rapid clip in the coming five years. Recent and projected near-term growth is supported by the industry’s primary federal incentive—the production tax credit (PTC)—having been extended for several years (though with a phase-down schedule, described further on pages 68-69), as well as a myriad of state-level policies. Wind additions are also being driven by improvements in the cost and performance of wind power technologies, yielding low power sales prices for utility, corporate, and other purchasers. At the same time, the prospects for growth beyond the current PTC cycle remain uncertain: growth could be blunted by declining federal tax support, expectations for low natural gas prices, and modest electricity demand growth. This annual report—now in its tenth year—provides a detailed overview of developments and trends in the U.S. wind power market, with a particular focus on 2015. The report begins with an overview of key installation-related trends: trends in U.S. wind power capacity growth; how that growth compares to other countries and generation sources; the amount and percentage of wind energy in individual states; the status of offshore wind power development; and the quantity of proposed wind power capacity in various interconnection queues in the United States. Next, the report covers an array of wind power industry trends: developments in turbine manufacturer market share; manufacturing and supply-chain developments; wind turbine and component imports into and exports from the United States; project financing developments; and trends among wind power project owners and power purchasers. The report then turns to a summary of wind turbine technology trends: turbine size, hub height, rotor diameter, specific power, and IEC Class. After that, the report discusses wind power performance, cost, and pricing trends. In so doing, it describes trends in project performance, wind turbine transaction prices, installed project costs, and operations and maintenance (O&M) expenses. It also reviews the prices paid for wind power in the United States and how those prices compare to short-term wholesale electricity prices and forecasts of future natural gas prices. Next, the report examines policy and market factors impacting the domestic wind power market, including federal and state policy drivers as well as transmission and grid integration issues. The report concludes with a preview of possible near-term market developments. This edition of the annual report updates data presented in previous editions while highlighting key trends and important new developments from 2015. The report concentrates on larger, utility-scale wind turbines, defined here as individual turbines that exceed 100 kW in size.

17 WIND ENERGY↗
NASA NTRS2013

First Cloud-to-Ground Lightning Timing Study

NASA's LSP, GSDO and other programs use the probability of cloud-to-ground (CG) lightning occurrence issued by the 45th Weather Squadron (45 WS) in their daily and weekly lightning probability forecasts. These organizations use this information when planning potentially hazardous outdoor activities, such as working with fuels, or rolling a vehicle to a launch pad, or whenever personnel will work outside and would be at-risk from lightning. These organizations would benefit greatly if the 45 WS could provide more accurate timing of the first CG lightning strike of the day. The Applied Meteorology Unit (AMU) has made significant improvements in forecasting the probability of lightning for the day, but forecasting the time of the first CG lightning with confidence has remained a challenge. To address this issue, the 45 WS requested the AMU to determine if flow regimes, wind speed categories, or a combination of the two could be used to forecast the timing of the first strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) lightning warning circles. The data was stratified by various sea breeze flow regimes and speed categories in the surface to 5,000-ft layer. The surface to 5,000-ft layer was selected since that is the layer the 45 WS uses to predict the behavior of sea breeze fronts, which are the dominant influence on the occurrence of first lightning in Florida during the warm season. Due to small data sample sizes after stratification, the AMU could not determine a statistical relationship between flow regimes or speed categories and the time of the first CG strike.. As expected, although the amount and timing of lightning activity varies by time of day based on the flow regimes and speed categories, there are extended tails of low lightning activity making it difficult to specify times when the threat of the first lightning flash can be avoided. However, the AMU developed a graphical user interface with input from the 45 WS that allows forecasters to visualize the climatological frequencies of the timing of the first lightning strike. This tool should contribute directly to the 45 WS goal of improving lightning timing capability for its NASA, US Air Force and commercial customers.

statistical analysis↗
DOE OSTI2023

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗
DOE OSTI2022

The Impact of Constrained Data Assimilation on the Forecasts of Three Convection Systems During the ARM MC3E Field Campaign

A constrained data assimilation (CDA) system based on the ensemble variational (EnVar) method and physical constraints of mass and water conservations is evaluated through three convective cases during the Midlatitude Continental Convective Clouds Experiment (MC3E) of the Atmospheric Radiation Measurement (ARM) program. Compared to the original data assimilation (ODA), the CDA is shown to perform better in the forecasted state variables and simulated precipitation. The CDA is also shown to greatly mitigate the loss of forecast skills in observation denial experiments when radar radial winds are withheld in the assimilation. Modifications to the algorithm and sensitivities of the CDA to the calculation of the time tendencies in the constraints are described.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Development of a Silicon Carbide Molecular Beam Nozzle for Simulation Planetary Flybys and Low-Earth Orbit

From commercial origins as a molybdenum molecular beam nozzle, a ceramic nozzle of silicon carbide (SiC) was developed for space environment simulation. The nozzle is mechanically stable under extreme conditions of temperature and pressure. A heated, continuous, supersonically-expanded hydrogen beam with a 1% argon seed produced an argon beam component of nearly 4 km/s, with an argon flux exceeding 1x1014 /cm2.s. This nozzle was part of a molecular beam machine used in the Atmospheric Experiments Branch at NASA Goddard Space Flight Center to characterize the performance of the University of Texas at Dallas Ram Wind Sensor (RWS) aboard the Air Force Communications/Navigation Outage Forecasting System (C/NOFS) launched in the Spring of 2008.

Patrick, E. L.↗
NASA NTRS2009

The Magnetic Field of Mars and its Interaction with the Solar Wind

The outermost layers of the Martian atmosphere are thought to be scientifically unique due to the large influences exerted by the highly dynamic lower atmosphere and the direct input of the solar wind from above. The nature of the solar wind interaction with the upper atmosphere is of particular interest because Mars lacks a global magnetic field, but is well shielded over some regions by strong crustal magnetic fields. Under such circumstances, the direct impact of solar wind plasma may have resulted in enhanced loss of volatiles over the ages including the components of water. The history of upper atmosphere and solar wind interaction measurements at Mars will be reviewed, recent results from the Mars Global Surveyor and Mars Express summarized, and prospects for new scientific advances enabled by the measurements that will be made by planned orbiter and penetrator missions. Special attention will be given to planetary magnetic field measurements, the measurement of ionospheric currents driven by the solar wind, and the role of space weather modeling and forecasting in the future of Mars exploration.

Le, Guan↗
NASA NTRS2005

Applied Meteorology Unit (AMU) Quarterly Report. First Quarter FY-05

This report summarizes the Applied Meteorology Unit (AMU) activities for the first quarter of Fiscal Year 2005 (October - December 2005). Tasks reviewed include: (1) Objective Lightning Probability Forecast: Phase I, (2) Severe Weather Forecast Decision Aid, (3) Hail Index, (4) Stable Low Cloud Evaluation, (5) Shuttle Ascent Camera Cloud Obstruction Forecast, (6) Range Standardization and Automation (RSA) and Legacy Wind Sensor Evaluation, (7) Advanced Regional Prediction System (ARPS) Optimization and Training Extension, and (8) User Control Interface for ARPS Data Analysis System (ADAS) Data Ingest

Bauman, William↗
NASA NTRS1985

Statrospheric warmings during the winter of 1979

Some of the arguments crucial to the current understanding of stratospheric warmings are recapitulated briefly. The circulation at 10 mb during the winter of 1979 is described. A review of numerical forecasts of stratospheric warmings reveals that, in general, these events are predictable from several days in advance. In some cases, however, relatively small errors in the predicted tropospheric zonal mean wind produce large differences in upward wave propagation and, consequently, in the stratospheric forecast.

Mechoso, C. R.↗