scholarly journals An Assessment of the Uncertainties in Ocean Surface Turbulent Fluxes in 11 Reanalysis, Satellite-Derived, and Combined Global Datasets

2011 ◽  
Vol 24 (21) ◽  
pp. 5469-5493 ◽  
Author(s):  
Michael A. Brunke ◽  
Zhuo Wang ◽  
Xubin Zeng ◽  
Michael Bosilovich ◽  
Chung-Lin Shie
Keyword(s):  
Wind Stress ◽  
Coupled System ◽  
Surface Flux ◽  
Ocean Surface ◽  
Turbulent Fluxes ◽  
Department Of Energy ◽  
Strong Wind ◽  
Wind Speeds ◽  
Direct Covariance ◽  
Environmental Prediction

Abstract Ocean surface turbulent fluxes play an important role in the energy and water cycles of the atmosphere–ocean coupled system, and several flux products have become available in recent years. Here, turbulent fluxes from 6 widely used reanalyses, 4 satellite-derived flux products, and 2 combined product are evaluated by comparison with direct covariance latent heat (LH) and sensible heat (SH) fluxes and inertial-dissipation wind stresses measured from 12 cruises over the tropics and mid- and high latitudes. The biases range from −3.0 to 20.2 W m−2 for LH flux, from −1.4 to 6.0 W m−2 for SH flux, and from −7.6 to 7.9 × 10−3 N m−2 for wind stress. These biases are small for moderate wind speeds but diverge for strong wind speeds (>10 m s−1). The total flux biases are then further evaluated by dividing them into uncertainties due to errors in the bulk variables and the residual uncertainty. The bulk-variable-caused uncertainty dominates many products’ SH flux and wind stress biases. The biases in the bulk variables that contribute to this uncertainty can be quite high depending on the cruise and the variable. On the basis of a ranking of each product’s flux, it is found that the Modern-Era Retrospective Analysis for Research and Applications (MERRA) is among the “best performing” for all three fluxes. Also, the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and the National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) reanalysis are among the best performing for two of the three fluxes. Of the satellite-derived products, version 2b of the Goddard Satellite-Based Surface Turbulent Fluxes (GSSTF2b) is among the best performing for two of the three fluxes. Also among the best performing for only one of the fluxes are the 40-yr ERA (ERA-40) and the combined product objectively analyzed air–sea fluxes (OAFlux). Direction for the future development of ocean surface flux datasets is also suggested.

scholarly journals On the Interaction between Wind Stress and Waves: Wave Growth and Statistical Properties of Large Waves

2020 ◽  
Vol 50 (2) ◽  
pp. 383-397
Author(s):  
J. H. Lee ◽  
J. P. Monty
Keyword(s):  
Wind Speed ◽  
Wind Stress ◽  
Wave Interaction ◽  
Order Theory ◽  
Statistical Properties ◽  
Wave Crest ◽  
Strong Wind ◽  
Wave Growth ◽  
Wind Speeds ◽  
Local Wave

AbstractStatistical properties and development of wave fields with different wind forcings are investigated through parametric laboratory experiments. Thirty different, random sea states simulated using a JONSWAP spectrum are mechanically generated in deep-water conditions. Each of the random simulated sea states is exactly repeated but subjected to a range of different wind speeds to study the interaction between wind stress and the existing random sea state waves, especially the isolated effect of the wind stress on the largest waves. Wave crest distributions are sensitive to the wind at the extreme end such that there is an observed deviation from second-order theory for the largest (lowest probability) waves at high wind speed. Because the local wave steepness increases with wind speed, eventually reaching a breaking point, the growth of extreme waves (relative to the significant wave height) due to wind stress is shown to be limited by wave breaking. Even when large waves are breaking, the data reveal that amplitude modulation of wave groups is enhanced substantially as the wind speed increases due to the difference in growth rates between the highest and the lowest wave crests in a wave group. However, there is no evidence of an increase in modulation instability with the wind speed, suggesting that the wind–wave interaction under strong wind forcing dominates the wave growth mechanism over nonlinear wave interactions in a broadband wave field.

scholarly journals Relating Wind and Stress under Tropical Cyclones with Scatterometer

2016 ◽  
Vol 33 (6) ◽  
pp. 1151-1158 ◽  
Author(s):  
W. Timothy Liu ◽  
Wenqing Tang
Keyword(s):  
Drag Coefficient ◽  
Tropical Cyclones ◽  
Turbulent Transport ◽  
Local Stress ◽  
Ocean Surface ◽  
Retrieval Algorithm ◽  
Strong Wind ◽  
Surface Cooling ◽  
Wind Retrieval ◽  
Wind Speeds

AbstractOcean surface stress, the turbulent transport of momentum, is largely derived from wind through a drag coefficient. In tropical cyclones (TCs), scatterometers have difficulty measuring strong wind and there is large uncertainty in the drag coefficient. This study postulates that the microwave backscatter from ocean surface roughness, which is in equilibrium with local stress, does not distinguish between weather systems. The reduced sensitivity of scatterometer wind retrieval algorithms under the strong wind is an air–sea interaction problem that is caused by a change in the behavior of the drag coefficient rather than a sensor problem. Under this assumption, a stress retrieval algorithm developed over a moderate wind range is applied to retrieve stress under the strong winds of TCs. Over a moderate wind range, the abundant wind measurements and the more established drag coefficient value allow for sufficient stress data to be computed from wind to develop a stress retrieval algorithm for the scatterometer. Using 0.9 million coincident stress and wind pairs, the study shows that the drag coefficient decreases with wind speed at a much steeper rate than previously revealed, for wind speeds over 25 m s−1. The result implies that the ocean applies less drag to inhibit TC intensification, and that TCs cause less ocean mixing and surface cooling than previous studies indicated.

scholarly journals Higher Ocean Surface Wind Speeds During Marine Cold Air Outbreaks

2017 ◽  
Author(s):  
Erik W. Kolstad
Keyword(s):  
Large Scale ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Surface Wind ◽  
Ocean Surface ◽  
Strong Wind ◽  
Cold Air ◽  
Wind Speeds ◽  
Ocean Surface Wind ◽  
Cold Air Outbreaks

Marine cold air outbreaks (MCAOs) are large-scale phenomena in which cold air masses are advected over open ocean. It is well-known that these events are linked to the formation of polar lows and other mesoscale phenomena associated with high wind speeds, and that they therefore in some cases represent a hazard to maritime activities. However, it is still unknown whether MCAOs are generally conducive to higher wind speeds than normal. Here this is investigated by comparing the behaviour of ocean surface wind speeds during MCAOs in three atmospheric reanalysis products with different horizontal grid spacings, along with case studies using a convection-permitting numerical weather prediction model. The study regions are the Labrador Sea and the Greenland–Iceland–Norwegian (GIN) Seas, where MCAOs have been shown to be important for air–sea interaction and deep water formation. The main findings are: 1) Wind speeds during the most extreme MCAO events are stronger than normal and higher than wind speeds during less severe events; 2) The peak times of MCAO usually occur when baroclinic waves pass over the regions; and 3) Reanalyses with grid spacings of more than 50 km appear to underestimate winds driven by the large ocean–atmosphere energy fluxes during MCAOs. It is also shown that while the strong wind episodes during MCAOs generally last for just a few days, MCAOs can persist for up to 50 days. These findings demonstrate that it would be worthwhile to forecast MCAOs, and that it might be possible to do this beyond the standard weather forecasting range of up to 10 days.

scholarly journals Ocean Surface Flux Algorithm Effects on Earth System Model Energy and Water Cycles

2021 ◽  
Vol 8 ◽  
Author(s):  
J. E. Jack Reeves Eyre ◽  
Xubin Zeng ◽  
Kai Zhang
Keyword(s):  
Surface Flux ◽  
Ocean Surface ◽  
Earth System Model ◽  
Surface Fluxes ◽  
System Model ◽  
Earth System ◽  
Ocean Heat Uptake ◽  
Wind Speeds ◽  
Global Mean ◽  
Water Cycles

Earth system models parameterize ocean surface fluxes of heat, moisture, and momentum with empirical bulk flux algorithms, which introduce biases and uncertainties into simulations. We investigate the atmosphere and ocean model sensitivity to algorithm choice in the Energy Exascale Earth System Model (E3SM). Flux differences between algorithms are larger in atmosphere simulations (where wind speeds can vary) than ocean simulations (where wind speeds are fixed by forcing data). Surface flux changes lead to global scale changes in the energy and water cycles, notably including ocean heat uptake and global mean precipitation rates. Compared to the control algorithm, both COARE and University of Arizona (UA) algorithms reduce global mean precipitation and top of atmosphere radiative biases. Further, UA may slightly reduce biases in ocean meridional heat transport. We speculate that changes seen here, especially in the ocean, could be even larger in coupled simulations.

scholarly journals Robustness of the Recent Global Atmospheric Reanalyses for Antarctic Near-Surface Wind Speed Climatology

2020 ◽  
Vol 33 (10) ◽  
pp. 4027-4043 ◽  
Author(s):  
Xu Dong ◽  
Yetang Wang ◽  
Shugui Hou ◽  
Minghu Ding ◽  
Baoling Yin ◽  
...  
Keyword(s):  
Wind Speed ◽  
Regional Scale ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Southern Annular Mode ◽  
Department Of Energy ◽  
Japan Meteorological Agency ◽  
Near Surface ◽  
Wind Speeds ◽  
Environmental Prediction

AbstractNear-surface wind speed observations from 30 manned meteorological stations and 26 automatic weather stations over the Antarctic Ice Sheet are used to examine the robustness of wind speed climatology in six recent global reanalysis products: the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), the Japan Meteorological Agency 55-Year Reanalysis (JRA-55), the Climate Forecast System Reanalysis (CFSR), the National Centers for Environmental Prediction–U.S. Department of Energy (DOE) Reanalysis 2 (NCEP2), and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and fifth-generation reanalysis (ERA5). Their skills for representing near-surface wind speeds vary by season, with better performance in summer than in winter. At the regional scale, all reanalysis datasets perform more poorly for the magnitude, but better for their year-to-year changes in wind regimes in the escarpment than the coastal and plateau regions. By comparison, ERA5 has the best performance for the monthly averaged wind speed magnitude and the interannual variability of the near-surface wind speed from 1979 onward. Intercomparison exhibits high and significant correlations for annual and seasonal wind speed Antarctic-wide averages from different datasets during their overlapping timespans (1980–2018), despite some regional disagreements between the different reanalyses. Furthermore, all of the reanalyses show positive trends of the annual and summer wind speeds for the 1980–2018 period, which are linked with positive polarity of the southern annular mode.

scholarly journals Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction

2017 ◽  
Vol 32 (6) ◽  
pp. 2217-2227 ◽  
Author(s):  
Siri Sofie Eide ◽  
John Bjørnar Bremnes ◽  
Ingelin Steinsland
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Bayesian Model Averaging ◽  
Weather Prediction ◽  
Model Averaging ◽  
Strong Wind ◽  
Ensemble Forecasts ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
The One

Abstract In this paper, probabilistic wind speed forecasts are constructed based on ensemble numerical weather prediction (NWP) forecasts for both wind speed and wind direction. Including other NWP variables in addition to the one subject to forecasting is common for statistical calibration of deterministic forecasts. However, this practice is rarely seen for ensemble forecasts, probably because of a lack of methods. A Bayesian modeling approach (BMA) is adopted, and a flexible model class based on splines is introduced for the mean model. The spline model allows both wind speed and wind direction to be included nonlinearly. The proposed methodology is tested for forecasting hourly maximum 10-min wind speeds based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts at 204 locations in Norway for lead times from +12 to +108 h. An improvement in the continuous ranked probability score is seen for approximately 85% of the locations using the proposed method compared to standard BMA based on only wind speed forecasts. For moderate-to-strong wind the improvement is substantial, while for low wind speeds there is generally less or no improvement. On average, the improvement is 5%. The proposed methodology can be extended to include more NWP variables in the calibration and can also be applied to other variables.

scholarly journals Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

2016 ◽  
Author(s):  
Clara M. St. Martin ◽  
Julie K. Lundquist ◽  
Andrew Clifton ◽  
Gregory S. Poulos ◽  
Scott J. Schreck
Keyword(s):  
Energy Production ◽  
Atmospheric Stability ◽  
Power Production ◽  
Department Of Energy ◽  
Power Performance ◽  
Stability Parameters ◽  
Wind Speeds ◽  
Stable Conditions ◽  
Wind Measurements ◽  
Power Curves

Abstract. Using detailed upwind and nacelle-based measurements from a General Electric [GE] 1.5 sle model with a 77 m rotor diameter, we calculated power curves and annual energy production (AEP) and explored their sensitivity to different atmospheric parameters. This work provides guidelines for the use of stability and turbulence filters in segregating power curves to gain a clearer picture of the power performance of a turbine. The wind measurements upwind of the turbine include anemometers mounted on a 135 m meteorological tower and lidar vertical profiles. We calculated power curves for different regimes based on turbulence parameters such as turbulence intensity (TI) and turbulence kinetic energy (TKE), as well as atmospheric stability parameters such as Bulk Richardson number (RB). AEP was also calculated with and without these atmospheric filters and differences between these calculations are highlighted in this article. The power curves for different TI and TKE regimes revealed that, at the U.S. Department of Energy (DOE) National Wind Technology Center (NWTC) at the National Renewable Energy Laboratory (NREL), increased TI and TKE undermined power production at wind speeds near rated, but increased power production at lower wind speeds. Similarly, power curves for different RB regimes revealed that periods of stable conditions produced more power at wind speeds near rated and periods of unstable conditions produced more power at lower wind speeds. AEP results suggest that calculations done without filtering for these atmospheric regimes may be overestimating the AEP. Because of statistically significant differences between power curves and AEP calculated with these turbulence and stability filters for this turbine at this site, we suggest implementing an additional step in analyzing power performance data to take atmospheric stability and turbulence across the rotor disk into account.

scholarly journals Western Iberian winter wind indices based on significant wind events

2005 ◽  
Vol 2 (2) ◽  
pp. 105-127 ◽  
Author(s):  
E. Mason ◽  
A. M. P. Santos ◽  
Á J. Peliz
Keyword(s):  
Negative Impact ◽  
Significant Negative Correlation ◽  
Hybrid Index ◽  
Easterly Wind ◽  
Annual Variations ◽  
Wind Speeds ◽  
Wind Event ◽  
Wind Events ◽  
Environmental Prediction ◽  
Offshore Transport

Abstract. Wind speed data obtained from the National Centers for Environmental Prediction (NCEP) Reanalysis project are used to construct winter (November–March) wind indices for the western Iberian Peninsula. The data used represent a 2.5&deg square area, centred at 41.0&deg N, 9.4&deg W, over the period 1948-2003. The NCEP data are well correlated with a time-series (1980–2001) of wind measurements from the Cape Carvoeiro lighthouse on the western Portuguese coast (39.4&deg N, 9.4&deg W). The new indices, of which there are four corresponding to northerlies, easterlies, southerlies and westerlies, constitute measures of numbers of significant wind event days, where a significant wind event is defined to be 4 or more consecutive days of wind speeds exceeding 4 m s-1. Results show both intra- and inter-annual variations in the numbers of significant wind event days, as well as clear decadal trends. A comparison between a hybrid index, composed of the numbers of significant northerly and easterly wind event days - both promote offshore transport, which is thought to have a negative impact on pelagic fish recruitment - and western Iberian sardine catch data, reveal an extensive period of significant negative correlation. The relationship over the most recent period, ~1999–2000, is unclear.

Statistical Characterization of Zonal and Meridional Ocean Wind Stress

2005 ◽  
Vol 22 (9) ◽  
pp. 1353-1372 ◽  
Author(s):  
Sarah T. Gille
Keyword(s):  
Wind Stress ◽  
Frequency Spectra ◽  
Low Frequencies ◽  
Statistical Characterization ◽  
Weather Forecasts ◽  
The Pacific ◽  
Meridional Winds ◽  
Wind Events ◽  
Environmental Prediction ◽  
The Tropics

Abstract Four years of ocean vector wind data are used to evaluate statistics of wind stress over the ocean. Raw swath wind stresses derived from the Quick Scatterometer (QuikSCAT) are compared with five different global gridded wind products, including products based on scatterometer observations, meteorological analysis winds from the European Centre for Medium-Range Weather Forecasts, and reanalysis winds from the National Centers for Environmental Prediction. Buoy winds from a limited number of sites in the Pacific Ocean are also considered. Probability density functions (PDFs) computed for latitudinal bands show that mean wind stresses for the six global products are largely in agreement, while variances differ substantially, by a factor of 2 or more, with swath wind stresses indicating highest variances for meridional winds and for zonal winds outside the Tropics. Higher moments of the PDFs also differ. Kurtoses are large for all wind products, implying that PDFs are not Gaussian. None of the available gridded products fully captures the range of extreme wind events seen in the raw swath data. Frequency spectra for the five gridded products agree with frequency spectra from swath data at low frequencies, but spectral slopes differ at higher frequencies, particularly for frequencies greater than 100 cycles per year (cpy), which are poorly resolved by a single scatterometer. In the frequency range between 10 and 90 cpy that is resolved by the scatterometer, spectra derived from swath data are flatter than spectra from gridded products and are judged to be flatter than ω−2/3 at all latitudes.

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