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 CYGNSS Ocean Surface Wind Validation in the Tropics

2020 ◽  
Author(s):  
Shakeel Asharaf ◽  
Duane E. Waliser ◽  
Derek J. Posselt ◽  
Christopher S. Ruf ◽  
Chidong Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Satellite System ◽  
Cold Pool ◽  
Tropical Ocean ◽  
Near Surface ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
Global Navigation Satellite

AbstractSurface wind plays a crucial role in many local/regional weather and climate processes, especially through the exchanges of energy, mass and momentum across the Earth’s surface. However, there is a lack of consistent observations with continuous coverage over the global tropical ocean. To fill this gap, the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016, consisting of a constellation of eight small spacecrafts that remotely sense near surface wind speed over the tropical and sub-tropical oceans with relatively high sampling rates both temporally and spatially. This current study uses data obtained from the Tropical Moored Buoy Arrays to quantitatively characterize and validate the CYGNSS derived winds over the tropical Indian, Pacific, and Atlantic Oceans. The validation results show that the uncertainty in CYGNSS wind speed, as compared with these tropical buoy data, is less than 2 m s-1 root mean squared difference, meeting the NASA science mission Level-1 uncertainty requirement for wind speeds below 20 m s-1. The quality of the CYGNSS wind is further assessed under different precipitation conditions, and in convective cold-pool events, identified using buoy rain and temperature data. Results show that CYGNSS winds compare fairly well with buoy observations in the presence of rain, though at low wind speeds the presence of rain appears to cause a slight positive wind speed bias in the CYGNSS data. The comparison indicates the potential utility of the CYGNSS surface wind product, which in turn may help to unravel the complexities of air-sea interaction in regions that are relatively under-sampled by other observing platforms.

scholarly journals Homogenization and Trend Analysis of Canadian Near-Surface Wind Speeds

2010 ◽  
Vol 23 (5) ◽  
pp. 1209-1225 ◽  
Author(s):  
Hui Wan ◽  
Xiaolan L. Wang ◽  
Val R. Swail
Keyword(s):  
Wind Speed ◽  
Trend Analysis ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
The United States ◽  
Homogeneity Test ◽  
Near Surface ◽  
Wind Speeds ◽  
Long Term Trends

Abstract Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends. This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.

scholarly journals Centennial-scale variability of terrestrial near-surface wind speed over China from reanalysis

2021 ◽  
pp. 1-52
Author(s):  
Cheng Shen ◽  
Jinlin Zha ◽  
Jian Wu ◽  
Deming Zhao
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Stepwise Regression ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Wind Speeds ◽  
Ocean Atmosphere ◽  
Forward Stepwise ◽  
Strong Winds

AbstractInvestigations of variations and causes of near-surface wind speed (NWS) further understanding of the atmospheric changes and improve the ability of climate analysis and projections. NWS varies on multiple temporal scales; however, the centennial-scale variability in NWS and associated causes over China remains unknown. In this study, we employ the European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA-20C) to study the centennial-scale changes in NWS from 1900–2010. Meanwhile, a forward stepwise regression algorithm is used to reveal the relationships between NWS and large-scale ocean-atmosphere circulations. The results show three unique periods in annual mean NWS over China from 1900–2010. The annual mean NWS displayed a decreasing trend of -0.87% decade-1 and -11.75% decade-1 from 1900–1925 and 1957–2010, respectively, which were caused by the decreases in the days with strong winds, with trends of -6.64 and -4.66 days decade-1, respectively. The annual mean NWS showed an upward trend of 55.47% decade-1 from 1926–1956, which was caused by increases in the days with moderate (0.43 days decade-1) and strong winds (23.55 days decade-1). The reconstructed wind speeds based on forward stepwise regression algorithm matched well with the original wind speeds; therefore, the decadal changes in NWS over China at centennial-scale were mainly induced by large-scale ocean-atmosphere circulations, with the total explanation power of 66%. The strongest explanation power was found in winter (74%), and the weakest explanation power was found in summer (46%).

Observed Coherent Trends of Surface and Upper-Air Wind Speed over China since 1960

2013 ◽  
Vol 26 (9) ◽  
pp. 2891-2903 ◽  
Author(s):  
Changgui Lin ◽  
Kun Yang ◽  
Jun Qin ◽  
Rong Fu
Keyword(s):  
Wind Speed ◽  
Tibetan Plateau ◽  
Regional Scale ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Spatial Gradient ◽  
The Tibetan Plateau ◽  
Strong Wind ◽  
Wind Speeds ◽  
The Past

Abstract Previous studies indicated that surface wind speed over China declined during past decades, and several explanations exist in the literature. This study presents long-term (1960–2009) changes of both surface and upper-air wind speeds over China and addresses observed evidence to interpret these changes. It is found that surface wind over China underwent a three-phase change over the past 50 yr: (i) it step changed to a strong wind level at the end of the 1960s, (ii) it declined until the beginning of the 2000s, and (iii) it seemed to be steady and even recovering during the very recent years. The variability of surface wind speed is greater at higher elevations and less at lower elevations. In particular, surface wind speed over the elevated Tibetan Plateau has changed more significantly. Changes in upper-air wind speed observed from rawinsonde are similar to surface wind changes. The NCEP–NCAR reanalysis indicates that wind speed changes correspond to changes in geopotential height gradient at 500 hPa. The latter are further correlated with the changes of latitudinal surface temperature gradient, with a correlation coefficient of 0.88 for the past 50 yr over China. This strongly suggests that the spatial gradient of surface global warming or cooling may significantly change surface wind speed at a regional scale through atmospheric thermal adaption. The recovery of wind speed since the beginning of the 2000s over the Tibetan Plateau might be a precursor of the reversal of wind speed trends over China, as wind over high elevations can respond more rapidly to the warming gradient and atmospheric circulation adjustment.

scholarly journals Projected Near-Surface Wind Speed Trends in Lithuania

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5425
Author(s):  
Justė Jankevičienė ◽  
Arvydas Kanapickas
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Observational Data ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Green Energy ◽  
Near Surface ◽  
Wind Speeds ◽  
Global Circulation ◽  
Global Circulation Models

Developing wind energy in Lithuania is one of the most important ways to achieve green energy goals. Observational data show that the decline in wind speeds in the region may pose challenges for wind energy development. This study analyzed the long-term variation of the observed 2006–2020 and projected 2006–2100 near-surface wind speed at the height of 10 m over Lithuanian territory using data of three models included in the Coupled Model Intercomparison Project phase 5 (CMIP5). A slight decrease in wind speeds was found in the whole territory of Lithuania for the projected wind speed data of three global circulation models for the scenarios RCP2.6, RCP4.5, and RCP8.5. It was found that the most favorable scenario for wind energy production is RCP2.6, and the most unfavorable is the RCP4.5 scenario under which the decrease in wind speed may reach 12%. At the Baltic Sea coastal region, the decline was smaller than in the country’s inner regions by the end of the century. The highest reduction in speed is characteristic of the most severe RCP8.5 scenario. Although the analysis of wind speeds projected by global circulation models (GCM) confirms the downward trends in wind speeds found in the observational data, the projected changes in wind speeds are too small to significantly impact the development of wind farms in Lithuania.

scholarly journals Global Near-Surface Wind Speed Trends in Observation and CMIP6 Historical Simulation for 1850–2014

2020 ◽  
Author(s):  
Kaiqiang Deng ◽  
Cesar Azorin-Molina ◽  
Lorenzo Minola ◽  
Deliang Chen
Keyword(s):  
Wind Speed ◽  
Land Use Changes ◽  
Surface Wind ◽  
Coupled Model ◽  
Surface Wind Speed ◽  
Human Society ◽  
Pollution Dispersion ◽  
Near Surface ◽  
Wind Speeds ◽  
Ocean Wind

<p>The changes in near-surface (10-m height) wind speed have direct impacts on human society, such as utilization of wind energy, air pollution dispersion and dust storm frequency, which requires comprehensive assessment and improved understanding. Based on ground-based observations and multiple atmospheric reanalysis datasets, previous research revealed significant negative and positive trends in wind speed over land and oceans, respectively. In this study, we used Coupled Model Intercomparison Project Phase 6 (CMIP6) historical simulations to investigate the association between global mean wind speed changes and human-induced forcing. It is found that both unforced pre-industrial control run and historical natural forcing experiments failed in reproducing the observed trends in land and ocean wind speeds. However, the CMIP6 historical greenhouse gas forcing successfully simulated the increasing trend in ocean wind speed, while the CMIP6 historical aerosol forcing and experiments with land use changes seemed to have caused a decreasing trend in wind speeds over both land and ocean, suggesting that anthropogenic forcings are crucial drivers for the recent changes in global wind speed. Further attribution studies are needed to better understand wind speed variability under a warming climate.</p>

Hurricane Surface Wind Measurements from an Operational Stepped Frequency Microwave Radiometer

2007 ◽  
Vol 135 (9) ◽  
pp. 3070-3085 ◽  
Author(s):  
Eric W. Uhlhorn ◽  
Peter G. Black ◽  
James L. Franklin ◽  
Mark Goodberlet ◽  
James Carswell ◽  
...  
Keyword(s):  
Wind Speed ◽  
Drag Coefficient ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Model Function ◽  
Near Surface ◽  
Wind Speeds ◽  
Extreme Wind ◽  
High Bias ◽  
Stepped Frequency

Abstract For the first time, the NOAA/Aircraft Operations Center (AOC) flew stepped frequency microwave radiometers (SFMRs) on both WP-3D research aircraft for operational hurricane surface wind speed measurement in 2005. An unprecedented number of major hurricanes provided ample data to evaluate both instrument performance and surface wind speed retrieval quality up to 70 m s−1 (Saffir–Simpson category 5). To this end, a new microwave emissivity–wind speed model function based on estimates of near-surface winds in hurricanes by global positioning system (GPS) dropwindsondes is proposed. For practical purposes, utilizing this function removes a previously documented high bias in moderate SFMR-measured wind speeds (10–50 m s−1), and additionally corrects an extreme wind speed (>60 m s−1) underestimate. The AOC operational SFMRs yield retrievals that are precise to within ∼2% at 30 m s−1, which is a factor of 2 improvement over the NOAA Hurricane Research Division’s SFMR, and comparable to the precision found here for GPS dropwindsonde near-surface wind speeds. A small (1.6 m s−1), but statistically significant, overall high bias was found for independent SFMR measurements utilizing emissivity data not used for model function development. Across the range of measured wind speeds (10–70 m s−1), SFMR 10-s averaged wind speeds are within 4 m s−1 (rms) of the dropwindsonde near-surface estimate, or 5%–25% depending on speed. However, an analysis of eyewall peak wind speeds indicates an overall 2.6 m s−1 GPS low bias relative to the peak SFMR estimate on the same flight leg, suggesting a real increase in the maximum wind speed estimate due to SFMR’s high-density sampling. Through a series of statistical tests, the SFMR is shown to reduce the overall bias in the peak surface wind speed estimate by ∼50% over the current flight-level wind reduction method and is comparable at extreme wind speeds. The updated model function is demonstrated to behave differently below and above the hurricane wind speed threshold (∼32 m s−1), which may have implications for air–sea momentum and kinetic energy exchange. The change in behavior is at least qualitatively consistent with recent laboratory and field results concerning the drag coefficient in high wind speed conditions, which show a fairly clear “leveling off” of the drag coefficient with increased wind speed above ∼30 m s−1. Finally, a composite analysis of historical data indicates that the earth-relative SFMR peak wind speed is typically located in the hurricane’s right-front quadrant, which is consistent with previous observational and theoretical studies of surface wind structure.

scholarly journals Evaluation of Near-Surface Wind Speed Changes during 1979 to 2011 over China Based on Five Reanalysis Datasets

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 804 ◽  
Author(s):  
Jiang Yu ◽  
Tianjun Zhou ◽  
Zhihong Jiang ◽  
Liwei Zou
Keyword(s):  
Wind Speed ◽  
Linear Trend ◽  
Surface Wind ◽  
Wind Farms ◽  
Surface Wind Speed ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Department Of Energy ◽  
Near Surface ◽  
Wind Resource

Wind speed data derived from reanalysis datasets has been used in the plan and design of wind farms in China, but the quality of these kinds of data over China remains unknown. In this study, the performances of five sets of reanalysis data, including National Centers for Environmental Predictions (NCEP)-U.S. Department of Energy (DOE) Reanalysis 2 (NCEP-2), Modern-ERA Retrospective Analysis for Research and Applications (MERRA), Japanese 55-year Reanalysis Project (JRA-55), Interim ECMWF Re-Analysis product (ERA-Interim), and 20th Century Reanalysis (20CR) in reproducing the climatology, interannual variation, and long-term trend of near-surface (10 m above ground) wind speed, for the period of 1979–2011 over continental China are comprehensively evaluated. Compared to the gridded data compiled from meteorological stations, all five reanalysis datasets reasonably reproduce the spatial distribution of the climatology of near-surface wind speed, but underestimate the intensity of the near-surface wind speed in most regions except for Tibetan Plateau where the wind speed is overestimated. All five reanalysis datasets show large weaknesses in reproducing the annual cycle of near-surface wind speed averaged over the continental China. The near-surface wind speed derived from the observations exhibit significant decreasing trends over most parts of continental China during 1979 to 2011. Although the spatial patterns of the linear trends reproduced by reanalysis datasets are close to the observation, the magnitudes are weaker in annual, spring, summer and autumn season. The qualities of all reanalysis datasets are limited in winter. For the interannual variability, except for winter, all five reanalysis datasets reasonably reproduce the interannual standard deviation but with larger amplitude. Quantitative comparison indicates that among the five reanalysis datasets, the MERRA (JRA-55) shows the relatively highest (lowest) skill in terms of the climatology and linear trend. These results call for emergent needs for developing high quality reanalysis data that can be used in wind resource assessment and planning.

scholarly journals The Analysis of the Spatiotemporal Variations and Mechanisms for the Near-Surface Wind Speed Over China in the Last 40 Years

2021 ◽  
Author(s):  
Xia Li ◽  
Yongjie Pan ◽  
Yingsha Jiang
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
The Other ◽  
Strong Wind ◽  
Reanalysis Dataset ◽  
Near Surface ◽  
Wind Speeds ◽  
Dispersion Degree ◽  
Weak Wind

Abstract Near-surface wind speed is of great significance in many aspects of the human production and living. This study analyses the spatiotemporal characteristics of the near-surface wind speed and wind speed percentiles with meteorological station observations in China from 1979 to 2019. Furthermore, the mechanisms of the wind speed variations are also investigated with ERA-Interim reanalysis dataset. Spatially, the wind speeds in the northern and eastern regions of China are larger than that in the central and southern regions. Seasonally, the wind speed in spring is significantly larger than that in the other seasons. The dispersion degree of wind speed in spring is larger than that in the other seasons both spatially and temporally. The near-surface wind speed in China shows significantly decreasing trends during 1979–2019, particularly in 1979–1999, but the wind speed trend reversed after 2000. After dividing the wind speed into different percentiles, it recognizes that the decreasing trend of stronger winds are more significant than that of weaker winds. The weaker the wind speed, the more significant increasing trend after 2000. Therefore, the decreasing wind speed trend before 2000 is mainly caused by the significant reduction of strong wind, while the reversal trend after 2000 results from the increase of weak wind. The variations of the wind speed over China attributed to both the U and V wind components, and the variations of zonal wind is closely related to the weakened upper westerly wind field and the uneven warming between high and low latitudes.

scholarly journals The Impact of Atmosphere–Ocean–Wave Coupling on the Near-Surface Wind Speed in Forecasts of Extratropical Cyclones

2021 ◽  
Author(s):  
Emanuele S. Gentile ◽  
Suzanne L. Gray ◽  
Janet F. Barlow ◽  
Huw W. Lewis ◽  
John M. Edwards
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Model Systems ◽  
Sea State ◽  
Near Surface ◽  
Extreme Surface ◽  
Wind Speeds ◽  
The Impact

AbstractAccurate modelling of air–sea surface exchanges is crucial for reliable extreme surface wind-speed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 m s$$^{-1}$$ - 1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 m s$$^{-1}$$ - 1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 m s$$^{-1}$$ - 1 , due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 m s$$^{-1}$$ - 1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

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