Observed Surface Wind Speed Trends Inferred from Homogenized in Situ Data and Reanalysis Datasets

Using hourly surface wind speed data from 155 stations in Canada, this study first developed a homogenized monthly mean wind speed dataset for the period of 1953-2023, which was then used to characterize observed changes in surface wind speed in Canada. The hourly data were first quality controlled and adjusted for non-standard anemometer heights before being used to calculate monthly mean wind speed series. To identify artificial discontinuities, the monthly mean wind speed series were subject to a semi-automated comprehensive data homogenization procedure, which uses a combination of station metadata and multiple statistical tests with and without using reference series. Reference series used include up to four best significantly-correlated neighbour stations’ data series, the ensemble mean series of monthly wind speed taken from the Twentieth Century Reanalysis version 3 (20CRv3), and monthly mean geostraphic wind speeds derived from homogenized surface pressure data. The results from the automated procedure were then reviewed manually using metadata and visual inspection of the multiphase regression fits with expert judgement. As a result, all the 155 data series were identified to have one or more artificial discontinuities, which were diminished by quantile matching adjustments. Anemometer height change, station joining, relocation, instrument changes/problems were found to be the main causes of data inhomogeneities. The homogenized dataset for 1953-2023 shows wind stilling in region from northern British Columbia (BC) to southern Yukon-Northwest Territories and from southern Prairies to Quebec-Labrador, which was matched with wind strengthening in the region from southern-central BC to the Rocky Mountains, and in Newfoundland and the high Arctics. The trend pattern of in-situ wind speed data bear substantial similarity to that of both the  ERA5 and 20CRv3 reanalysis wind speed data.

Previous studies have reported that much of the surface wind speed (SWS) over the mid‐latitudes of the northern hemisphere has declined. However, very few studies have investigated the relatively recent phenomenon of wind recovery. Based on 68 wind data series, this paper examines changes in wind speed in northwest China between 1969 and 2015. In 1992, following a decade of sharply decreasing at a rate of 0.036 m s−1 a−1 (p < .05), the SWS began to significant increase at a rate of 0.004 m s−1 a−1. The specific reasons for this increase are as follows: (a) The decrease in SWS during the pre‐1992 slowdown period is the result of declining wind speeds in spring and summer, whereas increases in wind speed during the post‐1992 recovery period are caused by increased wind in winter. (b) The number of days featuring strongly varying wind speeds has changed. Specifically, the number of days above 2 m s−1 all show a significant decreasing trend from 1969 to 1992, whereas the number of days of 1–3 m s−1 shows a significant upward trend from 1993 to 2015. (c) Stations located between 1,000 and 1,500 m.a.s.l. (meter above sea level) are more sensitive to climate change than those at other altitudes, which shows the biggest decline (increase) trend during wind speed slowdown (recovery) period. These stations could potentially act as climatic indicators to predict future wind speed changes. SWS in northwest China have been affected by changes both in large‐scale atmospheric circulation and in regional warming. Surface pressure gradient variations between high‐ and low‐latitude regions may be important contributors to wind speed changes under asymmetric warming. However, urbanization is only moderately responsible for trend changes in SWS.

The centennial trends in the surface wind speed over North America are deduced from global climate model simulations in the Climate Model Intercomparison Project—Phase 5 (CMIP5) archive. Using the 21st century simulations under the RCP 8.5 scenario of greenhouse gas emissions, 5–10 percent increases per century in the 10 m wind speed are found over Central and East-Central United States, the Californian Coast, and the South and East Coasts of the USA in winter. In summer, climate models projected decreases in the wind speed ranging from 5 to 10 percent per century over the same coastal regions. These projected changes in the surface wind speed are moderate and imply that the current estimate of wind power potential for North America based on present-day climatology will not be significantly changed by the greenhouse gas forcing in the coming decades.

Wind energy, as one of the renewable energy sources, plays a crucial role in the global energy system's transition to clean energy. China possesses vast and widely distributed wind energy resources, and in recent years, it has rapidly developed and begun large-scale commercial utilization. Therefore, studying changes in surface wind speeds (SWSs) is highly important for wind energy development in China. This study utilizes two initial condition large ensemble simulations to project future changes in SWSs over China. The two sets of initial large ensemble models used are CanESM2-LE and CESM1-LE. By comparing the results from these two large ensemble models, the influence of internal variability of the climate system on SWSs in China are studied. Both models can effectively reproduce the climatological spatial distribution of SWSs in reanalysis. Results from both models indicate that external forcing leads to an increase in winter SWSs in eastern China, while SWSs decreases in the southeastern coastal areas and southwestern Tibet. In summer, SWSs exhibits a pattern of decrease in the north and increase in the south. The magnitude of wind speed changes is greater in winter than in summer. Additionally, as the projected period extends, the magnitude of these changes intensifies. The research results can provide a scientific basis for the future planning of wind power deployment.

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.

Long-term changes in surface wind speed (SWS) are influenced by both large-scale circulation and relative resistance. The effects of large-scale circulation are embodied by the pressure-gradient force (PGF), which is mostly a natural factor, whereas the resistance is due to the drag between the air and the surface as well as in the different boundary layers, which is mainly caused by the anthropogenic land use and cover change (LUCC). We performed experiments using a simple dynamical method in which a balance among the PGF, Coriolis force, and drag is reached to separate the effects of the PGF and LUCC on the SWS, and then, to quantitatively estimate the influence of the LUCC on the SWS over the East China Plain (ECP) during the period 1980–2011. The results show a distinct decrease in the SWS in the station observation data with a rate of −0.13 m s−1 (10 year)−1, but there is no statistically significant long-term trend in the reanalysis data. At the same time, the drag coefficient induced by the LUCC shows an increasing trend, which is consistent with the 30 % increase in the rate of urbanization during the study period. In addition, the PGF fluctuates with distinct seasonal and interannual changes, and it has an insignificant long-term increasing trend during the period 1980–2011. At the same time, the spatial distribution of the linear trend coefficient of the normalized PGF is inconsistent with that of the SWS, but the linear trend coefficient of the normalized drag coefficient shows a similar spatial distribution as the SWS. Therefore, the increase in the drag coefficient induced by the LUCC should account for the long-term decrease in the SWS. The difference between the model wind speed, in which the drag coefficient is constrained to its value in the year 1980, and the observed wind speed at each station (SWSD) can reflect the influence of the LUCC on the SWS. Furthermore, the long-term changes in East Asian monsoons may not completely account for the observed wind speed decrease near the surface in the ECP region, but it is an important factor in the SWS.

Changes in surface wind speed are important for wind energy planning, especially in China, which has the highest new and total wind power capacities globally. In this article, based on a daily high‐resolution observation dataset for the period of 1961–2020, changes in the surface wind speed and its different grades over China were analysed. The results showed that following significant declines from 1961 to 2002, the annual and seasonal mean surface wind speeds began to increase over China and most of its subregions (all subregions except for East China) after 2002. Opposite trends were found in the probabilities for most different grades of surface wind speed from 1961 to 2002 and from 2002 to 2020. In addition, we compared the results with those from NCEP‐1, JRA‐55, and ERA5, which showed that all of the reanalysis data could reasonably reproduce the observed spatial distributions of the surface wind speed and its different grades, although with bias in values and smaller interannual variabilities. The wind reversal over China was closely related to changes in the trends of the sea level pressure gradient. Moreover, the variation in the Pacific Decadal Oscillation (PDO) has a significantly negative correlation coefficient with the surface wind speed over East, Central, and South China.

The present study investigates the influence of June through November (JJASON) thermal state of the western North Pacific warm pool on surface latent heat flux and their association with tropical cyclone (TC) genesis by using 25 level water temperature data with European Centre for Medium-Range Weather Forecasts (ECWMF) operational ocean analysis (ORA-S3), the monthly mean fluxes from Objectively Analyzed Air-sea Fluxes (OAFlux) Project, and the tropical cyclone data from the International Best Track Archive for Climate Stewardship (IBTrACS). It is found that positive (negative) latent heat flux anomalies over the western North Pacific are associated with warm (cold) state of the warm pool. The analysis suggests that the change in sea-air humidity difference has a direct contribution to surface latent heat flux anomalies over the western Pacific in warm state years of the warm pool. However, the change in surface wind speed is the main cause of surface latent heat flux anomalies over central tropical Pacific. In cold state years, change in the sea-air humidity difference has a direct contribution to surface latent heat flux anomalies over the western Pacific and central and eastern tropical Pacific, and the change in surface wind speed appears not to be a cause of identified surface latent heat flux anomalies. Moreover, the results show that the sea-air humidity difference contributes to tropical cyclone genesis in warm state years, but in cold state years, tropical cyclone genesis occurs mainly in regions of sea-air humidity difference decrease and surface wind speed increase.

Enabling the rational use of energy and the realization of the "dual carbon goals" across China will require systematic analysis of temporal and spatial changes in surface wind speed (SWS), determination of key factors influencing SWS, and quantification of wind energy resources. We investigated changes of SWS and their potential impact on wind energy resources using daily SWS data from meteorological observations and based on wind power density (WPD) across China during 1961-2021. The SWS changes were related to atmospheric circulation, surface friction (urbanization and vegetation changes), aerosol emissions and the replacement of observation instruments. The increase of SWS after 2015 was closely related to changes of atmospheric circulation that were reflected by changes of Asian Meridional Circulation Index, North Atlantic Oscillation, and Arctic Oscillation. Compared with the mean SWS, the extreme SWS exhibited a more obvious downward trend and earlier abrupt change. The annual mean SWS decreased by 16.80% in the last six decades, resulting in a decrease of 47.78% in wind energy potential. Regions with annual WPD more than 100W·m-2 were mainly in western China, northeastern China, northwestern China and some coastal areas. The WPD decreased mainly in northeastern China, northern China, and some coastal areas during the last six decades; it increased mainly in western China. Regions with annual WPD more than 100W·m-2 and robust coefficient of variation less than 0.5 are high-quality wind energy resource areas and were found mainly in western China, northern China, northeast China, and coastal areas.

The surface Walker and tropical tropospheric circulations have been inferred to slow down from historical observations and model projections, yet analysis of large-scale surface wind predictions is lacking. Satellite measurements of surface wind speed indicate strengthening trends averaged over the global and tropical oceans that are supported by precipitation and evaporation changes. Here we use corrected anemometer-based observations to show that the surface wind speed has not decreased in the averaged tropical oceans, despite its reduction in the region of the Walker circulation. Historical simulations and future projections for climate change also suggest a near-zero wind speed trend averaged in space, regardless of the Walker cell change. In the tropics, the sea surface temperature pattern effect acts against the large-scale circulation slow-down. For higher latitudes, the surface winds shift poleward along with the eddy-driven mid-latitude westerlies, resulting in a very small contribution to the global change in surface wind speed. Despite its importance for surface wind speed change, the influence of the SST pattern change on global-mean rainfall is insignificant since it cannot substantially alter the global energy balance. As a result, the precipitation response to global warming remains ‘muted’ relative to atmospheric moisture increase. Our results therefore show consistency between projections and observations of surface winds and precipitation.

Can Current AGCMs Reproduce Historical Changes in the Atmospheric Diabatic Heating over the Tibetan Plateau?

Recent studies have demonstrated a persistent decreasing trend in the spring sensible heat (SH) source over the Tibetan Plateau (TP) during the past three decades. By comparing simulations from nine state-of-the-art atmospheric general circulation models (AGCMs) driven by historical forcing fields with both observational data and five reanalysis datasets, the authors found that the AGCMs are unable to reproduce the change in the SH flux over the TP. This deficiency arises because the observed decreasing trend in SH flux depends primarily on the change in surface wind speed according to the bulk formula, whereas in the models it is also influenced largely by changes in the land-air temperature difference related to the systematic cold bias. In addition, an obvious discrepancy exists in other aspects of the diabatic heating simulated by the models, suggesting that a significant improvement is required in the physical schemes associated with land surface processes and diabatic heating over the compli...

This study characterizes historical changes in surface wind speed and ocean surface waves in the Beaufort–Chukchi–Bering Seas using Environment Canada’s Beaufort Wind and Wave Reanalysis for the period 1970–2013. The results show that both the significant wave height () and mean wave period () have increased significantly over the Bering Sea in July and August and over the Canadian Beaufort Sea westward to the northern Bering Sea in September, and that the 1992–2013 trends in September mean agree well with satellite-based trend estimates for 1993–2010. Most outstandingly, the regional mean has increased at a rate of 3%–4% yr−1 of the corresponding 1970–99 climatology; it has more than tripled since 1970. Also, the regional mean has increased at a rate of 0.3% to 0.8% yr−1. The trends of lengthening wave period and increasing wave height imply a trend of increasing wave energy flux, providing a mechanism to break up sea ice and accelerate ice retreat. The results also show that changes in the local wind speeds alone cannot explain the significant changes in waves. The wind speeds show significant increases over the Bering Sea to the north of Alaska in July and over the central part of the domain in August and September, with decreases in the region off the Canadian coasts in August. In the region west of the Canadian coast, the climatological mean wind direction has rotated clockwise in July and August, with the climatological anticyclonic center being displaced northeastward in August.

Based on wind speed data of 13 meteorological stations in 1958-2012,Mann-Kendall nonparametric test methods was been used to study on wind speed changes in Hexi Corridor.Spatial and temporal characteristics of seasonal and monthly wind speed changes was examined. (1) The maximum wind speed appeared in the higher elevations of study area, such as Wushaoling and Mazongshan station. From east to west mean wind speed increased in Hexi Corridor.For nearly 50 years wind speed had showed decreasing trend. (2)In each season Spring with an maximum mean wind speed was 3.4m/s,the Summer mean wind speed was 2.9 m/s,Autumn mean wind speed was 2.6 m/s,the mean Winter wind speed was 2.8m/s.The seasonal wind speed mainly had decline trend, each station.has different characteristics trends (3) Mean wind speed in each month was greater than 2.5m/s,maximum monthly wind speed appeared in April was 3.5m/s,the minimum wind speed appeared in the September-October was 2.53m/s,the wind speed in March,April and May was greater than the November month,December,January.In addition to Mazongshan and Wushaoling,other station monthly wind speed showed a decreasing trend.Monthly mean wind speed in Jiuquan,Dingxin and Zhangye was slow decreasing trend.Anxi,Yumen wind decreasing trend were more obvious.(4)Wind decreasing trend will have a significant impact on wind energy, wind speed changes and wind energy should be evaluated in the future.

Summary1. Climate change impacts on habitat suitability and demography are often studied, but direct effects on plant dispersal are rarely considered. To address this we analysed climate model projections of future wind speeds and modelled their possible impacts on dispersal and spread of wind‐dispersed plants.2. Projections for 17 Global Climate Models and three emission scenarios suggested great uncertainty about wind speeds in southern England by the period 2070–99. Projections ranged from −90% to +100% change in the mean wind speed, although the average projection was for large falls in both summer and winter wind speeds.3. Using a novel method for converting projected changes in mean wind speed to new seasonal wind speed distributions, we parameterized a mechanistic model of seed dispersal by wind using baseline and changes in mean wind speed from −80% to +80%.4. The mechanistic seed dispersal model was combined with demographic data in an analytical model of plant spread. This was carried out for three British native and three non‐native species, which represented a range of life‐forms.5. Dispersal kernels and population spread rates were affected disproportionately by changes in wind speed, demonstrating nonlinear propagation of uncertainty in wind speed projections through to modelled plant spread rates.6. Sensitivity analyses showed differences among the plant species in which demographic transitions were most important in determining spread rates. By contrast, sensitivity of spread rates to dispersal parameters showed great consistency among species, with seed release height being more important than seed terminal velocity.7. Synthesis. Plant populations will need to shift their geographic ranges to keep pace with climate change‐driven habitat loss. This study shows that climate change may affect that ability by decreasing the dispersal distances of wind‐dispersed plants and thus their potential spread rates. However, the modelling approach presented here illustrates that uncertainty in climate models leads to an even greater uncertainty about how dispersal and spread will change in future climates. Caution should therefore be exercised in making predictions as to how fast plant species may spread in response to climate change.