Global review and synthesis of trends in observed terrestrial near-surface wind speeds: Implications for evaporation

McVicar, Tim R.; Roderick, Michael L.; Donohue, Randall J.; Li, Ling Tao; Niel, Tom Van; Thomas, Axel; Grieser, Jürgen; Jhajharia, Deepak; Himri, Y.; Mahowald, N. M.; Mescherskaya, Anna V.; Kruger, Andries; Rehman, Shafiqur; Dinpashoh, Yagob

doi:10.1016/j.jhydrol.2011.10.024

Cited by 1,013 publications

(950 citation statements)

References 220 publications

Supporting

Mentioning

828

Contrasting

Unclassified

Order By: Relevance

“…As indicated by Chen et al (2012), a positive bias exists in mean near-surface wind speeds over China, and hence none of the models reproduce the recent decline in wind speed that is manifest in near-surface observations. During the last several decades, annual ET o has decreased in most regions worldwide, and this has been mainly attributed to declining wind speeds (Yin et al, 2010;McVicar et al, 2012). Decreased wind speed is usually associated with changes in the strength of large-scale changes in atmospheric circulation Rayner, 2007).…”

Section: Discussionmentioning

confidence: 99%

Projections of aridity and its regional variability over China in the mid‐21st century

Yin

et al. 2015

Intl Journal of Climatology

View full text Add to dashboard Cite

ABSTRACT:The effects of aridity on ecosystems and water cycles are pronounced and have received considerable attention. However, aridity changes due to future warming and its regional variability over China remain uncertain. This paper aims to identify the spatiotemporal variations in aridity and its key influencing factors over China in the mid-21st century based on five general circulation models (GCMs) and four representative concentration pathway (RCP) scenarios. An aridity index (AI), defined as the ratio of reference evapotranspiration (ET o ) to precipitation (P), was calculated. We show that the GCM ensemble means are able to reproduce the variation of aridity during the baseline period. Generally, ET o anomalies are consistently positive. Other than for the RCP2.6 low-emission scenario, precipitation and aridity are both projected to increase. There are pronounced regional differences in aridity changes; i.e. wetter across most of western China and drier across most of eastern China in the mid-21st century. Negative AI anomalies in western China can be attributed mainly to the projected increase in precipitation. In eastern China, the AI was higher despite positive precipitation anomalies, due mainly to the greater effect of climate change on increasing atmospheric moisture demand. This suggests that evapotranspiration demand should be incorporated into aridity changes under future warming.

show abstract

Section: Discussionmentioning

confidence: 99%

Projections of aridity and its regional variability over China in the mid‐21st century

Yin

et al. 2015

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…The six subdomains are defined by latitude and longitude and named NW (Northwest region), NC (North China), NE (Northeast Region), QT (Qinghai-Tibet Plateau), CE (Central and Eastern regions), and SC (South China), respectively. Global distribution of energy-limited and water-limited areas has been given by McVicar et al [2012]. In general, CE and SC belong to energy-limited landscapes, while the rest of China belongs to water-limited landscapes.…”

Section: 1002/2014jd023040mentioning

confidence: 99%

Evaporation variability under climate warming in five reanalyses and its association with pan evaporation over China

Feng

2015

JGR Atmospheres

View full text Add to dashboard Cite

With the motivation to identify actual evapotranspiration (AE) variability under climate warming over China, an assessment is made from five sets of reanalysis data sets [National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR), NCEP-Department of Energy (NCEP-DOE), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Interim Reanalysis, and Japanese 55-year Reanalysis (JRA-55)]. Based on comparison with AE estimates calculated using the Budyko equation, all five reanalysis data sets reasonably reproduce the spatial patterns of AE over China, with a clearly southeast-northwest gradient. Overall, JRA-55 (NCEP-DOE) gives the lowest (highest) reanalysis evaporation (RE) values. From 1979 to 2013, dominant modes of RE among five reanalyses are extracted using multivariate empirical orthogonal function analysis. Accordingly, the interdecadal variation of RE is likely driven by the change of temperature, and the interannual variation is constrained by the water supply conditions. Under climate warming, RE increase in the Northwest China, Yangtze-Huaihe river basin, and South China, while they decrease in Qinghai-Tibet Plateau, and northern and Northeast China. Moreover, the relationship between RE and pan evaporation (PE) are comprehensively evaluated in space-time. Negative correlations are generally confirmed in nonhumid environments, while positive correlations exist in the humid regions. Our analysis supports the interpretation that the relationship between PE and AE was complementary with water control and proportional with energy control. In view of data availability, important differences in spatial variability and the amount of RE can be found in Northwest China, the Qinghai-Tibet Plateau, and the Yangtze River Basin. Generally speaking, NCEP-NCAR and MERRA have substantial problems on describing the long-term change of RE; however, there are some inaccuracies in the JRA-55 estimates when focusing on the year-to-year variation.

show abstract

“…Long-term changes in the SWS can affect water vapor evaporation and hydrological cycles in some regions (Rayner 2007;McVicar et al 2007;Donohue et al 2010;Niyogi et al 2011;Mclnnes et al 2011;McMahon et al 2013). Previous studies have attributed decreases in pan-evaporation to long-term decreases in SWS in some regions over the past 50 years (Roderick et al 2007;McVicar et al 2012a). McVicar et al (2012a) carried out a sensitivity analysis in an irrigated area in southeastern Australia and showed that decreasing SWSs have resulted in a decrease in pan-evaporation, with a change of 2 m s −1…”

Section: Introductionmentioning

confidence: 99%

Changes in terrestrial near-surface wind speed and their possible causes: an overview

et al. 2017

View full text Add to dashboard Cite

drag forces are caused by changes in the external and internal friction in the atmosphere. Changes in surface friction are mainly caused by changes in the surface roughness due to land use and cover change (LUCC), including urbanization, and changes in internal friction are mainly induced by changes in the boundary layer characteristics. Future studies should compare the spatio-temporal differences in SWS between high and low altitudes and quantify the effects of different factors on the SWS. Additionally, in-depth analysis of extreme SWS events and prediction of future mean and extreme SWS values at global and regional scales are also necessary. Abstract Changes in terrestrial near-surface wind speed (SWS) are induced by a combination of anthropogenic activities and natural climate changes. Thus, the study of the long-term changes of SWS and their causes is very important for recognizing the effects of these processes. Although the slowdown in SWS has been analyzed in previous studies, to the best of knowledge, no overall comparison or detailed examination of this research has been performed. Similarly, the causes of the decreases in SWS and the best directions of future research have not been discussed in depth. Therefore, we analyzed a series of studies reporting SWS trends spanning the last 30 years from around the world. The changes in SWS differ among different regions. The most significant decreases have occurred in Central Asia and North America, with mean linear trends of − 0.11 m s −1 decade −1 ; the second most significant decreases have occurred in Europe, East Asia, and South Asia, with mean linear trends of − 0.08 m s −1 decade −1 ; and the weakest decrease has occurred in Australia. Although the SWS in Africa has decreased, this region lacks long-term observational data. Therefore, the uncertainties in the long-term SWS trend are higher in this region than in other regions. The changes in SWS, caused by a mixture of global-, regional-, and localscale factors, are mainly due to changes in driving forces and drag forces. The changes in the driving forces are caused by changes in atmospheric circulation, and the changes in the Keywords

show abstract

Global review and synthesis of trends in observed terrestrial near-surface wind speeds: Implications for evaporation

Cited by 1,013 publications

References 220 publications

Projections of aridity and its regional variability over China in the mid‐21st century

Projections of aridity and its regional variability over China in the mid‐21st century

Evaporation variability under climate warming in five reanalyses and its association with pan evaporation over China

Changes in terrestrial near-surface wind speed and their possible causes: an overview

Contact Info

Product

Resources

About