Evaluation and Projection of Wind Speed in the Arid Region of Northwest China Based on CMIP6

Near surface wind speed has significant impacts on ecological environment change and climate change. Based on the CN05.1 observation data (a gridded monthly dataset with the resolution of 0.25 latitude by 0.25 longitude over China), this study evaluated the ability of 25 Global Climate Models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating the wind speed in the Arid Region of Northwest China (ARNC) during 1971–2014. Then, the temporal and spatial variations in the surface wind speed of ARNC in the 21st century were projected under four Shared Socioeconomic Pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0, and SP5-8.5. The results reveal that the preferred-model ensemble (PME) can fairly evaluate the temporal and spatial distribution of surface wind speed with the temporal and spatial correlation coefficients exceeding 0.5 at the significance level of p = 0.05 when compared to the 25 single models and their ensemble mean. After deviation correction, the PME can reproduce the distribution characteristics of high wind speed in the east and low in the west, high in mountainous areas, and low in basins. Unfortunately, no models or model ensemble can accurately reproduce the decreasing magnitude of observed wind speed. In the 21st century, the surface wind speed in the ARNC is projected to increase under SSP1-2.6 scenario but will decrease remarkably under the other three scenarios. Moreover, the higher the emission scenarios, the more significant the surface wind speed decreases. Spatially, the wind speed will increase significantly in the west and southeast of Xinjiang, decrease in the north of Xinjiang and the south of Tarim Basin. What’s more, under the four scenarios, the surface wind speed will decrease in spring, summer and autumn, especially in summer, and increase in winter. The wind speed will decrease significantly in the north of Tianshan Mountains in summer, decrease significantly in the north of Xinjiang and the southern edge of Tarim Basin in spring and autumn, and increase in fluctuation with high values in Tianshan Mountains in winter.

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Estimating a relationship between aerosol optical thickness and surface wind speed over the ocean

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-6-11621-2006 ◽

2006 ◽

Vol 6 (6) ◽

pp. 11621-11651 ◽

Cited By ~ 4

Author(s):

P. Glantz ◽

D. E. Nilsson ◽

W. von Hoyningen-Huene

Keyword(s):

Wind Speed ◽

Optical Thickness ◽

Surface Wind ◽

Surface Wind Speed ◽

Sea Salt ◽

Aerosol Optical Thickness ◽

Marine Aerosols ◽

Hygroscopic Growth ◽

The North ◽

The North Pacific

Abstract. Retrieved aerosol optical thickness (AOT) based on data obtained by the Sea viewing Wide Field Sensor (SeaWiFS) is combined with surface wind speed, obtained at the European Centre for Medium-Range Weather Forecasts (ECMWFs), over the North Pacific for September 2001. In this study a cloud screening approach is introduced in an attempt to exclude pixels partly or fully covered by clouds. The relatively broad swath width for which the nadir looking SeaWiFS instrument scanned over the North Pacific means that the AOT can be estimated according to relatively large range of wind speeds for each of the scenes analyzed. The sensitivity in AOT due to sea salt and hygroscopic growth of the marine aerosols has also been investigated. The validation of the results is based on previous parameterization in combination with the environmental quantities wind speed, RH and boundary layer height (BLH), estimated at the ECMWF. In this study a factor of 2 higher mean AOT is obtained for a wind speed up to about 13 m s−1 for September 2001 over remote ocean areas. Furthermore, a factor of 2 higher AOT is more or less supported by the validation of the results. Approximately, 50% of the enhancement seems to be due to hygroscopic growth of the marine aerosols and the remaining part due to increase in the sea salt particle mass concentrations, caused by a wind driven water vapor and sea salt flux, respectively. Reasonable agreement occurs also between satellites retrieved aerosol optical thickness and AOT observed at several AERONET (Aerosol Robotic NETwork) ground-based remote sensing stations. Finally, possible reasons why relatively large standard deviations occur around the mean values of AOT estimated for a single scene are discussed.

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Recent recovery of surface wind speed in northwest China

International Journal of Climatology ◽

10.1002/joc.5679 ◽

2018 ◽

Vol 38 (12) ◽

pp. 4445-4458 ◽

Cited By ~ 8

Author(s):

Yupeng Li ◽

Yaning Chen ◽

Zhi Li ◽

Gonghuan Fang

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Northwest China

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Evaluation of Extratropical Cyclone Precipitation in the North Atlantic Basin: An Analysis of ERA-Interim, WRF, and Two CMIP5 Models

Journal of Climate ◽

10.1175/jcli-d-17-0308.1 ◽

2018 ◽

Vol 31 (6) ◽

pp. 2345-2360 ◽

Cited By ~ 17

Author(s):

James F. Booth ◽

Catherine M. Naud ◽

Jeff Willison

Keyword(s):

Wind Speed ◽

North Atlantic ◽

Surface Wind ◽

Wrf Model ◽

Surface Wind Speed ◽

Convective Precipitation ◽

Cmip5 Models ◽

Convection Scheme ◽

The North ◽

The North Atlantic

The representation of extratropical cyclone (ETC) precipitation in general circulation models (GCMs) and the Weather Research and Forecasting (WRF) Model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic basin. Lagrangian cyclone tracks of ETCs in ERA-Interim (ERAI), GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km-resolution WRF Model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with the GISS model generating the most, followed by ERAI and then the GFDL model. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC’s life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.

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A comparative assessment of IRS-P4 (MSMR)-derived sea surface temperature and sea surface wind speed over the north Indian Ocean

International Journal of Remote Sensing ◽

10.1080/01431161.2011.562932 ◽

2011 ◽

Vol 32 (24) ◽

pp. 9879-9891

Author(s):

Babula Jena ◽

Sanghamitra Sahu ◽

Madala Venkateswara Rao ◽

Bijoy Kumar Sahu

Keyword(s):

Wind Speed ◽

Indian Ocean ◽

Surface Wind ◽

Surface Wind Speed ◽

North Indian Ocean ◽

Comparative Assessment ◽

Sea Surface ◽

Sea Surface Wind Speed ◽

The North ◽

Sea Surface Wind

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Regional Dependence of Atmospheric Responses to Oceanic Eddies in the North Pacific Ocean

Remote Sensing ◽

10.3390/rs12071161 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1161 ◽

Cited By ~ 1

Author(s):

Jinlin Ji ◽

Jing Ma ◽

Changming Dong ◽

John Chiang ◽

Dake Chen

Keyword(s):

Wind Speed ◽

Pacific Ocean ◽

North Pacific ◽

North Pacific Ocean ◽

Surface Wind ◽

Surface Wind Speed ◽

Sea Surface ◽

The North ◽

Oceanic Eddies ◽

The North Pacific

Based on sea surface height anomaly (SSHA) from satellite altimeter and microwave radiometer datasets, this study investigates atmospheric responses to oceanic eddies in four subdomains of the North Pacific Ocean with strongest eddy activity: Kuroshio Extension (KE), Subtropical Front (SF), California Coastal Current (CC) and Aleutian Islands (AI). Analyses show that anticyclonic eddies cause sea surface temperature, surface wind speed and precipitation rate to increase in all four subdomains, and vice versa. Through a further examination of the regional dependence of atmospheric responses to oceanic eddies, it is found that the strongest and the weakest surface wind speed responses (in winter and summer) are observed in the KE and AI region, respectively. For precipitation rate, seasonal variation of the atmospheric responses to oceanic eddies is strongest in winter and weakest in summer in the KE, CC and AI regions, but stronger in summer in the SF area. The reasons for such regional dependence and seasonality are the differences in the strength of SST anomalies, the vertical kinetic energy flux and atmospheric instability in the four subdomains.

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Stilling and Recovery of the Surface Wind Speed Based on Observation, Reanalysis, and Geostrophic Wind Theory over China from 1960 to 2017

Journal of Climate ◽

10.1175/jcli-d-19-0281.1 ◽

2020 ◽

Vol 33 (10) ◽

pp. 3989-4008 ◽

Cited By ~ 1

Author(s):

Zhengtai Zhang ◽

Kaicun Wang

Keyword(s):

Wind Speed ◽

Decadal Variability ◽

Surface Wind ◽

Geostrophic Wind ◽

Surface Wind Speed ◽

Strong Wind ◽

Wind Speeds ◽

The North ◽

Wind Theory ◽

Weak Winds

AbstractSurface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near-zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of −0.24 m s−1 decade−1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of daily mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of −8% decade−1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of −2% decade−1. GWS decreased with a significant trend of −3% decade−1 before the 1990s; during the 1990s, GWS increased with a trend of 3% decade−1 whereas SWS continued to decrease with a trend of 10% decade−1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrending, both SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability and cannot capture the decreasing trend of SWS either.

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Can Polar Lows be Objectively Identified and Tracked in the ECMWF Operational Analysis and the ERA-Interim Reanalysis?

Monthly Weather Review ◽

10.1175/mwr-d-14-00064.1 ◽

2014 ◽

Vol 142 (8) ◽

pp. 2596-2608 ◽

Cited By ~ 43

Author(s):

Giuseppe Zappa ◽

Len Shaffrey ◽

Kevin Hodges

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Static Stability ◽

Life Cycles ◽

Heat Fluxes ◽

Polar Lows ◽

Operational Analysis ◽

Wind Speeds ◽

The North

Abstract Polar lows are maritime mesocyclones associated with intense surface wind speeds and oceanic heat fluxes at high latitudes. The ability of the Interim ECMWF Re-Analysis (ERA-Interim, hereafter ERAI) to represent polar lows in the North Atlantic is assessed by comparing ERAI and the ECMWF operational analysis for the period 2008–11. First, the representation of a set of satellite-observed polar lows over the Norwegian and Barents Seas in the operational analysis and ERAI is analyzed. Then, the possibility of directly identifying and tracking the polar lows in the operational analysis and ERAI is explored using a tracking algorithm based on 850-hPa vorticity with objective identification criteria on cyclone dynamical intensity and atmospheric static stability. All but one of the satellite-observed polar lows with a lifetime of at least 6 h have an 850-hPa vorticity signature of a collocated mesocyclone in both the operational analysis and ERAI for most of their life cycles. However, the operational analysis has vorticity structures that better resemble the observed cloud patterns and stronger surface wind speed intensities compared to those in ERAI. By applying the objective identification criteria, about 55% of the satellite-observed polar lows are identified and tracked in ERAI, while this fraction increases to about 70% in the operational analysis. Particularly in ERAI, the remaining observed polar lows are mainly not identified because they have too weak wind speed and vorticity intensity compared to the tested criteria. The implication of the tendency of ERAI to underestimate the polar low dynamical intensity for future studies of polar lows is discussed.

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Stilling and Recovery of the Surface Wind Speed Based on Observation, Reanalysis, and Geostrophic Wind Theory over China from 1960 to 2017

10.5194/egusphere-egu2020-2501 ◽

2020 ◽

Author(s):

Zhengtai Zhang ◽

Kaicun Wang

Keyword(s):

Wind Speed ◽

Decadal Variability ◽

Surface Wind ◽

Geostrophic Wind ◽

Surface Wind Speed ◽

Strong Wind ◽

Wind Speeds ◽

The North ◽

Wind Theory ◽

Weak Winds

Surface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of -0.24 m/s decade-1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of monthly mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of -8 % decade-1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of -2 % decade-1. GWS decreased with a significant trend of -3 % decade-1 before the 1990s, during the 1990s, GWS increased with a trend of 3 % decade-1 whereas SWS continued to decrease with a trend of 10 % decade-1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrended, both of SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability, and can not capture the decreasing trend of SWS either.

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