Influence of Soil Moisture on Urban Microclimate and Surface-Layer Meteorology in Oklahoma City

AbstractThe influence of soil moisture on the surface-layer atmosphere is examined in this paper by analyzing the outputs of model simulations for different initial soil moisture configurations, with particular emphasis on urban microclimate. In addition to a control case, four different soil moisture distributions within the urban and surrounding rural areas are considered in this study. Outputs from the Global Environmental Multiscale atmospheric model simulations are compared with observations from the Joint Urban 2003 experiment held in Oklahoma City, Oklahoma, and the relevant conclusions drawn in this paper are therefore valid for similar medium-size cities. In general, high soil moisture is found to be associated with colder near-surface temperature and lower near-surface wind speed, whereas drier soil resulted in warmer temperatures and enhanced low-level wind. Relative to urban soil moisture content, rural soil conditions are predicted to have larger impacts on both rural and urban surface-layer meteorological conditions. Dry rural and wet urban soil configurations are shown to have a strong influence on the urban–rural temperature contrast and resulted in city-induced secondary circulations that considerably affect the near-surface wind speed. Dry rural soil in particular is found to intensify the nocturnal low-level jet and significantly affect the thermal stability of nocturnal near-neutral urban surface layer by altering both thermal and mechanical generation of turbulence.

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Global Near-Surface Wind Speed Changes over the Last Decades Revealed by Reanalyses and CMIP6 Model Simulations

Journal of Climate ◽

10.1175/jcli-d-20-0310.1 ◽

2020 ◽

pp. 1-53

Author(s):

Kaiqiang Deng ◽

Cesar Azorin-Molina ◽

Lorenzo Minola ◽

Gangfeng Zhang ◽

Deliang Chen

Keyword(s):

Wind Speed ◽

Atmospheric Circulation ◽

Decadal Variability ◽

Surface Wind ◽

Coupled Model ◽

Surface Wind Speed ◽

Hadley Cell ◽

Near Surface ◽

Model Simulations ◽

Hydrological Cycles

AbstractNear-surface (10 m) wind speed (NWS) plays a crucial role in e.g. hydrological cycles, wind energy production and air pollution, but what drives their multi-decadal changes is still unclear. Using reanalysis datasets and Coupled Model Inter-comparison Projection Phase 6 (CMIP6) model simulations, this study investigates recent trends in the annual mean NWS. The results show that the northern hemisphere (NH) terrestrial NWS experienced significant (p<0.1) decreasing trends during 1980–2010, when the southern hemisphere (SH) ocean NWS was characterized by significant (p<0.1) upward trends. However, during 2010–2019, global NWS trends shifted in their sign: NWS trends over the NH land became positive, and trends over the SH tended to be negative. We propose that the strengthening of SH NWS during 1980–2010 was associated with intensified Hadley cell over the SH, while the declining of NH land NWS could have been caused by changes in atmospheric circulation, alteration of vegetation/land-use and the accelerating Arctic warming. The CMIP6 model simulations further demonstrate that the greenhouse gas (GHG) warming plays an important role in triggering the NWS trends over the two hemispheres during 1980–2010 through modulating meridional atmospheric circulation. This study also points at the importance of anthropogenic GHG forcing and the natural Pacific Decadal Oscillation to the long-term trends and multi-decadal variability in global NWS, respectively.

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Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.599-601.1605 ◽

2014 ◽

Vol 599-601 ◽

pp. 1605-1609 ◽

Cited By ~ 1

Author(s):

Ming Zeng ◽

Zhan Xie Wu ◽

Qing Hao Meng ◽

Jing Hai Li ◽

Shu Gen Ma

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Recurrence Plot ◽

Sampling Frequency ◽

Near Surface ◽

Gas Leakage ◽

Time Period ◽

Characteristics Analysis ◽

Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

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Effects of surface wind speed decline on hydrology in China

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-10-11293-2013 ◽

2013 ◽

Vol 10 (8) ◽

pp. 11293-11310

Author(s):

X. Liu ◽

X. Zhang ◽

Q. Tang ◽

X. Zhang

Keyword(s):

Soil Moisture ◽

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

River Basins ◽

Annual Runoff ◽

Infiltration Capacity ◽

Major River ◽

Speed Change ◽

Small Change

Abstract. Surface wind speed decline in China has been widely reported, but its effects on hydrology have not been fully evaluated to date. In this study, the effects of wind speed change on hydrology are investigated using the Variable Infiltration Capacity (VIC) hydrological model for China during 1966–2011. Two model experiments, i.e. VIC simulations with the observed (EXP1) and detrended wind speed (EXP2), are performed over the major river basins in China. The differences between the two experiments are analyzed to assess the effects of wind speed decline on hydrology. Results show that wind speed has decreased by 29% in China. The wind speed decline have resulted in a decrease of evapotranspiration by 1–3% of mean annual evapotranspiration and an increase of runoff by 1–6% of mean annual runoff at most basins in China. The effect of wind speed on runoff and soil moisture is large in the northern basins where small change in hydrological conditions would have significant implications for water management. In addition, Wind speed decline has offset the expansion of the drought area in China. It has contributed to a reduction of drought areas by 8.8% of the mean drought area (i.e. approximate 10.6 × 104 km2 out of 1.2 × 106 km2) over China. The effect of wind speed decline on soil moisture drought is large in most basins in China expect for the Southwest and Pearl River basins.

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Improved near surface wind speed predictions using Gaussian process regression combined with numerical weather predictions and observed meteorological data

Renewable Energy ◽

10.1016/j.renene.2018.04.019 ◽

2018 ◽

Vol 126 ◽

pp. 1043-1054 ◽

Cited By ~ 43

Author(s):

Victoria Hoolohan ◽

Alison S. Tomlin ◽

Timothy Cockerill

Keyword(s):

Wind Speed ◽

Gaussian Process ◽

Meteorological Data ◽

Surface Wind ◽

Gaussian Process Regression ◽

Surface Wind Speed ◽

Near Surface ◽

Numerical Weather

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A preliminary study on the influence of Beijing urban spatial morphology on near-surface wind speed

Urban Climate ◽

10.1016/j.uclim.2020.100703 ◽

2020 ◽

Vol 34 ◽

pp. 100703

Author(s):

Yonghong Liu ◽

Yongming Xu ◽

Fangmin Zhang ◽

Wenjun Shu

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Near Surface ◽

Spatial Morphology ◽

Preliminary Study

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Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm

Atmosphere ◽

10.3390/atmos11070738 ◽

2020 ◽

Vol 11 (7) ◽

pp. 738 ◽

Cited By ~ 1

Author(s):

Wenqing Xu ◽

Like Ning ◽

Yong Luo

Keyword(s):

Wind Speed ◽

Decision Tree ◽

Wind Power ◽

Surface Wind ◽

Surface Wind Speed ◽

Gradient Boosting ◽

Post Processing ◽

Near Surface ◽

Wind Power Forecasting ◽

Numerical Weather

With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.

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