Aridity Changes and Related Climatic Drivers in the Drylands of China during 1960–2019

2021 ◽  
Vol 60 (4) ◽  
pp. 607-617
Author(s):  
Jinqin Xu ◽  
Yan Zeng ◽  
Xinfa Qiu ◽  
Yongjian He ◽  
Guoping Shi ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Land Surface ◽  
Arid Regions ◽  
Climatic Factors ◽  
Sunshine Duration ◽  
Aridity Index ◽  
Maximum Temperature ◽  
The Impact ◽  
Precipitation And Temperature

AbstractDrylands cover about one-half of the land surface in China and are highly sensitive to climate change. Understanding climate change and its impact drivers on dryland is essential for supporting dryland planning and sustainable development. Using meteorological observations for 1960–2019, the aridity changes in drylands of China were evaluated using aridity index (AI), and the impact of various climatic factors [i.e., precipitation P; sunshine duration (SSD); relative humidity (RH); maximum temperature (Tmax); minimum temperature (Tmin); wind speed (WS)] on the aridity changes was decomposed and quantified. Results of trend analysis based on Sen’s slope estimator and Mann–Kendall test indicated that the aridity trends were very weak when averaged over the whole drylands in China during 1960–2019 but exhibited a significant wetting trend in hyperarid and arid regions of drylands. The AI was most sensitive to changes in water factors (i.e., P and RH), followed by SSD, Tmax, and WS, but the sensitivity of AI to Tmin was very small and negligible. Interestingly, the dominant climatic driver to AI change varied in the four dryland subtypes. The significantly increased P dominated the increase in AI in the hyperarid and arid regions. The significantly reduced WS and the significantly increased Tmax contributed more to AI changes than the P in the semiarid and dry subhumid regions of drylands. Previous studies emphasized the impact of precipitation and temperature on the global or regional dry–wet changes; however, the findings of this study suggest that, beyond precipitation and temperature, the impact of wind speed on aridity changes of drylands in China should be given equal attention.

scholarly journals Spatiotemporal Variations of Reference Evapotranspiration and Its Determining Climatic Factors in the Taihang Mountains, China

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3145
Author(s):  
Tingting Kang ◽  
Zeng Li ◽  
Yanchun Gao
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Reference Evapotranspiration ◽  
Climatic Factors ◽  
Sunshine Duration ◽  
High Elevation ◽  
Lower Sensitivity ◽  
Effective Measure ◽  
The Impact ◽  
The Relationship

Reference evapotranspiration (ETo) is an effective measure of atmospheric water demand of the land surface. In-depth investigations of the relationship between ETo and primary climatic factors can facilitate the adaptable agriculture and optimize water management, especially in the ecologically fragile Taihang Mountains (THM). This work assessed the spatiotemporal dynamics of ETo and its driving climatic factors from 1973 to 2016 in THM. Results showed: (1) Annual ETo slightly increased during 1973–2016; relative humidity (RH) decreased more slowly, the temperature increased more rapidly, and wind speed (WS) decreased more rapidly at higher elevation than those at lower elevations; (2) two breakpoints occurred in ETo series at 1990 and 1997, and an “evaporation paradox” existed in 1973–1990; (3) ETo at higher elevations had greater sensitivity to changes in RH and lower sensitivity to changes in Tmax and WS. Sensitivity of ETo to minimum air temperature (Tmin) at middle elevations was lowest among three elevation bands; (4) RH and sunshine duration (SD) were the dominant climatic factors of ETo for most periods and stations. This study helps us understand the impact of climate change on ETo in mountainous areas and confirms reference evapotranspiration in high-elevation areas is particularly sensitive to climate change.

scholarly journals Simulation of Pan-Evaporation Using Penman and Hamon Equations and Artificial Intelligence Techniques

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 793
Author(s):  
Abdul Razzaq Ghumman ◽  
Mohammed Jamaan ◽  
Afaq Ahmad ◽  
Md. Shafiquzzaman ◽  
Husnain Haider ◽  
...  
Keyword(s):  
Wind Speed ◽  
Water Resources ◽  
Arid Regions ◽  
Fuzzy Inference ◽  
Sunshine Duration ◽  
Pan Evaporation ◽  
Estimation Of Parameters ◽  
Inference System ◽  
Daunting Task ◽  
The Impact

The evaporation losses are very high in warm-arid regions and their accurate evaluation is vital for the sustainable management of water resources. The assessment of such losses involves extremely difficult and original tasks because of the scarcity of data in countries with an arid climate. The main objective of this paper is to develop models for the simulation of pan-evaporation with the help of Penman and Hamon’s equations, Artificial Neural Networks (ANNs), and the Artificial Neuro Fuzzy Inference System (ANFIS). The results from five types of ANN models with different training functions were compared to find the best possible training function. The impact of using various input variables was investigated as an original contribution of this research. The average temperature and mean wind speed were found to be the most influential parameters. The estimation of parameters for Penman and Hamon’s equations was quite a daunting task. These parameters were estimated using a state of the art optimization algorithm, namely General Reduced Gradient Technique. The results of the Penman and Hamon’s equations, ANN, and ANFIS were compared. Thirty-eight years (from 1980 to 2018) of manually recorded pan-evaporation data regarding mean daily values of a month, including the relative humidity, wind speed, sunshine duration, and temperature, were collected from three gauging stations situated in Al Qassim, Saudi Arabia. The Nash and Sutcliffe Efficiency (NSE) and Mean Square Error (MSE) evaluated the performance of pan-evaporation modeling techniques. The study shows that the ANFIS simulation results were better than those of ANN and Penman and Hamon’s equations. The findings of the present research will help managers, engineers, and decision makers to sustainability manage natural water resources in warm-arid regions.

scholarly journals Quantifying the Impacts of Climate Change and Vegetation Variation on Actual Evapotranspiration Based on the Budyko Hypothesis in North and South Panjiang Basin, China

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 508 ◽  
Author(s):  
Tiansheng Li ◽  
Jun Xia ◽  
Dunxian She ◽  
Lei Cheng ◽  
Lei Zou ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climatic Factors ◽  
Actual Evapotranspiration ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
North And South ◽  
Average Contribution ◽  
Vegetation Variation ◽  
Impacts Of Climate Change

Actual evapotranspiration (Ea) plays a key role in the global water and energy cycles. The accurate quantification of the impacts of different factors on Ea change can help us better understand the driving mechanisms of Ea in a changing environment. Climate change and vegetation variations are well known as two main factors that have significant impacts on Ea change. Our study used three differential Budyko-type equations to quantify the contributions of climate change and vegetation variations to Ea change. First, in order to establish the relationship between the parameter n, which usually presents the land surface characteristics in the Budyko-type equations, with basic climatic variables and the Normalized Difference Vegetation Index (NDVI), the stepwise linear regression method has been used. Then, elasticity and contribution analyses were performed to quantify the contributions of different numbers of climatic factors and NDVI to Ea change. The North and South Panjiang basin in China was selected to investigate the efficiency of the modified Budyko-type equations and quantify the impacts of climate change and vegetation variations on Ea change. The empirical formal of the parameter n established in this study can be used to simulate the parameter n and Ea for the study area. The results of the elasticity and contribution analyses suggest that climate change contributed (whose average contribution is 149.6%) more to Ea change than vegetation variation (whose average contribution is −49.4%). Precipitation, NDVI and the maximum temperature are the major drivers of Ea change, while the minimum temperature and wind speed contribute the least to Ea change.

scholarly journals Impact of Climate Change on the Streamflow Modulated by Changes in Precipitation and Temperature in the North Latitude Watershed of Nepal

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 117
Author(s):  
Manisha Maharjan ◽  
Anil Aryal ◽  
Rocky Talchabhadel ◽  
Bhesh Raj Thapa
Keyword(s):  
Climate Change ◽  
Temperature Distribution ◽  
Assessment Tool ◽  
Rate Of Change ◽  
Maximum Temperature ◽  
Water Yield ◽  
Impact Of Climate Change ◽  
Northern Latitudes ◽  
The Impact ◽  
Precipitation And Temperature

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between −7% and +7%, and the minimum temperature rises from +0.7% to +5% in intermediate- and high-emission scenarios. In contrast, the streamflow in the basin varies from −40% to +85%. Thus, there is a significant trend in the temperature increase and precipitation reduction in the basin. Further, the relationship between precipitation and temperature with streamflow shows a substantial dependency between them. The variability in precipitation and streamflow is successfully represented by the water yield in the basin, which plays an important role in the sustainability of the water-related projects in the basin and downstream to it. This also helps quantify the amount of water available for hydropower generation, agricultural production, and the water ecosystem in the TBRB.

scholarly journals Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China

2021 ◽  
Vol 10 (8) ◽  
pp. 515
Author(s):  
Yuming Lu ◽  
Bingfang Wu ◽  
Nana Yan ◽  
Weiwei Zhu ◽  
Hongwei Zeng ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Environmental Factors ◽  
Human Activities ◽  
Land Surface ◽  
Power Plants ◽  
Sunshine Duration ◽  
Central Area ◽  
Eastern Region ◽  
Human Beings

Global climate change and human activities have resulted in immense changes in the Earth’s ecosystem, and the interaction between the land surface and the atmosphere is one of the most important processes. Wind is a reference for studying atmospheric dynamics and climate change, analyzing the wind speed change characteristics in historical periods, and studying the influence of wind on the Earth-atmosphere interaction; additionally, studying the wind, contributes to analyzing and alleviating a series of problems, such as the energy crisis, environmental pollution, and ecological deterioration facing human beings. In this study, data from 697 meteorological stations in China from 2000 to 2019 were used to study the distribution and trend of wind speed over the past two decades. The relationships between wind speed and climate factors were explored using statistical methods; furthermore, combined with terrain, climate change, and human activities, we quantified the contribution of environmental factors to wind speed. The results show that a downward trend was recorded before 2011, but overall, there was an increasing trend that was not significant; moreover, the wind speed changes showed obvious seasonality and were more complicated on the monthly scale. The wind speed trend mainly increased in the western region, decreased in the eastern region, was higher in the northeastern, northwestern, and coastal areas, and was lower in the central area. Temperature, bright sunshine duration, evaporation, and precipitation had a strong influence, in which wind speed showed a significant negative correlation with temperature and precipitation and vice versa for sunshine and evapotranspiration. The influence of environmental factors is diverse, and these results could help to develop environmental management strategies across ecologically fragile areas and improve the design of wind power plants to make better use of wind energy.

scholarly journals THE IMPACT OF CLIMATIC FACTORS TOWARDS RICE PRODUCTION IN INDONESIA

Agro Ekonomi ◽  
2020 ◽  
Vol 31 (1) ◽  
Author(s):  
Aura Dhamira ◽  
Irham Irham
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Rice Production ◽  
Maximum Temperature ◽  
Function Form ◽  
Policy Makers ◽  
The Difference ◽  
The Impact ◽  
Analytical Frameworks ◽  
Adaptation And Mitigation

Rice production is greatly affected by climatic factors, while those factors keep changing along with time. Therefore, the effects of climate change toward rice production in Indonesia need to be studied. The objective of this study is to: (1) determine the difference of interregional climate in each region and (2) determine the impact of climatic factors on rice production in Indonesia. Just and Pope Production function was used as the analytical frameworks, and Cobb-Douglas function form was used to analyze the data. The analysis was conducted towards rice production in ten provinces in Indonesia from 1985 to 2017. The result shows that there are some differences in climatic condition in each region in Indonesia. The regression analysis shows that maximum temperature and minimum temperature have positive impacts on rice production, meanwhile, El Nino and La Nina impact negatively. The results of this study can be considered by the policy makers in making decisions related to adaptation and mitigation to encounter climate change.

scholarly journals Weather Factors Associated with Reduced Risk of Dengue Transmission in an Urbanized Tropical City

2021 ◽  
Vol 19 (1) ◽  
pp. 339
Author(s):  
Hao Gui ◽  
Sylvia Gwee ◽  
Jiayun Koh ◽  
Junxiong Pang
Keyword(s):  
Wind Speed ◽  
Minimum Temperature ◽  
Climatic Factors ◽  
Arima Model ◽  
Positive Association ◽  
Maximum Temperature ◽  
Weather Factors ◽  
Dengue Transmission ◽  
Non Linear ◽  
The Impact

This study assessed the impact of weather factors, including novel predictors—pollutant standards index (PSI) and wind speed—on dengue incidence in Singapore between 2012 and 2019. Autoregressive integrated moving average (ARIMA) model was fitted to explore the autocorrelation in time series and quasi-Poisson model with a distributed lag non-linear term (DLNM) was set up to assess any non-linear association between climatic factors and dengue incidence. In DLNM, a PSI level of up to 111 was positively associated with dengue incidence; incidence reduced as PSI level increased to 160. A slight rainfall increase of up to 7 mm per week gave rise to higher dengue risk. On the contrary, heavier rainfall was protective against dengue. An increase in mean temperature under around 28.0 °C corresponded with increased dengue cases whereas the association became negative beyond 28.0 °C; the minimum temperature was significantly positively associated with dengue incidence at around 23–25 °C, and the relationship reversed when temperature exceed 27 °C. An overall positive association, albeit insignificant, was observed between maximum temperature and dengue incidence. Wind speed was associated with decreasing relative risk (RR). Beyond prevailing conclusions on temperature, this study observed that extremely poor air quality, high wind speed, minimum temperature ≥27 °C, and rainfall volume beyond 12 mm per week reduced the risk of dengue transmission in an urbanized tropical environment.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Historical Period ◽  
Early Winter ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

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