Trends Of Aridity Index Research Articles

Semi-Arid to Arid Scenario Shift: Is the Cabrobó Desertification Nucleus Becoming Arid?

Monitoring areas susceptible to desertification contributes to the strategic development of regions located in environments of extreme hydric and social vulnerability. Therefore, the objective of this study is to evaluate the process of soil degradation in the Desertification Nucleus of Cabrobó (DNC) over the past three decades using remote sensing techniques. This study used primary climatic data from TerraClimate, geospatial data of land use and land cover (LULC), and vegetation indices (SAVI and LAI) via Google Earth Engine (GEE) from Landsat 5/TM and 8/OLI satellites, and established the aridity index (AI) from 1992 to 2022. The results indicated 10 predominant LULC classes with native vegetation suppression, particularly in agriculture and urbanization. SAVI ranged from −0.84 to 0.90, with high values influenced by La Niña episodes and increased rainfall; conversely, El Niño episodes worsened the rainfall regime in the DNC region. Based on the Standardized Precipitation Index (SPI), it was possible to correlate normal and severe drought events in the DNC with years under the influence of El Niño and La Niña phases. In summary, the AI images indicated that the DNC remained semi-arid and that the transition to an arid region is a cyclical and low-frequency phenomenon, occurring in specific periods and directly influenced by El Niño and La Niña phenomena. The Mann–Kendall analysis showed no increasing trend in AI, with a Tau of −0.01 and a p-value of 0.97. During the analyzed period, there was an increase in Non-Vegetated Areas, which showed a growing trend with a Tau of 0.42 in the Mann–Kendall analysis, representing exposed soil areas. Annual meteorological conditions remained within the climatic pattern of the region, with annual averages of precipitation and actual evapotranspiration (ETa) close to 450 mm and an average temperature of 24 °C, showing changes only during El Niño and La Niña events, and did not show significant increasing or decreasing trends in the Mann–Kendall analysis.

Estimation of regional meteorological aridity and drought characteristics in Baluchistan province, Pakistan.

Droughts and prevailing arid conditions have a significant impacts on the natural environment, agriculture, and human life. To analyze the regional characteristics of drought in Baluchistan province, the aridity index (AI) and standardized potential evapotranspiration index (SPEI) were used in. The study analyzed the rainfall, temperature, and potential evapotranspiration (PET) data and the same were used for the calculation of AI as well as SPEI to find out the drought spells during the study period. The linear regression and Mann-Kendall test were applied to calculate the trend in AI as well as in SPEI results. The AI results revealed that most of the meteorological stations are arid and semi-arid, where the highest increasing aridity is noted at Kalat (0.0065/year). The results of the SPEI at 1 and 6-months identified the extreme to severe drought spell during 1998-2002 in all meteorological stations of Baluchistan province. The distinct drought spells identified from the SPEI results were in the years 1998-2003, 2006-2010, 2015-2016 and 2019. The drought frequency results showed highest frequency percentage at Lasbella (46%) of extreme to severe drought. The Mann-Kendall trend results showed negative trend in monthly AI and 1-month SPEI results and most significant trend was observed in April and October months, this shows that aridity and drought in the region are decreasing to some extent except Dalbandin and Lasbella observed increasing trend in winter season (November to January months) and Kalat met-station observed increasing trend in June. Prior investigation and planning of drought situations can help in controlling the far-reaching consequences on environment and human society.

Correction to: Changes in spatio-temporal distribution of AgMERRA-derived agro-climatic indices and agro-climatic zones for wheat crops in the northeast Iran

This study evaluates the potential of gridded AgMERRA (the Modern-Era Retrospective Analysis for Research and Applications) to estimate aridity index (AI), growing degree days (GDD), and temperature seasonality (TS) for six land stations across northeast Iran. The researcher investigated the spatiotemporal variation of the AgMERRA-derived agro-climatic indices for the entire period 1981–2010 and three 10-year sub-periods for the 347 wheat harvested grid cells (0.25° × 0.25°) and their utility for agro-climate zoning in northeast Iran. Results indicated a good agreement between AgMERRA daily solar radiation, maximum and minimum temperatures, and annual total precipitation with corresponding land observations for the six studied sites. AgMERRA-derived evapotranspiration (ETo), AI, GDD, and TS also exhibited good agreement (R2 and d > 0.7) with the land station–derived indices for most of the locations. Annual analysis of the AI indicated a negative trend for all of the wheat harvested grid cells, but the decrease was significant (p < 0.05) only for 14.70% of grid cells, which were located in the southwest part of the studied region. The magnitude of the significant decreasing trends in annual AI was (−)0.0011 per year. The increase in aridity was due to the concurrent occurrences of positive ETo trends and negative precipitation trends. All of the wheat harvested grid cells showed a significant increasing trend (p < 0.05) for GDD at the rate of 24.10 °C d year−1. The TS series demonstrated an apparent increasing trend for 99.2% of wheat harvested grid cells; however, only 16.9% of them had the significant positive trend (p < 0.05) with the average rate of 0.023 °C year−1. The wheat harvested grid cells with increasing trend for TS were mainly distributed in the arid mountainous southern part of the study area. The 10 years sub-periods revealed that the best conditions in terms of most of the studied agro-climatic indices were found in sub-period 1981–1990 and the north Khorasan had better conditions in all three sub-periods. Based on AI, GDD, and TS, 13 major gridded agro-climatic zones were recognized in northeast Iran.

Changes in spatio-temporal distribution of AgMERRA-derived agro-climatic indices and agro-climatic zones for wheat crops in the northeast Iran.

This study evaluates the potential of gridded AgMERRA (the Modern-Era Retrospective Analysis for Research and Applications) to estimate aridity index (AI), growing degree days (GDD), and temperature seasonality (TS) for six land stations across northeast Iran. The researcher investigated the spatiotemporal variation of the AgMERRA-derived agro-climatic indices for the entire period 1981-2010 and three 10-year sub-periods for the 347 wheat harvested grid cells (0.25° × 0.25°) and their utility for agro-climate zoning in northeast Iran. Results indicated a good agreement between AgMERRA daily solar radiation, maximum and minimum temperatures, and annual total precipitation with corresponding land observations for the six studied sites. AgMERRA-derived evapotranspiration (ETo), AI, GDD, and TS also exhibited good agreement (R2 and d > 0.7) with the land station-derived indices for most of the locations. Annual analysis of the AI indicated a negative trend for all of the wheat harvested grid cells, but the decrease was significant (p < 0.05) only for 14.70% of grid cells, which were located in the southwest part of the studied region. The magnitude of the significant decreasing trends in annual AI was (-)0.0011 per year. The increase in aridity was due to the concurrent occurrences of positive ETo trends and negative precipitation trends. All of the wheat harvested grid cells showed a significant increasing trend (p < 0.05) for GDD at the rate of 24.10°C d year-1. The TS series demonstrated an apparent increasing trend for 99.2% of wheat harvested grid cells; however, only 16.9% of them had the significant positive trend (p < 0.05) with the average rate of 0.023°Cyear-1. The wheat harvested grid cells with increasing trend for TS were mainly distributed in the arid mountainous southern part of the study area. The 10 years sub-periods revealed that the best conditions in terms of most of the studied agro-climatic indices were found in sub-period 1981-1990 and the north Khorasan had better conditions in all three sub-periods. Based on AI, GDD, and TS, 13 major gridded agro-climatic zones were recognized in northeast Iran.

Distinct vegetation response to drying and wetting trends across an aridity threshold

Aridity regulates the terrestrial ecosystem productivity in water-limited regions. The aridity index (AI) is often defined as the ratio of annual precipitation to annual potential evapotranspiration. However, how the drying and wetting influence the vegetation response and its characteristic along aridity gradient remains unclear. Here, we examined trends of the AI and normalized difference vegetation index (NDVI) in the drylands of East Asia from 1982 to 2015, which denoted the drying and wetting trends and vegetation response, respectively. The results show that the variability in land area and AI from 1982–2015 was lower in the whole dryland than its subtypes including hyper-arid, arid, semi-arid, and dry sub-humid regions. Drying and wetting trends were observed in each AI interval along a spatial aridity gradient. Wetting trends are prevalent owing to their area and magnitude were twice those of drying trends. Spatial variation of aridity shaped the pattern of trends in vegetation response to drying and wetting trends; drier regions had smaller and narrower ranges of variation in NDVI trends relative to wetter regions. A shift in AI trends and NDVI trends along the spatial aridity gradient occurred at 0.4 of AI. Distinct patterns of vegetation response to aridity change were observed across the aridity threshold, and the transition region was identified in the studied drylands. The results suggest that changes in the subtypes might be masked by the entire drylands and then leading to failure in recognizing the transformation of the subtypes. This implies that terrestrial carbon storage variability prediction should consider the spatial aridity changes to avoid the uncertainties due to the divergent vegetation response to AI trends at different aridity levels.

Attribution Analysis of Long-Term Trends of Aridity Index in the Huai River Basin, Eastern China

This paper aims to combinedly investigate the spatiotemporal trends of precipitation (Pre), reference evapotranspiration (ET0), and aridity index (AI) by employing nonparametric methods based on daily datasets from 137 meteorological stations during 1961–2014 in the Huai River Basin (HRB). The dominant factors influencing ET0 and AI trends were also explored using the detrended and differential equation methods. Results show that (1) Pre, ET0, and AI were much larger in summer than in other seasons, and AI had a nonsignificant increasing trend in annual time scale, while Pre and ET0 exhibited decreasing trends, but AI showed a downward trend in spring and autumn (becoming drier) and an upward trend during summer and winter due to increased Pre (becoming wetter); (2) lower AI values were identified in north and higher in south, and lower ET0 was identified in south and higher in north in annual time scale, growing season and spring, while ET0 decreased from west to east in summer and winter, the spatial distribution of Pre was similar to that of AI; (3) for ET0 trends, in general, wind speed at two-meter height (u2) was the dominant factor in spring, autumn, winter, and annual time scale, while in other seasons, solar radiation (Rs) played a dominant role; (4) for AI trends, AI was mostly contributed by Pre in spring, autumn, and winter, the Rs contributed the most to AI trend in growing season and summer, then in annual time scale, u2 was the dominant factor; (5) overall, the contribution of Pre to AI trends was much larger than that of ET0 in spring, autumn, and winter, while AI was mostly contributed by ET0 in annual time scale, growing season and summer. The outcomes of the study may improve our scientific understanding of recent climate change effects on dry–wet variations in the HRB; moreover, this information may be utilized in other climatic regions for comparison analyses.

What were the changing trends of the seasonal and annual aridity indexes in northwestern China during 1961–2015?

The objective of this paper is to study the spatial and temporal variation characteristics of the UNESCO aridity index (AI) at annual and seasonal temporal scales in northwestern China during the 55-year study period (1961–2015). Based on climate data from 178 meteorological stations provided by the China Meteorological Data Service Center, AI trends were investigated by the Mann-Kendall test. The results showed that the annual and seasonal AIs displayed a mixed pattern of positive and negative trends for the period of 1961–2015 across the study area. In most regions, both annual and seasonal AIs exhibited slightly positive trends in northwestern China. Significant (P < .05) positive and negative annual trends were detected at 38 and 6 stations, respectively. The highest magnitude of the positive annual trend (0.0037 per year) appeared at Xining station, and the greatest decreasing annual trend (−0.0041 per year) appeared at Minxian station. In terms of seasonal AI, its trend magnitudes varied from −0.0058 to 0.0035 in spring, from −0.0062 to 0.0087 in summer, from −0.0105 to 0.0048 in autumn and from −0.0002 to 0.0443 in winter each year. Our study demonstrated that the AI spatial distribution may tend to be spatially homogeneous in the long term. Abrupt changes varied in different regions and seasons. Nevertheless, the positive trend shifts mostly began in the 1980s and became significant in the following decades. The correlation analysis indicated that the AI in winter and spring was probably mainly affected by the Indian Ocean Warm Pool Strength Index (IOWPSI), while the Multivariate ENSO Index (MEI), the Niño3.4 Sea Surface Temperature Anomaly Index (Niño3.4 SSTA) and the Southern Oscillation Index (SOI) were likely to be the conjoined influencing factors of the AI in summer and autumn. The spatiotemporal features of the long-term AI provided in this study may enhance our scientific understanding of the impacts of recent climate change on dryness/humidity changes in northwestern China; furthermore, this information might potentially be applied in other areas for comparison purposes.

ARIDITY INDEX BASED ON TEMPERATURE AND RAINFALL DATA FOR KURDISTAN REGION-IRAQ

Aridity index is a numerical indicator of the degree of dryness of the climate at a given location. Time series of annual precipitation, minimum and maximum temperature records for 22 meteorological stations in Kurdistan region-Iraq were collected from different agencies. In Kurdistan region-Iraq neither aridity index non it’s trend have been studied, therefore the purpose of this paper is to document the range of an aridity index, called De Martonne’s aridity index (IDM) and to find the trend of aridity index using Mann-Kendal nonparametric test. Spatial zoning of the region was done using inverse distance weight (IDW) interpolation method by ArcGIS software. Results showed that different types of climate in the region were appeared however most of the study area falls in the range of semi-arid zone. Seasonal aridity showed that Kurdistan region-Iraq has extremely humid climate in winter and arid climate in summer. The De Martonne aridity index, average precipitation and average temperature were drawn for 10, 20 and 30 years according to availability of the data. Aridity index for 30 years from De Martonne were compared with two other indices and the results were very close.&nbsp; Trend analyses were performed for precipitation, temperature, and aridity index for the average data of 10, 20, and 30 years. Results revealed that for 10 year duration Dukan temperature has significant increasing trend at the 95% confidence level. It can be concluded that the last decade (2006-2015) undergo insignificant increasing in precipitation and temperature. For 20 year duration Dukan and Hawler temperature showed significant increasing trend at the 95% confidence level. For 30 year duration all stations temperature increased, Dukan precipitation showed decreasing trend while Dukan aridity index showed increasing trend significantly at the 95% confidence level. Increased significant trends at the 95% confidence level for temperature appears at both short and long durations (10, 20 and 30 years) while precipitation and aridity index trends appear only in long duration (30 years).

Changes in aridity and its driving factors in China during 1961–2016

Understanding the changes in aridity is crucial because of the substantial impacts it can have on human society. However, realistic aridity changes and their underlying climatic mechanisms demonstrate large uncertainties in China. Here we adopted the aridity index (AI) to assess the aridity changes in China, and we quantified the relative contributions of various climatic drivers (the precipitation, net radiation, wind speed, relative humidity, and air temperature) to AI changes based on the station data during 1961–2016. Our results showed that the arid/semi‐arid northwest China and Tibet Plateau experienced wetting trends, while western sub‐humid north and northeast China and western humid south China exhibited drying trends during 1961–2016. The dominant climatic drivers involved in the changing AI trends changed from arid to humid regions. In arid northwest China, increasing precipitation and decreasing wind speeds contributed the most to the wetting trends (0.024 and 0.017 in 56 years, respectively). In the semi‐arid Tibet Plateau, increasing precipitation dominated the wetting trends (0.045 in 56 years). However, in sub‐humid/humid north and northeast China and south China, decreasing wind speed and net radiation dominated the annual AI changes (0.061 and 0.092 in 56 years, respectively). In addition, AI of northwest China and the Tibet Plateau exhibited a significant abrupt change in 1987 and exhibited wetter states afterwards, which could be caused by the abrupt increase in precipitation in 1987. This study could improve current understanding of the aridity changes in China and help adapt its potential impacts.

Spatiotemporal variations of aridity in China during 1961–2015: decomposition and attribution

Changes in global climate intensify the hydrological cycle, directly influence precipitation, evaporation, runoff, and cause the re-distribution of water resources in time and space. The aridity index (AI), defined as the ratio of annual precipitation to annual potential evapotranspiration, is a widely used numerical indicator to quantify the degree of dryness at a given location. This study examined the effects of climate change on AI in China during 1961–2015. The results showed that the nationally averaged AI experienced a notable interdecadal transition in 1993, characterized by increasing AI (wetter) between 1961 and 1993, and decreasing AI (drier) after 1993. Overall, the decreased solar radiation (solar dimming) was the main factor affected the nationally averaged AI during 1961–1993, while the relative humidity dominated the variations of nationally averaged AI during 1993–2015. However, the roles of individual factors on the changes in AI vary in different subregions. Precipitation is one of the important contributing factors for the changes of AI in almost all subregions, except the Mid-Lower Yangtze and Huaihe basins. Solar radiation has been significantly decreased during 1961–1993 in South China, Southwest China, Mid-Lower Yangtze and Huaihe basins, and the Tibetan Plateau. Therefore, it dominated the trends of AI in these subregions. The relative humidity mainly affected the Mid-Lower Yangtze and Huaihe basins, Southwest China, and the Tibetan Plateau during 1993–2015, hence dominated the trends of AI in these subregions. The changes of temperature and wind speed, however, played a relatively weak role in the variations of AI.

Spatiotemporal changes in aridity index and reference evapotranspiration over semi-arid and humid regions of Iran: trend, cause, and sensitivity analyses

The existence of significant trend and change point in the aridity index (AI), precipitation, and reference evapotranspiration (ET0) was evaluated using the Mann-Kendall and Pettitt tests, respectively, over 22 semi-arid, humid, and sub-humid sites of Iran during 1966–2012. Detrending method was also employed to quantify each factor’s contribution to the AI and ET0 trends. The ET0 and AI sensitivity to their input perturbations was analyzed using a derivative sensitivity coefficient. The results indicated a downward trend in precipitation and AI and an upward trend in ET0 on both seasonal and annual scales for majority of sites. Compared with AI and precipitation, more significant change points were detected, mainly during the 1990s, in the ET0 series. Except for wintertime, solar radiation (SR) was found as the most sensitive factor on the AI and ET0 dynamics in the semi-arid regions. However, with an exception for summertime, AI and ET0 exhibited greater sensitivity to the RH changes followed by the SR changes in the humid/sub-humid areas. For more than 70% of semi-arid stations and Gorgan (a sub-humid location), wind speed (U) was the most important variable contributing to seasonal and annual ET0 trends. However, the ET0 trend was primarily caused by the mean temperature (Tmean) changes for the humid environments. Further, the precipitation changes made the largest contribution to seasonal and annual AI trends for most cases followed by the U changes. An integrated water resource management is required to be implemented to reduce negative impacts of decreased AI and ET0 increment over Iran.

Spatio-Temporal Analysis of Meteorological Elements in the North China District of China during 1960–2015

The North China District (NCD) is one of the main grain production regions in China. The double cropping system of irrigation has been leading to the groundwater table decline at the speed of 1–2 m per year. Climate change leads to uncertainty surrounding the future of the NCD agricultural system, which will have great effects on crop yields and crop water demands. In this research, the Meteorological dataset from 54 weather station sites over the period 1960–2015 were collected to quantify the long-term spatial and temporal trends of meteorological data, including daily minimum temperature (Tmin), maximum temperature (Tmax), precipitation, solar radiation, reference evapotranspiration (ET0), and aridity index (AI). The results show that the long-term wheat and maize growing season and annual average air temperatures (Tmin and Tmax) showed strong north to south increasing trends throughout the NCD. The average annual precipitation was 632.9 mm across the NCD, more than 70% of which was concentrated in the maize growing season. The regional average annual ET0 was 1026.1 mm, which was 531.2 and 497.4 mm for the wheat and maize growing season, respectively. The regional precipitation decreased from northwest to southeast in each growing season and annual timescale. The funnel areas have lower precipitation and higher ET0 than the regional average, which may lead to the mining of the groundwater funnel area. The regional average annual AI is 0.63, which lies in the humid class. For temporal analysis, the regional average trends in annual Tmin, Tmax, solar radiation, ET0, precipitation, and AI were 0.37 °C/10a, 0.15 °C/10a, −0.28 MJ/day/m2/10a, −2.98 mm/10a, −12.04 mm/10a, and 0.005/10a, respectively. The increasing trend of temperature and the decreasing trend of solar radiation may have a negative effect on the regional food security. The funnel area AI showed a significant increasing trend for the winter wheat growing season and a decreasing trend for maize, which indicated that more irrigation will be needed for the maize growing season and the winter fallow policy may lead to the increasing trend precipitation being wasted. Analyzing the growing season and the annual meteorological elements of the spatiotemporal trends can help us better understand the influence of climate change on the natural resources and agricultural development in both the past and the future, and will provide us with invaluable information for the modification of cropping patterns to protect the regional and national water and food security.

Impacts of climate change on aridity index and its spatiotemporal variation in the Loess Plateau of China, from 1961 to 2014

The Loess Plateau, the transitional zone between humid and arid regions of China, is an important region to examine the regional hydrological cycle and variation in humid and arid regions under global climate change. Aridity index (AI), the ratio of precipitation (P) to potential evapotranspiration (ET0), is an important indicator of regional climate conditions and is also used to classify drylands. In this study, data from 51 national meteorological stations during the period of 1961–2014 were collected to estimate the AI in the Loess Plateau. Results show that a downward trend in annual AI was detected and the boundary of the drylands region based on the AI was expanded across the Loess Plateau over the period of 1961–2014. The spatiotemporal variability of P was the main cause in the AI variations. Furthermore, data analysis suggested the occurrences of the extreme minimum AI values were mostly affected by fluctuations of the two factors (ET0 and P) rather than its corresponding trend during the period. Thus, this study indicated the major driving factor of AI and the relationship between extreme AI values and the global climate anomalies in the Loess Plateau region, and meanwhile, provided an understanding of the impacts of climate change on hydrological cycle in the Loess Plateau of China.

Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET0) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving t test, and Morlet wavelet method were used. The results indicated that ET0 and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET0 and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET0 and AI were dissimilar and not clustered, either. Temporally, both ET0 and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET0, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET0 and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.

Nonlinear changes in aridity due to precipitation and evapotranspiration in China from 1961 to 2015

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 74:263-281 (2018) - DOI: https://doi.org/10.3354/cr01500 Nonlinear changes in aridity due to precipitation and evapotranspiration in China from 1961 to 2015 Yunhe Yin1,*, Danyang Ma1,2, Shaohong Wu1,2 1Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, PR China 2University of Chinese Academy of Sciences, Beijing 100049, PR China *Corresponding author: yinyh@igsnrr.ac.cn ABSTRACT: Changes in regional aridity have complicated spatio-temporal features during the past several decades and have important implications for hydrologic cycles under global climate change. However, nonlinear changes in aridity and its spatial variability in China remain poorly understood. Here, we analyzed the spatial-temporal changes in hydroclimatic variables, including reference evapotranspiration (ETo), precipitation (P), aridity index (AI) and their relationships, mainly based on the ensemble empirical mode decomposition method. A climate dataset from 573 meteorological stations in China was used for the period 1961-2015. The results show that the nonlinearity of changes in aridity was complex, with distinct spatial differences. Approximately 76.09% of stations showed reversed trends in AI during 1961-2015, among which AI initially decreased and then increased, mainly in Inner Mongolia and the areas south of the middle and lower reaches of the Yangtze River. However, their reversal times were not synchronous. The drying to wetting transition mainly occurred in northern areas, including the southern part of Northeast China, the eastern Loess Plateau and the southern North China Plain. Although the majority of stations experienced reversals from downward to upward trends of ETo (53.92%) mainly around the 1990s, increasing precipitation exerted a larger effect on AI. For most eco-geographical regions in China, the nonlinear variations in ETo and P jointly led to the decline in AI over the past 55 yr, and the P trend contributed more than the ETo trend to the change in AI, except in subtropical regions, where ETo variations played a key role. KEY WORDS: Aridity · Precipitation · Reference evapotranspiration · Nonlinear · Climate change · Ensemble empirical mode decomposition · EEMD Full text in pdf format PreviousCite this article as: Yin Y, Ma D, Wu S (2018) Nonlinear changes in aridity due to precipitation and evapotranspiration in China from 1961 to 2015. Clim Res 74:263-281. https://doi.org/10.3354/cr01500 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 74, No. 3. Online publication date: February 28, 2018 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2018 Inter-Research.

Attribute Analysis of Aridity Variability in North Xinjiang, China

Identifying the dominant meteorological factors affecting aridity variability can improve our understanding of climate change and its future trend in arid and semiarid regions. This study investigated the spatiotemporal aridity variability in North Xinjiang, China, from 1961 to 2013, based on the UNESCO aridity index (precipitation/potential evapotranspiration), and analyzed its association with meteorological factors. The results suggest that North Xinjiang is becoming more humid with an increasing trend in aridity index. Precipitation, temperature, and relative humidity have positive correlation with aridity, and evapotranspiration, sunshine hours, and wind speed have negative correlation with aridity. Wind speed and sunshine hours have a higher sensitivity and more contribution to aridity. This study provides an understanding of the effect of recent climate change on drought in northwest China.

Comparison of dryland climate change in observations and CMIP5 simulations

A comparison of observations with 20 climate model simulations from the Coupled Model Intercomparison Project, Phase 5 (CMIP5) revealed that observed dryland expansion amounted to 2.61×106 km2 during the 58 years from 1948 to 2005, which was four times higher than that in the simulations (0.55×106 km2). Dryland expansion was accompanied by a decline in aridity index (AI) (drying trend) as a result of decreased precipitation and increased potential evapotranspiration across all dryland subtype areas in the observations, especially in the semi-arid and dry subhumid regions. However, the CMIP5 multi-model ensemble (MME) average performed poorly with regard to the decreasing trends of AI and precipitation. By analyzing the factors controlling AI, we found that the overall bias of AI in the simulations, compared with observations, was largely due to limitations in the simulation of precipitation. The simulated precipitation over global drylands was substantially overestimated compared with observations across all subtype areas, and the spatial distribution of precipitation in the MME was largely inconsistent in the African Sahel, East Asia, and eastern Australia, where the semi-arid and dry subhumid regions were mainly located.

Spatiotemporal trends of aridity index in Shiyang River basin of northwest China

Drought/wetness conditions are fundamental not only for agricultural production but also ecology, human health, and economic activity. Dryness/wetness is a function of precipitation, temperature, vegetation and potential evapotranspiration. Regions with low moisture are often characterized by aridity which, in turn, reflects the degree of meteorological drought. Observed climatic data from eleven meteorological stations in and around Shiyang River basin, China, were used to calculate the aridity index (AI) which was defined as the ratio of potential evapotranspiration (ET0) to precipitation (P). ET0 was calculated using the Penman–Monteith method. The ordinary kriging method was used to interpolate the spatial variability of ET0, P and AI. The Mann–Kendall test with a pre-whitening method was employed using the Yue and Wang autocorrelation correction to detect temporal trends. The Theil–Sen estimator was used to estimate the slopes of trend lines. Results showed a higher AI in the north basin and a lower AI in the Qilian Mountain region. Annual ET0 and P had increasing trends with a slope of 0.672 and 0.459 mm per year, respectively, but trends were not statistically significant for most stations. While annual AI had a slight decreasing trend with a slope of −0.01 per year, the trend was not statistically significant for all stations. The decreasing trends in winter AI (at a rate of −0.313/a) was more significant than that in other seasons. The study indicates that the Shiyang River basin is getting slightly wetter, especially in winter.

Spatiotemporal trends in mean temperatures and aridity index over Rwanda

This study aims at quantifying the trends in mean temperatures and aridity index over Rwanda for the period of 1961–1992, based on analysis of climatic data (temperatures, precipitations, and potential evapotranspiration). The analysis of magnitude and significance of trends in temperatures and aridity index show the degree of climate change and mark the level of vulnerability to extreme events (e.g., droughts) in different areas of the country. The study reveals that mean temperatures increased in most parts of the country, with a significant increase observed in the eastern lowlands and in the southwestern parts. The highlands located in the northwest and the Congo-Nile crest showed a nonsignificant increase in mean temperatures. Aridity index increased only in March, April, October, and November, corresponding with the rainy seasons. The remaining months of the year showed a decreasing trend. At an annual resolution, the highlands and the western region showed a rise in aridity index with a decreasing pattern over the eastern lowlands and the central plateau. Generally, the highlands presented a nonsignificant increase in mean temperatures and aridity index especially during the rainy seasons. The eastern lowlands showed a significant increase in mean temperatures and decreasing trends in aridity index. Therefore, these areas are bound to experience more droughts, leading to reduced water and consequent decline in agricultural production. On the other hand, the north highlands and southwest region will continue to be more productive.

Spatio-temporal variation of reference evapotranspiration and aridity index in the Loess Plateau Region of China, during 1961–2012

Analyses of the spatial and temporal variation of reference evapotranspiration (ET0) and aridity index (AI) can further understand climate change and its effect on hydrology. In this study, based on date from 58 standard meteorological stations, the spatio-temporal variations and trends of ET0 and AI were calculated for the Loess Plateau Region (LPR) from 1961 to 2012 using the Mann–Kendall test, the moving t-test, and the Morlet wavelet methods. The results demonstrated: (1) the annual ET0 displayed a statistically significant decrease of −10.3 mm/10 y (P < 0.05) during 1961–2012. At that time, AI also had a decreasing trend of −0.013/10 y over the past 52 years. Compared with ET0, the inter-decadal variations of AI over the LPR seemed to show similar declined trends. (2) Spatially, about 81% stations displayed a decreasing trend for annual ET0 during 1961–2012, and most of them were distributed in the western, northern and southeastern LPR. In addition, about 60% of stations showed statistically decreasing trends for AI, and the major decreases were mainly in the east Qinghai division and northern LPR. (3) Abrupt changes were detected in annual ET0 series in the 1980s and in annual AI series in 1987. Wavelet analysis indicated significant 2 year and non-significant 7, 10 and 14 years in annual ET0 series, and there existed periods of 4, 8 and 12 years for AI. (4) For ET0, wind speed was the most sensitive meteorological factor, followed by sunshine hours, precipitation, and relative humidity. For AI, ET0 and precipitation were the sensitive factors. This study provides an understanding of the effect of recent climate change on hydrological cycle in the LPR.