Search

Droughts and climate change are causing severe and persistent dust storms in the arid and hot regions. The potential existence of significant relationships between the Oceanic Niño Index (ONI), Indian Ocean Dipole (IOD), and the MERRA-2 dust column mass density data are thus investigated in the State of Kuwait during 1990–2021 as a study case in the hot and arid regions. The findings show that the correlation starts from ONI-DJF (December–January-February) with the Pearson test value of -0.36 and increasing to a value of -0.55 on ONI-AMJ (April-May-June), the same results were obtained when applying the Spearman correlation test. The correlation exists between the July dust column mass density and IOD-January with a value of -0.484 and − 0.544 over Pearson and ' 'Spearman's test, respectively, all estimated p-values are lower than 0.05. The results of the One-Way ANOVA show that the output is pretty straightforward and statistically significant at p > 0.05, which was confirmed by the nonparametric Kruskal–Walli's test and Mann-Whitney Test. This considerable correlation means that active dust storms are linked with La Niña, while light dust storms occur during the El Niño event. A positive correlation occurs between precipitation and ONI - SON (September-October-November), while a negative correlation is found between precipitation and IOD-July. Our preliminary findings in this paper indicate that an appearance of -0.7°C in ONI-DJF could serve as a definitive marker of the La Nina phase and an indicator for at-risk communities to prepare for the expected activity dust storm. [ABSTRACT FROM AUTHOR]

This paper analyzes spatial and temporal changes of aridity in Argentina (1961–2022). The aridity degree, using Climatic Research Unit (CRU) monthly data, was defined through six climate types classified by De Martonne Aridity Index (DMI). Argentina presents a very arid, arid and semiarid region that extends from Puna to Patagonia, alongside two humid and very humid regions: one located in the Chaco-Pampas Plains and Mesopotamia, and another in the Patagonian Andes. Between these regions, there are subhumid areas with marked aridity variations. These structures persist over time, but advances or setbacks were observed in their bordering areas, with significant changes in the Andes (leading to more arid conditions) and the southwestern Pampas Plains (leading to more humid conditions) during the historical period. The contribution of temperature and precipitation changes to these DMI changes was quantified, indicating that precipitation modulated the DMI spatial changes, while temperature intensified or weakened the change magnitudes. The extension variations of the arid and semiarid regions in Argentina were related to three climate variability modes (El Niño – Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO] and South Atlantic Ocean Dipole [SAOD]). Significant correlations were found with PDO (r < 0) and SAOD (r > 0), which indicate that an increase in the area occupied by arid and semiarid climates are associated with PDO negative phase or SAOD positive phase. Moreover, when these phases occur simultaneously, the expansion of arid and semiarid regions is larger than under the action of an individual forcing. [ABSTRACT FROM AUTHOR]

Maize is a major crop in the semiarid region of northwestern China, and, in recent years, severe drought events have often severely impacted local maize production. In this paper, an assessment model for maize drought vulnerability in the semiarid region of northwestern China was constructed after an in-depth analysis of factors linked to drought vulnerability. The model establishes an evaluation index system for drought vulnerability and assesses the level of environmental sensitivity, degree of exposure, crop sensitivity, and adaptability. An assessment and a regionalization analysis of maize drought vulnerability were then conducted for the semiarid region of northwestern China. The results showed the spatial distribution characteristics of environmental sensitivity, degree of exposure, crop sensitivity, and adaptability. The high and sub high vulnerable areas for maize were located mainly in the northern and southern parts of the warm temperate zone (District I A) and covered most of the central region of the middle temperature zone (District II A). The low and sub low vulnerable areas were in the central part of District I A, in the eastern and western part of District II A, and across the whole of the warm temperate zone (Districts I B), the middle temperature zone (Districts II B), and the plateau area of the sub temperate zone (District III). The main factors affecting high drought vulnerability varied across different areas. These results provide a theoretical basis for the risk management of maize production and will help prevent drought disasters in the semiarid region of northwestern China. [ABSTRACT FROM AUTHOR]

Precipitation directly affects the socioeconomic development in the inland river basins of the arid regions of Northwest China. However, the scarcity of observed data makes it hard to adequately investigate precipitation changes. To help solve this problem, we evaluated the precipitation patterns and trends of 19 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in the northern mountains, central basin, and southern mountains of the Tarim River Basin based on observed data from 1965 to 2014, and conducted a comparison with CMIP5. The results showed that the CMIP6 models have spatial differences in capturing the monthly precipitation over the Tarim River Basin. Although it can capture the changes in monthly precipitation of mountains and basins, it does not capture the monthly maximum precipitation in mountains quite well. CMIP6 models capture precipitation with greater deviations in the wet season than in the dry season, especially for the peak precipitation in June and July. Underestimation of annual precipitation in the northern mountains is common in CMIP6 models with the RMSE of 42.51–50.55 mm. Most models capture the wetting trends in the southern mountains, but their reproduction of wetting trends in the northern mountains differs significantly in coverage. The change rates of annual precipitation from 2015 to 2100 in the northern mountains, central basin, and southern mountains under SSP2-4.5 and SSP5-8.5 are 0.20–0.29 mm/a, 0.10–0.18 mm/a, and 0.23–0.49 mm/a, respectively. The wetting trend in the Tarim River Basin is significantly higher under SSP5-8.5 than under SSP2-4.5. The comparison between CMIP5 and CMIP6 indicates that CMIP6 models are generally able to capture its fluctuating characteristics. However, there is no single model that can simultaneously represent the observed precipitation changes in the Tarim River Basin, especially for the differences in basins and mountains. [ABSTRACT FROM AUTHOR]

Drought is one of the most relevant natural disasters, especially in arid regions such as Iran. One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available in real time or near real time by different agencies and centers; however, for this purpose, these databases must be evaluated regionally and in different local climates. In this paper, a near real-time global climate model, a data assimilation system, and two gridded gauge-based datasets over Iran are evaluated. The ground truth data include 50 gauges from the period of 1980 to 2010. Drought analysis was carried out by means of the Standard Precipitation Index (SPI) at 2-, 3-, 6-, and 12-month timescales. Although the results show spatial variations, overall the two gauge-based datasets perform better than the models. In addition, the results are more reliable for the western portion of the Zagros Range and the eastern region of the country. The analysis of the onsets of the 6-month moderate drought with at least 3 months' persistence indicates that all datasets have a better performance over the western portion of the Zagros Range, but display poor performance over the coast of the Caspian Sea. Base on the results of this study, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset is a preferred alternative for drought analysis in the region when gauge-based datasets are not available. [ABSTRACT FROM AUTHOR]

The vegetation of desert oasis regulates the regional microclimate in arid or hyper-arid regions. A wide range of studies on the oasis microclimate effects have been conducted under sunny conditions. However, less concern has been focused on microclimatic variations of oasis effects caused by the influences of different types and coverage of vegetation in oasis during other different weather events, especially during catastrophic weather conditions. Based on the measurements from 1 August, 2010 to 30 December, 2014 in the Qira oasis, a hyper arid zone of southern Taklimakan desert, Northwest China, this paper investigates the existences and variabilities of the oasis microclimate effects during dust storm, blown sand, floating dust, and rain events and analyzes the impacts of different types of vegetation (bare desert, sparse desert grassland, desert oasis dense shrub grassland and forests, and oasis crops and fruit trees) on desert oasis microclimates. Moreover, the importance of maintaining the oasis sustainability mirrored by the oasis microclimate effects is highlighted and discussed. Results show that the oasis with abundant vegetation exerts cooling and humidifying effects under four weather events relative to bare desert land. As a result of high wind velocities, the oasis microclimatic effects are weakened during catastrophic weather conditions such as dust storm or blown sand events. The type and coverage of vegetation and the topography as well as weather events jointly impact on the oasis microclimate effects. The findings of this work provide an implication for the conservation and restoration of oasis vegetation to maintain both the oasis microclimate environment and the sustainability of desert oasis. [ABSTRACT FROM AUTHOR]

Regional extreme value analyses of drought characteristics provide information on probabilistic nature of drought occurrence, viewed as an essential tool in drought mitigation and planning. In this paper, L-moments are used to investigate the regional characteristics and probabilistic behavior of drought severity levels, represented by the Standardized Precipitation Index (SPI) annual minima (the minimum monthly SPI value). Rainfall data of 3, 6, 12, and 24 month time scales are investigated. A regional watershed in southwestern Iran is used as a case study area. The semi-arid nature of the study area requires appropriate selection of rainfall data. The boxplot approach is used to select those months with adequate data time series for the SPI analysis. Appropriateness of the suggested data time series is discussed in the context of the research by Wu et al. (). Based on the results, all of the suggested time scales are found appropriate for SPI investigations. For each time scale of interest regional homogeneity is evaluated and the best regional/sub-regional probability distribution function is selected. Regional quantiles are estimated for different time scales and their variability with respect to return period is discussed. [ABSTRACT FROM AUTHOR]

This paper presents the results of the first stage of an ongoing project of evaluating the spatial and temporal variability of soil water as fundamental factors for vegetation regeneration in the arid ecosystems in the Blue Nile-eastern Sudan. The specific aim of the present study is to understand the temporal and spatial variations of the major climate variables in the region and discuss its relevance to regional climate variability and changes. In this case, we systematically analyze the major climate variables (maximum and minimum air temperature, relative humidity, and net solar radiation). To evaluate the different characteristics of the climate variables, Mann–Kendall method, two-phase regression scheme, and wavelet transform technique are used; each method has its own strength and weakness, and the results of the three methods complement each other. The results show that the annual and seasonal maximum temperatures are increasing significantly. The annual minimum temperature and minimum temperature in dry seasons are decreasing. The minimum temperature in rainy season is increasing with a smaller rate as compared with the increase of maximum temperature in the season. The difference between maximum and minimum temperature is increasing in all the seasons. Net solar radiation in the region shows a significant increasing trend in all seasons, which corresponds well with the changes of maximum temperature. Besides, significant decreasing trends can be identified for relative humidity in all the seasons. [ABSTRACT FROM AUTHOR]

Using radiosonde dataset from 15 weather stations over West Africa, this paper investigates the contribution of the couple convection-static stability in the framework of the African monsoon multidisciplinary analyses Special Observing Period 3 (AMMA SOP3) experiment. Within this 31-day period, the boundary layer-winds depictions have revealed the West African monsoon's (WAM) depth (around 1500 m) is not thick enough to trigger intense convection. However, the midlevel winds distribution (700-600 hPa) has shown the average African easterly jet core strength (15 m s) is sufficient to allow the development of African easterly waves (AEWs) necessary for squall lines activities. In return, in the upper levels (200-100 hPa), the speed (below 18 m s) of the mean Tropical easterly jet (TEJ) core cannot favor midlevel updrafts. The free tropospheric humidity (FTH) depiction has indicated convective events are more likely in the western Sahel where the highest FTH (FTH >50 %) are recorded. The static stability analysis has testified that convection is stronger in the semi-arid (SA) area during night time (0000 GMT). However, convective activities are inhibited in the wet equatorial (WE) region due to mean low-level stability. We used METEOSAT Second Generation (MSG) infrared (IR10.8) imagery of the 8th September 2006 to confirm that result. Furthermore, a maximum midtropospheric static stability combined with maximum relative humidity (RH) was found on the fringe of the Saharan air layer's (SAL) top (altitude around 5.3 km) in the WE region. [ABSTRACT FROM AUTHOR]

The precipitation types (convective, stratiform, and mixed precipitation) are related to different atmospheric processes. To understand the isotopic characteristics of different types of precipitation, we collected 121 intra-event precipitation samples in Lanzhou of China from June to October 2021. These precipitation events were divided into mixed precipitation and stratiform precipitation using radar images. In the mixed precipitation events, the δ18O values show a similar variation trend. In contrast, the δ18O values of stratiform precipitation events have no coherent trend and are associated to local meteorological factors. The slope and intercept of local meteoric water line indicate that stratiform precipitation is more susceptible to evaporation. Our results provide observational constraints for understanding of isotope variations in different types in mid-latitude semi-arid region. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

This study investigates frequency analysis and its spatiotemporal characteristics of precipitation extremes based on annual maximum of daily precipitation (AMP) data of 753 observation stations in China during the period 1951-2010. Several statistical methods including L-moments, Mann-Kendall test (MK test), Student's t test ( t test) and analysis of variance ( F-test) are used to study different statistical properties related to frequency and spatiotemporal characteristics of precipitation extremes. The results indicate that the AMP series of most sites have no linear trends at 90 % confidence level, but there is a distinctive decrease trend in Beijing-Tianjin-Tangshan region. The analysis of abrupt changes shows that there are no significant changes in most sites, and no distinctive regional patterns within the mutation sites either. An important innovation different from the previous studies is the shift in the mean and the variance which are also studied in this paper in order to further analyze the changes of strong and weak precipitation extreme events. The shift analysis shows that we should pay more attention to the drought in North China and to the flood control and drought in South China, especially to those regions that have no clear trend and have a significant shift in the variance. More important, this study conducts the comprehensive analysis of a complete set of quantile estimates and its spatiotemporal characteristic in China. Spatial distribution of quantile estimation based on the AMP series demonstrated that the values gradually increased from the Northwest to the Southeast with the increment of duration and return period, while the increasing rate of estimation is smooth in the arid and semiarid region and is rapid in humid region. Frequency estimates of 50-year return period are in agreement with the maximum observations of AMP series in the most stations, which can provide more quantitative and scientific basis for decision making. [ABSTRACT FROM AUTHOR]

The arid region of northwest China is a large area with complex topography. Hydrological research is limited by scarcity and uneven distribution of rain gauges. Satellite precipitation products provide wide coverage and high spatial-temporal resolutions, but the accuracy needs to be evaluated before application. In this paper, the reliability of four satellite precipitation products (CMORPH [Climate Prediction Center's morphing technique], PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks], TRMM [Tropical Rainfall Measuring Mission] 3B42, and TRMM 3B43) were evaluated through comparison with ground data or reported values on daily, monthly, and annual scales from 2003 to 2010. Indices including frequency bias index, probability of detection, and false alarm ratio were used to evaluate recorded precipitation occurrences; relative mean bias, the correlation coefficient, and the Nash coefficient were used to assess precipitation amount. Satellite precipitation products were more accurate in the warm than in the cold season, and performed better in northern Xinjiang than in other regions during the cold season. CMORPH and PERSIANN tended to overestimate precipitation. TRMM 3B42 and TRMM 3B43 performed best because the former most accurately detected precipitation occurrences on a daily scale, and both produced accurate space-time distribution of precipitation and the best consistency with rain gauge observations. Only a few monthly precipitation values for TRMM 3B42 and TRMM 3B43, and annual precipitation values for TRMM 3B42 were with satisfactory precision. TRMM3B42 and TRMM 3B43 are therefore recommended, but correction will be needed before application. Factors including elevation, relative relief, longitude, and latitude had significant effects on the performance of satellite precipitation products, and these factors may be helpful in correcting satellite precipitation. [ABSTRACT FROM AUTHOR]

The current research intends to compare the agreement level between the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), the former's variant, at different timescales such as 1, 3, 6, 9, 12, and 24 months. This data was compiled from the Mekerra basin with the help of time series of rainfall and temperature data for 42 years from 1970 to 2011. The authors used Cohen's kappa statistics and the Bland–Altman method to determine the test of agreement between SPI and SPEI. Furthermore, the innovative trend analysis (ITA) method was also employed to analyze the severe and extreme dry trends. The outcomes achieved from the Cohen's kappa statistic revealed the presence of a significant level of agreement between the SPI and SPEI values across the timescales. Furthermore, the researchers observed a positive linear correlation (r > 0.75, p < 0.0001) between the ratings under study. The existence of a small mean difference between the Bland and Altman analyses confirmed the level of agreement between the analytical tools under consideration. In addition to these, the outcomes also infer that in case of the unavailability of the temperature data to conduct the SPEI. Therefore, it is acceptable to use the SPI as the current study found the presence of an acceptable degree of agreement between these two scales in the study location. The present study suggests utilizing various types of drought indices to evaluate the drought performance in a specific location or geographical area to make knowledge-driven decisions. [ABSTRACT FROM AUTHOR]

Downward longwave radiation ( LW) is a relevant variable for meteorological and climatic studies. Good estimates of this term are vitally important in correct determining of the net radiation, which, in turn, modulates the magnitude of the terms in the surface energy budget (e.g., evaporation). In remote sensing applications, the determination of daytime LW is required for estimation of the net radiation using satellite data. LW is not directly measured in weather stations and then is estimated using models with surface air temperature and humidity as input. In this paper, we identify the best models to estimate daytime downward longwave radiation from meteorological data in the sub-humid Pampean region. Several well-known models to estimate LW under clear and cloudy skies were tested. We use downward radiation components and meteorological data registered at Tandil (Argentina) from 2006 to 2010 (840 days). In addition, we propose two multiple linear regression models (MLRM-1 and MLRM-2) to estimate LW at the surface for all sky conditions. The new equations show better performance than the others models tested with root mean square errors between 12 and 16 W m, bias close to zero and best agreements with measured data ( r ≥ 0.85). [ABSTRACT FROM AUTHOR]

Using 51 meteorological stations in the arid region of northwest China in the mountain, oasis, and the desert areas obtained from 1960 to 2010, this paper conducted a comparative analysis for detecting temperature and precipitation changes in the diverse environments. In recent 50 years, temperature has increased at 0.325, 0.339, and 0.360 °C per decade in the mountain, oasis, and the desert areas, respectively; and also, precipitation has increased at 10.15, 6.29, and 0.87 mm per decade, but in which the increasing trend of precipitation in desert area was not significant. Before the 1990s, the increase in temperature was the fastest in the desert area, up to 0.214 °C per decade, but was the slowest in the mountain area, only 0.103 °C per decade. The temperature rising was faster after the 1990s, 0.606 °C per decade, in the oasis area was fastest, but was the slowest in the desert region with 0.402 °C per decade. The precipitation in each area was stable from 1960 to 1986, but an increase in the oasis and mountain area was larger from 1987 to 2010. [ABSTRACT FROM AUTHOR]

Statistical downscaling is a technique widely used to overcome the spatial resolution problem of General Circulation Models (GCMs). Nevertheless, the evaluation of uncertainties linked with downscaled temperature and precipitation variables is essential to climate impact studies. This paper shows the potential of a statistical downscaling technique (in this case SDSM) using predictors from three different GCMs (GCGM3, GFDL and MRI) over a highly heterogeneous area in the central Andes. Biases in median and variance are estimated for downscaled temperature and precipitation using robust statistical tests, respectively Mann-Whitney and Brown-Forsythe's tests. In addition, the ability of the downscaled variables to reproduce extreme events is tested using a frequency analysis. Results show that uncertainties in downscaled precipitations are high and that simulated precipitation variables failed to reproduce extreme events accurately. Nevertheless, a greater confidence remains in downscaled temperatures variables for the area. GCMs performed differently for temperature and precipitation as well as for the different test. In general, this study shows that statistical downscaling is able to simulate with accuracy temperature variables. More inhomogeneities are detected for precipitation variables. This first attempt to test uncertainties of statistical downscaling techniques in the heterogeneous arid central Andes contributes therefore to an improvement of the quality of predictions of climate impact studies in this area. [ABSTRACT FROM AUTHOR]

In this paper, the performance of the Centre for Medium Range Weather Forecast (ECMWF) model ( t + 27 h to t + 51 h) in predicting precipitation is discussed. This model is the first, which has been verified over Iran. The spatial resolution of the model is 0.351° and the 24-h forecasts are compared with daily observations. The study concentrates on year 2001 and the precipitation measurements were collected from the data of 2,048 rain gauges in Iran. The accuracy of four different interpolation methods (nearest neighborhood, inverse distance, kriging, and upscaling) was investigated. Using cross-validation, the inverse distance method (IDM) with minimum mean error was applied. Verification results are given in terms of difference fields (mean error = 0.46 mm/day), rank–order correlation coefficients (0.70), as well as accuracy scores (false alarm ratio = 0.50 and probability of detection = 0.60) and skill scores (true skill statistics [TSS] = 0.45) in year 2001. The position of the rain band was only partly captured by the ECMWF model; however, the position of maximum precipitations agrees with the observations well. The results show that the high values of TSS are associated with the large amounts of precipitation (over 25 mm). Slight to moderate precipitation events have been underforecasted by the model (bias < 1) and it leads to a small value of TSS for these thresholds (5–25 mm/day). The ECMWF model has better performance in high and mountainous regions than over flat terrain and in deserts. Comparing TSS over the Alborz and the Zagros Mountains, it is obvious that the ability of the model to predict the convective precipitation events needs some improvement. The amount of daily precipitation has been also slightly overestimated over Iran. From the beginning of January up to 21 March 2001, the ECMWF time series indicates an obvious phase shift of 1 day, although in other months, no phase shift is noticed. [ABSTRACT FROM AUTHOR]

Many climate studies in Mozambique have clearly identified signals of climate change, especially changes in the extreme temperatures. Regarding precipitation, there is still a gap on the knowledge of how it is behaving due to both internal and external factors in the climate system. In this study, we have investigated the existence of long-term correlations and trend in time series of precipitation. Two databases were used for this purpose: in situ observations along the period of 1960–2020 and the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) dataset, along the period from 1981 to 2021. We have applied the rescaled-range analysis and the detrended fluctuation analysis for long memory investigation, and the linear regression and Mann-Kendall methods for trend analysis. Results have shown the existence of long memory in precipitation in most parts of Mozambique, being stronger in the southern and central regions and weakening toward the north of the country. On the other hand, significant trend signals of precipitation were detected in some isolated areas of Mozambique, presenting an increase in some regions such as the southern part of Manica and eastern of Inhambane provinces and a decrease in other regions such as the coastal areas of Zambezia and Nampula. These findings indicate that the probability of a random occurrence of precipitation is minimal, and the observed trends are likely to continue for a long period in future. Dry land agriculture should be prepared to adapt to new precipitation regime in the regions mentioned hereof. [ABSTRACT FROM AUTHOR]

The study focuses on analyzing the impact of dryness/wetness, derived from Standardized Precipitation Evapotranspiration Index (SPEI), on vegetation phenology in different agro-ecological zones (AERs) of India during 2001–2018. Long-term CRU TS3 SPEI datasets at a 3-month time scale were used to characterize the drought events, while Normalized Difference Vegetation Index (NDVI) data from MODIS at a 250 m scale was used to extract crop phenology metrics. The results revealed that the dryness was prevalent in the hot sub-humid regions since the new millennium. Non-parametric trend analysis showed that northeast India experienced the highest increase in drought events over the past 38 years. In terms of phenology metrics, approximately 59, 23, and 61% of agricultural areas displayed an increasing trend of the start of season (SoS), seasonal NDVI amplitude (NDVImax), and length of season (LoS). However, 21% of agricultural area showed a decreasing trend in SoS, 5.17% in NDVImax, and 28% in LoS. The impact of climate extremes varied across different AERs, that too in dry and wet years. During drought years, most AERs exhibited a delayed SoS, reduced NDVImax, and decreased LoS. The sensitivity of LoS to dryness is higher in semi-arid and sub-humid regions compared to arid and humid regions. Under the projected increase in extreme events, understanding resilient crop growth in response to dryness/wetness is crucial for adaptation and mitigation strategies. The findings of this study help in identifying areas that are particularly vulnerable to drought events and can contribute in informed decision-making. [ABSTRACT FROM AUTHOR]

Droughts have far-reaching detrimental impacts on the environment, society, and economy, ranging from regional to national levels. As the drought characteristics are interrelated, multivariate analysis of those is necessary to understand the actual drought situation in a region. However, such studies are limited. Hence, this study aimed to develop a framework to investigate the meteorological and hydrological droughts using a multivariate analysis of drought characteristics in the Pennar River basin (a semi-arid region) of India, dominated by agricultural activity. Long-term observations (1980–2015) of precipitation, temperature, and streamflow were used to calculate the Standardized Precipitation Evapotranspiration Index (SPEI) and Streamflow Drought Index (SDI) at a 3-month timescale. Based on these indices, drought duration, severity, and peak were abstracted using the Run Theory. The best-fit marginal distribution was determined for every drought characteristic to establish the bivariate joint probability distribution (the copula function). Based on the best-fit copula function, the joint probabilities and the joint return periods were estimated. Results revealed that, for meteorological drought, Frank Copula and Survival Clayton copula were the best-fit copula function for the joint risk of drought duration and severity and the combination of drought duration and peak as well as drought severity and peak, respectively. The joint return period of a drought event with characteristics above the 25th percentile of the same varies between 1 and 2 years, whereas it spans between 1 and 45 years for the 50th percentile. This analysis will provide vital information for water management and planning in a region to mitigate droughts. [ABSTRACT FROM AUTHOR]

A warming climate cause changes in regional climate and climate extremes. However, understanding how future warming can affect the arid climate and drought in Asia is still unclear. Global warming (GW) impacts on shifts in arid regions and change patterns of drought in the Asia region are investigated using the shared socioeconomic pathway 5–8.5 of the Coupled Model Intercomparison Project Phase 6. The variations in the arid region are explored under potential GW targets above preindustrial levels (+ 0.66 °C for the reference period and + 1.5 °C, + 2.5 °C, + 3.0 °C for future periods). We examine changes in precipitation and temperature indices related to drought, the drought patterns corresponding to consistent arid zones and arid-wet shifting zones based on GW scenarios. The results indicate that warming climates influence temperature and precipitation, and consequently alter climate distribution toward an expansion of the arid region. Due to shifts in climate zones, arid regions may expand by 2.6% relative to the reference climate in response to 3.0 °C of warming. Changes in precipitation indices contribute to the spatial patterns and magnitude of drought changes. Future drought features induced by meteorological conditions exhibit different behaviors according to arid-wet shifts and drought events. Especially, drought features throughout Asia are likely to be aggravated in terms of both severity and frequency in response to a greater degree of GW, especially in arid regions and regarding extreme droughts. This study provides valuable information on the relationship between regional climate and drought features in a world affected by GW. [ABSTRACT FROM AUTHOR]

Using data observed at a photovoltaic (PV) power plant at the edge of the Gurbantünggüt Desert and at an undeveloped site in the Gobi desert in the summers of 2019 and 2020, we compared and analyzed the variations of radiation and surface albedo in various wavelength bands. Components of the solar radiation received by the surface of the arid regions of China were ranked infrared (IR) > visible (VIS) > ultraviolet (UV). The observed surface albedo of the PV site was significantly lower than that at the undeveloped desert site. The mean surface albedo values for shortwave broadband (SW), IR, VIS, and UV at the PV site were 0.14, 0.15, 0.13, and 0.08, respectively, and the corresponding values for the undeveloped site were 0.22, 0.23, 0.23, and 0.10, respectively. We also developed a parametric formula for the surface albedo at the PV plant given data observed on typical sunny days. We then validated the parametric formula using observations taken in the summers of 2019 and 2020. The results showed that the parametric formula could precisely simulate variations of the surface albedo and reflected radiation of the PV plant. [ABSTRACT FROM AUTHOR]

Drought severity and frequency are increasing in tropical regions and its occurrence is not uniform in space and time. The study assessed the spatio-temporal dynamics of agrometeorological drought in Mberengwa and Zvishavane districts between 1990 and 2020. An empirical research design was adopted in this study. GIS and remote sensing techniques were used to determine and analyze agricultural drought conditions and the standardized precipitation generator was used to compute SPI for meteorological drought monitoring and analysis. Microsoft Excel 2011 was adopted for the analysis of drought coverage and performing the Mann–Kendall trend test for precipitation trend analysis. Results indicated that the area covered by drought declined between the 1990 and 2000 and 2001–2010 decades before increasing during the 2011–2020 decade. Results indicated significant spatial dynamics of drought severity and frequency in Mberengwa and Zvishavane districts and the majority of wards experienced increased frequency of severe droughts during the 2011–2020 decade. It was highlighted that meteorological drought was not evenly distributed across all decades. Dry conditions in the first months (October and November) of the rainy season have been indicated during the 1990–2000 decade, followed by wetter conditions during the 2001–2010 decade and comparatively drier conditions in the same months during the 2011–2020 decade. This indicated the late onset of the rainfall season during the 1990–2000 and 2011–2020 decades compared to the 2001–2010 decade. It was also shown that rainfall cessation was earlier during the 2001–2010 and 2011–2020 decades and late during the 1990–2000 decade. The study concludes that drought has increased both in severity and frequency in Mberengwa and Zvishavane districts; hence, there is a need for more support to drought resilience-building initiatives in these areas. The government of Zimbabwe is advised to set up climate research centers in all provinces of the country to improve the availability of climate change–related data which is useful when addressing the impacts of climate change. [ABSTRACT FROM AUTHOR]

Drought usually occurs as a result of an imbalance between water supply and demand. Drought indices, an important tool for studying drought, are commonly used for drought monitoring and drought risk assessment. The ground-based drought indices, with high accuracy, are limited in the area monitored. In contrast, the remotely sensed drought index covers a large area but with poor accuracy. Data-driven data fusion–based estimation of ground indices helps to fill this gap. The overall objective is to determine whether various remotely sensed drought factors can effectively monitor drought in arid and semi-arid northern China. In this study, the ground-based drought index SPEI was reconstructed by using remotely sensed drought factors, divided from the Global Precipitation Measuring Mission GPM, GLDAS, and MODIS satellite sensors as well as environmental covariates. Based on climate elements, soil elements, vegetation, and environmental covariate elements, a composite drought index CDIS was established in this study. In this study, the single drought index, multivariate linear integrated drought index, and bias-corrected random forest method were used as the prediction model. Based on ground truth historical climate data as reference data, the performance of the model-predicted composite drought index CDIS in drought monitoring was evaluated. Our results indicate that the drought index on 1-month time scale has no significant advantage over the maximum single drought index. The bias-corrected random forest model with drought index predictions outperformed multiple linear regression and single drought index, with higher prediction accuracy in semi-arid and semi-humid regions than in arid regions. Compared with the ground station drought indices, the drought map based on bias-corrected random forest shows visual and statistical consistency. Under the background of a non-homogeneous and complex surface environment, the model prediction results integrating environmental covariates performed best, and the method used in the study was effective and could be extended and applied. For areas where information is scarce, remote sensing data can be easily extended to regional scale monitoring, which can better achieve high-precision drought monitoring at the regional scale. [ABSTRACT FROM AUTHOR]

Arid, semi-arid, and semi-humid regions (drylands) with fragile ecological balance have undergone dramatic climate change in past decades, and how the desertification will change under a continuous warming background still remain uncertain. In this study, the bias-corrected Community Earth System Model outputs from Coupled Model Intercomparison Project phase 5 were dynamically downscaled using the Weather Research and Forecasting (WRF) model, based on which the evolution trend of desertification over northern China (NC) in the past (1972–2000) and the near future period (2021–2050) under the RCP8.5 scenario were analyzed using the dune mobility index, and the impacts of climate change on the intensification or reversal of desertification over NC in the near future were explored. The results show that WRF downscaling can reproduce the desertification changes over NC in the past. The regions with a high risk of desertification are mainly located on the border of the desert and gobi. Under a rapidly warming climate in the near future, desertification will likely reverse in most regions of NC, especially for regions north of 40°N over NC. Potential evapotranspiration changes will exacerbate desertification, while precipitation changes will promote rehabilitation, and wind speed changes show obvious local impacts on desertification. The results in this study imply that, with rising temperatures in the future, the extent of desertification will not always continue, desertification will likely reverse at the front and margin of deserts and gobi, and responses of desertification to climate change have significant spatial differences. [ABSTRACT FROM AUTHOR]

The aridity index, also known as the Budyko index, describes spatiotemporal changes in the hydroclimatic system in the long-term perspective. Defined as the ratio between potential evapotranspiration and precipitation, it can be used to determine wet (humid) and dry (arid) regions. In this study, we evaluated the aridity index estimated in different temporal scales, investigated its spatial patterns, and highlighted the long-term changes in Europe using three gridded data sets (CRU, E–OBS, and ERA5). A significant dry region expansion is evident in all data sets since the late 1980s. The extent of the dry regions has increased in Western, Central, and Eastern Europe, especially at low and medium altitudes. The results show the long-term development of the European hydroclimatic system and which areas have changed from wet to dry. [ABSTRACT FROM AUTHOR]

The global hydrological cycle is predicted to be intensified under the warming climate, with more extreme precipitation events and longer dry spell in between. Here, we evaluated how extreme precipitation events (EPEs) with antecedent dry (dry-EPEs) and wet (wet-EPEs) water conditions influence carbon exchange along gradient of arid, semi-arid, and sub-humid ecosystems based on eddy covariance datasets. After EPEs, ecosystem respiration and gross primary productivity (GPP) were stimulated by pulses of soil moisture in arid and semi-arid regions, but suppressed by decreased soil temperature in sub-humid region. Antecedent water condition determined asynchronous response of ecosystem respiration and GPP to EPEs, and therefore fluctuations in net carbon balance. Net carbon uptake capacity was enhanced immediately following wet-EPEs because of more rapid and greater response of GPP than respiration. However, after dry-EPEs, net carbon uptake capacity decreased immediately and increased thereafter because the response of GPP to dry-EPEs lagged behind ecosystem respiration. More antecedent precipitation further stimulated accumulative net carbon uptake. In general, the accumulated net carbon uptake within 3 weeks after wet-EPEs was two times and seven times of that after dry-EPEs in arid and semi-arid region, respectively. In sub-humid region, ecosystems acted as a carbon sink after wet-EPEs, but as a carbon source after dry-EPEs. We conclude that antecedent water conditions and local climate regimes need to be considered when interpreting the response of carbon exchange to EPEs in dryland ecosystems. [ABSTRACT FROM AUTHOR]

Global surface temperature is increasing significantly under climate change with increasingly uneven distribution of precipitation, which has been making an important impact on the sustainable development of the dryland agriculture in semi-arid regions. The Inner Mongolia Autonomous Region (IMAR) has the largest area ratio of semi-arid regions in China, and spring wheat is one of its major grain crops, and the negative impacts of climate change pose a serious threat to its production. In order to reduce this threat, we assessed the impact thresholds and risks posed by the main climatic factors to spring-wheat production, and put forward quantitative adaptive countermeasures. The results showed that, from 1961 to 2012, the appropriate impact thresholds of average temperature, precipitation, fertilization level, and water supply level were 15.6 °C, 333 mm, 319.5 kg/ha, and 743.7 mm, respectively. Compared with the average values in 1996–2012, the maximum fertilization level and water supply level could be increased by 162.2 kg/ha and 406.5 mm, respectively, to improve the adaptive yield of spring wheat. The risks of adverse impacts of temperature rise, precipitation decrease, and their combined effect on spring-wheat production were found to be 11.1%, 9.3%, and 10.3%, respectively. The whole IMAR showed a high risk of adverse impacts of temperature rise and the combined action of temperature rise and precipitation decrease on spring-wheat production. In particular, the spring-wheat production in the northeastern, eastern, and central areas were found to be at the highest risk to the impacts of climate change. Based on the determined appropriate thresholds of fertilization level and water supply level, it was determined that in the northeastern area, the maximum fertilization level and water supply level could be increased by 229.9 kg/ha and 441.4 mm, respectively, to increase the adaptive yield of spring wheat. In the eastern area, the two factors could be increased by 142.2 kg/ha and 464.3 mm, respectively. In the central area, they could be increased by 242.2 kg/ha and 513.7 mm, respectively. In the southwestern area, they could be increased by 41.4 kg/ha and 201.7 mm, respectively. [ABSTRACT FROM AUTHOR]

Drought is a dominant climatic feature in arid and semiarid regions. Climate change, temperature variability, and anthropogenic activities caused an increase in agricultural droughts in many regions. Investigation of drought dynamics is important for innovative planning and management of natural resources in drought-prone areas. Remote sensing indices and earth observational datasets were used in this study to investigate droughts in the Bikaner city of Rajasthan, India. Vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI), estimated from multitemporal Landsat datasets, were used for monitoring the drought-prone areas. Land use land cover (LULC) map, normalized difference vegetation index (NDVI), and surface temperature were also calculated for monitoring the decadal changes in surface features. The results showed that barren lands decreased from around 162.75 to 79.59 km2. The annual average temperature increased by 0.72 °C, while agricultural land increased by 33.83 km2 during 1990‒2020. There was a gradual increase in droughts, but the increase was more in recent years than in the early period. The climatic condition revealed from VCI, TCI, and NDVI maps indicated most of the Bikaner city is prone to moderate and extreme droughts. The study indicates the need for VCI-based real-time drought monitoring for drought management. [ABSTRACT FROM AUTHOR]

The availability of quality precipitation records in the current climate situation is of great importance in the scientific-technical field but also for the public institutions that manage the meteorological networks. This work has implemented a comprehensive spatial quality control procedure in the semiarid region of Andalusia (Southern Spain), using precipitation time series from 1947 stations from three meteorological networks: Spanish Meteorological Agency (AEMET), Agroclimatic Information Network of Andalusia (RIA), and Phytosanitary Information Alert Network (RAIF). The method consists of three consecutive steps: basic, absolute, and relative quality control processes. The latter step compares data from neighboring stations taking into account their proximity, height difference, and correlation, leading to a complete evaluation of each daily value. Finally, the quality of each year at each station can be declared as acceptable, good, or excellent. The automatic weather station networks RIA and RAIF gave absolute quality index Q above 85% for almost 87% of their stations, while only 57% of AEMET network reached this percentage. However, one of the longest AEMET datasets, San Fernando-Cádiz, obtained, except for 1 year, Q values over 90% in all available years for more than a century of measurements, since 1870 until 2000. From a total of more than 15 million daily records, almost 82% was flagged as correct. Despite the limitations of Andalusia region (low density of stations and its structural water deficit), the complete quality control procedure has been satisfactorily applied. Finally, related to the number of outliers, no temporal trend was found across the region. [ABSTRACT FROM AUTHOR]

Analysing alternative methods for estimating reference evapotranspiration (ET0) is essential for improving the management of water resources, especially where meteorological data are not fully available for application of the standard Penman–Monteith (PM) method. In this study, the aim was (a) to propose a model for estimating ET0 and (b) to investigate its application together with alternative methods in an area of fruit production in the semi-arid region of Brazil. The Souza-Silva model was generated to estimate ET0 and together with other original methods based on thermal-water variables and global incident solar radiation was tested relative to the PM method. The Souza-Silva method (ET0SS = − 0.00728 + 1.356325DPV + 0.174658Qg, where VPD is the water vapour-pressure deficit and Qg the global incident solar radiation) showed excellent performance in estimating ET0 with a low level of error (RMSE = 0.467 mm day−1 and MBE = − 0.034 mm day−1). Among the original alternative methods, those for Hargreaves (ET0HS) and Camargo (ET0C) models did not perform well in the region under study. The Benevides and Lopes (ET0BL) and Valiantzas1 (ET0V1) methods gave excellent results; these were however even lower than methods based on the solar radiation. Compared to each of the original methods, the result of the Souza-Silva method showed greater precision and accuracy, with smaller estimation errors. It is concluded that this method, based on the water vapour-pressure deficit and solar radiation, can be used to estimate ET0 in places where data collection is limited. [ABSTRACT FROM AUTHOR]

Understanding historical drought changes is critical to water resource management, vegetation growth, and human life in arid regions with vulnerable and sensitive ecological environments. Based on the Schrenk spruce (Picea schrenkiana) sampled from the whole Tianshan Mountains located northwestern China, we developed a tree-ring chronology to study the dry–wet changes through multiple sites sampling. The results showed the stable significantly positive response of tree-ring width chronology to the standardized precipitation and evapotranspiration index (SPEI) in current April and May, indicating that the tree-ring of Schrenk spruce contained the stronger signal of drought variation at the beginning of the growing season. Therefore, we reconstructed the SPEI from 1735 to 2016 in the study regions with 55.1% of the explained variance of reconstruction equation for 1960–2016, which verified the high accuracy of the reconstructed results. Droughts had alternated over the past three centuries with 14 distinct dry and wet periods. Analyzing the 282-year reconstructed drought showed a significant tendency to become wet for the study regions, which were also well correlated with historical droughts and volcanic eruptions events. The SPEI in the study regions was influenced mainly by large-scale atmospheric–oceanic variability with spectral analysis (MTM) revealing some significant low-frequency periods (53.7–78.7, 15.6–16.7, 7.7–8.2, 5.2–5.3, 3.7–3.9, and 2.1–2.2 years). In particular, the HYSPLIT model proved that the westerly circulation was the driving force of the dry–wet changes in the Tianshan Mountains and that the water vapor originated mainly from the North Atlantic. [ABSTRACT FROM AUTHOR]

Water scarcity is the key challenge in arid regions, which exacerbates under climate change (CC) and must be considered to assess the impacts of CC on cropping systems. A climate-crop modeling approach was employed by using the CSM-CERES-Wheat model in some arid regions of northeast Iran to project the effects of CC on irrigated winter wheat production. Current climate data for 1990–2019 and climate projections of three climate models for the near-future climate period of 2021–2050 under RCP4.5 and RCP8.5 emission scenarios were used to run the crop model. Two irrigation scenarios with different irrigation efficiencies were also simulated to investigate the impacts of water scarcity associated with changing climate and irrigation management on winter wheat productivity. Results indicated that mean temperature is projected to increase in the range of 1.74–2.73 °C during the reproductive growth period of winter wheat over the study areas. The precipitation projections also indicated that the precipitation rates would decrease over most of the wheat-growing period. The length of the vegetative growth period will extend in some regions and shorten in others under the near future climate period due to a cooling and warming trend, respectively. However, the grain filling duration will be reduced by about 2–4 days across all regions. The mean seasonal potential evapotranspiration is expected to decrease by about 24 mm from 2021 to 2050 in Mashhad, Sabzevar, and Torbat-e Jam. A mean overall reduction in winter wheat yield due to future climate conditions would be about 12.3% across the study areas. However, an increase of 15–30% in the irrigation efficiency will be able to offset yield reductions associated with limited water supply under future climate scenarios. The results suggest that CC will exacerbate limited irrigation water resource availability, so implementing high-efficiency irrigation systems should be a priority to adapt to climate change in the arid cropping system of north-east of Iran. [ABSTRACT FROM AUTHOR]

Vegetation is an indicator of changes in the ecological environment and a key source of feedback on the impact of drought. In this work we selected northern China as the study area and used the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI) to assess the relationship between drought and vegetation dynamics at annual and seasonal scales for the period 1982–2015. The results indicated that annual drought showed a slight increase in northern China during this time, and it was mainly attributed to the intensified summer drought; the percentages of areas where significant drying, drying, wetting, and significant wetting occurred accounted for 3.30%, 53.36%, 40.39%, and 2.95%, respectively. Annual NDVI showed a highly significant (p < 0.01) upward trend in northern China, suggesting that vegetation there is greening. However, there was still a significant decrease in the NDVI trend in 13.65% of the study area, and forest accounted for the greatest area among the three land cover types studied. A positive correlation between annual SPEI and annual NDVI was found in most of northern China, and 18.66% of the study area (p < 0.05) were mainly distributed in the central-eastern part of Inner Mongolia, the central part of the Loess Plateau, and northwestern part of Xinjiang Province. Residual analysis found that the percentages of vegetation dynamics affected by human-induced degradation, human-induced improvement, and drought accounted for 13.91%, 47.91%, and 38.18%, respectively; however, 54.15% of the areas affected by drought were located in arid and semi-arid regions and that about 54.61% of those were grassland. The work could provide guidance for vegetation construction and water resource management in northern China. [ABSTRACT FROM AUTHOR]

The frequency of drought events in the Mediterranean region has increased significantly in recent years, along with a substantial increase in their spatial and temporal extent. These events are associated with high temperatures and low precipitation. Our study presents a vision on the impact of temperature on agricultural drought frequency, severity, and temporal extent under future scenarios over seven vast plains located in the semi-arid region of the Mediterranean basin. A multivariate frequency analysis of both meteorological and agricultural drought characteristics is based using the copula theory. The return periods of past and future drought events are determined using the two drought indices standardized precipitation index and standardized precipitation evapotranspiration index. The projected drought events are determined based on climate simulations (monthly precipitations and temperatures) from the RCA4-MPI-ESM-LR model, and the projection period was forced by the two representative concentration pathway scenarios RCP4.5 and RCP8.5. Results showed that the frequency of drought events is much higher if only precipitation (SPI) is taken into account than if overall climate (precipitation and temperature, SPEI) is considered while their severity and duration are more intense using SPEI. The risk of drought is best estimated by multivariate frequency analysis where the unvaried return periods, considering the duration or severity, underestimate the recurrence of events. Drought events in the plains are likely to be more severe and to last longer, particularly during the hot season (between May and September) between 2021 and 2071 according to the two future scenarios. In addition, agricultural production is threatened by a spring agricultural drought (between February and April) between 2050 and 2100 under the RCP4.5 scenario, which can have serious consequences on agricultural income as well as food security. [ABSTRACT FROM AUTHOR]

Close management of irrigation could have considerable impacts on water resources, especially for cropping systems dominated by corn. The experiment was carried out to compare the influence of porous capsule irrigation (PCI), surface drip irrigation (DI), and subsurface drip irrigation (SDI) systems, with or without mulching, on actual evapotranspiration (ETc act), crop coefficients (Kc single and Kc dual), biomass yield, and water use efficiency (WUE) of corn in a semiarid region of Iran. The experiment was arranged in a split-plot design with the three irrigation systems assigned to the main plots and two mulching (with or without foil type) treatments (M1 and M2) assigned to the sub-plots. The corn ETc act varied significantly (P < 0.05) with the different irrigation systems, being (mm) 389.8 for PCI, 377.0 for DI, and 372.8 for SDI. The highest Kc average and Kcb (0.82 and 1.22) and the lowest Ke (0.12) were observed under the PCI system. The dry and wet biological biomass yields were highest (29.98 and 107 t/ha) under the PCI + M1 treatment, and the lowest (23.19 and 58.54 t/ha, respectively) were under the DI + M2 treatment. The highest WUE (7.89 kg/m3) was also observed under the PCI + M1 treatment; PCI produced the best biological biomass yield, WUE and IWUE in comparison to DI and SDI systems. Accordingly, the PCI system could be a viable alternative to drip irrigation for areas with scarce water resources, particularly for smallholder farmers. [ABSTRACT FROM AUTHOR]

Soil erosion is one of the most serious problems that cause environmental degradation and loss of agricultural productivity in semiarid regions. To investigate the applicability of satellite-estimated data for assessing rainfall and erosivity in the eastern portion of the Brazilian semiarid region, data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) were evaluated and compared with measured rainfall data. Rainfall dynamics simultaneously considering precipitation temporal series and geomorphology were analyzed. To evaluate satellite-estimated rainfall data and estimated erosivity, the correlation coefficient (R), relative bias (BIAS), average error (ME), and root mean square error (RMSE) were used based on rain gauge-measured data. The results showed that both estimated rainfall datasets perform well when compared to the rain gauge-measured rainfall data. CHIRPS-estimated rainfall data were slightly more accurate on a monthly scale and captured the spatial variability of the rainfall when compared to the other dataset. Finally, the study pointed to CHIRPS- and PERSIANN-CDR-estimated rainfall data as good alternatives to estimate rainfall and erosivity in a Brazilian semiarid region. [ABSTRACT FROM AUTHOR]

Climate change has caused a shift in aridity, particularly in the world's dry regions, affecting several sectors, predominantly the agricultural and water resources. This research examined the climate change effects on crop water demand (CWD) in Syria during 1951–2010. Given the lack of observed data, this analysis relied on Global Precipitation Climatology Center (GPCC) precipitation and Climatic Research Unit (CRU) temperature. Potential evapotranspiration (PET) at each grid was estimated using the Penman–Monteith model and the CWD using the FAO-56 method. The analysis revealed that CWD in Syria increased during 1981 − 2010 compared to that during 1951 − 1980. The increase in CWD was found for grapes, tobacco, barley, and cotton, whereas the maximum changes were during April and May. The most remarkable changes in CWD were for barley, between − 20 and 40 mm. It showed a decreased CWD in the south and a rise in the north (0 − 40 mm). The CWD for wheat showed a decline in most parts of the country, except in the north. The increase in CWD for barley and wheat caused an increase in agricultural water stress in the region. Agriculture planning needs to be developed according to the expected future climate changes to maintain the agricultural production in the region. [ABSTRACT FROM AUTHOR]

Abrupt changes are referred to as fundamental changes in the mean of a system's variable or its variability which occur in a short term. Abrupt changes in climatic factors may, especially in arid lands, lead to the transition of plant communities as their response to such disturbing elements. However, such a relationship (between factor and response) which helps develop more sustainable policies for ecosystem management has so far been underresearched. This study, therefore, set out to identify the abrupt changes occurred in plant communities and their relationship with the sudden variations of climatic factors in Sirjan desert and semi-desert region, located in Kerman, Iran, from 2000 to 2019. To this end, first, the meteorological data were collected from the region's representative station (Sirjan synoptic Station) and the plant communities' maps were extracted based on field operations. Then, the Moderate Resolution Imaging Spectroradiometer's (MODIS) monthly data from 2000 to 2019 were used to extract Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) whose maps were limited to the community's maps under zonal statistic survey, using Arc-GIS 10.4.1 package. Finally, the sequential Mann–Kendall (SMK) test was administered to identify the abrupt changes in climatic factors and those of each plant communities. The abrupt changes in yearly total precipitation (YTP) in 2002, 2008, 2014, and 2018 occurred concurrently with the responses made by plant communities including the Artemisia sieberi-Zygophyllum atriplicoides, Ephedra intermedia-Cousinia multilobe. In this regard, the cumulative effect of the abrupt change of the winter precipitation (WP) factor in 2002 and 2014 and the abrupt increase of the average yearly temperature (YAT) factor in 2018 was highly effective in the intensification of the stimulating role of total yearly precipitation (YTP) in making the plant communities respond as a result. Despite the concurrent responses observed in the vast majority of plant communities, the reason behind some of their responses in 2006, 2011, 2013, and 2016 remained unknown, requiring more investigations in terms of other environmental variables. [ABSTRACT FROM AUTHOR]

Climate and especially air temperature have a direct and high impact on nut trees in arid regions. In this regard, the use of multi-model ensemble projections as more reliable models is important. In this study, based on multi-model ensembles (MME) from the coordinated regional climate downscaling experiment Middle East North Africa (CORDEX-MENA), the air temperature in RCP8.5 and RCP4.5 pathways in pistachio cultivation areas in Iran was projected. The period 1980 to 2017 was identified as the reference period. Due to the sensitivity of climate change and the existing uncertainties, the hourly temperatures based on the models of chilling hours (CH) and chilling portions (CP) were also used for the reference period. The results of CORDEX simulations for pistachio cultivation areas suggest that the minimum and maximum annual air temperature (MMAT) and growing season temperature (GST) at the end of the current century compared to 1980–2017 as the reference period will increase significantly to 4 °C. The downward trend of winter chill accumulation during the cold season based on observational data will confirm the increase in air temperature in pistachio cultivation areas in Iran. In the output simulation of CORDEX project, the date of flowering pistachio tree for late-maturing varieties by 2080 under representative concentration pathway (RCPs) RCP8.5 and RCP4.5 will occur 16 days and 6 days sooner, respectively. The amount of heat accumulation or growing degree days (GDD) in the future in pistachio cultivation areas will be increased, and deviation from the historical period, based on RCP8.5 and RCP4.5 on average, will occur 3200 and 2600 GDD, respectively. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) plays a fundamental role in governing the water and energy balance at land-atmosphere interfaces and in controlling plant growth and biological interactions, which makes it a key indicator in drought identification. We compared and evaluated two types of surface SM datasets (Global Land Data Assimilation System-Noah-simulated (GLDAS-Noah); Europe Space Agency's Climate Change Initiative (ESA CCI)) for drought analysis in China over 1979–2014. The cumulative density function (CDF) matching method was employed to fill the data gap of ESA CCI data using the GLDAS-Noah SM products. Drought characteristics of duration, severity, and frequency were appraised on a grid basis using the Standardized Soil Moisture Index (SSI). The results show that the SSI values calculated based on these two SM products are significantly correlated (p < 0.05) over most parts (70%) of China, with similar patterns of average drought duration, severity, and frequency. The duration and severity at the arid and semiarid regions (with duration over 3 months; with an average severity of −3.1) are generally higher than those over humid regions (with the duration of 2 months; with an average severity of −2.7), but both SM datasets show higher drying trends in humid regions. However, the two SM datasets exhibit large discrepancies in the spatial patterns of drought duration, severity, and frequency trends, especially in arid and cold regions. Both SM products are capable of monitoring extreme drought events reported in southwestern, southern, and northern China compared with the Standardized Precipitation Index (SPI). Overall, both data sources have the potential to be used for drought monitoring; however, caution should be paid in high altitude and latitude regions where a large discrepancy exists. [ABSTRACT FROM AUTHOR]

The study of the maximum number of consecutive dry days (MCDDs) is one approach to analyze precipitation behavior in arid and semi-arid regions of Iran. This study is a first attempt to investigate the MCDDs and their relationship with the El Niño/Southern Oscillation (ENSO) in winter months over Iran. The study was carried out using Tropical Rainfall Measuring Mission (TRMM) satellite data on a daily basis at 1° latitude × 1° longitude spatial resolution and reanalysis data for the period 1998–2019. Results showed that the highest values of MCDDs are observed in southeastern Iran and the lowest in northwestern Iran. Based on the coefficients of the linear trend of the MCDDs, the significant increasing trends are remarkably more abundant than declining trends, especially in the northern half of the country in December and January. The results regarding the relationship between ENSO and MCDDs indicated a non-stationary behavior, with a significant negative correlation for December (especially in the southwest) and positive correlation for January and February (especially in the southeast). The largest differences in the correlation coefficients were observed between December and January. In general, during El Niño (La Niña) phases, the length of MCDDs decreases (increases) in December and increases (decreases) in January especially in the southern half. By comparing different large-scale climate parameters for the 2 months, we found that during El Niño (La Niña) phases, a negative (positive) anomaly of geopotential height and a positive (negative) anomaly of zonal wind and specific humidity are observed over the region in December, while the opposite situation occurs in January. The innovation of this study is the use of satellite data that provide a continuous spatial coverage of the region and the consideration of the ENSO teleconnection pattern in regards to dry spells. We find that El Niño (La Niña) has contradictory effects on MCDDs in different winter months in the southern half of the country. These findings are of great importance for a country like Iran that lies in arid and semi-arid regions, as they can be useful for water resources management. [ABSTRACT FROM AUTHOR]

Different sources of uncertainty exist in climate change impacts projection. This study aims to propose a framework to deal with the various sources of uncertainties involved in hydro-climate projections of Zayandeh-Rud River Basin with area of 26,917 km2 in Central Iran. The Bayesian model averaging (BMA) was here used through two distinct approaches for weighting the hydrologic outputs (App. I) as well as the global climate models (GCMs) (App. II) based on their abilities to simulate the baseline period. The results showed that different GCMs have different abilities in estimating the hydro-climatic variables and the application of uncertainty analysis is necessary for climate change studies. Application of the BMA can significantly reduce the errors in historical runoff prediction. Although App. I showed a better performance of generating the stream flow time series during the baseline period, the App. II approach has an acceptable ability in different months. The findings of flow duration curves under both approaches revealed that App. II is more appropriate to deal with uncertainty of hydro-climate projection especially in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

To combat desertification, an understanding of its current development is necessary, including that of causative factors associated with climate change and increasing human activity. Whereas, there is an ongoing debate surrounding impact factors for change in vegetation and desertification in arid regions. The present study assesses the spatiotemporal characteristics of vegetation change in the Ulan Buh Desert, northwest China. Driving factors for desertification were discussed using the Global Inventory Monitoring and Modeling System Normalized Difference Vegetation Index (GIMMS NDVI) and SPOT Vegetation NDVI datasets, high-resolution satellite images, and meteorological and socioeconomic data in the period 1982–2018. The results show a trend of overall greening, with increasing trends at rates between 0.0008/year and 0.0013/year indicated by the two NDVI datasets and with a corresponding reduction in dune activity. The spatial variations of two NDVI datasets verified the significantly greening trend in the northern and southern areas of the desert. Human activity was observed to have impacted vegetation dynamics. It is predicted that the implementation of ecological projects will contribute to the restoration of vegetation during a warmer, wetter climate trend. However, the reduction of wind strength played a dominant role in vegetation greenness and dune stability in the Ulan Buh Desert. The present study revealed the spatiotemporal characteristics of vegetation variations and the driving factors for desertification in arid regions. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean resides on the border between the temperate and semi-arid and arid climate zones, and is thus influenced by both mid-latitude and sub-tropical weather systems. Precipitation and extreme weather in this region are mainly associated with either Cyprus Lows or the "wet" Red Sea Troughs. Current regional climate projections indicate that the region may become warmer and drier in future decades. Here, we analyze the influence of enhanced greenhouse gas forcing on the climatological properties of the 'wet' and 'dry' Red Sea Trough (WRST & DRST, respectively). With this aim, a regional synoptic classification and a downscaling algorithm based on past analogs are applied to eighteen rain stations over the main ground water basins in Israel. The algorithms are applied to the NCEP/NCAR reanalysis data for 1986–2005 and to eight CMIP5 model simulations for the historical (1986–2005) and end of the century (2081–2100) climate conditions according to the RCP8.5 scenario. For the historical period, the CMIP5 models are largely able to represent the characteristics of the Red Sea Trough. Based on the multi-model mean, significant changes are found for WRST and DRST for the late XXI Century. First, an increase in the meridional pressure gradient is found for both the WRST and the DRST, implying stronger horizontal winds. Furthermore, a significant decrease in the occurrence of the WRST (− 20%) and a significant increase in the frequency of the DRST (+ 19%) are identified. Accordingly, the persistence of the WRST decreases (− 9%), while for DRST increases (+ 9%). The decline in the frequency of WRST occurs primarily in the transition seasons, while the increase for DRST is found throughout the wet season. In total, the daily rainfall associated with the WRST system is projected to significantly decline (− 37%) by the end of the XXI century. These results document the projected changes in a dominant synoptic system in this area, which can facilitate a better estimation of the arising challenges, e.g., related to shortage of water resources and associated political unrest, reduced agricultural potential, and increased air pollution and forest fires. Such a pathway can ultimately foster novel mitigation strategies for water resources management and regional climate change adaptation. [ABSTRACT FROM AUTHOR]

The present study aimed to assess the performance of CMIP6 and CMIP5 projects in projecting mean precipitation at annual, summer, autumn, winter, and spring timescales in the north and northeast of Iran over the period 1987–2005 using relative bias, correlation coefficient, root mean square error, relative error, and the Taylor diagram. This is the first attempt to compare CMIP6 and CMIP5 data in an arid region at a seasonal and annual scale. The results showed that the precipitations simulated by the ensembles of CMIP6 and CMIP5 models were different. The relative bias for winter was lower at all stations in CMIP6 than in CMIP5, so CMIP6 performed better in this respect. CMIP6 outperformed CMIP5 in projecting annual and spring precipitation in 60 and 69% of the stations, respectively. Whereas CMIP6 overestimated precipitation in 70% of the stations, CMIP5 underestimated it in 77% of the stations. CMIP5 models exhibited better performance in 70% of the stations only in autumn. In most seasons and stations, CMIP6 CGMs' ensemble outperformed CMIP5. The results of HadGEM2-ES from CMIP5 and CESM2 from CMIP6 were more accurate than the models' ensembles in both projects. Overall, CMIP6 models exhibited better performance than CMIP5 models. [ABSTRACT FROM AUTHOR]

Natural variability of climate considerably affects hydro-climatic trend significance, and therefore, removal of such influence is essential to understand the unidirectional trends due to global warming. The objective of this study was to evaluate the trends in precipitation extremes in the arid province of Pakistan by removing the natural variability of climate to understand the effect of global warming on precipitation extremes during two major cropping seasons, Rabi and Kharif. Daily precipitation data of APHRODITE (Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation) for the period 1951–2015 was used for this purpose. An improved form of classical Mann-Kendall (MK) test known as modified Mann-Kendall (MMK) was used which can estimate trends by discarding the influence of natural cycles present in time series. The results were compared with the classical MK test to show the novelty in the findings of this investigation. The results revealed a large influence of climate fluctuations on the trends in all the extreme precipitation indices for both seasons. The reduction in trend significance was noticed between 25 and 100% for different precipitation indices when MMK instead of MK test was used. The reduction was observed more for the positive trends in the indices compared with negative trends. The results revealed that global warming caused an increase in total annual precipitation at a rate of 2.8–34.8 mm/decade during 1951–2015. Besides, the annual number of extreme precipitation days was found to increase in the north by 0.1–0.84 days/decade and the number of annual precipitation days to decrease in the west for all seasons up to − 8.6 days/decade. An increase in continuous precipitation days was detected by 0.6–1.0 day/decade in the northeast while a decrease by − 0.5 to − 1.0 days/decade in the southwest and northwest. The continuous dry days decreased in the north and the central regions by up to − 6.3 days/decade while a rise in 1-day maximum precipitation by 6.6–35 mm/decade in the central north. Analysis of results revealed that the overestimation of trends by classical MK test is more in the arid region of Pakistan compared with other regions. [ABSTRACT FROM AUTHOR]

Drought is a type of destructive hydro-climatic disaster that has a significant impact on agriculture and natural resources. Meteorological drought features, including severity, duration, and peak, exhibit various patterns in different climatic regions and geographical conditions. Several indices have been developed to assess the drought potential of different areas across the world, among which the drought hazard index (DHI) is one of the most commonly employed for semi-arid and the flat regions. This study investigates the effects of the elevation and precipitation on DHI, which has received little attention in previous studies. For this purpose, DHIs were computed for 15 stations located at different elevations of the study area over 31 years by considering the occurrence of various drought classes with different weights. The results showed that the elevation and mean precipitation both have inverse effects on the DHI in the study area, which means that the DHI increases when the elevation and mean precipitation are low. The results of the estimation of the DHI for three different periods (i.e., 6, 9, and 12 months) revealed that a 9-month period is optimum for DHI estimations in terms of the reliability of the results. [ABSTRACT FROM AUTHOR]

Countries located in arid and semi-arid regions of the world, such as Iran, with highly dependent economy to agriculture, are more vulnerable to climate change. Six agro-climatic indices have been used, which include the length of the growing season and the frost-free season, dates of the occurrence of the last frost in spring and the first frost in autumn, and annual sum of the growing degree-days (GDD) for two temperature thresholds. To explore variabilities of the indices in the future, outputs of three regional climate models (RCMs) have been analyzed based on two Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios for the South Asia CORDEX region, with the horizontal resolution of 0.44°. Differences between the historical and future simulated agro-climatic indices have been calculated, in which the former is obtained from historical outputs of three models for the period 1961–1990, while the latter is based on future simulations during the period 2061–2090 applying RCP4.5 and RCP8.5 scenarios. Both RCP scenarios indicate an increase in the number of frost-free days (maximum 40 and 70 frost-free days according to the RCP4.5 and RCP8.5 scenarios, respectively), with higher changes in mountainous regions. Our results indicate that shorter frost days will be more common in northwestern and western Iran in the future period. The highest increase in annual sum of the GDD will be in southern and central Iran, but the lowest increase will be in northwestern Iran. [ABSTRACT FROM AUTHOR]