Maximum Dry Spell Length Research Articles

Nonlinear Trend and Multiscale Variability of Dry Spells in Senegal (1951–2010)

Dry spells occurring during the rainy season have significant implications for agricultural productivity and socioeconomic development, particularly in rainfed agricultural countries such as Senegal. This study employs various chaos-theory-based tools, including the lacunarity method, rescaled analysis, and the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method, to investigate the distribution, predictability, and multiscale properties of the annual series of maximum dry spell length (AMDSL) in Senegal during the rainy season. The analysis focuses on 29 stations across Senegal, spanning the period from 1951 to 2010. The findings reveal persistent behavior in the AMDSL across nearly all stations, indicating that predictive models based on extrapolating past time trends could enhance AMDSL forecasting. Furthermore, a well-defined spatial distribution of the lacunarity exponent β is observed, which exhibits a discernible relationship with rainfall patterns in Senegal. Notably, the lacunarity exponent displays a south-to-north gradient for all thresholds, suggesting its potential for distinguishing between different drought regimes and zones while aiding in the understanding of spatiotemporal rainfall variability patterns. Moreover, the analysis identifies five significant intrinsic mode functions (IMFs) characterized by different periods, including interannual, interdecadal, and multidecadal oscillations. These IMFs, along with a nonlinear trend, are identified as the driving forces behind AMDSL variations in Senegal. Among the inter-annual oscillations, a 3-year quasi-period emerges as the primary contributor and main component influencing AMDSL variability. Additionally, four distinct morphological types of nonlinear trends in AMDSL variations are identified, with increasing–decreasing and increasing trends being the most prevalent. These findings contribute to a better understanding of the variability in annual maximum dry spell lengths, particularly in the context of climate change, and provide valuable insights for improving AMDSL forecasting. Overall, this study enhances our comprehension of the complex dynamics underlying dry spell occurrences during the rainy season and presents potential avenues for predicting and managing the AMDSL in Senegal.

Drivers of Dry Day Sensitivity to Increased CO2

AbstractPersistent precipitation deficits are among the most impactful consequences of global warming. Here we focus on changes in the annual number of dry days (NDD) and in the annual maximum length of dry spells due to a quadrupling of atmospheric CO2. We use atmosphere‐only simulations to decompose the projected changes into additive contributions. A fast adjustment leads to a global increase in NDD despite notable regional exceptions (e.g., South Asia and Sahel). The effect of the uniform component of the surface ocean warming is model‐dependent but shapes the regional distribution of the NDD response in each model. Finally, the ocean warming pattern also contributes to large uncertainties, likely through contrasting changes in large‐scale circulation. Our results thus highlight the complexity of the NDD response, with policy‐relevant practical implications for mitigation and adaptation strategies.

Observed Changes in Rainfall and Characteristics of Extreme Events in Côte d’Ivoire (West Africa)

This study evaluates how the characteristics of daily rainfall and extreme events in Côte d’Ivoire changed during 1961–2015 using the rain gauge observation network of the National Meteorological Service (SODEXAM). The results indicate that the northern and southern parts of Cote d’Ivoire experienced a change from a wet to a dry period, with cut-offs in 1982 and 1983, respectively. In the northern part, this dry period was marked by a decrease in rainfall intensity, the length of wet spells, and the contribution of heavy and extreme rainfall, as well as an increase in the number of rainy days and a decrease in the length of dry spells. Over the southern part, this dry period was marked by an increase in the maximum length of dry spells associated with an increase in the maximum 1-day and 5-day precipitation events. The western part of Côte d’Ivoire experienced a late cut-off from the wet to dry period in 2000; the dry period was associated with a decrease in the number of rainy days, rainfall intensities, and maximum length of wet spells. Changes in the central part of Cote d’Ivoire presented high variability, and trends were less marked, even though a cut-off from a wet to dry period was detected in 1991. This study shows that Côte d’Ivoire, which is located in a subhumid and humid region and has an economy dependent on agriculture (especially cash crops, which comprise 60% of the GDP), is experiencing dry spells that are increasing in frequency and length. Combined with deforestation to increase production, this situation could lead to desertification and compromise the sustainable development goals of the country. The contribution of heavy rainfall was found to increase during the last 15 years, increasing the overall risk of floods, especially in urban areas where city authorities and populations are not prepared, thereby threatening infrastructure and human security.

Spatio-Temporal Analysis of Dry Spell for Agricultural Decision Support in North-Central Nigeria

This study aims to examine the trend and geospatial variability of dry spells for agricultural decision support. Daily precipitation data spanning from 1981 to 2020 was analyzed using the Instat climatic software to calculate rainfall onset, onset plus 50, length of the growing season, cessation, dry spell 1, and dry spell 2. Multiple regression analysis was used to analyze the trend in maximum dry spell length. Kriging method in Surfer 13 software was used to interpolate and plot dry spell distribution into a spatial grid in the study region. Based on records of daily rainfall data obtained from eight meteorological stations, the spatial distribution of dry spells was generated for the beginning and end of the season. The results obtained revealed a decreasing trend for maximum dry spell length during onset, meaning its recurrence is declining except in Bida, Minna, and Jos that show a positive trend. While the trend for maximum dry spell length at end of the season appears to be positive except for Lafia and Minna that shows a negative trend. The result further indicates that dry spells towards the end of the season are more severe than dry spells at beginning of the season.

Temporal Changes in Flow Regime along the River Vistula

The flow regime in the River Vistula is influenced by climatic and geographical factors and human intervention. In this study, we focus on an analysis of flow and precipitation variability over time and space following the course of the River Vistula. Multi-purpose statistical analyses of a number of runoff and precipitation characteristics were performed to present a general overview of the temporal and spatial changes. Since the important feature of the hydrological regime of Polish rivers is the seasonality of runoff associated with the occurrence of cold (winter) and warm (summer) seasons within a hydrological year, a seasonal approach is applied to describe specific seasonal features that can be masked when using annual data. In general, the results confirm popular impressions about changes in winter season runoff characteristics, i.e., significantly decreasing daily maxima, increasing daily minima and a decrease in concentration, and so a bigger uniformity of winter daily flows. An interesting behaviour of minimum flows in the summer has been revealed, which is contrary to social perceptions and the alarming changes taking place in the other parts of the world. Additionally, precipitation indexes related to the formation of droughts show no trends, e.g., the mean value of the maximum dry spell length.

Future Changes in Wet and Dry Season Characteristics in CMIP5 and CMIP6 simulations

AbstractClimate change will result in more dry days and longer dry spells, however, the resulting impacts on crop growth depend on the timing of these longer dry spells in the annual cycle. Using an ensemble of Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6) simulations, and a range of emission scenarios, here we examine changes in wet and dry spell characteristics under future climate change across the extended tropics in wet and dry seasons separately. Delays in the wet seasons by up to two weeks are projected by 2070-2099 across South America, Southern Africa, West Africa and the Sahel. An increase in both mean and maximum dry spell length during the dry season is found across Central and South America, Southern Africa and Australia, with a reduction in dry season rainfall also found in these regions. Mean dry season dry spell lengths increase by 5-10 days over north-east South America and south-west Africa. However, changes in dry spell length during the wet season are much smaller across the tropics with limited model consensus. Mean dry season maximum temperature increases are found to be up to 3°C higher than mean wet season maximum temperature increases over South America, Southern Africa and parts of Asia. Longer dry spells, fewer wet days, and higher temperatures during the dry season may lead to increasing dry season aridity, and have detrimental consequences for perennial crops.

Observed changes in rainfall amount and extreme events in southeastern Ethiopia, 1955–2015

This study analysed spatio-temporal variability and trends in rainfall amount and extreme events in the southeastern part of Ethiopia for the period 1955–2015. Daily rainfall data from 44 recording stations were used to define total rainfall amounts and 12 extreme event indices for three wet seasons and annual time scale. Mann–Kendall’s trend test and Sen’s slope estimator were used to determine trends and rates of change, respectively. Results showed the emergence of different trend signals across seasons and over space in the study area. Trend tests for total rainfall amount and extreme indices for annual and March–May season show a global significant downward tendency. However, the number of wet and dry days, maximum consecutive wet and dry spells and wet day rainfall intensity for the annual time scale show mixed significant upward and downward tendencies, while trends for the number of dry days and maximum consecutive dry spells showed a global significant increasing trend for the March–May season across the study area. On the other hand, mixed global significant upward and downward tendencies were found in all rainfall indices for the June–September season over the northern part of the study area. Different from the two wet seasons, the trend test for the September–November wet season in the southern part of the study area shows an increasing tendency, although only few of the upward trends were statistically significant. In contrast, the number of dry days and maximum dry spell length for this season reveal decreasing trends at most of the stations. Empirical evidences generated in rainfall trends using dense gauging stations provide useful information to develop spatially relevant climate change adaptation and climate risk management plans.

The Climatic Analysis of Summer Monsoon Extreme Precipitation Events over West Africa in CMIP6 Simulations

We evaluate the capability of 21 models from the new state-of-the-art Coupled Model Intercomparison Project, Phase 6 (CMIP6) in the representation of present-day precipitation characteristics and extremes along with their statistics in simulating daily precipitation during the West African Monsoon (WAM) period (June–September). The study uses a set of standard extreme precipitation indices as defined by the Expert Team on Climate Change Detection and Indices constructed using CMIP6 models and observational datasets for comparison. Three observations; Global Precipitation Climatology Project (GPCP), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Tropical Applications of Meteorology using SATellite and ground-based observation (TAMSAT) datasets are used for the validation of the model simulations. The results show that observed datasets present nearly the same spatial pattern but discrepancies in the magnitude of rainfall characteristics. The models show substantial discrepancies in comparison with the observations and among themselves. A number of the models depict the pattern of rainfall intensity as observed but some models overestimate the pattern over the coastal parts (FGOALS-f3-L and GFDL-ESM4) and western part (FGOALS-f3-L) of West Africa. All model simulations explicitly show the pattern of wet days but with large discrepancies in their frequencies. On extreme rainfall, half of the models express more intense extremes in the 95th percentiles while the other half simulate less intense extremes. All the models overestimate the mean maximum wet spell length except FGOALS-f3-L. The spatial patterns of the mean maximum dry spell length show a good general agreement across the different models, and the observations except for four models that show an overestimation in the Sahara subregion. INM-CM4-8 and INM-CM5-0 display smaller discrepancies from their long-term average rainfall characteristics, in terms of extreme rainfall estimates than the other CMIP6 datasets. For the frequency of heavy rainfall, TaiESM1 and IPSL-CMGA-LR perform better when compared with observational datasets. MIROC6 and GFDL-ESM4 displayed the largest error in representing the frequency of heavy rainfall and 95th percentile extremes, and therefore, cannot be reliable. The study has assessed how rainfall extremes are captured in both observation and the models. Though there are some discrepancies, it gives room for improvement of the models in the next version of CMIP.

A landscape hydrology approach to inform sustainable water resource management under a changing environment. A case study for the Kaleya River Catchment, Zambia

Study regionKaleya River Catchment in southern Zambia. Study focusThe ability of a landscape hydrology approach to detect controls on water availability in a fragmented landscape to inform interventions under a changing environment was investigated. Simple and measurable climatic and landscape pattern attributes were analysed using change detection, trend analysis and backward variable elimination with Partial Least Squares Regression (PLSR) to identify controls on seasonal river flows and how landscape components could be enhanced to augment natural river flows. New hydrological insights for the regionLandscape pattern showed increasing fragmentation, expansion of irrigated cropland and reservoirs and loss of forestland. Significant increasing trends (p < 0.05) were observed for reference evapotranspiration (ETo), one-day maximum rainfall, coefficient of variation (CV) of rainfall, maximum dry spell length, and start of rains but not annual rainfall. Increased CV of rainfall, rainfall intensity and ETo were the main climatic stressors on river flows. Increased Percentage of Landscape (PLAND) of irrigated cropland, PLAND of reservoirs, Patch Density (PD) and Largest Patch Index (LPI) of reservoirs were the main landscape pattern stressors. Only the LPI of forestland positively explained seasonal river flows. Water resource interventions in the region must adapt more to changing seasonal rainfall characteristics than to annual rainfall totals. Additionally, regeneration of larger forest patches could improve river flows. The approach can be applied in other regions.

Rainfall and dry spell occurrence in Ghana: trends and seasonal predictions with a dynamical and a statistical model

Improved information on the distribution of seasonal rainfall is important for crop production in Ghana. The predictability of key agro-meteorological indices, namely, seasonal rainfall, maximum dry spell length (MDSL) and dry spell frequency (DSF) was investigated across Ghana (with an interest on the coastal savannah agro-ecological zone). These three variables are relevant for local agricultural water management. A dynamical model (i.e. European Centre for Medium-Range Weather Forecasts (ECMWF) System 4 seasonal forecasts) and a statistical model (i.e. response to sea surface temperatures (SSTs)) were used and analysed using correlation and other discrimination skill metrics. ECMWF-System 4 was bias-corrected and verified with 14 local stations’ observations. Results show that differences in variability and skills of the agro-meteorological indices are small between agro-ecological zones as compared to the differences between stations. The dynamic model System 4 explains up to 31% of the variability of the MDSL and seasonal rainfall indices. Coastal savannah exhibits the highest level of discrimination skills. However, these skills are generally higher for the below and above normal MDSL and seasonal rainfall categories at lead time 0. Similarity in skills for the agro-meteorological indices over the same zones and stations is found both for the dynamical and statistical models. Although System 4 performs slightly better than the statistical model, especially, for dry spell length and seasonal rainfall. For dry spell frequency and longer lead time dry spell length, the statistical model tends to perform better. These results suggest that the agro-meteorological indices derived from System 4′ updated versions, corrected with local observations, together with the response to SST information, can potentially support decision-making of local smallholder farmers in Ghana.

Evaluation of CORDEX Regional Climate Models in Simulating Extreme Dry Spells in Southwest China

In recent decades, Southwest China (SWC) has experienced a series of severe and extensive droughts resulting in tremendous socioeconomic losses. The annual maximum dry spell length (AMDSL), which refers to the number of consecutive days without rainfall, or days with rainfall below a threshold, plays an important role in triggering drought. The main objective of this study is to provide a comparison of the capabilities of current regional climate models (RCMs) in simulating extreme dry spell characteristics in mountainous SWC. Five available RCM simulations utilized in the Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia project over 1981 to 2005 were employed in this study; the RCMs being NIMR-HadGEM3, SNU-MM5, SNU-WRF, KNU-RegCM4 and YSU-RSM. Firstly, it was found that all RCMs reasonably simulate the main seasonality features of rainfall and dry days in SWC. Furthermore, besides YSU-RSM, the other four RCMs can accurately capture the spatial pattern of dry-day occurrence based on Taylor diagram diagnosis. Secondly, we assessed the performance of five RCMs to detect and reproduce the climatology and variability of the AMDSL. In general, RCMs simulate the spatial pattern of long-term mean and interannual variability of the AMDSL in SWC well. Based on Taylor diagram evaluation, NIMR-HadGEM3 was the best among 5 RCMs in simulating the AMDSL characteristics. Thirdly, the generalized extreme value (GEV) distribution is considered the most suitable model fitting the AMDSL in both observation and RCM experimental data in comparison to other three-parameter probabilistic models. Higher value centers of the scale parameter and the location parameter indicate a wider and amplified distribution of the AMDSL over the low-latitude highlands (LLH) region against other areas in Southwest China, which is consistent with spatial patterns of climatological AMDSL. In addition, sensitivity analysis of different thresholds for dry days show that the 1 mm threshold is suitable for this study and different threshold choices have little effect on simulation ability.

High resolution climate precipitation analysis for north-central Italy, 1961–2015

Observational daily precipitation data from a group of 1762 stations over north-central Italy and adjacent areas are used to produce a high resolution daily gridded precipitation analysis covering the period from 1961 to 2015. Input data are checked for quality, time consistency, synchronicity and statistical homogeneity and the final result has been used to describe the spatial and temporal variability of precipitation over the area. Data are interpolated using a modified Shepard scheme and the interpolation errors are compatible with those presented in Isotta et al. (Int J Climatol 34(5):1657–1675, 2014). The analysis is compared with other similar products available over the area considered, and differences and similarities are described, taking into account the impacts of different spatial resolution and time coverage. The data set is used to describe local climate with respect to precipitation, including mean values and seasonality, by using a group of climate annual and seasonal indices: cumulated precipitation, maximum number of consecutive dry days, frequency of wet days, mean precipitation intensity and 50th and 90th percentile of daily precipitation over a season. The linear trends over the full period of these indices are described and compared. It is shown that although the time series of area average total annual precipitation over north-central Italy does not show significant linear trends, these are present locally. In particular, significant negative trends of annual total precipitation are found in central Italy and in the inner part of northern plains, while significant positive linear trends are present in several areas over the Alps and over the Liguria coast. The seasons most affected by changes in precipitation are summer and autumn, which, in most areas, are the driest and wettest seasons. In summer, significant positive trends in total precipitation have been found in areas close to the northern national borders, while significant negative trends are located elsewhere. The number of wet days is significantly decreasing over most of the domain, but the 90th percentile of precipitation is significantly increasing over most of the Alpine area and northern Po Valley. Over the southern part of the Po Valley and central Italy summer precipitation is significantly becoming less frequent and, generally, less intense. In autumn, total precipitation is characterised by significant positive trends over large areas in Northern Italy and by significant negative trends in inner areas of the Central Apennines. The trend patterns present great similarities with those of the 90th percentile of daily precipitation for the same season. The maximum length of dry spell is significantly decreasing in autumn over most areas, including central Italy, while the number of wet days presents negative but mostly non significant trends over the whole domain.

Impacts of Summer Extreme Precipitation Events on the Hydrothermal Dynamics of the Active Layer in the Tanggula Permafrost Region on the Qinghai‐Tibetan Plateau

AbstractThe characteristics of long‐term variation for extreme precipitation events were analyzed at the Tanggula site in the continuous permafrost regions of the Qinghai‐Tibetan Plateau (QTP). In addition, the impacts of extreme precipitation events in summer on soil thermal‐moisture dynamics were also investigated. The results showed that local extreme precipitation indices fluctuated significantly and that the trend magnitudes of local very wet days (R95p), annual total wet‐day precipitation (PRCPTOT), number of heavy precipitation days (R10mm), maximum length of dry spell (CDD), and simple daily intensity index (SDII) were larger than those of the western QTP, other regions of China, and even the global average. The freeze‐thaw cycling in the local active layer occurred from October to the next September during 2006 to 2014. The influence of extreme precipitation event in summer on local soil hydrothermal conditions could reach soil depths up to 105 cm or so, and these were more pronounced than with light or moderate precipitation events. Soil temperature reacted more promptly to local extreme precipitation events than did soil moisture. The rate at which local soil temperature fell after an extreme precipitation event was greater than the rate of increasing temperature on nonprecipitation days. Moreover, the amount of precipitation received during extreme precipitation events had a greater effect on local soil moisture and temperature than duration time for these events. Consecutive extreme precipitation events with a longer duration time did not necessarily to have a greater effect than a single precipitation event with a shorter duration. Finally, the thawing process of active layer and local water migration modes could also affect the response of soil hydrothermal conditions to an extreme precipitation event to a large extent.

Evolution Des Indices Pluviométriques Extrêmes Par L'analyse De Modèles Climatiques Régionaux Du Programme CORDEX: Les Projections Climatiques Sur Le Sénégal

This study aims at characterizing the extreme rainfall events over West Africa particularly in the Sahel region and Senegal by 2100 (far future) under the greenhouse gas emission scenario RCP8.5 by analyzing the simulations of four (4) regional climate models (RCMs) of CORDEX (Regional COordinated climate Downscaling Experiment) program. The study of these extreme climate indices is crucial for the understanding of the impacts of climate change on some vital socio-economic sectors such as the agriculture in Sahel and Senegal. The results show that almost all the RCMs predict a decrease of the rainfall over most parts of the Sahel region particularly over the Western Sahel. The analysis of the climate indices such as the highest one day precipitation amount, the 99th percentile and the maximum dry spell length (CDD) shows that the RCMs (except CanRCM4) project an increase of these exceptional rainfall events over the Sahel (especially over the Western Sahel) by 2100. In Senegal, the RCMs (except RCA4) agree on a decrease of the precipitation and the number of wet days by 2100. When considering the evolution of rainfall events intensity, the highest one day precipitation amount and the 99th percentile, the RCMs (except CanRCM4) predict an increase of the extreme events which may translate into strong floods in Senegal. As for the dry and wet sequences, the RCMs projections (except those of RCA4) show an increase (respectively a decrease) of the maximum dry spell length (respectively of the maximum wet spell length) in Senegal. This increase in extreme rainfall indices may translate into a strengthening of natural disasters such as floods and drought. This work can be considered as a support for the policymakers in West Africa and particularly in Senegal for the better long-term planning of water resources and disaster management as wells as the build of a resilient agricultural system.

The Spatiotemporal Characteristics of Extreme Precipitation Events in the Western United States

Changes in the frequency or intensity of extreme precipitation events would have profound impacts on both human society and the natural environment. In this paper, we present the results of a comprehensive analysis of the spatiotemporal changes of extreme precipitation in the western United States. The analyses explore the spatial characterization of the El Nino-Southern Oscillation (ENSO)-extreme precipitation response pattern and identify the multi-scale temporal variability in precipitation extremes in the western United States. Results indicate: (1) Extreme precipitation expressed in indices such as seasonal count of days when precipitation is large than 10 mm (R10), seasonal maximum 5-day precipitation (R5D), maximum length of dry spell (CDD), and seasonal total precipitation exceeding 95 percentile (R95) have a dipolar pattern and a transition zone which separates the west into two main dipolar centers regarded as Pacific Northwest and Desert Southwest. The simple precipitation intensity index (SDII) has little correlation with large scale natural oscillations over most of the west. (2) The spatial distributions of annual trend of R10, R5D, SDII, and R95 have seasonal variability in southern California and Lower Colorado River Basin. (3) There are consistent multi-year bands ranging from 2 to 20 years in the R10, R5D, CDD, and R95 winter time series which may be caused by the inter-decadal or multi-decadal modulation of ENSO effects on precipitation extremes. The results can provide beneficial reference to the prediction of precipitation extremes in the west.

Dry spell, onset and cessation of the wet season rainfall in the Upper Baro-Akobo Basin, Ethiopia

In this study, maximum dry spell length and number of dry spell periods of rainy seasons in the upper Baro-Akobo River basin which is a part of the Nile basin, Western Ethiopia, were investigated to analyse the drought trend. Daily rainfall records of the period 1972–2000 from eight rain gauge stations were used in the analysis, and Mann-Kendall test was used to test trends for significance. Furthermore, the beginning and end of the trend development in the dry spell were also tested using the sequential version of Mann-Kendall test. Results have shown that there is neither clear monotonic trend found in dry spell for the basin nor significant fluctuation in the onset, cession and duration of rainfall in the Baro-Akobo river basin. This sufficiently explains why rain-fed agriculture has suffered little in the western part of Ethiopia. The predictable nature of dry spell pattern may have allowed farmers to adjust to rainfall variability in the basin. Unlike many parts of Ethiopia, the Baro-Akobo basin climate variability is not a limiting factor for rain-fed agriculture productivity which may contribute significantly to national food security.

Regional Frequency Analysis of Extreme Dry Spells during Rainy Season in the Wei River Basin, China

Our research analyzes the regional changes of extreme dry spell, represented by the annual maximum dry spell length (noted as AMDSL) during the rainy season in the Wei River Basin (WRB) of China for 1960–2014 using the L-moments method. The mean AMDSL values increase from the west to the east of the WRB, suggesting a high dry risk in the east compared to the west in the WRB. To investigate the regional frequency more reasonably, the WRB is clustered into four homogenous subregions via theK-means method and some subjective adjustments. The goodness-of-fit test shows that the GEV, PE3, and GLO distribution can be accepted as the “best-fit” model for subregions 1 and 4, subregion 2, and subregion 3, respectively. The quantiles of AMDSL under various return levels figure out a similar spatial distribution with mean AMDSL. We also find that the dry risk in subregion 2 and subregion 4 might be higher than that in subregion 1. The relationship between ENSO events and extreme dry spell events in the rainy season with cross wavelet analysis method proves that ENSO events play a critical role in triggering extreme dry events during rainy season in the WRB.

The spatial and temporal analysis of precipitation concentration and dry spell in Qinghai, northwest China

Understanding precipitation variations from various aspects is important for the assessment of drought risk and the utilization of water resources. The precipitation concentration index (PCI) and the concentration index (CI) were used to investigate/quantify the heterogeneity of the monthly and daily rainfall in Qinghai province that is part of northwestern China, respectively. The precipitation concentration in Qinghai shows a significant irregularity of the monthly rainfall distribution and highly homogeneous distribution of the daily rainfall. It is found that PCI and CI show negative trends at most stations. Meanwhile, the spatial and temporal variation of nine dry spell (DS) indices are analyzed. From the spatial perspective, drought in the northwestern area is much severer than that in other areas of Qinghai. According to the results of temporal analysis by using the Mann–Kendall test, the number of very long DSs, maximum length of DS, mean length of DSs, and the total dry days of extreme DS all decrease. All these results verify that the warm dry climatic pattern in Qinghai can be changed into the warm wet climatic pattern.

Rainfall Simulation Using RegCM4 Model in Kalimantan during El Nino Southern Oscillation

The performance of Regional Climate Model 4 (RegCM4) in simulating rainfall is evaluated through a comparison of several observations using Asian Precipitation-Highly Resolved Observational Data Integration towards Evaluation (APHRODITE) and Climate Research Unit (CRU) in 19-year simulation period of 1982-2000 in Kalimantan. The analysis includes the perormance of RegCM4 in capturing the rainfall type, the rainfall characteristics when ENSO, the error and the diversity of data, and dominant cycles in Kalimantan. The analysis is continued with a calculation of Maximum Dry Spell Length (MDSL) and Probability Distribution Function (PDF). We found that RegCM4 produces overestimated value, but it is capable in capturing rainfall type, rainfall characteristics during ENSO, and dominant cycles in Kalimantan.

Spatial and temporal variability of drought during 1960–2012 in Inner Mongolia, north China

In this study, drought in Inner Mongolia was studied by using standardized precipitation index (SPI) and dry spells (DS). Principal component analysis (PCA) was applied to the SPI series computed on 24-month time scale. The results demonstrate noticeable spatial patterns, with six sub-regions characterized by different climatic variability. Overall, most parts of Inner Mongolia are dominated by dry tendencies, except for the western and easternmost areas. Three DS indices, including the number of dry spells (NDS), mean length of dry spells (MDS) and maximum length of dry spells (MxDS), and four periods (spring, summer, autumn and winter), are considered. The results show that a predominant east to west increasing gradient for mean MDS and MxDS has been found in all periods. Mean NDS shows an opposite distribution to that of mean MDS and MxDS. Drought in the western area is more severe than in the eastern area. According to temporal analysis by using the Mann–Kendall trend method, summer is the only season showing strong trends for all the DS indices. During summer, the trends of MDS and MxDS dominantly are positive, while the trends of NDS are dominantly negative. This means that the summer droughts have become increasingly serious in Inner Mongolia.