Extreme dry and wet spells face changes in their duration and timing

Durations of monthly precipitation wet and dry spells are calculated using historical records and regional climate model (RCM) simulations for the Wadi Al-Lith basin in western Saudi Arabia. The characteristics of durations of wet and dry spells are based on the 50% risk level corresponding to the monthly records for average regional precipitation. The duration of wet spells in the model data is compared with observations for the base period 1971–2000. The impact of climate change on the durations of wet and dry spells is obtained using three global climate models projections with RCP4.5 and RCP8.5 scenarios downscaled by RCM. The probability distribution functions (PDFs) of the climate model scenarios and the precipitation records for the base period prove that climate change has a clear impact on the durations of wet and dry spells over the study area. There is an increase in wet spells frequency in the far future (2070–2099) compared to the near future (2020–2049). The increase in wet spells can be partly explained by the increase in extreme rainfall events and by the decrease in dry spells expected to occur over the study area towards the end of 21st century.

Information on dry spell analysis plays an important role in proper utilization of available rainwater resources. In the present study, probability analysis of critical dry and wet spells along with onset and withdrawal of rainy season was estimated for Beed and Jalna districts of Marathwada region of Maharashtra. Results indicated that, the average date of OEM was 20 June and 11 June and its withdrawal was 14 Oct and 22 September were observed in Beed and Jalna respectively. Data on average number of first, second and third critical dry spell (CDS) were also estimated and is indicated that a greater number of CDS i.e. (04) were observed in Jalna. Similarly, data on wet spells indicated that, Jalna accounts 108 wet spells and 94 wet spells were observed in Beed district. Results on Fortnightly dry spell probability analysis showed that, Mean duration of critical dry spell for Beed and Jalna district was observed as 18.93 was highest during second fortnight and 13.96 days was highest during seventh fortnight. These findings are helpful to study area for understanding the events of occurrence of dry spell and wet spell for effective agricultural planning and to decrease the adverse effects of dry spell at sensitive crop development stages, for water resource management.

A K-nearest neighbour weather-generating model is applied to simulate: 1) total precipitation during extreme precipitation events; 2) duration of extreme wet spells; 3) duration of extreme dry spells in the Satluj River basin - a key basin in the central Himalayas under climate change scenarios projected by 15 different combinations of global climate models (GCMs) and emission scenarios. The intent is to assess the vulnerability of the basin to extreme hydrological events, including floods and droughts, resulting from extreme precipitation events. The driving data set for the K-NN model was obtained by applying the precipitation change fields obtained from different combinations of the GCM and emission scenarios to the observed data. Results indicate that several extreme wet and dry spells that were more severe than the observed were simulated. Results of frequency analysis of storm depths indicated that ECHAM5 model under A2 scenario produced the highest one-day precipitation maxima for each return period considered.

This study aimed to analyze the probability of the occurrence of dry/wet spell rainfall using the Markov chain model in the Upper Awash River Basin, Ethiopia. The rainfall analysis was conducted in the short rainy (Belg) and long rainy (Kiremt) seasons on a dekadal (10–day) scale over a 30-year period. In the Belg season, continuous, three-dekad dry spells were prevalent at all stations. Persistent dry spells might result in meteorological, hydrological, and socio-economic drought (in that order) and merge with the Kiremt season. The consecutive wet dekads of the Kiremt season indicate a higher probability of wet dekads at all stations, except Metehara. This station experienced a short duration (dekads 20–23) of wet spells, in which precipitation is more than 50% likely. Nevertheless, surplus rainwater may be recorded at Debrezeit and Wonji only in the Kiremt season because of a higher probability of wet spells in most dekads (dekads 19–24). At these stations, rainfall can be harvested for better water management practices to supply irrigation during the dry season, to conserve moisture, and to reduce erosion. This reduces the vulnerability of the farmers around the river basin, particularly in areas where dry spell dekads are dominant.

Hydroclimate variability results in sequencing between wetter and drier periods at both day-to-day and longer timeframes. Variability at the day-to-day scale can result in sudden water surpluses or deficiencies resulting in extreme events such as floods and flash droughts. Longer-term variability, however, can significantly influence water security through the impact of droughts and reduced streamflow. Variability at both timescales poses significant challenges to water resources management, with follow-on impacts on local ecosystems and communities. In this study we investigate changes in day-to-day hydroclimate variability, focussing on the intermittency patterns of rainfall (wet and dry spells).Our investigation, at the catchment scale, uses rainfall for 467 Hydrological Reference Stations (HRS) catchments from 1950-2022 across the Australian continent. We look at long-term trends in rainfall frequency, duration, and intensity characteristics at annual and seasonal timescales and break down our analysis by similar climatic regions. We find a clear trend towards more dry days per year across most catchments in Australia. Interestingly, there are no consistent trends in annual rainfall totals or annual mean dry spell length, despite the increase in the dry days per year. There are however consistent declining trends in annual mean and maximum wet spell lengths with shorter spells over ~80% and ~50% of catchments respectively, with the majority being in southern and eastern Australia. Northern Australia sees the opposite of this drying trend with fewer dry days per year and more intense rainfall during wet spells. Depending on the season, some regions are experiencing an increase in the number of wet spells, potentially suggesting there are changes to the dominant weather systems delivering rainfall to the region.The presence of trends towards shorter wet spells and an increase in their frequency aligns with the change towards more episodic rainfall and highlights the need to further investigate both wet and dry spells concurrently. We conclude that wet and dry spell characteristics are changing and will continue to do so under the influence of climate change and need to be considered to manage water security across Australia.

Four methods of downscaling daily rainfall sequences from general circulation model (GCM) simulations are intercompared over Senegal, using a 13-station network of daily observations during July–September 1961–98. The local scaling method calibrates raw GCM daily rainfall at the closest grid point to a given station so that the climatological distribution of rainfall matches the observed one. The k-nearest neighbor and weather classification schemes resample historical station rainfall observations according to the similarity between the daily wind fields from an ensemble of GCM simulations and a historical library of reanalysis [from 40-yr ECMWF Re-Analysis (ERA-40)] daily wind fields. The nonhomogenous hidden Markov model uses a small set of hidden states to describe the relationship between daily station rainfall observations and low-pass-filtered simulated winds to simulate stochastic sequences of daily rainfall. The four methods are assessed in terms of seasonal statistics of daily rainfall, including seasonal amount, rainfall frequency, and the mean length of wet and dry spells. Verification measures used are mean bias error, interannual anomaly correlation, root-mean-square error, and ranked probability skill score. The k-nearest neighbor and weather-type classification are shown to perform similarly well in reproducing the mean seasonal cycle, interannual variability of seasonal amount, daily rainfall frequency, as well as the mean length of dry and wet spells, and generally slightly better than the nonhomogeneous hidden Markov model. All three methods are shown to outperform the simple local scaling method. This is due to (i) the ability of the GCM to reproduce remarkably well the mean seasonal cycle and the transitions between weather types defined from reanalysis and (ii) the GCM’s moderate-to-strong skill in reproducing the interannual variability of the frequency occurrence of the weather types that strongly influence the interannual variability of rainfall in Senegal. In contrast, the local scaling exaggerates the length of wet and dry spells and reproduces less accurately the interannual variability of the seasonal-averaged amounts, occurrences, and dry/wet spells. This failure is attributed primarily to systematic errors in the GCM’s precipitation simulation.

The Indian Summer Monsoon (June–September, JJAS) plays a critical role in regulating water resources, agriculture, and hydroclimatic extremes across India, yet projecting future changes in monsoon variability remains challenging due to the coarse spatial resolution and biases of earth system models (ESMs). In this study, we develop high-resolution (0.25°) projections of monsoon rainfall over India using a statistical downscaling framework that combines weather typing with transfer functions, and we demonstrate how Standardized Precipitation Index (SPI) projections can be used to diagnose future changes in monsoon characteristics. Downscaled simulations from five GCMs are analyzed for a historical period and for two future socioeconomic pathways (SSP2-4.5 and SSP5-8.5). SPI is computed at monthly scale for June, July, August, and September, as well as for the seasonal JJAS total, enabling assessment of both intra-seasonal and seasonal hydroclimatic variability. Evaluation against observations shows that the historical simulations reproduce observed rainfall statistics with high fidelity, capturing both the mean and standard deviation across most regions of India. Furthermore, the downscaled GCMs successfully represent historical extremes, with more than 70% of grid cells capturing observed extreme drought events and over 80% capturing extreme wet events, providing confidence in the robustness of the derived SPI projections. Our next objective is to test the hypothesis that SPI contains discernible signals of key monsoon characteristics, including onset, withdrawal, and intraseasonal variability. If such signals are evident, SPI can serve as a useful diagnostic tool for inferring these features, which are otherwise difficult to predict directly. This framework further enables a range of analyses, including assessment of future projections and evaluation of shifts in the frequency, duration, and intensity of dry and wet spells during the monsoon season under both moderate and high-emission scenarios, thereby revealing changes in intraseasonal variability that may not be captured by seasonal mean rainfall alone.

Anomalous conditions in the tropical oceans, such as those related to El Niño–Southern Oscillation and the Indian Ocean dipole, have been previously blamed for extended droughts and wet periods in Australia. Yet the extent to which Australian wet and dry spells can be driven by internal atmospheric variability remains unclear. Natural variability experiments are examined to determine whether prolonged extreme wet and dry periods can arise from internal atmospheric and land variability alone. Results reveal that this is indeed the case; however, these dry and wet events are found to be less severe than in simulations incorporating coupled oceanic variability. Overall, ocean feedback processes increase the magnitude of Australian rainfall variability by about 30% and give rise to more spatially coherent rainfall impacts. Over mainland Australia, ocean interactions lead to more frequent extreme events, particularly during the rainy season. Over Tasmania, in contrast, ocean–atmosphere coupling increases mean rainfall throughout the year. While ocean variability makes Australian rainfall anomalies more severe, droughts and wet spells of duration longer than three years are equally likely to occur in both atmospheric- and ocean-driven simulations. Moreover, they are essentially indistinguishable from what one expects from a Gaussian white noise distribution. Internal atmosphere–land-driven megadroughts and megapluvials that last as long as ocean-driven events are also identified in the simulations. This suggests that oceanic variability may be less important than previously assumed for the long-term persistence of Australian rainfall anomalies. This poses a challenge to accurate prediction of long-term dry and wet spells for Australia.

Precipitation durations and intensities over the period 1950–2008 are analysed using daily rain gauge data from the Deutsche Wetterdienst raingauge network—one of the densest and most properly maintained precipitation observational networks in Europe. Truncated geometric distribution of the family of discrete distributions was applied for quantifying probability distribution of the durations of wet spells. Further intensities of wet spells of different durations were analysed along with wet spell lengths. During the cold season (October–March) wet periods over the whole of Germany demonstrate a robust pattern of lengthening by about 2–3% for the mean durations of wet spells and up to 6% for extremely long wet periods. This tendency is clearly associated with growing (up to 10% per decade in Eastern Germany) intensity of precipitation during long wet periods (more than 5 days) and the weakening of precipitation events associated with short and moderately long wet periods with both signals being statistically significant. Trends are superimposed with interdecadal variability, which is the strongest in Northern and Central Germany. In the warm season (April–September) there is no robust pan-German trend pattern in the wet spell durations and associated precipitation intensities. Strong structural changes in winter precipitation over Germany potentially imply growing rates of winter ground water recharge over Germany and increasing probability of winter flash and river flooding.

Climate variability modulates spatio-temporal variability of dry spells (DSs) and wet spells (WSs) within a river basin and will affect water resources management practices leading to various impacts on the socio-economic development in river basins. In this study, we evaluated spatio-temporal variability of DS and WS in Huai River basin (HRB), China, by developing copula-based severity-duration-frequency (SDF) curves. The result shows that the upper reach and the southern part of middle reach of HRB are prone to both DS and WS; however, the duration and severity of WS are comparatively higher in comparison to DS. It was observed that DS is more frequent in spring and summer, whereas WS in summer and autumn. The choice of copula plays an important role in deriving the SDF curves, and an inappropriately chosen copula function may result in a large bias of SDF estimation. The arch12 copula was found to be the best choice in the majority of stations for deriving the SDF curves. The constructed SDF curves primarily shows two major patterns for DS and WS, i.e. concave down pattern and convex up pattern. The frequency of extreme DS decreases from 1960s to 1990s, and increases after 2000s, while the frequency of extreme WS increases from 1970s to 1990s and then decreases from 1990s to 2000s. The results in this study can provide useful information for designing conservation structures and to develop water allocation strategies at different temporal scales.

Extreme rainfall events in India, causing floods and droughts, damage lives and livelihoods and thereby significantly impact agriculture production, natural and constructed landscapes, water resources, and the economy. This part of the world is also a global hotspot for air pollution due to the increase of anthropogenic aerosols since the late 20th century. Aerosols influence the radiation budget and cloud microphysical and dynamical processes, thus influencing monsoon rainfall patterns and trends. However, temporal modulations in monsoon rainfall over the Indian subcontinent, characterized by wet and dry spells, are yet to be understood in the context of the role of enhanced anthropogenic aerosol emissions. To address this gap, in this study, we examine the link between increased aerosol levels and dry and wet spell characteristics of the Indian summer monsoon of the recent era (2001-2025), using observations and model simulations (ECHAM-HAM), made with a regionally representative Indian emission inventory.We find aerosol-induced drying of both wet and dry rainfall extremes, in the recent period, over the Indian core monsoon region, using Indian Meteorological Department (IMD)’s rainfall and satellite-derived Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) datasets. In the recent era, aerosol enhancements correlate with increasing dry spells but decreasing wet spells, as well as, decreasing rainfall intensity in both wet and dry spells. Model simulations reveal aerosol-induced stabilization and reduction in convective potential energy, inhibiting upward moisture transport. There is also a cloud microphysical effect, reducing cloud drop size and inhibiting rainout. This study illustrates how high aerosol pollution levels over India can lead to rainfall deficits, affecting the region's water supplies and exacerbating climate risks.

This study uses daily precipitation records from 517 Russian stations (1966–2010) to examine the relationships between continuous dry and wet day duration and surface air temperature for all four seasons. The study found that both mean and extreme durations of dry periods increase with air temperature at about 7.0% (0.24 day/°C) and 7.7% (0.86 day/°C) respectively, while those of wet periods decrease at about 1.3% (−0.02 day/°C) and 2.2% (−0.10 day/°C) respectively averaged over the entire study region during summer. An increase in the duration of dry periods with higher air temperature is also found in other seasons at locations with a mean seasonal air temperature of about −5 °C or higher. Opposite relationships of shorter durations of dry periods and longer wet periods associated with higher air temperature are observed over the northern part of the study region in winter. The changes in durations of both dry and wet periods have significant correlations with the changes in total dry and wet days but are about 2.5 times higher for dry periods and 0.5 times lower for wet periods. The study also found that locations with longer durations of dry periods experience faster rates of increase in air temperature, suggesting the likelihood of exacerbating drought severity in drier and/or warmer locations for all seasons.

<p>Short drought-intermittent rainfall (SDIR) events, i.e., short rainfall events after long dry spells, typically re-wet top few centimeters of soil layer and often has little impact on the water balance of the ecosystem. Nevertheless, these SDIR events could provide the much-needed short-term water supply during dry spells to the terrestrial ecosystem, especially trees. An efficient use of these SDIR events could provide the trees with a buffer to withstand longer drought conditions, which will become more frequent and intense with the upcoming changes in climate.</p><p>This study aims to quantify the tree water use (TWU) recovery in terms of sapflow recovery following SDIR events across multiple global forest sites (35 sites) spanning over 250 site-years. SDIR events are identified probabilistically as rainfall periods (1-2 days with daily rainfall < 75<sup>th</sup> percentile) occurring after an extreme dry spell (> 90<sup>th</sup> percentile of dry spell duration) during the growing season. For each tree, TWU recovery (R<sub>TWU</sub>) is estimated based on percentage increase in sapflow rate after the SDIR event (S<sub>a</sub>), compared to before the SDIR event (S<sub>b</sub>), and standardized by seasonal maximum sapflow (S<sub>max</sub>). The inter-species R<sub>TWU</sub> and intra-species R<sub>TWU</sub> relationship with tree allometry (height and diameter) is used to explain the recovery rates. The main hypothesis tested here is that the intra-species differences in R<sub>TWU</sub> are positively related to tree size due to better root development in larger trees. The understanding of R<sub>TWU</sub> provides a new axis to understand and predict tree recovery after drought events.</p>

ABSTRACTSummer rainfall in north‐central China, accounted for 70% of the annual rainfall, is sensitive to anomalies in the East Asian summer monsoon (EASM) and westerlies due to lying in the EASM marginal belt. Summer rainfall and the durations and frequency of dry spells were investigated using daily rainfall data from 332 weather stations, the European Centre for Medium‐range Weather Forecasting (ECMWF) re‐analysis data and Climate Research Unit (CRU) surface temperature data. The results demonstrate that summer rainfall exhibits an ‘early wetting later drying’ pattern with a weak increasing in June and a dramatic decreasing trend in July and August (JA). Decreased rainfall in JA is associated with prolonged dry spells; the frequency and durations of dry spells exceeding 7 days increase, especially for dry spells exceeding 15 days. This increase in dry spell duration is positively correlated with a northward shift in planetary waves expressed by the 5700‐gpm isoline at 500 hPa and the westerly jet at 200 hPa, which lead north‐central China to close to the left of jet entrance and a positive vorticity convergence region on the high level, it is helpful to downward movements and less rainfall. The northward shift in planetary waves is affected by boundary forcing. Dramatic increases in temperature over the Tibetan Plateau (TP) result in a large temperature gradient and thermal contrast between the TP and mid‐high latitude, and likely strengthening and widening the South Asian High (SAH) pattern and pressure gradient. These conditions contribute to the northward shift in planetary waves and prolonging dry spells.

<p>Global warming is expected to enhance El Niño Southern Oscillation (ENSO), with potential impacts on frequency and severity of floods and droughts in numerous countries of the Asia-Pacific region. However, the limited time coverage of historical records and the large uncertainties underlying climate model projections impair our ability to identify trends in extreme rainfall and dry spells. Here, we generate and analyze a long-term stochastic precipitation dataset for New Zealand that accounts for the potential effects of climate change. For this purpose, we draw on a 60 year-dataset of daily precipitation maps to identify the rainfall principal components and quantify their temporal correlations with the ENSO signal. We then generate a long-term stochastic set of daily rainfall maps correlated with ENSO projections, corresponding to different climate change scenarios. Our results indicate that climate change may lead to more intense precipitation in the Southern Alps during positive ENSO phases. Conversely, extreme precipitation is likely to increase in the North Island during negative ENSO phases. Our analyses also suggest that the duration of extreme dry spells may significantly increase along the east side of the North and South Islands during positive ENSO phases. These results may guide the implementation of effective adaptation and mitigation strategies against the increasing risk of natural catastrophes.</p>