Soil moisture strongly regulates land-atmosphere interactions, yet its influence on rainfall over the Maritime Continent remains uncertain. Using a coupled land-atmosphere regional model, we compare control simulations (CTL) initialized with realistic soil moisture against sensitivity experiments (SENS) initialized with dry soil conditions for two dry (May 2013, 2023) and two wet (December 2014, 2023) seasons. The results reveal a pronounced seasonal asymmetry in the role of soil moisture on precipitation over the islands of the Maritime Continent. In dry seasons, reduced soil moisture in the SENS experiment suppresses rainfall by reducing transpiration and direct soil evaporation relative to CTL. This leads to a sharp reduction in surface latent heat flux and weaker afternoon convection. In contrast, wet-season rainfall increases in SENS due to increased moisture advection from surrounding ocean despite reduced terrestrial evaporation. Analysis of the diurnal cycle shows a pronounced suppression of the afternoon precipitation peak in the dry seasons in SENS, whereas in the wet seasons, the diurnal peak is weakened and flattened, but nocturnal rainfall is enhanced. Evaporation partitioning helps explain this seasonal contrast: in the dry seasons, transpiration is reduced under SENS, while in the wet seasons, canopy evaporation persists due to frequent rainfall that sustains canopy wetness. These findings highlight the important role of land-atmosphere coupling in the dry seasons and greater oceanic control in the wet seasons, and call for better observation of these processes to improve rainfall predictions over tropical islands.

Northwestern South Asia, encompassing the historically semiarid regions of Pakistan and northwest India, has seen increased persistent heavy rainfall and catastrophic flooding in recent decades. While most studies emphasize seasonal mean changes, the role of subseasonal dynamics remains unclear. Here, we present observational evidence that the northward-propagating monsoon intraseasonal oscillation (ISO) has strengthened and penetrated farther inland, with its convective anomalies amplifying rainfall extremes. Simultaneously, the southeastward-propagating mid-latitude ISO along the westerly jet has slowed, prolonging anomalous circulations that sustain rainfall episodes. Together, these ISOs account for ~44% of the observed increase in flood frequency, a contribution comparable to that from mean-state changes (~40%). CMIP6 projections suggest that these ISO-driven processes will further intensify flood risks, posing escalating threats to this climate-sensitive region under continued global warming. Our findings reveal a fundamental yet overlooked mechanism linking subseasonal variability to emerging hydroclimatic extremes in a warmer world.

Compounding effects from global warming and urban expansion modulate local atmospheric circulations, exacerbating heat stress and increasing cooling energy demand, especially in large cities. Using a sophisticated urban-modeling framework, we investigate summertime local circulations in the greater Houston, Texas metropolitan area under present and future climate states. We show that by 2100, city-wide cooling energy demand will nearly double due to elevated near-surface temperatures, increased humidity, and weakened landsea breeze. Results indicate that urban expansion and projected warming collectively weaken sea-breeze intensity by approximately 15-20%, reduce inland penetration by similar to 20-25 km, and lower the frequency of composite land-sea-breeze days by 10-15% during summer months. These changes increase near-surface temperature by up to 3.9 degrees C, elevate heat index by 6-7 degrees C, and nearly double citywide cooling energy demand across the Greater Houston Area. This heightened vulnerability to heat stress is most severe in urban coastal regions, where diminished coastal winds fail to alleviate urban heat island (UHI) effects but sufficiently strong to increase near-surface humidity. These results highlight the pressing need for immediate and sustainable strategies, such as urban greening, high reflective surfaces, and ventilation corridors, to mitigate the escalating impacts of heat stress and rising energy demand, particularly in vulnerable coastal cities worldwide.

Soil moisture (SM) is a key regulator of ecosystem biogeophysics, influencing plant water relations and land-atmosphere energy exchanges. We evaluate the representation of SM in 16 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) using the International Land Model Benchmarking (ILAMB) framework, focusing on surface (0-5, 0-10 cm) and rootzone (0-100 cm) depths, as well as key ecohydrological variables like gross primary productivity (GPP), leaf area index (LAI), and evapotranspiration (ET), and their coupling. Models are benchmarked against multiple observational and assimilated datasets to assess both state variables and cross-variable relationships. Surface SM is generally well represented (r > 0.87), while rootzone SM variability is systematically overestimated (normalized standard deviation > 1). ET shows strong agreement with observations (r > 0.9), whereas GPP and LAI exhibit larger inter-model spread. Skill in individual variables does not guarantee realistic SM-ecohydrology coupling, which varies strongly across models and depends on the reference dataset. K & ouml;ppen-based regional analyses reveal strong regime dependence, with several models performing well in Tropical and Temperate regions but degrading in Continental (high-latitude) zones. Across both global and regional benchmarks, models cluster by land surface framework, indicating that structural choices in soil hydrology and soil-plant coupling exert a first-order control on performance. These results provide process-relevant benchmarks and suggest that improving the representation of vertical soil structure, rooting depth distributions, and soil-plant hydraulic coupling will be central to advancing soil moisture realism in next-generation Earth system models.

ABSTRACT In this study, probabilities of tropical cyclogenesis in the Bay of Bengal (BoB) were analyzed across the full two‐dimensional phase space of the real‐time multivariate Madden–Julian oscillation (MJO) (RMM) index for pre‐ and post‐monsoon periods from 1990 to 2025. Results show that cyclogenesis anomalies span the phase space and depend largely on the sign of the first principal component of the index, RMM1. Moreover, on days when the intraseasonal index is in phases previously found favorable for cyclogenesis, the anomalies are statistically significant for only a limited range of amplitudes in those phases. Skill scores were calculated for vertical velocity (VV), relative humidity (RH), sea level pressure (SLP), vertical wind shear (VWS), and sea surface temperature (SST) to quantify how well each parameter identifies cyclogenesis in the intraseasonal phase space. Among these variables, 700‐hPa VV was most skillful at identifying both pre‐ and post‐monsoon cyclogenesis anomalies, outperforming RH, SLP, VWS, and SST, although all had high false alarm ratios. The 700‐hPa VV was also more skillful than the 500‐hPa VV, suggesting that it should be included in intraseasonal genesis indices. In the post‐monsoon period, SST showed little to no skill at identifying intraseasonal cyclogenesis anomalies, in agreement with recent work suggesting it be considered alongside other modes of variability. The results of this study fill a critical gap in our understanding of the MJO–tropical cyclone relationship in the BoB by establishing basin‐specific probabilities of cyclogenesis across multiple MJO states and identifying drivers of the variability.

Abstract The evolution of moist static energy (MSE) is widely used to understand the organization and propagation of the Madden‐Julian Oscillation (MJO). Past studies, largely based on reanalysis or short‐term observations, have highlighted humidity as the dominant driver of MJO evolution. Using 14 years of bias‐corrected radiosonde observations from the Department of Energy—Atmospheric Radiation Measurement Facility site at Manus in the western Pacific, we show that temperature has a non‐negligible influence on the vertically integrated MSE during MJO's transition from suppressed to active phase. Specifically, during the transition phase in boreal winter (spring), ∼48% (∼31%) of the vertically integrated MSE anomalies are attributed to temperature anomalies. This temperature contribution is confined to the mid‐ and upper‐troposphere, where temperature and MSE anomalies exhibit a strong correlation. These findings have important implications for MJO theory and provide new constraints for evaluating MJO transition processes in models.

This study aims to quantify and regionalize future changes in daily minimum (Tmin), maximum (Tmax), and the diurnal temperature range (DTR = Tmax − Tmin) across South America for 2015–2100, addressing the current lack of dedicated sub-regional assessments of DTR projections using Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Model skill was assessed against the Climatic Research Unit (CRU) Time-Series (TS) dataset, and the five best-performing members were used to build sub-regional ensembles for ten predefined domains to improve local signal detection. Trend analysis shows a continent-wide tendency toward DTR compression driven by stronger nighttime warming: median DTR trends are − 7.6 × 10⁻³ °C year⁻¹ (SSP2-4.5; Shared Socioeconomic Pathways) and − 1.28 × 10⁻² °C year⁻¹ (SSP5-8.5), with mean reductions between 2015 and 2025 and 2090–2100 of ≈ − 0.71 °C (SSP2-4.5) and ≈ − 1.04 °C (SSP5-8.5). The spatial pattern is heterogeneous: most domains exhibit the largest declines, while parts of the eastern coast show near-neutral DTR under the low-emission pathway and a clear tendency to increase under the high-emission pathway. Trend significance was evaluated using a modified Mann–Kendall test (α = 0.05) and Theil–Sen slope estimates; 5 of 10 sub-regions display statistically significant DTR trends under SSP2-4.5, increasing to 8 of 10 under SSP5-8.5, indicating stronger and more widespread signals under higher forcing. Crucially, regionalizing ensembles uncovers coastal signatures masked in continental means, offering a novel contribution to CMIP6-based assessments of DTR in South America. Given model limitations, targeted attribution studies and investments in high-resolution observational networks and regional climate modeling are recommended. Despite these uncertainties, the results provide valuable guidance for adaptation planning in health, agriculture, and energy sectors across South America. This visual summary presents a study that quantifies projected changes in Tmin, Tmax, and the DTR across South America through 2100, using subregional ensembles of CMIP6 models composed of the five highest-skill members in each domain. It conveys the workflow and main results through integrated visual components: the top-left panel maps South America into 10 subregions; the central-top panel displays the multimodel CMIP6 catalogue; the top-right panel shows Taylor diagrams and historical series used to select the top five models per subregion; the central flow outlines spatial aggregation, skill evaluation, ensemble construction, trend estimation with the Theil–Sen estimator, and significance testing via a modified Mann–Kendall test; the bottom-right contains time-series panels of Tmin and Tmax under scenarios; and the bottom maps present projected DTR anomalies (SSP2-4.5, SSP5-8.5) while the bottom-left summarizes DTR by subregion, highlighting spatial heterogeneity. Projections indicate continent-wide DTR compression, with median trends of -7.6 × 10⁻³ °C year⁻¹ (SSP2-4.5) and − 1.28 × 10⁻² °C year⁻¹ (SSP5-8.5), and mean reductions from 2015 to 2025 to 2090–2100 of ≈ − 0.71 °C and ≈ − 1.04 °C. The decline reflects warming of both Tmax and Tmin, with a stronger rise in Tmin. This asymmetric warming may be related to enhanced longwave radiation, higher humidity, cloud-cover changes, or land-use alterations. Most domains show robust, significant DTR declines, while parts of the eastern coast exhibit neutral or positive trends in some seasons and scenarios — patterns revealed only by the subregional ensemble approach. These shifts imply hotter nights, reduced thermal comfort, greater stress on health and energy systems, altered phenology, and uneven agricultural impacts between interior and coastal regions, underscoring the need for locally targeted adaptation and high-resolution attribution studies. Continent-wide DTR compression driven by stronger nighttime warming (median trends − 7.6 × 10⁻³ °C year⁻¹ SSP2-4.5; -1.28 × 10⁻² °C year⁻¹ SSP5-8.5). Mean DTR reductions between 2015 and 2025 and 2090–2100: ≈−0.71 °C (SSP2-4.5) and ≈ − 1.04 °C (SSP5-8.5). Coast–interior contrasts: interior domains show largest DTR declines; segments of the eastern coast show neutral or positive trends. Regionalized, skill-based CMIP6 ensembles (five best models per subregion) reveal coastal signals masked by continental means. Negative DTR trends are stronger and more often statistically significant under SSP5-8.5; seasonality amplifies regional contrasts.

This study presents a 21-year climatology (1998–2018) of Easterly Wave Disturbances (EWDs) over the Tropical South Atlantic (TSA). The identification of these systems was performed subjectively using infrared satellite images and fields of relative vorticity and streamlines at 1000, 850, 700, 500, and 200 hPa levels from the ERA-Interim (ERAI) reanalysis. Additionally, the TracKH automatic tracking algorithm was applied, successfully capturing approximately 66% of the subjectively identified events. A total of 518 EWDs were recorded during the study period, with 97% reaching the Northeast Brazil (NEB) region, and 64% exhibiting convective characteristics. The highest frequency of events was observed between April and August, with an average of approximately 25 EWDs per year. The primary genesis areas were located between 20°S–5°N and 35°W–15°W. The trajectories and dissipation predominantly occurred along the NEB's eastern coastline, particularly between Alagoas and Rio Grande do Norte. Dissipation generally occurred rapidly after the systems moved inland. Several atmospheric systems were identified as key contributors to EWD genesis, including the Intertropical Convergence Zone (ITCZ), Upper-Tropospheric Cyclonic Vortices (UTCV), cold fronts, and convective clusters originating from the west coast of Africa. These factors played a significant role in the intensification and organization of the disturbances. During the wet season, the synoptic patterns associated with EWDs revealed anomalous cyclonic and confluent circulations, along with convergence and negative vorticity from low levels up to 200 hPa, where only a trough feature was observed. Negative anomalies of vertical motion and temperature, coupled with increased relative humidity, were also identified, fostering favorable conditions for enhanced convection and precipitation associated with the disturbances.

The diurnal cycle of convection in the Maritime Continent (MC) has been hypothesized to act as a barrier to the eastward propagation of the Madden-Julian oscillation (MJO). To test this hypothesis, we use a regional model with realistic MJO to simulate an event from the boreal spring of 2013 that weakened and stalled over the MC. Two simulations are conducted: one that includes the diurnal cycle of insolation (CTL), and another without it (NO_DC). The MJO in the simulations was identified and tracked using a large-scale precipitation tracking method that distinguishes propagation and non-propagation unlike the usual Real-time Multivariate MJO method. In the NO_DC simulation, the absence of diurnal heating reduces land precipitation, allowing more continuous eastward MJO propagation. An analysis of moist static energy budget reveals that MJO maintenance in NO_DC is due to increased longwave heating and reduced advection, whereas the persistent MJO propagation in NO_DC is due to increased advection and reduced longwave heating and surface latent heat flux. These processes, however, may vary across different parts of the MC, emphasizing the complexity of MJO propagation across the MC.

ABSTRACT Skillful prediction of the Mid‐Summer Drought (MSD) is important for various socioeconomic sectors in southern Mexico, Central America and the Caribbean. However, operational forecasting errors of the MSD have rarely been evaluated systematically. In this study, we address this research gap by examining operational forecasts of the MSD derived from the North American Multimodel Ensemble (NMME; 1991–2020). We assess these forecasts before and after applying a Model Output Statistics (MOS) scheme based on Canonical Correlation Analysis (CCA). Before applying MOS, only a couple of forecasts exhibited a bimodal signal between July and September, but none of them reproduced the particular signals of the MSD; they generally suffered from two main errors: excessively weak precipitation during the June–September season (particularly in June) and a weak peak in July instead of a relative minimum. While the root cause of these errors can be associated with warm sea surface temperature (SST) bias in the tropical eastern Pacific and cold SST bias in the Gulf of Mexico, Caribbean Sea and northwestern tropical Atlantic, their immediate cause is an erroneous evolution of the eastern Pacific Intertropical Convergence Zone (ITCZ). During June and September, the eastern Pacific ITCZ remains too far south near the equator, while in July and August it expands and intensifies but stays too close to the coasts of southern Mexico and Central America, failing to migrate westward. After applying MOS, the forecasts showed high skill scores during the onset of the MSD (July and August) but not in the months before and after (June and September). As revealed by the CCA analysis, this improved skill is due to the MOS‐corrected forecasts' improved representation of a key relationship: drier MSD episodes are associated with a stronger westward SST gradient between the eastern tropical Pacific Ocean and the Caribbean Sea. Models that adequately capture this relationship exhibit reduced uncertainty in forecasting MSD intensity. This finding can provide a valuable pathway to mitigate uncertainties in projecting future changes in MSD intensity under different climate change scenarios.

The simultaneous occurrence of heatwaves and droughts is becoming more frequent and intense under climate change, particularly affecting vulnerable regions like Northeast Brazil (NEB). This study presents a comprehensive assessment of these compound extremes using long-term in situ observations and ERA5 reanalysis. Heatwaves were defined by daily temperatures exceeding the 90th percentile, and droughts by the standardised precipitation index (SPI-1). Results reveal substantial spatio-temporal variability in these events, with sharp increases in frequency, duration, and intensity since the early 1990s-especially in 1998, 2006 and 2015, linked to La Ni & ntilde;a and El Ni & ntilde;o events. Atmospheric analyses showed positive temperature anomalies at 2 m, persistent negative specific humidity at multiple pressure levels, and contrasting circulation anomalies: positive flow at 850 hPa, negative at 500 hPa, and changes in divergence and vorticity. The semiarid region of the northeast was the most affected by drought, while the northeastern coast had higher frequencies of heatwaves, with longer durations. These findings highlight the complex interactions driving compound extremes in NEB and underscore the urgent need for regional adaptation and mitigation strategies.

Understanding and forecasting the spatial and temporal distributions of extreme precipitation over urban areas is crucial for effective planning and mitigation efforts. However, this task remains challenging as accurate forecasting depends on properly representing urban surfacees and their interactions with the planetary boundary layer (PBL). We examined the hindcast of an extreme precipitation event over Beijing on 21-22 July 2012. The primary focus was assessing its sensitivity to two widely used PBL parameterizations (MYJ and YSU), two urban parameterizations (SLUCM and BEP_BEM), and two different land-use and land-cover (LULC) datasets. Sensitivity experiments were initialized at different times to explore the model dependence on initial conditions. The analyses were conducted over three selected regions: the entire model domain covering the Beijing metropolitan area, an upwind region of Beijing, and the entire urban area of Beijing. The results show that the MYJ PBL scheme performs better than the YSU PBL scheme in capturing near-surface air temperature as well as the location and timing of the heaviest precipitation. The variability in simulated precipitation among the chosen PBL schemes is lower compared to that among different time of initializations. The LULC impacted the spatial distribution of precipitation but its effect on the amount of precipitation was minimal. Overall, using a combination of the MYJ PBL scheme, SLUCM urban parameterization, and locally-enhanced Beijing LULC, and initializing the model simulations at 0000 UTC July 20, 2012, demonstrated superior performance in capturing precipitation levels, despite some spatial discrepancies in the precipitation distribution. The performance of BEP_BEM urban parameterization is similar to SLUCM across various factors such as average rain rate, maximum rain rate, and rain volume. These findings offer valuable insights towards better simulations of extreme precipitation and flooding in rapidly urbanizing areas such as Beijing.

Abstract Precipitation can induce a surface sensible heat flux since the raindrops are generally cooler than the surface. This precipitation‐induced sensible heat flux (QP) is typically ignored in models. However, during heavy rainfall, QP can be large and may not be negligible such as over India during the summer monsoon season. We provide the first results of incorporating QP in a simulation that shows ∼2% (∼5%) reduction in precipitation over India compared to the simulation without QP during a monsoonal active phase in 2017 (2018). This reduction was primarily due to a reduction in vertical advection of moisture. Additionally, QP modified the spatial distribution of precipitation with 40% of the geographical area encountering alterations of at least 20% in precipitation. This change in precipitation distribution across the region can have important implications for regional agriculture and irrigation practices. Changes in the partitioning of surface heat flux components due to QP is also discussed.

The surface sensible heat flux induced by precipitation (QP) is a consequence of the temperature difference between the surface and the rain droplets. Despite its seemingly negligible nature, QP is frequently omitted from both meteorological and climatological models. Nevertheless, it is important to acknowledge the numerous occasions in which the instantaneous values of QP can be significant, particularly during extreme precipitation events. This study undertakes a comprehensive assessment of QP across the contiguous United States (CONUS) utilizing high-resolution reanalysis, observational data, and numerical modeling to examine the influence of QP on precipitation and the surface energy budget. The findings indicate that the spatial distribution of QP climatology is analogous to that of precipitation, with magnitudes ranging from 2 to 3 W m-2 predominantly over the Midwest and Southeast regions. A seasonal analysis of QP reveals that the highest values occurring during the June-August (JJA) period, averaging 3.18 W m-2. Peak QP values of approximately 4 W m-2 are observed during JJA over the Great Plains region. We hypothesize that the QP during an extreme precipitation event would be nonnegligible and have a significant impact on the local weather. To test this conjecture, we perform high-resolution simulations with and without QP during an extreme precipitation event over the Chicago Metropolitan Area (CMA). The results show that the QP may be a dominant factor compared to other components of surface heat flux during the zenith of precipitation hours. Also, QP has the potential to not only diminish precipitation but also alter and reconfigure the remaining surface energy budget components.

The Maritime Continent (MC) exhibits a pronounced diurnal cycle in precipitation, with many high-resolution models overestimating the diurnal peak and predicting earlier precipitation over the islands than observed. We hypothesize that part of this model bias comes from ignoring precipitation-induced surface sensible heat flux (QP). To test this conjecture, we performed simulations with and without QP for April 2009 and June 2006. The inclusion of QP reduced the bias in diurnal peak precipitation amplitude by 83% in April 2009 and 23% in June 2006. Similarly, the bias in precipitation peak timing decreased by 26% and 15%, respectively. This bias reduction was even more prominent during periods of heavier rainfall. This improvement in both the amplitude and phase of diurnal precipitation also led to a reduction in bias for total precipitation by similar to 10%. These findings suggest that QP cannot be neglected over the MC, particularly during heavy precipitation.

This study assesses the performance of the latest phase of Coupled Model Intercomparison Project (CMIP6) models in simulating easterly wave disturbances (EWD) over the tropical South Atlantic (TSA) impacting northeast Brazil (NEB). Initially, we evaluate simulated precipitation from 17 historical CMIP, 16 AMIP, 7 hist-1950, and 10 highresSST-present models against the Global Precipitation Climatology Project (GPCP) dataset to identify models that accurately reproduce the spatial and temporal precipitation patterns in the study region. The ensemble's spatial analysis demonstrates their capability in reproducing annual and seasonal precipitation climatology. However, models underestimate precipitation intensity along NEB's coast while overestimating it in TSA and NEB's north. Model uncertainties tend to be greater with higher latitudes. The models represented the annual cycle in all subareas within the study region, particularly from July to October, albeit with a greater spread in the first half of the year, especially over the Intertropical Convergence Zone (ITCZ). Based on it, three top-performing models from each ensemble were selected for EWD evaluation. The automatic tracking algorithm for EWDs showed the model's ability to represent mean values of EWD lifetime ( 6 days) and phase speed ( 7 m s−1) as found in ERA5 reanalysis. However, they failed to capture EWD's interannual variability or climatological mean frequency. Despite CMIP6 model weaknesses, they accurately identified two primary EWD genesis regions: one over the TSA and another near the West African coast. Overall, CMIP6 models, particularly atmospheric and high-resolution models (HighResMIP), effectively captured precipitation climatology and EWD characteristics over NEB and the adjacent TSA.

Tropical cyclones do not form easily near the equator but can intensify rapidly, leaving little time for preparation. We investigate the number of near-equatorial (originating between 5°N and 11°N) tropical cyclones over the north Indian Ocean during post-monsoon season (October to December) over the past 60 years. The study reveals a marked 43% decline in the number of such cyclones in recent decades (1981-2010) compared to earlier (1951-1980). Here, we show this decline in tropical cyclone frequency is primarily due to the weakened low-level vorticity modulated by the Pacific Decadal Oscillation (PDO) and increased vertical wind shear. In the presence of low-latitude basin-wide warming and a favorable phase of the PDO, both the intensity and frequency of such cyclones are expected to increase. Such dramatic and unique changes in tropical cyclonic activity due to the interplay between natural variability and climate change call for appropriate planning and mitigation strategies.

The large spatial and temporal variability of wet and dry spells of the Indian Summer Monsoon (ISM) poses the great challenge in understanding and predicting monsoonal rainfall. This challenge is further exacerbated over smaller regions, such as the southern tip of India, which receives the first spell of ISM rainfall. In this study, the characteristic features and possible precursors for wet and dry spells of rainfall over the southern tip of India are investigated. We also explore the variability in monsoon low-level jet (LLJ) in relation to wet and dry spells over a coastal station Thiruvananthapuram (8.48(degrees)N, 76.95(degrees)E) in southwest India using in situ observations and other ancillary datasets. The results show that a wet spell spanning 3-4 days contributes about 30% of seasonal rainfall. Wet spells are characterized by westerly wind anomaly in the southern tip of India and easterly wind anomaly in northern India, leading to anomalous cyclonic vorticity over the Indian subcontinent. The opposite happens during dry spells. These characteristics are prominent from 2 days prior to the initiation of the spells, suggesting they may be used as precursors for forecasting wet and dry spells over Thiruvananthapuram. Analysis of low- to mid-tropospheric (2 and 4 km) humidity reveals significant moistening (drying) during wet (dry) spells. Yet, both wet and dry spells experience humid (>80%) boundary layer. The differences in mid-level humidity and thermodynamical structures between wet and dry spells seem to contribute to distinct rainfall characteristics over the southern tip of India. These results indicate that the use of in situ observations along with large-scale reanalysis datasets may provide valuable information on the precursors for wet and dry spells over the southern tip of India, which can help both in regional- and city-level planning and management of water resources.