Extreme Daily Precipitation Research Articles

Inferring the impacts of climate extreme in the Kabul River Basin

The increasing temperature and variability in precipitation, in terms of both frequency and intensity, are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extremes in the Kabul River Basin (KRB) of the western Himalaya using high-resolution climate datasets. We selected four representative General Circulation Model (GCM) runs from Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, based on future projections, climatic extremes and their abilities to represent the historical climate cycle (1981–2010) of KRB. The seasonal analysis of precipitation shows decreasing pattern during the winter and pre-monsoon seasons and annual mean temperature will increase consistently by 3 to 5 °C in RCP4.5 and 8.5 scenarios. Ten indices were selected to study climatic extremes pertaining to the health, agriculture and water resources sectors. The extremes, like consecutive summer days, warm days and heatwaves, will increase, whereas the frost days, cold nights, cold waves and extreme precipitation days will decrease towards the end of this century. Besides, the extremes are not homogenous in time and space. Based on the results of this study, there is a need for prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build resilient livelihoods in the KRB.

Circulation patterns in the middle and upper troposphere and their relationships with summer precipitation in the Jianghuai River Basin

AbstractThe upper and lower‐level circulations can be divided into four distinct modes based on ERA5 daily reanalysis data. The impact of these patterns on the summer persistent precipitation (SPP) in the Jianghuai River Basin (JRB) is investigated, with the ‘−SR (Silk Road)/+EAP (East Asia‐Pacific)’ mode identified as the most favourable for triggering SPP. The main manifestations are as follows: (1) From 1981 to 2020, 29.4% (30.7%) of extreme precipitation days (the frequencies of persistent extreme precipitation) are related to the ‘−SR/+EAP’ mode, indicating the importance of the ‘−SR/+EAP’ mode to the SPP in the JRB. (2) The ‘−SR’ pattern accelerates the westerly jet, leading to strong divergence over the JRB. Concurrently, the eastward movement of the South Asia High and westward shift of the Western Pacific subtropical high (WPSH) create conditions favourable for SPP in the JRB. (3) Abundant water vapour, facilitated by strong moisture convergence and upward motion, significantly contributes to SPP in the JRB.

Summer long-lived heatwaves in Northeast Asia promote heavy precipitation in South China

Heatwaves interact with various extreme weather events, amplifying their impacts beyond the risks associated with high temperatures alone. However, previous research has often overlooked the extent to which heatwaves influence regions beyond their origin. In this study, we introduce a classification of heatwaves in Northeast Asia, distinguishing between long-lived heatwaves (LHWs) lasting five days or more and short-lived heatwaves (SHWs) lasting less than five days. The study highlights the significant role of LHWs in triggering heavy precipitation in South China. The anticyclonic anomalies associated with LHWs are influenced by a slow-moving wave train, initiating and sustaining cyclonic anomalies over South China, resulting in upward airflow anomalies. Additionally, easterly wind anomalies in the southern region of the anticyclonic anomalies facilitate moisture transport to South China, creating favorable conditions for precipitation. The findings underscore that LHWs could account for a noticeable portion (17.6%) of total summer extreme precipitation days in South China. The study highlights the significant role of LHWs-related circulations in triggering heavy precipitation in South China.

Constraining the Pattern and Magnitude of Projected Extreme Precipitation Change in a Multimodel Ensemble

Abstract Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution.

Climatic characteristics and main weather patterns of extreme precipitation in the middle Yangtze River valley

Abstract Based on the daily precipitation data and ERA5 reanalysis data of 40 years from 1981 to 2018 in the middle Yangtze River Valley (MYRV), the climatic characteristics of extreme precipitation are analyzed using statistical methods. The multivariate empirical orthogonal functions and spectral clustering methods are used to classify and synthesize the extreme precipitation weather. The results show that: (1) The spatial distribution of the extreme precipitation threshold is uneven due to the regional topography. The spatial distribution of the average precipitation and frequency of extreme precipitation days is characterized by the north-south antiphase distribution. (2) According to the main influencing systems, the 215 regional extreme precipitation days in the MYRV in the past 40 years can be classified into three types: southwest vortex type, typhoon type, and cold trough shear line type. (3) The southwest vortex type of extreme precipitation occurs in the deep warm and humid airflow in front of the southwest vortex trough, but the typhoon type has better thermal dynamic conditions, and the cold and warm airflow convergence of the cold trough shear line type is more obvious. The rainfall area of three types of extreme precipitation is the result of the synergistic effect of the system.

Brief communication: A first hydrological investigation of extreme August 2023 floods in Slovenia, Europe

Abstract. Extreme floods occurred from 4 to 6 August 2023 in Slovenia causing three casualties and causing total direct and indirect damage, including post-disaster needs according to the Post-Disaster Needs Assessment (PDNA), close to EUR 10 billion. The atypical summer weather conditions combined with the high air and sea temperatures in the Mediterranean and the high soil moisture led to the most extreme flood event in Slovenia in recent decades. The return periods of both daily and sub-daily precipitation extremes and peak discharges reached 250–500 years, and the runoff coefficient of a typical torrential and mostly forested mesoscale catchment was around 0.5. In addition, flooding, soil erosion, mass movements and river sediment transport processes caused major damage to buildings (more than 12 000 houses) and diverse infrastructure.

Historical Shifts in Seasonality and Timing of Extreme Precipitation

AbstractGlobal warming impacts the hydrological cycle, affecting the seasonality and timing of extreme precipitation. Understanding historical changes in extreme precipitation occurrence is crucial for assessing their impacts. This study uses relative entropy to analyze historical changes in seasonality and timing of extreme daily precipitation occurrences on the global domain for 63 years of fifth generation of the European Reanalysis reanalysis data. Our analysis reveals distinct regional patterns of change. During the second half of the 20th century, Africa and Asia experienced high clustering of precipitation extremes. Over the past 60 years, clustering increased in Africa while becoming more spread out in Asia. North America and Australia had initially lower clustering and showed slight increases over time. Extreme events in extra‐tropical land regions mainly occurred in summer, with modest shifts in timing. These findings have implications for risk assessments of natural hazard like flash floods and landslides, emphasizing the necessity for region‐specific adaptation strategies.

Climate Risk and Vulnerability Assessment of Georgian Hydrology under Future Climate Change Scenarios

The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios.

Climatological trends of mean and extreme daily precipitation in Arizona (USA)

Precipitation in Arizona, USA, represents a fundamental resource for the needs of agriculture, people, and the environment. However, due to the risk associated with flash flooding, extreme precipitation also constitutes a natural hazard. Available research on precipitation in Arizona has been limited in scope and focus and there currently exists no comprehensive assessment of statewide, historical, mean, and extreme precipitation. We use daily precipitation records from 43 Global Historical Climate Network daily (GHCNd) weather stations to examine trends in mean and extreme precipitation across Arizona from 1950 to 2020. We use a suite of standardized precipitation indices and explore the statistical significance of historical changes at the annual, monthly, and seasonal scales. Our analysis returns a motley collection of results displaying a great degree of spatial variability and sensitivity to the temporal scale of analysis. Mean total precipitation at the statewide scale underwent a small decreasing trend of 0.15 mm year−1, with considerable interannual variability being a dominant feature. The majority of stations experienced no statistically significant change in extreme precipitation at the annual scale. Monsoon season mean precipitation followed a similar pattern to annual means, with an overall reduction of 0.14 mm year−1 across the state. One fourth of stations, all located at elevations lower than 650 m, recorded decreases in monsoon precipitation intensity. Winter season analysis presents a different picture, displaying a positive statewide trend of 0.11 mm year−1 in mean precipitation. One tenth of stations recorded increases in extreme precipitation intensity and decreases in the number of consecutive dry days. Results of our observational analysis indicate a lack of a clear consensus on the climatological trends of mean/extreme precipitation in Arizona during the study period. Our findings are in contrast to those from other similarly arid areas across the world and highlight the role of regional differences in modulating the potential hydrometeorological impacts associated with climate change. However, while we do not find widespread, significant, modification in the spectrum of precipitation changes examined, the hydrologic system of the state has been – and will continue to be - impacted by the ongoing temperature increase associated with the buildup of greenhouse gases and continued population growth.

Modeling the influence of daily temperature and precipitation extreme indices on vegetation dynamics in Katsina State using statistical downscaling model (SDM)

Climate change significantly impacts local, regional, and global vegetation changes. These changes have continued to threaten ecosystems, especially in dryland areas where moisture is scarce, and the livelihoods of rural communities are at risk because of such changes, as well as their capacity to provide outputs and sustain the livelihoods of rural communities. This study aims to derive a simulation model of vegetation conditions concerning daily temperature and extreme precipitation indices in Katsina State, Nigeria. This study uses remote sensing and Geographic Information System (GIS)-based analysis, time series analysis of precipitation, maximum and minimum temperature, and twenty-four indices defined by the Expert Team on Climate Change Detection to evaluate the influence of Temp and precipitation extreme indices on vegetation dynamics/NDVI. The results indicate that the statistical downscaling model (SDSM) is performing satisfactorily in predicting maximum and minimum temperatures, along with precipitation, for the time horizon of the simulation. Mean precipitation of 1.98 mm (RCP2.6), 2.03 mm (RCP4.5), and 2.07 mm (RCP8.5) was revealed in the study area. Tmax and Tmin were projected under low emissions at 20.1 0C and 14.25 0C (RCP2.6), 20.13 °C and 14.26 0C (RCP4.5), and 20.15 0C and 14.27 0C (RCP8.5) respectively. All the scenarios present increasing minimum and maximum temperatures and decreasing precipitation, except for RCP8.5, which predicted a more adverse trend. However, in Katsina State, the Normalized Difference Vegetation Index (NDVI), precipitation, Tmax, and Tmin, extreme temperature and precipitation indices, and drought indices successfully demonstrated spatial and temporal variability.

Quantification of uncertainties in projections of extreme daily precipitation simulated by CMIP6 GCMs over homogeneous regions of India

AbstractGlobal climate model (GCM) projections are subject to significant uncertainties. Quantifying uncertainties in climate change projections improves credibility and makes climate data more reliable. This study aims to quantify the uncertainties in projected extreme precipitation during the 21st century over the homogeneous rainfall regions of India simulated by Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs. The percentile‐based square root error variance (SREV) method estimates model, scenario and ensemble uncertainties in projections of extreme precipitation. The uncertainty is investigated at four thresholds: 95th, 99th, 99.9th and 100th percentiles. The results show that the wet northeast region has a greater SREV, which is consistent with previous studies. At 99th and 99.9th percentiles, relative model SREV is dominant over the northeast (NE) region. However, at the 95th percentile high relative model SREV is found over the northwest (NW) region during southwest (June, July, August and September) and NE (October, November and December) monsoon seasons. Model uncertainty is the main source of uncertainty, followed by scenario and ensemble uncertainties. The study indicates that the arid NW region in India has a higher level of uncertainty than other regions with homogeneous rainfall. These findings will assist policymakers in planning infrastructure development in arid regions of India.

Population Exposure Changes to Mean and Extreme Climate Events Over Pakistan and Associated Mechanisms.

The increasing prevalence of warmer trends and climate extremes exacerbate the population's exposure to urban settlements. This work investigated population exposure changes to mean and extreme climate events in different Agro-Ecological Zones (AEZs) of Pakistan and associated mechanisms (1979-2020). Spatiotemporal trends in mean and extreme temperatures revealed significant warming mainly over northern, northeastern, and southern AEZs. In contrast, mean-to-extreme precipitation changes showed non-uniform patterns with a significant increase in the northeast AEZs. Population exposure to mean (extreme) temperature and precipitation events increased two-fold during 2000-2020. The AEZs in urban settlements (i.e., Indus Delta, Northern Irrigated Plain, and Barani/Rainfall) show a maximum exposure to extreme temperatures of about 70-100×106 (person-days) in the reference period (1979-1999), which increases to 140-200×106 person-days in the recent period (2000-2020). In addition, the highest exposure to extreme precipitation days also increases to 40-200×106 person-days during 2000-2020 than 1979-1999 (20-100×106) person-days. Relative changes in exposure are large (60%-90%) for the AEZs across northeast Pakistan, justifying the spatial population patterns over these zones. Overall, the observed changes in exposure are primarily attributed to the climate effect (50%) over most AEZs except Northern Irrigated Plain for R10 and R20 events, where the interaction effect takes the lead. The population exposure rapidly increased over major AEZs of Pakistan, which could be more vulnerable to extreme events due to rapid urbanization and population growth in the near future.

On the Resolution Sensitivity of Equatorial Precipitation in a GFDL Global Atmospheric Model

AbstractWe performed a series of aquaplanet simulations at the horizontal resolution from 50 to 6 km with identical parameterization settings using the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4 implemented with the two‐moment Morrison‐Gettelman cloud microphysics with prognostic precipitation (GFDL AM4‐MG2). At the finer resolution, the global mean resolved‐scale precipitation increases and that from cumulus parameterization decreases. The model also simulates less/thinner clouds over the low latitudes and more/thicker clouds over the high latitudes as the resolution increases. The precipitation over the deep tropics is investigated in detail. We find little resolution sensitivity in the daily mean precipitation extremes. Changes of the equatorial resolved precipitation with resolution cannot be fully explained by the resolution dependence in the vertical velocity amplitude. We report a robust sensitivity in the convective organization over the deep tropics to the model resolution. In simulations of finer resolution, the localized convection is suppressed, and the organized convective system associated with large‐scale circulations becomes more prominent.

Identifying Robust Changes of Extreme Precipitation in Japan From Large Ensemble 5‐km‐Grid Regional Experiments for 4K Warming Scenario

AbstractTo evaluate the impacts of global warming on local‐scale extreme precipitation in Japan, 720‐year ensemble dynamical downscaling is conducted by a regional climate model with a 5 km grid spacing. Our dynamical downscaling is based on the large ensemble data set called the database for Policy Decision making for Future climate change (d4PDF). Comparing the historical and 4K warming climates, the annual maximum daily and hourly precipitation are enhanced over Japan due to global warming. The increasing rate of annual maximum daily precipitation is larger over the coast of the Pacific Ocean in eastern and western Japan and the northern parts of Japan. The periods in which the extreme daily precipitation increases in each region depend on the movement of the Baiu front and the number of typhoons from June through September. The 50‐year return value of the maximum 24‐hr land precipitation within 500 km of the typhoon center is 960 mm/24hr in the 5 km experiment. This value is larger by 1.87 times than that of the 20 km experiment. The rate of future increase in the 50‐year return value related to typhoons is 1.30 relative to the present values for the 5 km experiments. The local‐scale quasi‐stationary band‐shaped precipitation system, which is called senjo‐kousuitai in Japanese, sometimes brings local‐scale heavy precipitation to Japan. The senjo‐kousuitai is well reproduced in the 5 km experiments and shows increases in frequency and intensity under the 4K warming condition. This study also discusses the application of our 5 km experiments to hydrological fields.

The Effect of Greenhouse Gas–Induced Warming on the Impact of El Niño and La Niña Events on Daily Precipitation Extremes in the Boreal Cold Season

Abstract El Niño–Southern Oscillation (ENSO) has a profound influence on the occurrence of extreme precipitation events at local and regional scales in the present-day climate, and thus it is important to understand how that influence may change under future global warming. We consider this question using the large-ensemble simulations of CESM2, which simulates ENSO well historically. CESM2 projects that the influence of ENSO on extreme precipitation will strengthen further under the SSP3–7.0 scenario in most regions whose extreme precipitation regimes are strongly affected by ENSO in the boreal cold season. Extreme precipitation in the boreal cold season that exceeds historical thresholds is projected to become more common throughout the ENSO cycle. The difference in the intensity of extreme precipitation events that occur under El Niño and La Niña conditions will increase, resulting in “more extreme and more variable hydroclimate extremes.” We also consider the processes that affect the future intensity of extreme precipitation and how it varies with the ENSO cycle by partitioning changes into thermodynamic and dynamic components. The thermodynamic component, which reflects increases in atmospheric moisture content, results in a relatively uniform intensification of ENSO-driven extreme precipitation variation. In contrast, the dynamic component, which reflects changes in vertical motion, produces a strong regional difference in the response to forcing. In some regions, this component amplifies the thermodynamic-induced changes, while in others, it offsets them or even results in reduction in extreme precipitation variation.

An increasing trend in daily monsoon precipitation extreme indices over Pakistan and its relationship with atmospheric circulations

This study assessed spatiotemporal trends in daily monsoon precipitation extremes at seasonal and sub-seasonal scales (June, July, August, and September) and their links with atmospheric circulations over Pakistan. The study used observed precipitation data from fifty in-situ stations and reanalysis products from the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) during 1981–2018. A suite of seven extreme precipitation indices and non-parametric statistical techniques were used to infer trends in the frequency and intensity of extreme precipitation indices. An increase in frequency and intensity of overall extreme indices was evident, with a maximum tendency in the country’s northwestern (z-score=>2.5), central, and eastern (z-score > 4) monsoon-dominant parts. The northern and southwestern parts of the country exhibited a slight decrease (z-score <–2) in frequency and intensity. The Sen’s Slope estimator (SSE) shows an increase in western parts (0.20 days) indicating a shift in the maxima of the monsoon precipitation. The regional precipitation shows an increase in wet days (R1 mm) with higher values of mMK (3.71) and SSE (0.3) in region 2 Similar results of moderate regional increase are evident for extreme indices except regions 1 and 3. The extreme 1-day maximum precipitation increased in region 3 (mMK: 1.39, SSE: 2.32). The extremely wet days (R99p TOT) precipitation has a moderate increase in all regions with a decrease in region 1. The temporal mutations showed dynamic changes, clearly reflecting the country’s historical extreme events. The frequency and intensity of precipitation extremes negatively correlated with the altitude (R = −0.00039). The probability density function (PDF) showed a significant increase in the density during June and September with a probabilistic positive shift during July and August. The intensified mid-latitude westerlies and subtropical zonal easterlies teleconnections, strengthening of the monsoon trough, and land-ocean thermal contrast are the potential drivers of the increasing trend in precipitation extremes. The current study could serve as a benchmark for future researchers and policymakers to devise effective mitigation strategies for sustainable development.

Continental‐scale trends of daily precipitation records in late 20th century decades and 21st century projections: An analysis of observations, reanalyses and CORDEX‐CORE projections

AbstractWe apply a methodology to identify and count records (events of unprecedented intensity) in daily precipitation time series to two sets of data: (1) different observational and reanalysis products for recent decades and (2) twenty‐first century projections (RCP8.5 and RCP2.6 scenarios) completed with two regional climate models driven by three global climate models over nine continental‐scale domains. Comparison of the detected (or actual) number of records with the corresponding number theoretically expected in stationary climate conditions (or “reference” number of records) provides indications of trends in daily precipitation extremes, as expected in a changing climate. In particular, we measure deviations from stationary conditions using the ratio of actual to reference records (RAtR) as a basic metric. We find that the observational products provide mixed indications of precipitation record trends across regions, while in the reanalysis products and the model simulations for the historical period the RAtR value shows a prevailing increasing trend with time over most continents. The RAtR shows a consistent and pronounced increase in all RCP8.5 continental‐scale projections, when sustained warming occurs throughout the 21st century, while smaller to no significant trends are found in the RCP2.6 scenario, when the warming stabilizes after about mid‐21st century. These results are indicative of an increase in precipitation extremes with global warming as measured by the higher number of local precipitation events of unprecedented intensity compared to what expected in stationary climate conditions, although a marked variability of this response is found across different regions. Our method can have useful applications in detection and attribution of hydroclimatic extremes and in impact and vulnerability assessment studies.

Characteristics of Water Vapor Transport for Extreme Summer Precipitation in the Eastern Southwest China and Its Impact Mechanism

To improve understanding of the characteristics of extreme summer rainfall and its water vapor transport in the eastern part of southwestern China (ESWC), this study analyzed data on daily precipitation from 118 meteorological stations in the ESWC from 1979 to 2020, as well as daily reanalysis data from ERA5 and daily reanalysis data from NCEP/NCAR. The study employed polynomial fitting, correlation, regression, clustering, and mixed single-particle Lagrangian trajectory (HYSPLITv5.0) modeling methods to simulate extreme summer precipitation and its water vapor transport characteristics in the ESWC and its possible formation mechanism. The results show that: (1) The contribution rate of extreme precipitation in the ESWC from 1979 to 2020 varied significantly on the interannual time scale. When the number of extreme precipitation days is high (low), the contribution rate of extreme precipitation is also high (low), while the contribution rate of general precipitation (the percentage of the sum of general precipitation to the total summer precipitation of that year) is often low (high). (2) When extreme precipitation occurs in the ESWC, compared with general precipitation, the high-level potential vortices are stronger, and the cold air from higher latitude is more likely to move southward. Meanwhile, the amount of water vapor input to the region is significantly larger than that of general precipitation. (3) There are four channels of water vapor sources in the ESWC during the period of extreme precipitation: the Bay of Bengal, the Arabian Sea, the western Pacific, and the northwest. The contribution of water vapor from the Bay of Bengal is the highest. The number of extreme summer precipitation days in the ESWC is significantly negatively correlated with the water vapor budget of the eastern boundary and positively correlated with Indian Ocean Basin-Wide (IOBW) index in the previous winter. (4) When the winter SST is high in the IOBW mode, it can cause the western Pacific subtropical high and the South Asian high to be stronger and shifted southward in summer, resulting in an increase in the number of extreme precipitation days in the ESWC.

A spatio-temporal analysis of the role of climatic drivers influencing extreme precipitation events in a Costa Rican basin

Regional patterns of rainfall are changing around the world, putting pressure on social, economic, and environmental systems, and changing the outlook for food, water, and health security. This is the case in the Tempisque-Bebedero River Basin (TBRB), located on the Pacific slope of northwest Costa Rica, which relies heavily on water resources for tourism, agriculture, ranching, and fish farming. In this study, we use non-stationary extreme value analysis to characterize the climatic drivers of extreme precipitation in the TBRB. Daily extreme precipitation events at stations across the TBRB are selected using a peak-above-threshold approach, and interannual climate variability is included as time-varying covariates in a non-stationary point process model, using three regional climate indices: the Caribbean Low-Level Jet (CLLJ) index, the Oceanic Niño Index (ONI), representative of the El Niño Southern Oscillation (ENSO), and the Atlantic Multidecadal Oscillation (AMO) index. We find that the magnitude and frequency of precipitation extremes in the basin are driven by the CLLJ and the AMO. The ONI is only a significant driver of extreme precipitation in the northwestern region of the basin. This is likely because ENSO controls the strength of the CLLJ, thus the dominant impact of ENSO on precipitation in the TBRB may be incorporated within the CLLJ component of our model.

Possible factors for the recent changes in frequency of central Indian Summer Monsoon precipitation extremes during 2005–2020

The transitions of short-term trends of Indian Summer Monsoon daily precipitation extremes remain poorly understood. Here, we show a short-term declination of temporal frequency of monsoonal precipitation extremes over Central India for the last 15 years starting from 2005 to 2020 while the low and moderate events show increasing trends. The possible dynamical and thermodynamical factors for the observed decline in precipitation extremes include depletion in moisture transport to Central India via cross-equatorial flow and the low-level Somali jet, caused by reduced evaporation from the regional moisture sources. In addition, the vertical gradient of the moist static energy exhibits favorable conditions for increased lower atmospheric stability, supporting the declining trends. Lastly, the Atlantic Zonal Mode seems to be a potential large-scale climate driver for the less frequent central Indian extreme rainfall events during 2005–2020.