Precipitation Projections Research Articles

Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM

Abstract This study focuses on the spatio-temporal analysis of rainfall variability, trend patterns, and projected changes using GCM CCSM4 for RCP4.5 and RCP8.5 in Khyber Pakhtunkhwa. The historical rainfall variability (1971–2018), trend, and magnitude were assessed using Mann–Kendall and Spearman's Rho. In addition, to downscale GCMs data of precipitation at the regional level of Khyber Pakhtunkhwa, the SDSM conditional sub-model was applied. The monthly Mann–Kendall and Spearman's Rho trend test results revealed that most of the meteorological stations located in the northeastern mountains recorded a decreasing trend while Parachinar observed an increasing trend in almost all months except December. The trend results for seasonal rainfall showed a decreasing trend in winter, spring, and summer in the north and northeastern parts of Khyber Pakhtunkhwa whereas an increasing trend was observed in all seasons at Parachinar. The RCP4.5 projections depicted an increase in precipitation especially in the monsoon-dominating regions in comparison to the western disturbances, while decreasing rainfall projection was observed in RCP8.5. The projections for the summer and winter seasons depicted an increasing trend until the mid-century but in the latter half, a decline is registered. Such seasonal changes may initially cause flooding followed by drought, which calls for effective water management strategies.

Future projection of extreme precipitation within CORDEX East Asia phase II: multi-model ensemble

Future projection of extreme precipitation within CORDEX East Asia phase II: multi-model ensemble

The Role of the North Atlantic Oscillation for Projections of Winter Mean Precipitation in Europe

AbstractClimate models generally project an increase in the winter North Atlantic Oscillation (NAO) index under a future high‐emissions scenario, alongside an increase in winter precipitation in northern Europe and a decrease in southern Europe. The extent to which future forced NAO trends are important for European winter precipitation trends and their uncertainty remains unclear. We show using the Multimodel Large Ensemble Archive that the NAO plays a small role in northern European mean winter precipitation projections for 2080–2099. Conversely, half of the model uncertainty in southern European mean winter precipitation projections is potentially reducible through improved understanding of the NAO projections. Extreme positive NAO winters increase in frequency in most models as a consequence of mean NAO changes. These extremes also have more severe future precipitation impacts, largely because of mean precipitation changes. This has implications for future resilience to extreme positive NAO winters, which frequently have severe societal impacts.

Assessment of CMIP6 models’ performances and projection of precipitation based on SSP scenarios over the MENAP region

Abstract Precipitation is the main component of the hydrological cycle. It has a significant effect on the ecosystem especially, irrigation and drainage system design and management, crop production, and flood and drought management. In this study, 11 global circulation models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) were investigated under three shared socioeconomic pathway (SSP) scenarios for precipitation simulation and projection in the future period (2021–2050). Then, the results were compared with the base period (1985–2014). The research was conducted in the MENAP region. The evaluation of GCMs’ performances by the Taylor diagram, R2, MSE, MAE, and RMSE indices showed that among the 11 models, the MPI-ESM1-2-HR model with an average R2 and RMSE of 0.6 and 18.9, respectively, was more accurate than other models in precipitation simulation in the entire region. The projection of precipitation indicated that the precipitation will mainly decrease except in areas such as the Black Sea, Mediterranean, and Red Sea coastal areas as well as mountainous and higher altitude regions in the eastern part of the study area. In addition, highest decrease rates will happen in the Middle East countries, Afghanistan, Morocco, Algeria, and Sudan. Based on different scenarios in the MENAP region, precipitation will vary between −77.3 and + 51.1 mm compared to the base period. Moreover, the lowest and highest precipitation changes were estimated based on SSP1-2.6 and SSP5-8.5 scenarios. According to the various scenarios, the amount of precipitation in the future period will decrease compared to the historical period in most parts of the areas under study.

Quantifying Heavy Precipitation throughout the Entire Tropical Cyclone Life Cycle

Abstract Tropical cyclones (TCs) and their associated precipitation can have devastating impacts on the areas affected, with outcomes ranging from mudslides to inland flash flooding. Previous studies have used a fixed radius around the TC to isolate storm-related precipitation. One previous study instead used a dynamic radius of 8 m s−1 winds, but the wind field of the TC can deteriorate or shift quickly after landfall or the onset of extratropical transition (ET). This study uses a dynamical radius derived from the 500-hPa geopotential height in and around the TC to define TC- and post-tropical cyclone (PTC)-related heavy precipitation, allowing for the analysis of precipitation with tropical origins after the official demise of the original TC. Climatologies are constructed, indicating a maximum in TC- and PTC-related heavy precipitation in the west North Pacific and a secondary maximum in the east North Pacific. PTC-related heavy precipitation accounts for as much as 40% of the annual heavy precipitation in the northwest portion of the west North Pacific basin and 3.13% of heavy precipitation globally. We observe that the major hurricane stage contributes on average 2.6% of the global TC- and PTC-related precipitation, while the less intense but more common tropical storm stages of the TC life cycle contribute 85.7% of this observed precipitation. This analysis framework can be further extended to assess model biases and climate projections of TC and PTC precipitation.

A comprehensive analysis of observed and projected climate extremes of temperature and precipitation in Belo Monte Hydropower Plant ‐ eastern Amazon, Brazil

AbstractIn this work, the climatology, observed trends, and future projections of temperature and precipitation extremes are analysed in the drainage area of the Belo Monte Hydropower Plant in the Xingu River basin. Observed data come from gridded information for the period 1980–2013. The climate projections until the end of the 21st century are provided by the regional climate model Eta‐20 km nested to the global climate model MIROC5. Seventeen climate indicators were selected for this assessment, and statistical tests were used to evaluate the significance and magnitude of trends. A tropical climate predominates in the whole basin but with differences in the climatology of extreme temperature. The average annual rainfall (PRCPTOT) presents values between 1,500 and 2,200 mm. Remarkable contrasts of consecutive dry days (CDD) can also be seen. We found a warming signal during the examined period in much of the Xingu River basin, with an increase in the frequency of extremely warm days and nights. In the northern (south‐central) area of the basin, there is an increase (reduction) in precipitation. There is a contrasted and local distribution of detected trends in all climate extremes indices related to rainfall. CDD has displayed a considerable elevation in the south‐central area over the last decades. The study area exhibits statistically significant warming projections to the future climate. As for the precipitation projections, future changes are toward a dryer climate. We also found that dry periods may last longer in the following decades. Thus, heatwaves can be excited by subsequent days without precipitation in the basin in the future climate. The impacts of climate change on the balance of different environmental and socioeconomic sectors in this area must be wholly investigated.

A Flashforward to Today Made in the Past: Evaluating 25-Year-Old Projections of Precipitation and Temperature over West Africa

While scientists generally generate new projections with the newest models, the paper suggested the use of past projections as a different approach which could be explored and then complement classical approaches. With the idea that today is yesterday’s future, a set of past Intergovernmental Panel on Climate Change (IPCC) climate projections (first-AR1, second-AR2 and third-AR3 assessment reports) were compared to gauge-based observations of the last three decades (1990–2016). Why would someone need to check previous models and scenarios when the new ones are currently available? Some in-depth discussion points were raised to answer that question. Monthly and annual precipitation and temperatures were analyzed over West Africa, divided into 3 climatic sub-regions. The results revealed that observed differences are greater at higher latitudes and are strongly scenario dependent. The Business-as-Usual scenario (few or no steps are taken to limit greenhouse gas emissions) appeared to be closest to the observations. The AR1 projections were shown to be disconnected from the observations. AR2 exhibited the best performance, and AR3 presented higher uncertainties in the northern areas. The relative importance and potential implications of the differences between projections and observations on society were appreciated with regard to certain climate and weather-related factors that could greatly influence sustainable development in the region, such as water resources management, agriculture practices and yields, health conditions, and fishery management. Finally, some recommendations to policy and decision makers were given as well as further research topics for the scientific community.

Projections of future precipitation and air temperature over the Tibetan Plateau based on Coupled Model Intercomparison Project Phase 6 multimodel ensembles

AbstractIn the context of global warming and the release of projection results from the Coupled Model Intercomparison Project Phase 6 (CMIP6), it is important to conduct research on climate change on the Tibetan Plateau (TP) which exhibits unique geographic characteristics and complex climatic conditions. Using 10 general circulation models (GCMs) from CMIP6 corrected for bias by the daily translation (DT) method, we investigated the projected changes in precipitation and air temperature for the mid‐term (2031–2050) and long‐term (2061–2080) of the 21st century on the TP after evaluating the reliability of the bias correction, for four scenarios based on different combinations of shared socioeconomic pathways and representative concentration pathways. The multimodel ensembles (MMEs) indicated that the projected annual precipitation shows an increasing trend for the mid‐term and long‐term periods, with the projected increase for the long‐term primarily concentrated in areas with less precipitation. Meanwhile, the future precipitation changes exhibit a significant elevation dependency. The rate of increase of precipitation firstly fluctuates and then gradually increases along with the elevation increasing from 1,500 to 5,800 m. The valley value of rate mainly appears in two elevation zones (2,200–2,600 m and 3,400–3,800 m). The projected temporal changes in annual air temperatures reveal obvious warming over the TP. The projected warming is overall more pronounced with increase in elevation; however, it reaches a peak at approximately 5,000–5,200 m and then slows down slightly, indicating that warming is not dependent on elevation in the higher elevation zones. The present results have important implications for investigating the impacts of climate change on the water cycle in alpine regions.

Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6

In this study, future projections of monthly total precipitation and monthly average temperatures are carried out using 22 global circulation models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) of the Mediterranean region. The Multi-Model Ensembles (MME) are created with GCMs that best estimate observed values with the Artificial Neural Networks (ANN) based statistical downscaling method. The performance of GCMs is evaluated with six different statistical performance criteria. The MMEs are found to be better than used individual GCMs in simulating historical temperature and precipitation in the region. The projections are made for the years 2021–2100 according to the two integrated scenarios of socio-economic development and greenhouse gas emissions (SSP2–4.5, SSP5–8.5). The projections with the MMEs show that decreasing precipitation is calculated as 15% for SSP2–4.5 and 20% for SSP5–8.5. Also, the increase in temperature is found between 1.0 and 2.2 °C and between 1.8 and 3.1 °C for the SSP2–4.5 and SSP5–8.5, respectively. In addition, the possible decrease in precipitation in the coastal part of the region is higher than in other regions. On the other hand, possible temperature increases in the region's high altitudes have been determined more than in the coastal areas.

Projections of precipitation and temperature in Southern Iraq using a LARS-WG Stochastic weather generator

Iraq is located in the Middle East, a climatic region distinguished by arid and semi-arid environments and which is expected being more susceptible to possible effects of global warming and climate change. In current research, a stochastic weather generator, LARS-WG 6.0, was utilized to simulate historical and projected future daily climatic data and the appropriateness of the model to project daily temperature and daily precipitation. Considering the enormous uncertainties associated with future climate projections, five general circulation models (GCMs), MIROC5, CanESM2, HadGEM2-ES, NorESM1-M, and CSIRO-Mk3.6.0, which represent the most suitable models for the region according to previous studies, were utilized to project the future climate depending on two important scenarios of emissions, RCP4.5 and RCP8.5, across the current century by three periods. The climate data from six meteorological stations located in Southern Iraq were used to validate the model, which was based on historical data spanning thirty years (1980–2010). According to the findings, the yearly maximum temperature will rise based on the generated predictions at the end of the twenty-first century by 1.32–3.94 °C under RCP4.5 and 1.50–5.92 °C under RCP8.5 for all stations studied. For precipitation, the model projections show that there are various trends over all the GCMs used. This denotes the high level of uncertainty of the precipitation prediction if applied to one model only, as some models, e.g., CanESM2, predict an increase in precipitation while other models, e.g., MIROC5, refer to a decreasing trend or no change in precipitation in the future. Changes in rainfall and temperature will have a big effect on how much water is available in the south of Iraq, especially in the marsh and agricultural areas, which will face desertification, water shortages, and other environmental problems.

Assessing future climate change impacts on groundwater recharge in Minnesota

• Minnesota recharge will decrease despite increased precipitation, due to increased ET. • Soil moisture availability can limit ET increase and consequently recharge decrease. • Changes in runoff can modulate recharge response to climate. • Less frozen ground in warmer future can reapportion spring runoff to recharge. Although the northern Laurentian Great Lakes region is projected to undergo major climate changes, it has had a paucity of future groundwater recharge studies. We used the state of Minnesota (USA) as a testbed to understand how recharge will respond to changing climate in upper mid-latitude, low-elevation temperate settings. Not only can this inform water resource management, but it can help probe difficult-to-predict sign changes in recharge in temperate zones, as well as the under-studied land-surface processes controlling them. Our study implemented the Community Land Model with ensemble outputs from five climate models under two emissions scenarios (RCP8.5 and RCP4.5) to investigate future changes in recharge for 2026–2055 relative to the baseline historical period of 1976–2005. We found that despite quite consistent projections of higher precipitation (P) and some local occurrences of increased recharge, state-average recharge will mostly decline or remain about the same due to warming-induced evapotranspiration (ET) increases. However, our simulations showed that several processes serve to buffer recharge decreases. In drier ecoregions in the west, soil moisture limitations start to constrain evapotranspiration, thus curbing reductions in recharge. These regions also include higher historical surface runoff due to its runoff-prone soils, and because much of future reductions in net atmospheric inputs (P-ET) are partitioned to lower this runoff instead of recharge, decreases in recharge are further modulated. Statewide warming also lessens frozen ground coverage, reapportioning early spring runoff of snowmelt to infiltration and recharge. Our results demonstrate that in addition to precipitation change and warming, moisture feedbacks on ET and the influence of hydrogeological properties and frozen ground dynamics on runoff must be considered when quantifying climate change impacts on recharge in temperate zones.

Mechanisms for Extreme Precipitation Changes in a Tropical Archipelago

Abstract The Maritime Continent is one of the most challenging regions for atmospheric models. Processes that modulate deep convection are poorly represented in models, which affects their ability to simulate precipitation features accurately. Thus, future projections of precipitation over the region are prone to large uncertainties. One of the key players in modeling tropical precipitation is the convective representation, and hence convection-permitting experiments have contributed to improve aspects of precipitation in models. This improvement creates opportunities to explore the physical processes that govern rainfall in the Maritime Continent, as well as their role in a warming climate. Here, we examine the response to climate change of models with explicit and parameterized convection and how that reflects in precipitation changes. We focus on the intensification of spatial contrasts as precursors of changes in mean and extreme precipitation in the tropical archipelago. Our results show that the broad picture is similar in both model setups, where islands will undergo an increase in mean and extreme precipitation in a warmer climate and the ocean will see less rain. However, the magnitude and spatial structure of such changes, as well as the projection of rainfall percentiles, are different across model experiments. We suggest that while the primary effect of climate change is thermodynamical and it is similarly reproduced by both model configurations, dynamical effects are represented quite differently in explicit and parameterized convection experiments. In this study, we link such differences to horizontal and vertical spatial contrasts and how convective representations translate them into precipitation changes.

Temporal Variations and Futuristic Projections of Temperature and Precipitation: A study of Vijayawada city

Abstract: Examining the temporal dynamics of meteorological variables in the context of changing climate, particularly in Vijayawada, where agriculture is predominant. Therefore, the study uses trend analysis of rainfall and temperature change in Vijayawada using precipitation data obtained from Precipitation and temperature data. Data have been analysed using the coefficient of variation and standard deviation. Furthermore, the Mann-Kendall test was used to detect the time series trend. The result revealed variability of rainfall and temperature. The month-wise analysis of the temperature and precipitation trends established different unique patterns. This is due to the fact that the sensitivity of the world to climate change varies temporally and spatially. The scope of the study lies in developing the analysis to study different extreme events such as cloudbursts, heat waves, cold waves, etc. Furthermore, the spatial variations of the study can be used to establish the climate sensitivity with temporal factors.

Future Projections of Precipitation using Bias–Corrected High–Resolution Regional Climate Models for Sub–Regions with Homogeneous Characteristics in South Korea

Future Projections of Precipitation using Bias–Corrected High–Resolution Regional Climate Models for Sub–Regions with Homogeneous Characteristics in South Korea

Out-Performing Bias-Corrected GCM Models and CMIP6-Based Precipitation and Temperature Projections for the Bagmati Irrigation Area

The selection of General circulation models (GCMs) and suitable bias correction methods for any particular study area in very crucial for the projection of precipitation and temperature using climate models which can be used for estimating the future crop water requirement. The results of a General Circulation Model (GCM) are being downscaled and compared to a baseline climatology for two IPCC scenarios (ssp245 and ssp585) based on Coupled Model Inter-comparison Project Phase 6 (CMIP6) climate model. We choose four GCMs models out of ten by evaluating their performance to observe historical data. Performance indicators (NSE, PBAIS, and RSR) are computed by comparing bias-corrected historical data with observed historical data. We found that GCM models EC-Earth3, NorESM2-MM, GDFL-ESM4, and IPSL-CM6A-LR showed a higher rating for maximum and minimum temperature, and GCM models EC-Earth3, NorESM2-MM, GDFLESM4, and MPI-ESM2-MM showed a higher rating for precipitation. Among the different bias correction functions power Xo transformation and Power transformed functions, Bernoulli’s Weibull showed the best performance for minimum temperature), maximum temperature, and precipitation, respectively. These models and bias correction could be used to project the climate variables of the surrounding basins.

Performance evaluation of CORDEX South Asia models for projections of precipitation over the Kabul basin, Afghanistan

Precipitation is one of the key input data for hydrological modelling and water resources assessment. Climate projections are regionally available at a finer resolution, but it is still necessary to validate such data against the observations before any application. In this study the precipitation data available from the Coordinated Regional Downscaling Experiment (CORDEX) program of the South Asian domain was examined against APHRODITE (Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation) precipitation, which is used as observations in the absence of in situ measurements for the data-scarce Kabul basin in Afghanistan. The evaluation methods include verification statistics as well as visual verification by mapping the data over the basin. The evaluation results showed that some of the RCMs (Regional Climate Models) are following an entirely different precipitation pattern both temporally and spatially; however, their driving GCMs might be the same. Six of the 17 RCMs examined in this study performed well for the Kabul basin. The ensemble results of these selected RCMs suggest a decreasing trend in the future precipitation under both RCPs (Representative Concentration Pathways), with variations ranging from −14% to +6% under RCP 4.5 and −17% to +8% under RCP 8.5 for most areas, especially in the central parts of the basin.

Evaluation of the CMIP6 Performance in Simulating Precipitation in the Amazon River Basin

The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water to the people and environment and are critical to moisture recycling and transport, and represents an important variable for climate models to simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This is done by discussing results from spatial pattern mapping, Taylor diagram analysis and Taylor skill score, annual climatology comparison, cumulative distribution analysis, and empirical orthogonal function (EOF) analysis. Precipitation analysis shows: (1) This region displays higher rainfall in the north-northwest and drier conditions in the south. Models tend to underestimate northern values or overestimate the central to northwest averages. (2) The southern Amazon has a more defined dry season (June, July, and August) and wet season (December, January, and February) and models simulate this well. The northern Amazon dry season tends to occur in August, September, and October and the wet season occurs in March, April, and May, and models are not able to capture the climatology as well. Models tend to produce too much rainfall at the start of the wet season and tend to either over- or under-estimate the dry season, although ensemble means typically display the overall pattern more precisely. (3) Models struggle to capture extreme values of precipitation except when precipitation values are close to 0. (4) EOF analysis shows that models capture the dominant mode of variability, which was the annual cycle or South American Monsoon System. (5) When all evaluation metrics are considered, the models that perform best are CESM2, MIROC6, MRIESM20, SAM0UNICON, and the ensemble mean. This paper supports research in determining the most up-to-date CMIP6 model performance of precipitation regime for 1981–2014 for the Brazilian Amazon. Results will aid in understanding future projections of precipitation for the selected subset of global climate models and allow scientists to construct reliable model ensembles, as precipitation plays a role in many sectors of the economy, including the ecosystem, agriculture, energy, and water security.

Projection of Future Extreme Precipitation in China Based on the CMIP6 from a Machine Learning Perspective

In recent years, China has suffered from frequent extreme precipitation events, and predicting their future trends has become an essential part of the current research on this issue. Because of the inevitable uncertainties associated with individual models for climate prediction, this study uses a machine learning approach to integrate and fit multiple models. The results show that the use of several evaluation metrics provides better results than the traditional ensemble median method. The correlation coefficients with the actual observations were found to improve from about 0.8 to 0.9, while the correlation coefficients of the precipitation amount (PRCPTOT), very heavy precipitation days (R20mm), and extreme precipitation intensity (SDII95) reached 0.95. Based on this, the precipitation simulations of moderate forced scenario for sharing socio-economic path (SSP2-4.5) from 27 coupled models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to explore potential changes in future extreme precipitation events in China and to calculate the distribution and trends of the PRCPTOT, extreme precipitation amount (R95pTOT), maximum consecutive 5-day precipitation (Rx5day), precipitation intensity (SDII), SDII95, and R20mm for the early 21st century (2023–2050), mid-21st century (2051–2075), and late 21st century (2076–2100), respectively. The results showed that the most significant increase in extreme precipitation indices is expected to occur by the end of the century, with the R95pTOT, Rx5day, and SDII95 increasing by 13.73%, 9.43%, and 9.34%, respectively, from the base period. The remaining three precipitation indexes, the PRCPTOT, SDII, and R20mm, also showed increases of 8.77%, 6.84%, and 4.02%, respectively. Additionally, there were apparent differences in the spatial variation of extreme precipitation. There were significant increasing trends of extreme precipitation indexes in central China and northeast China in the three periods, among which the total annual precipitation showed an increasing trend in central and northern China and a decreasing trend in western and south China. An increasing trend of annual precipitation intensity was found to be mainly concentrated in central China and south China, and the annual precipitation frequency showed a larger increasing trend at the beginning of this century. The annual precipitation frequency showed an increasing trend in the early part of this century. In general, all the indices showed an overall increasing trend in the future period, with the PRCPTOT, Rx5day, and SDII95 showing the most significant overall increasing trends.

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America

AbstractA warmer climate impacts streamflows and these changes need to be quantified to assess future risk, vulnerability, and to implement efficient adaptation measures. The climate simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), which have been the basis of most such assessments over the past decade, are being gradually superseded by the more recent Coupled Model Intercomparison Project Phase 6 (CMIP6). Our study portrays the added value of the CMIP6 ensemble over CMIP5 in a first North America wide comparison using 3,107 catchments. Results show a reduced spread of the CMIP6 ensemble compared to the CMIP5 ensemble for temperature and precipitation projections. In terms of flow indicators, the CMIP6 driven hydrological projections result in a smaller spread of future mean and high flow values, except for mountainous areas. Overall, we assess that the CMIP6 ensemble provides a narrower band of uncertainty of future climate projections, bringing more confidence for hydrological impact studies.

Observed trends and projections of temperature and precipitation in the Olifants River Catchment in South Africa.

Among the projected effects of climate change, water resources are at the center of the matrix. Certainly, the southern African climate is changing, consequently, localized studies are needed to determine the magnitude of anticipated changes for effective adaptation. Utilizing historical observation data over the Olifants River Catchment, we examined trends in temperature and rainfall for the period 1976-2019. In addition, future climate change projections under the RCP 4.5 and RCP 8.5 scenarios for two time periods of 2036-2065 (near future) and 2066-2095 (far future) were analysed using an ensemble of eight regional climate model (RCA4) simulations of the CORDEX Africa initiative. A modified Mann-Kendall test was used to determine trends and the statistical significance of annual and seasonal rainfall and temperature. The characteristics of extreme dry conditions were assessed by computing the Standardized Precipitation Index (SPI). The results suggest that the catchment has witnessed an increase in temperatures and an overall decline in rainfall, although no significant changes have been detected in the distribution of rainfall over time. Furthermore, the surface temperature is expected to rise significantly, continuing a trend already evident in historical developments. The results further indicate that the minimum temperatures over the Catchment are getting warmer than the maximum temperatures. Seasonally, the minimum temperature warms more frequently in the summer season from December to February (DJF) and the spring season from September to November (SON) than in the winter season from June to August (JJA) and in the autumn season from March to May (MAM). The results of the SPI affirm the persistent drought conditions over the Catchment. In the context of the current global warming, this study provides an insight into the changing characteristics of temperatures and rainfall in a local context. The information in this study can provide policymakers with useful information to help them make informed decisions regarding the Olifants River Catchment and its resources.