Impact Of Climate Variability Research Articles

Deterioration of steel structures due to corrosion considering the global effects of climate change

The randomness of atmospheric conditions is among the key contributing factors that affect the ability to accurately predict the corrosion growth in steel structures. Climate change has the potential to alter the long-term characteristics of these factors over the lifespan of steel structures, both those already existing and those newly built. The impact of climate variability on the stochastic nature of atmospheric variables, which greatly influence corrosion conditions, can add complexity to corrosion predictions in these structures. This paper introduces an integrated framework to quantify the impact of climate change on corrosion rates of steel structures worldwide. It considers the changes in environmental conditions, specifically temperature, relative humidity and wind speed and their effects on atmospheric corrosion. Global Climate Models are employed to evaluate the long-term impacts of climate change on these environmental conditions. An analytical model for predicting corrosion rate is integrated with climate change models to predict alterations in the corrosion rates of steel components relative to historical conditions. This paper also discusses the impact of climate change on the variations of these climatic parameters and offers a comparison between historical data and projected conditions across the globe. The results indicate that the effect of climate change on the corrosion rate depends on the considered region. While regions such as Australia, North America and Europe see an increase, others such as Asia and Africa observe a decline. Notably, all oceans, especially the Antarctic and Arctic, experience a significant increase in corrosion by the end of the century.

Impact of climatic variations in horticulture sector, Kinnaur, Himachal Pradesh, India

Climate change has an impact on the horticulture crops of Himachal Pradesh in relation to the varying climatic conditions in the Himalayan Region. The purpose of the study was to determine how frequently these differences in horticultural crops occur in the Kinnaur district of Himachal Pradesh since the horticulture industry in Himachal Pradesh greatly benefits from this district. Long-term temperature (maximum, minimum, and diurnal) and rainfall data from 1990 to 2020 were analyzed for different phenological stages (pre-flowering, flowering, and fruit setting). The findings revealed that the average maximum and diurnal temperatures were found to have increased significantly, at the rate by 0.027 °C and 0.042 °C, respectively, during the flowering stages. However, there were no appreciable changes in the variations for other phenological stages. Under trend analysis of crop yield, the productivity of Pear and Almond notably fell over the past 20 years, at -0.029 t/ha/year and -0.016 t/ha/year, respectively, whereas Walnut productivity climbed at 0.008 t/ha/year. The relationship or impact between the climate and the crop was also examined in addition to the trend analysis for crop and climatic variables. The results showed that among the three phenological stages, Apple and Apricot were highly impacted (54.4%) during pre-flowering stage, followed by Apricot, i.e., 72.6% during flowering, and Grapes (53.2%) during the fruit setting stage. In the current situation, climate fluctuations had a favorable effect on Apples, Walnuts and Grapes while having a negative effect on Apricots, Plums, Pears and Almonds.

Anatomically modern human dispersals into Europe during MIS 3: Climate stability, paleogeography and habitat suitability

The initial large-scale dispersal of Anatomically Modern Humans (AMHs) into Europe, associated with the Aurignacian technocomplex, occurred during Marine Isotope Stage 3 (MIS 3), a critically unstable climatic period. The impact of climate change (millennial-scale Dansgaard-Oeschger events) and climate variability (annual and seasonal variation) on the mobility and initial dispersal of AMHs on the continent is not fully demonstrated. Here we show that both climate change and variability affected the spatial behavior of Aurignacian groups and structured their arrival on the continent. Using Random Forest, a machine learning algorithm, we produced habitat suitability (HS) models for AMHs under stadial (GS) and interstadial (GI) climate conditions. These models demonstrate that climate variability was a key factor governing the spatial behavior of human groups across MIS 3. They also illustrate that the structure and distribution of suitable habitat in Europe were affected by climatic conditions, with implications in terms of our species’ adaptability and behavioral plasticity. Finally, our results support the suggestion that initial dispersals followed a Mediterranean coastal route, likely under interstadial conditions.

Enhancing solids deposit prediction in gully pots with explainable hybrid models: A review.

Urban flooding has made it necessary to gain a better understanding of how well gully pots perform when overwhelmed by solids deposition due to various climatic and anthropogenic variables. This study investigates solids deposition in gully pots through the review of eight models, comprising four deterministic models, two hybrid models, a statistical model, and a conceptual model, representing a wide spectrum of solid depositional processes. Traditional models understand and manage the impact of climatic and anthropogenic variables on solid deposition but they are prone to uncertainties due to inadequate handling of complex and non-linear variables, restricted applicability, inflexibility and data bias. Hybrid models which integrate traditional models with data-driven approaches have proved to improve predictions and guarantee the development of uncertainty-proof models. Despite their effectiveness, hybrid models lack explainability. Hence, this study presents the significance of eXplainable Artificial Intelligence (XAI) tools in addressing the challenges associated with hybrid models. Finally, crossovers between various models and a representative workflow for the approach to solids deposition modelling in gully pots is suggested. The paper concludes that the application of explainable hybrid modeling can serve as a valuable tool for gully pot management as it can address key limitations present in existing models.

Simple hydrological models for assessing the impact of forest cover change on streamflow for large catchments with a dry tropical climate

ABSTRACT Hydrological models are widely used to assess the impact of climate variability and land use change on streamflow. However, it is uncertain whether these models are capable of simulating the impact given parameter interactions and inter-annual climate variability for large dry catchments. Two such catchments with extensive land clearing were selected to test three models – AWBM, Sacramento and SimHyd – in terms of their capacity to simulate streamflow during periods of vastly different levels of forest cover. AWBM outperformed others, and thus was further simplified as AWBM_C a with minimum performance deterioration to have only one transferable parameter: the average storage capacity, C a. A reduction of 21–28% in the C a value for the post-clearing period indicates a decrease in the amount of water stored for transpiration and consequently an increase in runoff-generation capacity. AWBM_C a can be used to predict the impact of forest cover change on streamflow with different C a values.

Land use changes and climate parameters assessments in a tropical highland region of Cameron Highlands, Malaysia

Abstract Tropical highland regions are susceptible to climate change and natural disasters due to their geographical location and hilly terrain. The objectives of this study are to determine land use land cover (LULC) changes in the Cameron Highlands and analyse the climatic parameters of the Cameron Highlands. This study integrates LULC analysis using remote sensing techniques and 10-year climatic parameters data to evaluate the impact of climate variability on the sustainability of the Cameron Highlands. Based on the validation results, the overall accuracy of LULC was 95.42% in 2016, 96.60% in 2018, and 97.40% in 2020. The results show an 18% rise in agriculture, a 16% increase in urban growth, and an 8.14% decline in forest coverage in Tanah Rata and Ringlet, Cameron Highlands, from 2016 to 2020. The Mann -Kendall and Sen slope indicated a statistically significant increasing trend in rainfall (Kendall's Tau, z = 0.102, p < 0.0001 and Sen value= 0.131, p < 0.001, respectively) and temperature (Kendall's Tau, z = 0.151, p < 0.001 and Sen value = 0.294, p < 0.001, respectively) from 2012 to 2021, increasing the area's susceptibility towards climate change impact and natural disasters. This study highlights the vulnerability of the Cameron Highlands to natural disasters, emphasizing the crucial need for efficient land management in slope areas.

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

AbstractAlthough considerable effort has been deployed to understand the impact of climate variability and vegetation change on runoff in major basins across Africa, such studies are scarce in the Gulf of Guinea Basin (GGB). This study combines the Budyko framework and elasticity concept along with geospatial data to fill this research gap in 44 nested sub‐basins in the GGB. Annual rainfall from 1982 to 2021 show significant decreasing and increasing trends in the northern and southern parts of the GGB, respectively. Annual potential evapotranspiration (PET) also shows significant increasing trends with higher magnitudes observed in the northern parts of the GGB. Changing trends in climate variables corroborates with shift to arid and wetter conditions in the north and south, respectively. From 2000 to 2020 vegetation cover estimated using enhanced vegetation index (EVI) shows significant increasing trends in all sub‐basins including those experiencing a decline in annual rainfall. Vegetation composition measured using vegetation continuous fields (VCFs) from 2000 to 2020 show an increase in tree canopy cover (TC), a decline in short vegetation cover and marginal changes in bare ground cover (BG). Elasticity coefficients show that a 10% increase in annual rainfall and PET may lead to a 33% increase and 24% decline in runoff, respectively. On the other hand, a 10% increase in EVI may lead to a 4% decline in runoff while a 10% increase in TC, SV and BG may reduce runoff by 4% and increase runoff by 3% and 2%, respectively. Even though changes are marginal, decomposing vegetation into different parameters using EVI and VCFs may lead to different hydrological effects on runoff which is one of the novelties of this study that may be used for implementing nature‐based solutions. The study also demonstrates that freely available geospatial data together with analytical methods are a promising approach for understanding the impact of climate variability and vegetation change on hydrology in data‐scarce regions.

Influence of climatic variation on microbial communities during organic Pinot noir wine production.

To assess the possible impact of climatic variation on microbial community composition in organic winemaking, we employed a metabarcoding approach to scrutinize the microbiome in a commercial, organic, Pinot noir wine production system that utilizes autochthonous fermentation. We assessed microbial composition across two vintages (2018 and 2021) using biological replicates co-located at the same winery. Microbial dynamics were monitored over four important fermentation time points and correlated with contemporaneous climate data. Bacterial (RANOSIM = 0.4743, p = 0.0001) and fungal (RANOSIM = 0.4738, p = 0.0001) compositions were different in both vintages. For bacteria, Lactococcus dominated the diversity associated with the 2018 vintage, while Tatumella dominated the 2021 vintage. For fungal populations, while Saccharomyces were abundant in both vintages, key differences included Starmerella, copious in the 2018 vintage; and Metschnikowia, substantive in the 2021 vintage. Ordination plots correlated the climatic variables with microbial population differences, indicating temperature as a particularly important influence; humidity values also differed significantly between these vintages. Our data illustrates how climatic conditions may influence microbial diversity during winemaking, and further highlights the effect climate change could have on wine production.

Geographic range of plants drives long-term climate change

Long computation times in vegetation and climate models hamper our ability to evaluate the potentially powerful role of plants on weathering and carbon sequestration over the Phanerozoic Eon. Simulated vegetation over deep time is often homogenous, and disregards the spatial distribution of plants and the impact of local climatic variables on plant function. Here we couple a fast vegetation model (FLORA) to a spatially-resolved long-term climate-biogeochemical model (SCION), to assess links between plant geographical range, the long-term carbon cycle and climate. Model results show lower rates of carbon fixation and up to double the previously predicted atmospheric CO2 concentration due to a limited plant geographical range over the arid Pangea supercontinent. The Mesozoic dispersion of the continents increases modelled plant geographical range from 65% to > 90%, amplifying global CO2 removal, consistent with geological data. We demonstrate that plant geographical range likely exerted a major, under-explored control on long-term climate change.

Temporal and Spatial Assessment of Carbon Flux Dynamics: Evaluating Emissions and Sequestration in the Three Northern Protection Forest Project Areas Supported by Google Earth Engine

Contemporary research on terrestrial carbon exchange processes is paramount for a nuanced comprehension of global and local climatic fluctuations and their interaction with anthropogenic activities. This study delves into the spatiotemporal dynamics of vegetation carbon exchanges within the Three Northern Protection Forest Project Area, leveraging two decades of MODIS NPP data and an innovative NEP estimation model. Our analysis highlights a generally increasing trend in Net Ecosystem Productivity (NEP) from 2000 to 2020, with significant growth in approximately 32.97% of the study area and slight increases in 24.18%. Notably, lower NEP values were found in desert and arid zones, whereas higher values were observed in more vegetated regions like Ningxia, Hebei, Inner Mongolia, and the northeast. The study also assesses the impact of climate variables and land-use changes on NEP, identifying both negative and positive correlations in specific regions. Despite the overall positive trend towards ecological restoration and enhancement, significant uncertainties remain, emphasizing the urgent need for further research to support ecosystem resilience and sustainable management practices.

Dual-purpose crops productivity and small-scale dairy farmers’ food security efforts toward climate variability and change in Benin

Dual-purpose cropping (sowing crops with the intention of both grazing them during vegetative growth and harvesting grain thereafter for household consumption) is certainly a promising way to address challenges face by small-scale dairy farmers in Benin due to climate variability and change. This study evaluated the impact of climate variability and change on dual-purpose crops productivity performances and nutritional values in Benin’s climatic regions. Four dual-purpose crops were studied. They are maize fodder, sorghum fodder, peanut fodder and cowpea fodder. The grain yield across various climate regions and years were assessed. Also fodders samples were analysed according to official methods of AOAC. The results showed that dual purposes crops yield were significantly affected particularly in some years in many regions of Benin by climate parameters variation. The variation of humidity had a negative effect on cereals dual-purpose crops production in Guinean region while the impacts of temperature and rainfall on dual purpose crops were higher in Sudanian region. The model for predicting the resistance of dual-purpose crops to climate variability and change revealed that The Annual Yield of Sorghum Grain was significantly influenced by humidity (P=0.0111), Rainfall (P=0.0374) and Weather station/Region (P=0.0493), as well as by the interaction between temperature and Grain Yield per Hectare (P=0.0423). The annual quantity of maize produced varied significantly with temperature (P=0.00154), humidity, Rainfall (P=0. 00792), Weather station/ Region (P=0.00362). The Annual Yield of Cowpea Grain production varied significantly with Temperature and Humidity (0.0205). Furthermore, temperature, humidity, year and Grain Yield per Hectare significantly affected the Annual Yield of Peanut Grain Produced. Nutritional values of the four studies dual-purpose crops were assessed. The energy values were 0.60 and 0.50 UFL/kg of Dry Matter respectively for sorghum-fodder and maize-fodder, the contents of digestible nitrogenous materials (MAD) were 1 and 0 g/kg of DM respectively for sorghum-fodder and maize-fodder. If the energy values were quite good for cereals fodder, the nitrogen values were very low. This study highlighted the nutritional advantage of leguminous fodders over cereal fodders.

Climate Influences on Latex Yield in South Sumatra, Indonesia

This study addresses the impact of climate variability on latex yield. Field research was carried out in the Indonesian Rubber Research Institute Experimental Field, located in South Sumatra, Indonesia for 2020 to 2022. The study used mature IRR 118 clones of rubber (Hevea brasiliensis) planted in clay loam soil. Latex yields for dry and rainy seasons were compared to obtain the effects of climatic factors. A purposive sampling of latex clone IRR 118 was applied in the field. The results showed that declined rainfall and soil moisture content contributed to the low latex yield during dry season. A declined water availability acts as a limiting factor resulting in decreased latex yield. Latex yield consistently decreased when soil moisture content fell below 21.5%. Based on statistical analysis, the correlation between latex yield and climate factor was 0.36, 0.42, and 0.52 for rainfall, soil moisture content, and evapotranspiration, respectively. Our findings highlight the crucial influence of climatic factors, emphasizing the significance of optimal water availability for latex production.

Assessing the impact of climatic variability on acute respiratory diseases across diverse climatic zones in South Africa

Acute respiratory diseases are a significant public health concern in South Africa, with climatic variables such as temperature and rainfall being key influencers. This study investigates the associations between these variables and the prevalence of acute respiratory diseases in Johannesburg, Cape Town, and Gqeberha (Port Elizabeth), representing distinct climatic zones. Spearman's correlation analyses showed negative correlations in Johannesburg for respiratory disease claims with maximum temperature (r = −0.12, p < 0.0001) and mean temperature (r = −0.13, p < 0.0001), and a negative correlation with daily rainfall (r = −0.12, p < 0.0001). Cape Town demonstrated a negative correlation with maximum temperature (r = −0.18, p < 0.0001) and a positive correlation with rainfall (r = 0.08, p < 0.0001). Utilizing Distributed Lag Non-linear Models (DLNM), the study revealed that in Johannesburg, the relative risk (RR) of respiratory claims increases notably at temperatures below 12 °C, and again at a Tmax between 16 and 23 °C. The risk escalates further at >30 °C, although with a considerable error margin. For Cape Town, a stable level of moderate RR is seen from Tmax 15–24 °C, with a significant increase in RR and error margin above 30 °C. In Gqeberha, the DLNM results are less definitive, reflecting the city's moderate climate and year-round rainfall. The RR of acute respiratory diseases did not show clear patterns with temperature changes, with increasing error margins outside the 22 °C threshold. These findings emphasize the imperative for region-specific public health strategies that account for the complex, non-linear influences of climate on respiratory health. This detailed understanding of the climate-health nexus provides a robust basis for enhancing public health interventions and future research directed at reducing the impacts of climate factors.

Impact of climate variability on moonfish (Mene maculata) catch rate in the waters off southwestern Taiwan

AbstractA commercially significant small coastal forage fish, moonfish (Mene maculata), accounts for almost 98% of Taiwanese purse seine capture, primarily in the southwestern Taiwan region. Research indicates that climate indices affect coastal fish catch and dispersal, while the link between moonfish and climatic variability in this region is still unclear. This study found that the delayed period of Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO) and North Pacific Gyre Oscillation (NPGO) affect moonfish distribution and catch rates off southwestern Taiwan. Understudied are the environmental factors connected to these oscillations and their delayed consequences on moonfish catch rates. We focussed on Taiwan purse seiner capture rates (catch per unit effort or CPUE) of moonfish in southwestern Taiwan from 2014 to 2020 and delayed oscillation occurrences up to 5 years to better understand these processes. CPUE demonstrated a 3 to 4‐year positive connection (r &gt; 0.5) with NPGO, NPO and PDO. The region's moonfish catch rates were most affected by NPGO with a 4‐year lag, followed by a 3‐year lag of PDO and lastly a 4‐year lag of NPO, according to the results of generalized additive models (GAMs). All the three oscillations had the greatest impact on moonfish catchability when a lag of &gt;2 years was present. Between 2014 and 2020, moonfish CPUE fluctuated, peaking in 2019. The climatic parameters that affect moonfish in southwestern Taiwan and the Taiwanese purse seine fisheries catches are shown by this study.

Climatic Variability and Degradation of the Banks of Mayo-Dorbo (South-West Chad)

This article deals with climate variability and degradation of the banks of Mayo-Dorbo, a town located in the southwest of Chad. Degradation is one of the causes creating a socio-economic imbalance for farmers. The objective of this study is to assess the impact of climate variability and bank degradation in the Mayo Dorbo watershed. To carry out this study, the methodology is based on observations, field measurements, and questionnaires. The results show that the 1970s began with negative indices reflecting drought but from the 1990s, the rainfall situation improved with positive rainfall indices. According to field measurements in the dry season and in the rainy season, the degradation process is slow at the start of the rainy season with a decline of 44.5 cm, it reaches its optimum during the floods of the months (July and August) with a retreat on average by 120.5cm where precipitation is significant. The summary of measurements for the 2022 watershed season shows an average retreat of 130. 29cm along the banks. This decline is caused by the abundance of rains 79% soil to 13% and the relief to 8%.

Impact of climate variability and environmental policies on vegetation dynamics in the semi-arid Tigray

Anthropogenic and climate-related phenomena are among the main factors responsible for variations in vegetation structure and composition worldwide. However, studies that integrate the effects of human activities and climate variability in fragile tropical ecosystems, including the semi-arid Tigray region, are lacking. The objective of this study was to examine the effects of climate variability and environmental policy changes on the spatial distribution and pattern of vegetation cover in the semi-arid Tigray region of Ethiopia over the past four decades. We used satellite-based vegetation index (normalized difference vegetation index) and monthly rainfall data to analyze the relationship between vegetation cover and climatic variability. Residual analysis was also used to further disentangle the effects of climatic variability and environmental policy on vegetation cover. The regression analysis (r2 = 0.19) showed an insignificant causal relationship between vegetation dynamics and precipitation over the 41-years study period. This study also highlighted negative impact of the global rise in temperature on vegetation cover due to water stress caused by evapotranspiration. On the other hand, the residual analysis results (r = − 0.55, z-stat = − 11.58, p < 0.01) indicated a strong relationship between vegetation change and environmental policies implemented within the specified study period. Overall, the study revealed that environmental policies had a greater impact than climate variables on vegetation. Policymakers should, therefore, prioritize implementing effective environmental policies to restore degraded ecosystems and mitigate the effects of climate change.

Critical Analysis and Ameliorative Strategies in Combating the Impact of Climate Variability on Pesticide Dynamics and Efficacy

Background: The importance of pesticides in the economy especially in agriculture, cannot be over-emphasized. It is therefore very crucial to uphold and maintain the efficacy of these pest control agents. This study seeks to explore the effect of climate variables on the potency of pesticides. Climate change has emerged as one of the most significant global challenges, disrupting weather patterns and altering ecosystems. These changes pose serious implications for pest dynamics, distribution, and behavior, thereby directly influencing the performance of pesticides. This study analyzed relevant articles related to climate change and pesticides systematically sourced from credible reference databases for a period of 21 years from 2002 to 2023, using the most suitable keywords. Recent scientific research and empirical evidence, analyzing the effects of rising temperatures, altered precipitation patterns, and changing humidity levels on pests and their interactions with pesticide applications were studied. The relevant impact of these effects is seen in reduced agricultural yield, loss of livelihood and source of income, infestation and destruction of agricultural crops, and reduced living standard in the society amongst others. The projected changes include; the development of adaptive agricultural practices and integration of climate-resilient pest management strategies that could improve the efficacy of pesticides. This involves exploring the potential of eco-friendly and biologically-based pest control approaches to reduce the destructive impacts that arise from climate change. These sustainable practices and novel technologies aimed at improving pest control under changing climatic conditions must be encouraged and upheld tenaciously.

Integrating Remote Sensing Data and MODFLOW Modeling for Sustainable Groundwater Resource Management and Monitoring in the Guinea Region, West Africa

Groundwater is vital in ensuring water security, supporting agriculture, and sustaining ecosystems in the Guinea region of West Africa. However, the region faces increasing challenges related to groundwater availability and quality due to population growth and climate change. This research presents pixel-based spatial-temporal trends assessment of groundwater mappings using an integrated approach that combines remote sensing data with MODFLOW modelling. The study focuses on the Guinea region, characterized by diverse topography and hydrogeological conditions. Remote sensing data, including satellite imagery of shallow groundwater storage (GWS), relative humidity, temperature, NDVI, and rainfall, provided valuable insights into observing hydrological cycles and climate changes. The MODFLOW modelling framework was employed to simulate groundwater flow (Hydraulic Heads) and variability of groundwater levels. It enabled the investigation of groundwater recharge and discharge processes, as well as the impact of climatic variations on groundwater dynamics. Furthermore, the trend modelling approach facilitated and revealed that the direction of the western to the northern part of the study area suffered from a depletion rate of groundwater level. The integrated analysis of remote sensing data and MODFLOW modelling highlights the complex interactions between climate change and groundwater resources. This research underscores the importance of proactive and informed groundwater management strategies to ensure the sustainable use of this invaluable resource. By combining remote sensing technology and groundwater modelling, it offers a holistic approach to support evidence-based decision-making for groundwater resource management and monitoring in the Guinea region of the West Africa.

Quantifying the impact of multi-scale climate variability on electricity prices in a renewable-dominated power grid

The variability and intermittency of renewable energy sources pose several challenges for power systems operations, including energy curtailment and price volatility. In power systems with considerable renewable sources, co-variability in renewable energy supply and electricity load can intensify these outcomes. In this study, we examine the impacts of interplay between renewable resource and load co-variability and power system constraints across multiple spatial and temporal scales. We use the New York State power system as our case study, which is undergoing a major transition toward increased renewable generation. We characterize the spatiotemporal co-variability of renewable energy-generating resources and electricity load and investigate the impact of climatic variability on electricity price volatility. We use an accurate, reduced-form representation of the New York power system, which integrates additional wind and solar power resources to meet the state’s energy targets through 2030. Our study shows while diversifying renewables mitigates power variability, short-term fluctuations can still lead to inefficient energy use and substantial curtailment. Annual electricity prices varied by 9%, with price spikes fluctuating by up to 56%, while reflecting a state-wide heterogeneity. Hydropower primarily influences yearly prices, whereas solar and wind mainly affect short-term volatility. Our results underscore the importance of considering both spatiotemporal dynamics and system constraints when planning investments in renewable energy infrastructure.

Impact of Local Climate Variability on Cholera Outbreaks in Bida Metropolis of Niger State, Nigeria

This study assessed local climate variability effects on cholera outbreaks in Bida Metropolis and the environs of Niger State. Bida Metropolis and Environs were purposively sampled. Climatic data (Rainfall and Temperature) of Bida and Environs between the years 2000 to 2020 were collected from the Nigerian Meteorological Agency (NiMET) and the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), while cases of reported cholera were collected from Umaru Saad General Hospital and Federal Medical Center Bida. Regression analysis of the collected data reveals that there is positive relationship between rainfall and cholera cases with an Fvalue of 0.637. This implies that, more cholera cases were reported during the period of high rainfall. However, there is no positive relationship between temperature and cholera cases with a t-value of 0.987. A two-factor regression analysis of the data reveals there is no significant relationship between the climatic elements combined (rainfall and temperature) and cholera cases. Most of the cases of cholera were reported at the beginning of the rainy season between March and April while the cases of cholera were low during the dry season. The study recommended that the government needs to enlighten the people on the need for adequate environmental sanitation with a high level of consciousness at the beginning of the rainy season of the relationship between climatic elements and cholera incidences. There is a need for the people to be enlightened about climate variability, its effects and the means of mitigating or moderating its impact in order to reduce the influence of climate on cholera outbreak.