Rainfall Areas Research Articles

Investigating Rainfall Patterns in South Singhbhum: A Non-parametric Approach Utilizing Mann-Kendall Tests and Sen's Slope Estimator

Aims: The South Singhbhum region is a physical region that experiences monsoon climate and frequent tropical cyclones and has global importance because of its abundant mineral resources like iron, manganese and its mining activities. The agricultural practices mainly depend on rainfall as it is a hilly area. For that reason, sustainable management is necessary to fulfill ecological, industrial, and community water requirements. So, the investigation carried out in this study focuses on the analysis of rainfall patterns within the South Singhbhum region by utilizing non-parametric statistical methodologies with the objective of identifying any discernible trends and variations that have occurred over time. Place and Duration of Study: South Singhbhum region of Odisha is extended between latitude to and longitude to . The area spread over on 45 blocks of Eight district in Odisha, India. The duration of time extended from 2008 to 2022. Methodology: The Mann-Kendall (MK) test is utilized to effectively detect the presence of monotonic trends within both the annual and seasonal rainfall datasets. Furthermore, the sequential Mann-Kendall (S-MK) test is employed to provide a comprehensive understanding of the temporal progression of these identified trends. The Sen's slope estimator is applied to accurately quantify the magnitude of the observed changes in rainfall patterns. Results: The annual study shows a steady declining trend from 2008 to 2021, with a Sen's Slope of 2.0376 and a Z value of 1.0949. However, March is the only month with a positive trend, as seen by its Sen's Slope of 3.0328 and Z value of 1.9708. There are significant variances in Sen's Slope values, which show disparities in the amount of changes, even if negative trends are common. The steepest negative slope is in July (-3.554), and the highest slope is in August (8.981). The S-MK Test was used to determine the start time of the South Singhbhum Region's annual rainfall time series, which revealed statistically declining patterns. It has been observed that the area's rainfall tendency varies frequently. In 2009, 2011, 2017, and 2019, the lines in the u(t) and u'(t) graphs intersect. The rainfall series experienced a reduction from 2008 to 2009, a rise from 2009 to 2011, a decrease from 2011 to 2017, another increase from 2017 to 2019, and a decline starting in 2019. Conclusion: The findings demonstrate that the South Singhbhum Region's rainfall patterns are trending negatively, which makes it clear that quick implementation of comprehensive water resource management methods is necessary to support sustainable development initiatives in the near future.

Three new species of Pelargonium, section Hoarea (Geraniaceae) from the Western Cape Province, South Africa

Pelargonium auriculipetalum, P. leucopetalum, and P. tortandrum are described as new species. All three species are deciduous geophytes with turnip-shaped tubers belonging to section Hoarea. They differ with regard to flower colour, flower and leaf structure, and all of them occur in the winter rainfall area along the west coast of southern Africa. All three species are illustrated and distribution maps are provided for the species.

Effects of seasonal climate forecasts on livelihood outcomes: a case of smallholder farmers in rural Zambia

In as much as seasonal climate forecasts are an essential tool for supporting livelihoods in rainfed agriculture production, the effects of seasonal climate forecasts on income and yield at the agro ecological zone and wealth quartile levels are not sufficiently researched in Zambia. In order to close this gap, we focused on investigating the impacts of using climate information on productivity and income, while using an endogenous switching regression on a representative subnational and national level data from 7241 agricultural households. Using STATA 17 for analysis, the study found that smallholder farmers who integrated seasonal climate forecasts outperformed those who did not have the information, achieving higher yields (421.54 kg/ha). The localized effects of seasonal forecasting by agro ecological zone indicated that low rainfall areas had significant yield gains than other zones, and wealth results for wealth quartiles showed that farmers in higher quartiles had better yield (126.14 kg/ha) and income (1509.44 kg/ha) gains.. This study therefore recommends that policymakers develop policies and strategies that are region-specific to foster climate awareness to and integration of adaptation techniques by farmers. Additionally, the study also recommends the provision of social safety net to less-endowed farmers as well as investing in better early warning systems to enhance participation in using forecasted information for a sustainable future.

Fire, environmental and anthropogenic controls on pantropical tree cover

Explaining tropical tree cover distribution in areas of intermediate rainfall is challenging, with fire’s role in limiting tree cover particularly controversial. We use a novel Bayesian approach to provide observational constraints on the strength of the influence of humans, fire, rainfall seasonality, heat stress, and wind throw on tropical tree cover. Rainfall has the largest relative impact on tree cover (11.6–39.6%), followed by direct human pressures (29.8–36.8%), heat stress (10.5–23.3%) and rainfall seasonality (6.3–22.8%). Fire has a smaller impact (0.2–3.2%) than other stresses, increasing to 0.3–5.2% when excluding human influence. However, we found a potential vulnerability of eastern Amazon and Indonesian forests to fire, with up to 2% forest loss for a 1% increase in burnt area. Our results suggest that vegetation models should focus on fire development for emerging fire regimes in tropical forests and revisit the linkages between rainfall, non-fire disturbances, land use and broad-scale vegetation distributions.

Soil Loss Estimation and Community Awareness Assessment on Integrated Watershed Management: The Case of Lake Hashenge Watershed, Tigray, Ethiopia

Ethiopia is recognized as one of the most severely affected regions by soil erosion globally, posing significant threats to its national economy. This study investigates soil loss estimation and community awareness within the framework of integrated watershed management in the Lake Hashenge watershed, Tigray, Ethiopia. The mean annual rainfall and total drainage area of Lake Hashenge watershed is 988.7 mm and 129km2 respectively. Utilizing the Revised Universal Soil Loss Equation (RUSLE) model, we quantified soil erosion rates and identified critical areas prone to severe soil loss. Our findings indicate significant soil degradation, exacerbated by both natural and anthropogenic factors. The estimated soil loss yield entering Lake Hashenge in the form of sheet and rill erosion was 61.94 tons/ha/year. According to the universal soil loss factsheet, the soil loss estimated in the watershed was categorized as severe, indicating that the lake is in danger. Concurrently, we assessed community awareness and participation in soil conservation practices through surveys and interviews with a multidisciplinary team of researchers. The results reveal a moderate level of awareness and engagement, highlighting the need for enhanced educational and participatory approaches to foster sustainable watershed management. This research underscores the importance of integrating scientific soil loss assessments with community-based integrated watershed management strategies to mitigate soil erosion, protect the lake from sedimentation, and promote environmental sustainability in the region.

Movements of adult and fledgling Carnaby’s Cockatoos (Zanda latirostris Carnaby, 1948) from eleven breeding areas throughout their range

Context Carnaby’s Cockatoo is an endangered species and the subject of a recovery plan. Aims Our study examined movements of adult and fledgling Carnaby’s Cockatoos from 11 breeding populations in southwestern Australia to establish where the cockatoos spent the non-breeding season (February–May) and sub-adult life-stage. Methods Data were collected on point-to-point movements from re-sightings and recoveries of cockatoos individually marked with patagial tags or leg bands. Sites were mostly located in the wheatbelt of Western Australia. Distribution patterns in the breeding and non-breeding seasons, including nesting sites were derived from location data from the Department of Biodiversity, Conservation and Attractions’ Threatened and Priority Database. Key results After breeding, adults and their fledglings moved from breeding areas to higher rainfall areas closer to the west and south coasts of south-western Australia where the food supply is greater and more reliable. Sub-adult cockatoos roam much more widely than adults and utilize foraging habitat not previously recognized as being important to this species. Conclusions Important foraging habitat and locations have been identified for breeding populations in the north and south of the range of Carnaby’s Cockatoos. Implications More conservation attention needs to be focussed on locating additional breeding populations, assessing the viability of these populations, and the extent and condition of their nesting and foraging habitat used during their non-breeding season. Conservation of Carnaby’s Cockatoo depends on the maintenance of remnant native vegetation and revegetation of nesting and foraging habitat throughout its range.

Integrated Geospatial and Analytical Hierarchy Process Approach for Assessing Sustainable Management of Groundwater Recharge Potential in Barind Tract

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 × 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation.

Construction of landslide warning by combining rainfall threshold and landslide susceptibility in the gully region of the Loess Plateau: A case of Lanzhou City, China

Regional forecasting of the landslide rainfall threshold is complex, and the empirical prediction of the rainfall threshold relies on historical statistical data. To obtain the intensity (I) ∼ duration (D) rainfall threshold, Lanzhou City was selected as the research object, and a field investigation, 3S technology, mathematical statistics and a Python language environment were employed to develop a set of automatic rainfall threshold calculation programs. Factor elimination, the information value method, weight of evidence, the frequency ratio, the density method and receiver operating characteristic (ROC) curve were applied to obtain landslide susceptibility, and the I ∼ D rainfall threshold (temporal probability) and landslide susceptibility (spatial probability) were combined to construct regional landslide rainfall threshold warning levels (red, orange, yellow and blue). The results showed the rainfall duration of historical landslides ranged from 0.99 to 216 h, thereinto, it was accounted for 92.78 % with that of between 6 and 96 h, and the rainfall intensity was between 0.11 and 23.6 mm/h, and the α and β of rainfall threshold curve was gradually increased with an increase in the rainfall threshold probability. Additionally, when the rainfall condition probability was the same, landslides occurrence was more frequent in Chenguan District, where there are large areas of bare land, and slope and annual rainfall are less than 10 °and 300 mm, respectively. Fifteen, nine, and six factors were used to obtain landslide susceptibility, and the accuracy of the ROC ranged from 0.78 to 0.80 under different methods and different factor combinations. The spatial distribution of landslide susceptibility was very similar. There were 35, 12, 25 and 108 landslides associated with red, orange, yellow and blue levels, respectively, under the spatial–temporal probability, but 30, 26, 54 and 70, respectively, under temporal probability. Under the different conditions, there were 89, 69 and 22 landslide points with unchanged, increased and decreased warning levels, respectively. The ability and accuracy of rainfall threshold warning and prediction were effectively improved by integrating the temporal and spatial probabilities of the rainfall threshold.

Pathways to adoption and mitigation: A dynamic perspective on good agricultural practices in Rural Malawi

Many researchers have noted the limited adoption of farming management practices that should increase the resilience of smallholder farmers to weather shocks and mitigate their impact on the changing climate in sub-Saharan Africa. In this paper, we evaluate the dynamics of adopting “good agricultural practices” in Malawi, using data from a three-wave panel collected as part of an impact assessment of the Sustainable Agricultural Production Programme, funded by the International Fund for Agricultural Development. In addition to project impacts, we also evaluate additional mechanisms though which farmers may learn about the costs and benefits of different practices. We also evaluate the extent to which climatic conditions – such as being located in drought-prone or heavy rainfall areas – drive adoption decisions. Given the three waves of data, we first look at the range of adoption pathways observed, through the use of an adoption pathway trees. We identify six pathways, noting that adoption is not continuous for a large percentage of households. We then run a multinomial logit to assess the factors that increase the likelihood of falling into different adoption categories vis-a-vis remaining a never adopter. Results suggest that learning through information dissemination, such as through the SAPP project, and wider learning opportunities significantly increased the likelihood of pursuing different adoption pathways, while climatic conditions and learning through observing have limited impacts. On the other hand, for land-intensive management practices, being located in drought-prone areas or being located in areas prone to heavy rainfall increased the likelihood of pursuing different adoption pathways, as did greater ability to learn by observing. Learning by information sharing had limited impacts for land-intensive adoption pathway decisions. Overall, results suggest that information dissemination is important, though the mechanism differs by type of practice promoted. Flexibility in adoption status is an attribute of this system and there is a need to identify and promote practices that are both flexible and increase resilience to climate change.

A semi-quantitative risk model for dairy farms to pinpoint and break source-pathway connections between nutrient sources and open drainage channel sections

IntroductionOn intensive grassland dairy farms in high rainfall areas with poorly drained soils, networks of open drainage channels linked to in-field drainage systems are needed to enable farm operations. Nitrogen and phosphorus point and diffuse sources may be connected to this open drainage channel network along surface and subsurface pathways, with negative impacts upon delivery to the downstream aquatic system.MethodsThis study developed a semi-quantitative risk assessment model by: (1) selecting parameters (categorical or continuous) representing the nutrient transfer continuum and (2) scoring (relative magnitude and impact) the risk of nutrient source connectivity and delivery for every open drainage channel section across seven dairy farms.Results and DiscussionA Risk Index Classification System consisting of low, medium, high, or very high-risk class was developed, with high or above requiring a mitigation plan. Results showed that 23%, 68%, 9% and 0% of all open drainage channels on study farms were identified as low, moderate, high and very high-risk, respectively. A range from 2% to 25% per farm of the open drainage channels was classified as high-risk that potentially needed mitigation, although none was identified as very high-risk. Two-thirds of the high-risk open drainage channels were connected to the farmyards, with potential for high nutrient loss from point sources. A combined approach of source management and targeted breaking of the pathway (e.g., in-channel filters, water diversion bars) may help minimise nutrient losses from high risk open drainage channels on poorly draining soils.

Numerical simulation of the impact of rainfall on tunnel fire

An improved understanding of tunnel fire dynamics is crucial for fire and life safety. This work highlights the significance of Computational Fluid Dynamics (CFD) techniques in addressing the interaction between tunnel fires and rainfall. The discrete phase model based on the Lagrangian approach is applied to simulate raindrops, while the species transport model is used to simulate fuel combustion. A numerical model is established to investigate the impact of rainfall on tunnel fires, and the correctness of the model is verified by comparing the results to model-scale tunnel experiments. Results show that the raindrops increase the local pressure in the rainfall area, creating a pressure difference between the rainfall tunnel portal and the no-rain portal, which leads to longitudinal airflow inside the tunnel. This rain-induced airflow prevents smoke from moving toward the rainfall tunnel portal and decreases the smoke height near the no-rainfall portal. Correlations between the local increased pressure, induced-airflow velocity, and rainfall parameters are proposed. Besides, the model is scaled up to full-size, and real-scale tunnel fires under the influence of rainfall are evaluated. Findings draw attention to tunnel fire dynamics under extreme weather conditions for improved fire safety and evacuation strategies.

Land use & land cover dynamics and its relationship with nitrate pollution in groundwater around inactive mine areas using geospatial techniques, SW part of Cuddapah basin, Southern India

Geospatial maps can show how the ineffective operations of inactive mines affect water and aquifer quality. As such, the purpose of this study is to assess the impact of mining and irrigation on the aquifer ecosystem through the evaluation of LULC and slope maps through the application of Landsat 8 OLI/TIRS and DEM data. A total of 50 groundwater samples were prepared from villages in the close proximity to inactive mines during pre and post monsoon periods in 2021. The results of the analysis revealed alarming statistics, that 14% of groundwater samples exceeded the WHO nitrate limit in pre & post monsoon season, indicating a high-risk in the study area. According to guidelines (USEPA, 2014), 34% in pre-monsoon and 26% post-monsoon of samples exceeded the THI levels for adults and children respectively, indicating non-carcinogenic health risks. In addition, 80% of the samples in both seasons exhibited high NPI values, indicating nitrate contamination associated with blue baby syndrome. From the Geospatial analysis the findings from the LULC classification indicate that there has been a significant increase in cropland area from 2016 to 2021 due to changes in forest land, fallow land, and water resources. These problems have been exacerbated by the expansion of cultivated land, which has increased from 71.1 square kilometers in 2016 to 118 square kilometers in 2021, accounting for 13.1% of the total area. This expansion, coupled with elevated water body resource availability, has compounded the nitrate pollution including in intensely irrigated regions. The slope map analysis revealed that the inactive mines occur at low slope, high rainfall areas and these are compounded by runoff from other sources such as domestic and agricultural wastes. For these matters, sealing and remediating these inactive mines is essential so as to prevent further nitrate leakage.

Revisiting moated sites in Northeast Thailand: integrating spatial analysis with previous and new research insights

Moated sites in northeast Thailand serve as pivotal evidence of human–environment interaction since the Iron Age and have been subject to extensive study. This research conducts a comprehensive examination of moated sites, aiming to analyze their spatial characteristics and relationships with physical environmental factors across various scales, including regional and major river basins. To achieve these goals, advanced GIS tools including average nearest neighbor (ANN) analysis, kernel density estimation (KDE), standard deviational ellipse (SDE) analysis, and the Kruskal–Wallis test are employed. By incorporating a dataset of 468 moated sites and expanding the geographic scope beyond previous studies, this research offers new insights into settlement patterns and environmental interactions. Contrary to earlier interpretations suggesting random dispersion, the study’s findings reveal a clustering pattern, indicating intentional spatial organization by ancient communities. The study also highlights the influence of rainfall on the number of moats, with multiple moats more common in lower rainfall areas and single moats in higher rainfall regions. Additionally, the results observe that sites with more moats are typically found at higher elevations, although no significant correlation between elevation and site size was identified, challenging previous studies' conclusions. These results underscore the importance of local environmental conditions, such as rainfall and elevation, in shaping the distribution and characteristics of moated sites. The findings highlight the complex interplay between environmental factors and human settlement strategies, emphasizing the role of water management in ancient communities.

A Comparative Study of Cloud Microphysics Schemes in Simulating a Quasi-Linear Convective Thunderstorm Case

An investigation is undertaken to explore a sudden quasi-linear precipitation and gale event that transpired in the afternoon of 30 May 2024 over Beijing. It was situated at the southwestern periphery of a double-center low-vortex system, where a moisture-rich belt efficiently channeled abundant warm, humid air northward from the south. The interplay between dynamical lifting, convergent airflow-induced uplift, and the amplifying effects of the northern mountainous terrain’s topography creates favorable conditions that support the development and persistence of quasi-linear convective precipitation, accompanied by gale-force winds at the surface. The study also analyzes the impacts of five microphysics schemes (Lin, WSM6, Goddard, Morrison, and WDM6) employed in a weather research and forecasting (WRF) numerical model, with which the simulated rainfall and radar reflectivity are compared against ground-based rain gauge network and weather radar observations, respectively. Simulations with the five microphysics schemes demonstrate commendable skills in replicating the macroscopic quasi-linear pattern of the event. Among the schemes assessed, the WSM6 scheme exhibits its superior agreement with radar observations. The Morrison scheme demonstrates superior performance in predicting cumulative rainfall. Nevertheless, five microphysics schemes exhibit limitations in predicting the rainfall amount, the rainfall duration, and the rainfall area, with a discernible lag of approximately 30 min in predicting precipitation onset, indicating a tendency to forecast peak rainfall events slightly posterior to their true occurrence. Furthermore, substantial disparities emerge in the simulation of the vertical distribution of hydrometeors, underscoring the intricacies of microphysical processes.

The Diagnostic Analysis of the Thermodynamic Characteristics of Typhoon “Maysak” during Its Transformation Process

This study utilized high-resolution numerical simulation data from the WRF model to conduct a thermodynamic diagnosis of the process by which Typhoon “Maysak” transformed and merged with the Northeast Cold Vortex. The results indicated that the continuous intrusion of cold vortex air and the relative cold advection formed by the typhoon’s movement led to the demise of the typhoon’s warm core structure. The low-level low-pressure convergence and upper-level high-pressure divergence structure disappeared. After the transformation and merging with the Northeast Cold Vortex, the cyclone became cold throughout the entire layer, with a cold center appearing at low levels. During the process of the typhoon’s transformation and merging with the Northeast Cold Vortex, cold air accumulated near the low levels of the cyclone, causing the pseudo-adiabatic potential temperature lines to tilt and resulting in the slanted development of vertical vorticity in the mid-levels of the cyclone. After the typhoon transformed and merged with the Northeast Cold Vortex, the positive vertical vorticity advection at the bottom of the upper-level cold vortex trough promoted the cyclone’s development directly from the mid-levels to the upper levels, while the jet stream at the bottom of the cold vortex trough facilitated the maintenance of the positive vertical vorticity advection. Concurrently, the thermodynamic shear vorticity parameter could describe the typical vertical structure characteristics of the dynamic and thermodynamic fields above the rain area during the typhoon transformation process. In terms of temporal evolution trends, there was a certain correspondence with the development and movement of the ground rain area, and the perturbation thermodynamic divergence parameter had a good indicative effect on the area of heavy rainfall.

Comparative analysis of heavy rainfall area between landfalling typhoon LUPIT (2109) and typhoon LISA (9610)

Based on the ERA5 reanalysis data and the surface observations from automatic weather stations, a comparative analysis has been conducted to investigate the differences in heavy rainfall distributions caused by two landfalling tropical cyclones (TCs): LUPIT (2109) and LISA (9610). The two TCs have similar tracks, intensity and landing points, but show different asymmetric features in their rainstorm location relative to their tracks. The results indicate that the TC rainfall differences are mainly caused by different rainstorm formation mechanisms. The wind shear contributes most to the rainstorm of LISA, while land-sea contrast and topographical effect are the main factors of LUPIT rainstorm. Under the influence of strong environmental vertical wind shear and the weak cold air invasion from the west, the circulation center of LISA tilts westward with height, which cooperates with the low-level water vapor convergence and vertical ascending movement on the western side of the TC center to jointly cause the heavy rainstorm to the west of LISA center. In contrast, LUPIT has weak environmental vertical wind shear and no obvious structure tilting with height. Topographic effect plays a crucial role in causing the heavy rainstorm on the north of TC center. The southeasterly jet is blocked by the Taimu Mountain in the northeastern Fujian Province, and the strong ascending motion caused by the terrain-induced convergence appears to the north of LUPIT center. In addition, the moisture convergence is more pronounced in the north and weaker in the south. The intrusion of weak cold air from the east to the coastal areas of central-northern Fujian, and the moisture-convergence distribution, jointly cause the heavy rainstorm to the north of LUPIT.

Assessing Soybean Yield Potential and Yield Gap in Different Agroecological Regions of India Using the DSSAT Model

The study used the DSSAT model to assess potential soybean yields in different regions of India and validated it under diverse agroecological conditions. The average simulated yield under irrigated conditions was 3794 kg ha−1 relative to the simulated average rainfed yield of 2446 kg ha−1, showing a 35.52% reduction in grain yield due to adverse moisture conditions under rainfed conditions. Relative to simulated yield, the average observed (actual) rainfed yield across 43 districts of India was 1025 kg ha−1, which was 2769 and 1421 kg ha−1 lower than irrigated and rainfed potential yield, respectively. A significant positive correlation was observed between simulated water non-limited yield and solar radiation (R2 = 0.55, p ≤ 0.05). The simulated rainfed grain yield (R2 = 0.66, p ≤ 0.05) had a significant, positive, and curvilinear relationship with growing season rainfall. On the other hand, the actual yield (R2 = 0.008) showed a non-significant relationship with mean crop seasonal rainfall across locations. The gap between simulated yield under irrigated and rainfed conditions is huge at locations with low seasonal rainfall and narrows with increasing rainfall. In addition, the gap between actual yield and simulated yield under rainfed conditions was larger, even in high seasonal rainfall areas. The yield gap under rainfed conditions is due to the non-adoption of improved crop management practices and could be reduced with proper interventions. This includes adapting drought-resistant varieties, conserving rainwater, changing land configuration, and adopting waterlogging-tolerant varieties using improved technology to reduce the soybean yield gap.

Summer Convective Precipitation Changes Over the Great Lakes Region Under a Warming Scenario

AbstractTo understand future summer precipitation changes over the Great Lakes Region (GLR), we performed an ensemble of regional climate simulations through the Pseudo‐Global Warming (PGW) approach. We found that different types of convective precipitation respond differently to the PGW signal. Isolated deep convection (IDC), usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), usually concentrated upwind of the GLR, shift to the downwind region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to increase across almost the entire studied domain, creating a potential environment more favorable for stronger convection systems and less favorable for weaker ones. Meanwhile, changes in the lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, highlighting the significance of these thermodynamic factors in controlling precipitation over the domain. Our results indicate that the decrease in LCL and LCF in areas with increased convective precipitation is mainly due to increased atmospheric moisture. In response to the prescribed warming perturbation, MCSs occur more frequently downwind, while localized IDCs exhibit more intense rain rates, longer durations, and larger rainfall area.

An epidemiological investigation into the reasons for high bovine tuberculosis incidence in cattle herds of the Burren, Ireland, prior to 2020

Herd-level bovine tuberculosis (bTB) incidence was examined in the Burren, an area in the west of Ireland where herd owners practice distinctive transhumance practices, with upland winter grazing. Prior to the initiation of our study in 2020, bTB incidence had for many years been unusually high in the Burren in comparison with the rest of the country, although the most recent figures have come down to being closer to the national average. Using data from the period prior to 2020, we mapped bTB infection in Burren herds alongside a range of indicators thought to have an association with it - herd size, herd density, herd type, cattle movement, and badger (Meles meles) population and control data, as well as rainfall and altitude. We also looked at how summary statistics for these variables differed when Burren herds with a history of bTB were compared to other Burren herds, as well as bTB positive and negative herds from outside the Burren. We found that for many indicators Burren herds would be expected to be low risk when compared to other herds in Ireland. An exception to this was for rainfall: hot spot areas for bTB in the Burren were found in areas of higher rainfall, on average herds in the Burren experienced more rainfall than those outside it, and bTB herds in the Burren experienced higher rainfall than non-bTB herds. Separately, for Burren herds only, a logistic regression model was developed to explain bTB breakdown occurrence using a matched case-control approach. Cases were herds which had experienced a new bTB breakdown between 2015 and 2019 (n = 260) and these were matched on herd type and herd size with the same number of herds not experiencing a breakdown during this period. This showed that, of a range of exogenous variables, rainfall was the most strongly associated with herd-level bTB incidence. These results suggest that high levels of exposure to inclement weather, and/or better environmental survival of Mycobacterium bovis in the environment, may contribute to high bTB rates in the Burren. However, as rainfall showed a highly aggregated distribution, this relationship may be due to an unmeasured factor correlated with it. Mapping and graphical output suggested that, although herd sizes in the Burren were on average lower than nationally, within the Burren they were higher in areas of higher prevalence, suggesting that mechanisms associated with herd size, such as increased contacts between and within herd, and with wildlife, may also play a role.

Crop planning using innovative trend analysis of 62-years rainfall data

The success of climate-smart agriculture in high rainfall zone lies in understanding the rainfall trend and planning or modifying the cropping system for maximum yield. Moisture stress in critical crop growth stages is detrimental to the crop and drastically reduces the yield. Udhagamandalam region in Western Ghats is a high rainfall area and is largely cultivated by vegetable crops. Rainfall trend based crop planning would enhance the crop yield without water stress. A study was carried out at ICAR-Indian Agricultural Research Institute, Dhemaji, Assam focused on assessing the long-term seasonal and monthly rainfall trends of Udhagamandalam region, Tamil Nadu using non-parametric tests and Innovative Trend Analysis (ITA). Daily rainfall of 62 years from 1960–2021 was analyzed with non-parametric tests, viz. Mann-Kendall and modified Mann-Kendall and ITA to find the seasonal rainfall characteristics. Mann- Kendall (3.055) and modified Mann-Kendall (3.055) tests showed a significantly increasing trend in the annual and seasonal monsoonal rainfall. ITA revealed either a significant positive or a negative trend in all the months except February, with the highest trend in June (2.625). In contrast to standard non-parametric tests, ITA detected a significant positive trend in all seasons and annual rainfall, except in cold winters where the trend is negative. The long-term trend analysis results suggest that the ITA is more precise for rainfall trend analysis than standard non-parametric tests and can be used to evaluate hidden variations of rainfall trends. Hence, ITA is recommended for analyzing rainfall trends for crop planning in high-rainfall regions. IT analysis of 62 years of rainfall data of Udhagamandalam suggested that vegetable crop planning can be done by farmers from August–November months as the rainfall trend during this period is assured as an increasing trend of rainfall pattern was observed.