Cycle Of Rainfall Research Articles

Rainfall characteristics over the Congo Air Boundary Region in southern Africa: A comparison of station and gridded rainfall products

Strong meridional rainfall gradients exist between the tropics and subtropics in southwestern Africa, bounded to the north by the moist Congo basin and to the south by the Kalahari Desert. This domain received relatively little scientific attention compared to the rest of southern Africa. In this study, the limited available station data are assessed against six gridded rainfall products (CHIRPS, PERSIANN-CDR, ERA5, GPCC and CPC) for various rainfall characteristics. The nearest neighbour approach was used to match the closest rainfall dataset pixel to each station location, with the assumption that each rain gauge represents observation of various pixels of products, irrespective of product resolution. Results reveal that ERA5, CHIRPS and PERSIANN-CDR tend to represent the monthly rainfall totals and number of rainy days well for most stations although magnitudes and monthly peaks differ. CPC and GPCC tend to perform poorly for magnitudes of rainfall, rainy days and monthly cycles especially for Angolan stations. These products also fail to adequately capture spatial distributions of rainfall, with poor representation of the strong gradients found in the region.Correlations between various gridded rainfall products mostly show good agreement in rainfall totals and rainy days. For early summer (October–November-December) moderate rainy days, ERA5 and CHIRPS products tend to have more days than the stations while CPC and GPCC products perform poorly over Angola and in the south. ERA5 generally overestimates rainfall in mountainous regions, while other products tend to underestimate it. Based on the Simple Daily Intensity Index, it was found that for most of the gridded rainfall products tend to overestimate rainfall during rainy days in the northern and wetter part of the domain. Furthermore, for heavy rainfall, CPC and GPCC tend to compare fairly well with stations in the southern and eastern parts of the domain but poorly with those in the western parts. PERSIANN-CDR tends to underestimate heavy rainy days for most stations in early and late summer (January–February-March-April). However, CHIRPS compares well at several stations, while ERA5 performs well for stations located in the south. This study helps provide useful guidance in choosing suitable rainfall gridded datasets for assessing long term rainfall cycles, daily rainfall characteristics as well as extremes over southwestern Africa.

Trends and cycles in rainfall, temperature, NDVI, IOD and SOI in the Mara-Serengeti: Insights for biodiversity conservation

Trends and cycles in rainfall, temperature, NDVI, IOD and SOI in the Mara-Serengeti: Insights for biodiversity conservation

Triple oxygen isotope variability of precipitation in a tropical mountainous region

We present one year of δD, δ18O, d-excess, and Δʹ17O data from monthly precipitation at a Caribbean coastal site in Panama and from tap waters across the country to constrain geographic, climate, and moisture source controls on isotopic variability and better understand the sources and mechanisms of precipitation in Central America, a region facing significant modifications to the annual rainfall cycle due to climate change. Monthly precipitation δD ranged from –52.2 to +14.3 ‰, δ18O from –7.6 to +0.4 ‰, d-excess from +7.1 to +11.6 ‰, and Δ′17O from +11 to +29 per meg. Rainy season precipitation samples were found to have lower δD, δ18O, and d-excess due to Rayleigh distillation during the condensation and rainout of Pacific moisture over the central cordilleras, which results in decoupling between d-excess and Δ′17O. Outlier Δ′17O values during peak dry and rainy months may reflect seasonal changes in water vapor sourcing, from Caribbean to Pacific and/or locally recycled moisture, or may be a result of organic contamination. Tap water δD ranged from –82.3 to –14.3 ‰, δ18O from –11.6 to –2.4 ‰, d-excess from +4.3 to +12.2 ‰ and Δ′17O from –2 to +84 per meg. Tap water δD and δ18O values increase eastward due to lower orographic effects and Pacific and locally recycled moisture contributions to rainfall and greater secondary evaporation. Tap water d-excess and Δ′17O values are also de-coupled but lack clear spatial trends and controls. The results of this study indicate the promise of adding Δ′17O to the isotopic toolkit in tropical mountainous regions with complicated water cycling dynamics and provide a baseline for future triple oxygen isotope investigations.

Rainfall cycle causes the inter-seasonal instability of ecosystem service trade-offs: A case study in the Tana River Basin, Kenya

As a crucial climate condition, the inter-seasonal rainfall cycle directly impacts the livelihoods and productivity of billions residing in monsoon regions. However, there is still limited understanding regarding its effects on trade-offs among ecosystem services (ES). This knowledge gap may impede the sustainable development of human well-being in these regions. In this study focused on Tana River Basin, a representative monsoon region, we assessed the seasonal supply and trade-offs of three ESs including water yield (WY), soil conservation (SC), and net primary production (NPP), which are closely linked to local human well-being. To comprehend the driving mechanism of inter-seasonal variation, the influential factors were identified using the Geographical Detector Model. Furthermore, by quantifying the seasonal trade-off intensity among three ESs, the managemental optimization priority areas were identified.The results showed that (1) all three ES supply presented an increasing trend from 2000-2020. Seasonally, both the supply and trade-offs of ESs were significantly enhanced in the rainy seasons, with spatial heterogeneity observed in the response to inter-seasonal rainfall cycle. (2) Natural condition factors presented stronger influence on the seasonal variation of ES trade-offs, which is crucial to consider the comprehensive hydrological response resulting from vegetation growth as the foundation for these seasonal variations. For the WY-SC trade-off, precipitation was identified as the primary influential factor, while vegetation coverage impact on SC-NPP and WY-NPP trade-offs. Higher precipitation and vegetation coverage would intensify the trade-off between corresponding ESs. (3) Regarding the spatial distribution of seasonal instability, several sub-watersheds aggregated in the midstream hill region were identified as the primary optimized zones, more flexible management strategies should be implemented preferentially. The findings contribute to a better understanding of how the inter-seasonal rainfall cycle impact on the ES trade-offs, supporting effective ecosystem management in monsoon regions.

Synoptic Influences on the Diurnal Cycle of Rainfall over Western Puerto Rico

Abstract The objective of this study is to understand rainfall processes over tropical islands by identifying synoptic conditions that influence the diurnal cycle of rainfall over western Puerto Rico. Summer rainfall over Puerto Rico is dominated by its afternoon peak, yet there is large variability in its behavior that remains challenging to predict. We use radiosonde and airborne data collected through the NASA Convective Processes Experiment—Aerosols and Winds (CPEX-AW) field campaign (August–September 2021) to achieve our objective, in addition to the network of surface station data over the island. We find that the background wind speed and humidity have strong influences on afternoon rainfall through different mechanisms. A stronger background wind inhibits afternoon rainfall likely by reducing land–sea thermal contrast and weakening sea-breeze convergence over the island. At the same time, an inversion layer often forms with a stronger background wind that further inhibits deep convection. When the background wind is weak and sea breezes are prominent, afternoon rainfall increases exclusively over the island, while limited rainfall appears over the surrounding ocean. However, enhanced rainfall still occurs over the island with weak sea breezes if humidity is high, accompanied by enhanced rainfall over the surrounding ocean due to the offshore movement and development of convective storms. The sources of variability in background wind and humidity are mostly independent, resulting in a wide range of synoptic conditions and associated effects on the island rainfall. This expanded understanding of the mechanisms causing variability of diurnal rainfall can lead to improved forecasts over Puerto Rico and other tropical islands.

Effect of crack depth on the initiation and propagation of crack-induced sliding in a paleosol area on a loess slope: Three-dimensional investigation based on model testing and laser scanning

On the Chinese Loess Plateau (CLP), crack-induced sliding in paleosols triggers retrogressive slope collapse, compromising the long-term stability of loess slopes. Establishing a quantitative relationship between crack depth and slide size is key to elucidating the progressive evolution of crack-induced sliding in paleosols; however, research on this topic is scarce. In this study, a model test was conducted on a paleosol slope subjected to five drying–rainfall cycles. Three-dimensional (3D) laser scanning technology was employed to accurately quantify the variations in crack depth and slide size, and water content sensors were embedded to monitor the preferential flow changes induced by these cracks. Results reveal that crack depth plays a pivotal role in initiating and controlling the propagation of crack-induced sliding in paleosols by influencing the preferential flow capacity through cracks. In the slide initiation stage, a critical crack depth capable of triggering sliding by inducing a sufficiently significant preferential flow and large saturation zones was identified. The depth at which sliding occurs can be expressed as a variable dependent on crack depth based on the single triggering effect of cracking on sliding. Once a crack-induced slide is initiated, the combined action of prior sliding events and current crack propagation accelerates the subsequent sliding in terms of increased size and varying spatial locations by influencing the preferential flow capacity and sliding force values. A comprehensive empirical formula was established to characterize the depth of crack-induced slides, considering the dominant influence of crack depth and slope gradient on sliding development at this stage of slide evolution. Our findings emphasize the pivotal role of crack depth in triggering progressive crack-induced sliding in paleosols, thereby providing valuable insights for soil conservation in paleosol areas on loess slopes on the CLP.

Climate Profile Over Jeldu Woreda of West Shewa Zone, Oromia, Ethiopia

Identifying the climate profile of an area is essential for effective water resource management, agricultural planning and disaster preparedness. This study focuses on characterizing rainfall patterns and identifying the variability of Jeldu woreda in Oromia, Ethiopia. Previously and recently, little study tried to show the woreda profile, which did not bases on station data properly. Forty years (1981-2020) of stations’ rainfall and temperature data were utilized. The study area had natural forest, highland and mid land with varying topography. Based on the annual rainfall cycle, the woreda had bi-modal rainfall types, with the peak of the year being July. Statistical methods and python script were applied to identify the climate profile. The results show that main rainy seasonal rainfall starts on average from 12-14 June and ceases averagely around 10-15 October. During second rainy period, the rain starts from 25 February to 10 March. The mean annual rainfall of woreda is 1395.1 mm, and the average maximum temperature is 19.5°. Kiremt contributes the highest percent, which is more than 64 % of the annual total rainfall. The 1987 and 2015 were the driest years, and 1996 and 2010 is the wettest during kiremt, 1987 and 2010 the wettest, and 1999 and 2015 the driest during Belg. Seasonal rainfall had a regular to moderate precipitation concentration over woreda. Identifying the causes of unseasonal rainfall that happened during dry season over the study area can help to decrease weather hazard during the season.

A New Paradigm for Active–Break Cycle in the Indian Summer Monsoon

Abstract A multichannel singular spectrum analysis of 121 years of daily rainfall over India and 43 years of outgoing longwave radiation and horizontal wind has revealed two dominant intraseasonal oscillations (ISOs) that describe the space–time variability of monsoon rainfall. The two nonlinear oscillations are not perfectly periodic but exhibit broadband spectra centered at 45 and 28 days. These modes have coherent and near-regular spatial structure and temporal variations. This study posits that the two nonlinear oscillations provide a consistent and comprehensive framework to study the variability and predictability of intraseasonal rainfall variations. The active and break cycles of monsoon rainfall over India have been traditionally defined by using an arbitrarily chosen duration of persistence of arbitrarily chosen amount of rainfall averaged over an arbitrarily chosen area. This study shows that the phases of the two objectively derived modes of variability provide an objective method for defining the active and break cycles. The two ISOs are further shown to make negligible contribution to the seasonal mean rainfall and its interannual variability. This study proposes that the investigations of the origins of these nonlinear modes, and modulations of their amplitudes and phases, provide a new paradigm for future research on validation and predictability of intraseasonal variations in climate models.

Using the Observed Variations of the Start Date of the Rainy Season over Central America for Its Reliable Seasonal Outlook

Abstract We introduce a simple method to define the start and the end of the rainiest part of the year as the first and the last day of the year when the daily rain rate is more or less than the annual mean climatological rain rate for a region or at a given grid point of the rainfall analysis, respectively. A novelty of this work is the adoption of a perturbation technique to generate a total of 1001 ensemble members to account for observational and analysis uncertainties. This allows for a probabilistic estimate of the start and retreat dates of the rainy season at the granularity of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), version 6, rainfall analysis over Central America. The seasonal cycle of the IMERG rainfall analysis is also found to verify with in situ observations in the region. Many large-scale climate drivers affect regional rainfall, often with complex interactions that affect the onset date, retreat date, and magnitude of the seasonal rainfall cycle, making it difficult to predict the length or total quantity of seasonal rainfall using climate drivers alone. Once an onset date is established, however, this metric alone can be more indicative of both the length and total seasonal rainfall anomaly than predicting how the climate drivers will interact to affect the quantity and duration of upcoming seasonal rainfall. The local relationships of the start date with seasonal length and rainfall anomaly are leveraged to produce effective seasonal outlooks of the rainy season for the region by just monitoring the start date variations. Significance Statement The start date and retreat date of the rainy season in Central America are defined every year, precisely to a specific date from our proposed definition of it. This is possible because the region exhibits a strong seasonality of the rainfall. As a result, the year-to-year (interannual) variation of the seasonal rainfall during the rainy season is also determined by the variations in the length of the season that are usually overlooked in fixed calendar seasons. We define the start or retreat date of the rainy season as the first or the last day of the year when the daily rain rate exceeds or falls below the average daily rainfall from 2001 to 2022, respectively. We also find that both start and retreat date variations independently influence the length and total seasonal rainfall of the rainy season. Consequently, these relationships are leveraged to provide an outlook of the forthcoming rainy season from the diagnosis of the variations of its onset date, which is shown to be an effective predictor with significant useful seasonal prediction skills.

Impacts of the new UM convection scheme, CoMorph-A, over the Indo-Pacific and Australian regions

A new convection scheme, ‘CoMorph-A’, has been introduced into the latest UK Met Office coupled (GC4) and atmosphere-only (GA8) models. In this study, the impact of CoMorph-A is assessed in atmosphere-only Atmospheric Model Intercomparison Project simulations, as well as in sets of initialised 28-day forecasts with both the coupled and uncoupled models. Initial results show improvements over the Indo-Pacific and northern Australian regions, as well as improvements in the rainfall bias, Madden–Julian Oscillation simulation and prediction, tropical cyclone forecasts and the diurnal cycle of rainfall over the Maritime Continent. The improvements are mostly consistent across the initialised forecasts and the climate simulations, indicating the effectiveness of the new scheme across applications. The use of this new convection scheme is promising for future model configurations, and for improving the simulation and prediction of Australian weather and climate. The UK Met Office is continuing to develop CoMorph and will soon release version B.

Variation in under-5 mortality attributable to anomalous precipitation during El Niño–Southern Oscillation cycles: Assessment of the intertemporal inequality in child health

ObjectiveTo explore the health effect of anomalous precipitation on deaths among children younger than 5 years (under-5 deaths) in low- and middle-income countries (LMICs). MethodsBased on a sample of 1.6 million children from 56 LMICs, we conducted a sibling-matched Cox regression model to examine the association between under-5 deaths and anomalous precipitation in annual average. We established a nonlinear exposure–response function to characterize heterogeneity in the association, and checked its robustness by conducting a few sensitivity analyses. To illustrate absolute risks embedded in the complex climate-health linkage, across 100 LMICs, we calculated burden of under-5 deaths attributable to anomalous precipitation, and showed how the burden varied with the El Niño–Southern Oscillation (ENSO), a well-known predictable climate pattern affecting the rainfall cycle. We focused on the intertemporal inequality in the attributable burden. ResultsThe epidemiological analyses showed a robust negative association between anomalous precipitation and under-5 deaths for arid areas, and a potentially positive association for humid areas. The anomalous precipitation was significantly associated to an intertemporal inequality in under-5 mortality. Across the 100 LMICs, 26.7% or 134 million under-5 children lived in ENSO-sensitive areas. Among them, anomalous rainfall decreased under-5 deaths by 46,246 (CI: 24,599–68,703) during an El Niño year (October 2015 to September 2016), and increased under-5 deaths by 77,505 (CI: 55,890–99,815) during a La Niña year (March 2008 to February 2009) across the 100 LMICs. ConclusionAnomalous precipitation can lead to intertemporal inequality in child health. Healthcare resources should be allocated according to predicted variability in precipitation, such as ENSO-mediated extreme rainfall.

Australian Summer Monsoon: Reanalyses Versus Climate Models in Moist Static Energy Budget Evolution

AbstractThe Australian summer monsoon (ASM) influences the tropical hydro‐climate of Northern Australia during the extended summer months (October–April). Despite advances in understanding the ASM, climate models vary widely in their depiction and projections of its future behavior remain uncertain. This study investigates the moist static energy (MSE) budget and examines the gross moist stability (GMS) evolution throughout the monsoon cycle using two reanalysis data sets. We then assess the ability of Atmospheric Modeling Intercomparison Project (AMIP) simulations of climate models to reproduce not only the monsoon seasonal cycle of rainfall but the associated mechanisms revealed by the budget analysis. The budget analysis shows a strong influence of the regions to the north and west of our study area for the import of moisture and export of energy into and away from the ASM. We find that models reproduce this influence qualitatively, but not quantitatively. As in previous studies, we identify two major regimes of the GMS associated with the absence (higher GMS) or presence (lower GMS) of convection. Whilst climate models are able to distinguish the two regimes, they significantly overestimate the GMS in convectively active periods, owing largely to profile of ascent that is too top heavy. Models with more realistic precipitation do not consistently offer more accurate representations of dynamic processes, as evaluated by the MSE budget and GMS. This highlights limitations in assessing models based solely on single variables. To enhance the generalizability of these findings, future studies should employ models without prescribed sea surface temperatures.

An investigation into the physical factors that control slow mass movements

The behavior of slow mass movements like soil creep is well known to be governed by soil composition, slope, and cycles in temperature and rainfall. However, their magnitude and importance vary dramatically in often unpredictable ways, with important consequences for creep rate and infrastructure damage prediction. Here, we present long-term (2015–2022) creep measurements for four regions of the UK characterized by intense mass movement activity but different bedrock lithologies. We also obtained co-located temperature and precipitation time series over this period, as well as local measurements of slope and soil thickness and composition. Our goal was to deconvolve the relative importance of each observable on creep behavior. Our results imply that parent lithology governs first-order creep rates indirectly via hillslope repose angles and soil thickness and composition. Rates of ground movement on peat and sandstone soils are dictated by annual fluctuations in precipitation and temperature, respectively. By employing a simple error-minimizing regression routine, we demonstrate how creep rates can be predicted in these settings as a function of climatological observables. Over thinner limestone and thicker clay soils, however, our model fails: in these settings, we suggest that creep behavior is instead dominated by variations in regolith thickness, and slope and clay mineral content, respectively.

BAYESIAN NEURAL NETWORK RAINFALL MODELLING: A CASE STUDY IN EAST JAVA

Rainfall is an important parameter in meteorology and hydrology, and it measures the amount of rain that falls from the atmosphere to the ground surface in liquid form. However, in the process of measuring rainfall, changes in the rainfall cycle sometimes occur due to climate change, global warming, and other factors. Therefore, this research aims to model daily rainfall using the Bayesian Neural Network (BNN) approach, combining the Bayesian Method and Artificial Neural Network (ANN). ANN is suitable for rainfall models that have intermittent characteristics. Meanwhile, the Bayesian method provides advantages in producing model parameter inferences that provide uncertainty measurements in predictions. BNN is expected to deliver better daily rainfall predictions than ANN. This research used daily rainfall data in East Jawa, and the results show that the Bayesian Neural Network produces better rainfall predictions when describing rainfall in East Java. These predictions will be very useful for the government and the people of East Java province to prevent flooding. Also, with rainfall predictions, people will know more about what crops should be planted during the rains.

Optimization of CMIP6 models for simulation of summer monsoon rainfall over India by analysis of variance

AbstractThe advent of weather and climate models has equipped us to forecast or project monsoon rainfall patterns over various spatiotemporal scales; however, utilizing a single model is not usually sufficient to yield accurate projection due to the inherent uncertainties associated with the individual models. An ensemble of models or model runs is often used for better projections as a multimodel ensemble (MME). This study analyzes the accuracy of MME in simulating the Indian summer monsoon rainfall (ISMR) variability using Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. The results highlighted that although the MME primarily reproduces the observed pattern and annual cycle of rainfall, significant biases are noted over homogeneous meteorological regions of India, except northeast India. To overcome this issue, an analysis of variance (ANOVA) and post hoc statistical tests are employed to identify a group of models for which the modified MME gives a better estimate of rainfall and reduces the bias significantly. Our findings underscore the potential of ANOVA and post hoc tests as a practical approach to enhancing the accuracy of multimodel ensemble rainfall for the assessment of model projections.

Rainfall analysis and deriving design storm for hydrological modelling of Koyna dam catchment area in Maharashtra state of India

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event.In this study, 40 years (1982–2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series.From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment.

Effect of freeze-thaw frequency plus rainfall on As and Sb metal(loid)s leaching from the solidified/stabilized soil remediated with Fe-based composite agent

The composite agent of ferrous sulfate, fly ash, and calcium lignosulfonate (FFC) can remediate the soil contaminated by As and Sb under cyclic freeze-thaw (F-T) via stabilization/solidification (S/S). However, the impact of high-frequency F-T cycles on the leaching behavior and migration of As and Sb in FFC-treated soils remains unclear. Here the leaching concentrations, heavy metal speciation (Wenzel's method), and Hydrus-1d simulations were investigated. The results showed that FFC effectively maintained the long-term S/S efficiency of arsenic remediation subject to an extended rainfall and freeze-thaw cycles, and stabilized the easily mobile form of As. The short-term S/S effect on Sb in the remediated soils suffering from F-T cycles was demonstrated in the presence of FFC. In a 20-year span, the mobility of Sb was affected by the number of F-T cycles (FT60 > FT20 > FT40 > FT0) in soil with a depth of 100 cm. As leaching progressed, FFC slowed the upward proportion of adsorbed As fractions but converted parts of the residual Sb to the form of crystalline Fe/Al (hydro) oxide. Moreover, the adsorption rate and capacity of As also preceded that of Sb. Long-term curative effects of FFC could be observed for As, but further development of agents capable of remedying Sb under cyclic F-T and long-term rainfall was needed. The predictive results on the migration and leaching behavior of heavy metals in S/S remediated soils may provide new insight into the long-term assessment of S/S under natural conditions.

Evaluation of the Effect of De-icing Chemicals on Performance of Airport Concrete Pavement under Freeze-Thaw Cycles

Weather conditions such as rainfall and freeze-thaw cycles affect the pavement performance of airports; therefore, methods such as using de-icing chemicals are considered in order to maintain the normal condition of the airport runway. In addition to the above factors, de-icing chemicals play an important role in pavement performance and the damage caused to it due to their chemical nature. Therefore, investigating the effect of de-icing chemicals and determining the appropriate material to maintain the airport's pavement is a priority for engineers. In this study, the effect of three de-icing chemicals, sodium chloride, potassium acetate, and ethylene glycol (at concentrations of 23.3%, 49%, and 69.07%, respectively) on skid resistance (The British Pendulum Test (BPT) and The Road Test Machine (RTM)) and the mechanical properties (Compressive Strength Test) of the concrete under Freezing and Thawing Cycle were investigated. The BPT test results showed that sodium chloride resulted in better skid resistance than other chemicals when the number of cycles is more than 100 cycles. This result was also obtained for all cycles in the RTM test. Also, ethylene glycol was not suitable for improving skid resistance based on BPT and RTM tests. Furthermore, the results of the compressive strength of concrete mixtures showed that the de-icing chemicals reduced the compressive strength of concrete mixtures. Based on all the results, sodium chloride had better results than other chemicals.

Revisiting the Seasonal Cycle of Rainfall over Central Africa

Abstract The intertropical convergence zone (ITCZ), with its twice-annual passage over central Africa, is considered as the main driver of the rainfall seasonality. In this ITCZ paradigm, high rainfall occurs over regions of large low-level convergence. But recently, this paradigm was challenged over central Africa. Here, we show that a shallow meridional overturning circulation—driven by surface conditions—plays a thermodynamical control on the rainfall seasonality over central Africa. Indeed, due to the local evaporative cooling effect, the foot of the ascending branch of Hadley cells occurs where the temperature is the warmest, indicating a thermal low. This distorts the southern Hadley cell by developing its bottom-heavy structure. As result, both shallow and deep Hadley cells coexist over central Africa year-round. The deep mode is associated with the poleward transport of atmospheric energy at upper levels. The shallow mode is characterized by a shallow meridional circulation, with its moisture transport vanishing and converging in the midtroposphere rather than at lower troposphere. This midtropospheric moisture convergence is also the dominant component that shapes the vertically integrated moisture flux convergence, with little contribution of African easterly jets. This convergence zone thus controls the precipitating convection. Its meridional migration highlights the interhemispheric rainfall contrast over central Africa and outlines the unimodal seasonality. On the other hand, forced by the Congo basin cell, the precipitable water regulates the deep convection from the vegetated surface of Congo basin, acting as a continental sea. This nonlinear mechanism separates the rainfall into three distinct regimes: the moisture-convergence-controlled regime, with convective rainfall exclusively occurring in the rainy season; the local evaporation-controlled regime with drizzle in the dry season; and the precipitable-water-controlled regime, with exponential rainfall increase in the dry season.

A panel data study on the effect of climate change on life expectancy

The life and health of billions of people is endangered by climate change today. Life expectancy is generally used as the best metric for assessing the population health status of a nation. Against this backdrop, this paper investigates the effect of climate change on life expectancy using the panel data model. To do so, imprimis, this paper develops a conceptual framework linking direct and indirect pathways by which climate change affects health. The direct pathways are through weather variables and natural disasters. The indirect pathways are mediated through economic systems and ecosystems. Then this paper estimates the effect of climate change on life expectancy using cross-national data from 191 countries covering the period 1940–2020 and employing the fixed-effect method. The finding of this study suggests that if the annual average temperature increases by 1°C, then the life expectancy at birth will decline by 0.44 years. Moreover, the temperature rise will further negatively impact life expectancy by interacting with the rainfall cycle. If the composite climate change index, an index of the geometric mean of temperature and rainfall, increases by 10 points, the life expectancy at birth will decline by 0.50 years. Moreover, climate change will disproportionately reduce the life expectancy of females more than the life expectancy of males. A negative relationship between a composite climate change index and life expectancy underscores the urgency of addressing climate change as a public health crisis. Mitigation efforts to reduce greenhouse gas emissions and adapt to changing conditions are essential to minimize the health risks associated with climate change. Thus, countries should come forward with prompt initiatives to contain global temperature rise and protect the health of the population on the verge of climate change.