Climatic Zones Research Articles

A protocol and analysis of year-long simulations of global storm-resolving models and beyond

We propose a protocol to evaluate and analyze year-long simulations of global storm-resolving models (GSRMs). The proposed protocol complements an earlier 40-day simulation protocol under the DYAMOND (DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains) project to allow the analysis of the seasonal cycle and associated climatic relevant phenomena. This intercomparison aims to reveal how GSRMs, which can simulate mesoscale convective systems (MCSs) in the global domain, reproduce atmospheric large-scale structures related to convection beyond month-long simulations. The intercomparison for one-year simulations is conducted by either atmosphere-only models or atmosphere–ocean coupled models with atmospheric horizontal mesh sizes less than 5 km. We recommend the continuous four seasons from March 2020 to February 2021 as a target period for the intercomparison but with options for many groups to join more flexibly. The output variables are collected at 0.25° resolution, and archives of a small set of native grid variables are encouraged to analyze tropical cyclones and MCSs. Through the proposed global storm-resolving simulation, we will evaluate the climatological distributions of the atmospheric large-scale circulations, such as the Intertropical Convergence Zone (ITCZ), monsoon, midlatitude jets, their time evolution, and the upscale impacts on them. We present sample analyses from a one-year simulation using the 3.5 km mesh Nonhydrostatic Icosahedral Atmospheric Model (NICAM), revealing the realistic zonal contrast of tropical precipitation, no double ITCZ structure, the reasonable midlatitude jet position and intensity but a weak bias of storm track activities, and a warm bias over the Eurasia during boreal winter. We also clarify the cross-scale interaction, such as the effects of cold pools on mean precipitation over the Maritime Continent through the precipitation diurnal cycle and the effects of resolved gravity waves on midlatitude mean flows. The proposed one-year simulation protocol is referred to as the “Sendai Protocol.” This protocol is not unique or definite for evaluating GSRMs; we prospect a hierarchical set of experiments from short-term to multi-year simulations as GSRM intercomparisons.A protocol and analysis of year-long simulations of global storm-resolving models. Daisuke Takasuka, Masaki Satoh, Tomoki Miyakawa, Chihiro Kodama, Daniel Klocke, Bjorn Stevens, Pier Luigi Vidale, Christopher R. Terai. Progress in Earth and Planetary Science. Sample analysis of a one-year experiment with the global storm-resolving model, Nonhydrostatic Icosahedral Atmospheric Model (NICAM). Top: seasonal mean precipitation obtained from the (left) the Global Precipitation Climatology Project (GPCP) product and (right) 3.5-km NICAM simulation for (a, b) March-April-May, (c, d) June-July-August, (e, f) September-October-November, and (g, h) December-January-February in 2011-2012. Bottom: time-latitude diagrams of the monthly mean precipitation averaged from 160°E to 140°W over the Pacific for the (left) GPCP product and (right) 3.5-km NICAM simulation

Vernacular Iranian housing as a sustainable model of functional and aesthetic comfort in contemporary passive dwellings

In the recent years, with global warming and the change in climatic characteristics, buildings and interior arrangements in dry and cold climates, that previously did not have cooling problems, now require built and pre-planned cooling systems as well as heating. On the other hand, the enormous increase in energy consumption and the rapid depletion of energy resources causes concern and anxiety for future generations. In this regard, utilizing natural resources and incorporating sustainable solutions into building design are critical. Vernacular technical systems and design ideas can still be accepted and applied to create sustainable solutions. In this context, design strategies for energy efficiency and provision of physical and spatial comforts could be considered based on traditional architecture. In this study, sustainable building design solutions that have been used in Iran’s vernacular houses, which has four distinct climate zones, aimed to create a paradigm for the general modern passive house designs in the global context. Traditional Iranian residential architecture incorporates architectural features for physical, spatial, and climatic needs, as well as aesthetic comfort for the user. In this manner, user needs and interior space organization in vernacular residential architecture can be considered as a sustainable housing model that meets today’s technology requirements in passive house design.

Model‐based impact analysis of climate change and land‐use intensification on trophic networks

There is well‐established evidence that land use is the main driver of terrestrial biodiversity loss. In contrast, the combined effects of land‐use and climate changes on food webs, particularly on terrestrial trophic networks, are understudied. In this study, we investigate the combined effects of climate change (temperature, precipitation) and land‐use intensification on food webs using a process‐based general mechanistic ecosystem model (‘MadingleyR'). We simulated the ecosystem dynamics of four regions in different climatic zones (Brazil, Namibia, Finland and France) according to trait‐based functional groups of species (ectothermic and endothermic herbivores, carnivores and omnivores). The simulation results were consistent across the selected regions, with land‐use intensification negatively affecting endotherms, whereas ectotherms were under increased pressure from rising temperatures. Land‐use intensification led to the downsizing of endotherms, and thus, to smaller organisms in the food web. In combination with climate change, land‐use intensification had the greatest effect on higher trophic levels, culminating in the extinction of endothermic carnivores in Namibia and Finland and endothermic omnivores in Namibia. Arid and tropical regions showed a slightly higher response of total biomass to climate change under a high‐emissions scenario with rising temperatures, whereas areas with low net primary productivity showed the most negative response to land‐use intensification. Our results suggest that 1) further land‐use intensification will significantly affect larger organisms and predators, leading to a major restructuring of global food webs. 2) Arid low‐productivity regions will experience significant changes in community composition due to global change. 3) Climate changes appear to have slightly greater effects in tropical and arid climates, whereas land‐use intensification tends to affect less productive environments. This paper shows how general ecosystem models deepen our understanding of multitrophic interactions and how climate change or land‐use drivers affect ecosystems in different biomes.

Quantitative method and influencing factors analysis of demand response performance of air conditioning load with rebound effect

AbstractUnder the emerging trend of the new power systems, enhancing the energy flexibility of air conditioning loads to promote electricity demand response is crucial for regulating the real-time balance. As a typical temperature-controlled loads, air conditioning loads can generate rebound effect when participating in demand response, resulting in sudden load increases and posing risks to grid security. However, the existing research mainly focuses on the energy flexibility, which leads to an imperfect demand response mechanism and thus affects the optimal scheduling strategy. Therefore, the study proposes a comprehensive quantification method in view of rebound effect for the demand response performance of air conditioning loads, by using probability distribution, Latin hypercube sampling, Monte Carlo simulation, and scenario analysis methods. The demand response event was divided into response phase and recovery phase, and by considering energy flexibility during the response phase and rebound effect during the recovery phase, three dimensionless evaluation indexes for comprehensive demand response performance were constructed. Using this quantification method, the impact patterns of three types of random variables were compared, including meteorological, design variables, and control variables. Additionally, considering the differences in building types (office and hotel buildings) and building capacities (small, medium, and large), the effectiveness of air conditioning load participation in demand response measures in different building application scenarios was explored. The results show that the influence of the design variables on the response performance is less than that of the control variables, but significant, reaching 45% compared to the control variables. Moreover, the influence varies with building type, capacity and climate zone, and building demand response design has more potential in the following scenarios: the cold climate, the hot summer and cold winter climate, the medium building and the hotel building.

Global Warming and Landscape Fragmentation Drive the Adaptive Distribution of Phyllostachys edulis in China

Global warming and landscape fragmentation significantly affect the spatial distribution pattern of bamboo forests. This study used high-resolution data and an optimized MaxEnt model to predict the distribution of Phyllostachys edulis in China under current and future climatic conditions in three climate scenarios (SSP126, SSP370, SSP585), and analyzed its land use landscape fragmentation using landscape indices. The results indicate that Phyllostachys edulis currently has potentially suitable habitats majorly distributed in East China, Southwest China, and Central South China. The precipitation of the driest month (BIO14) and the precipitation seasonality (BIO15) are the key environmental factors affecting the distribution of Phyllostachys edulis. In the next three scenarios, the adaptive distribution area of Phyllostachys edulis is generally expanding. With an increase in CO2 concentration, the adaptive distribution of Phyllostachys edulis in the 2050s migrates towards the southeast direction, and in the 2070s, the suitable habitat of Phyllostachys edulis migrates northward. In the suitable habitat area of Phyllostachys edulis, cropland and forests are the main land use types. With the passage of time, the proportion of forest area in the landscape pattern of the high-suitability area for Phyllostachys edulis continues to increase. Under SSP370 and SSP585 scenarios, the cropland in the Phyllostachys edulis high-suitability area gradually becomes fragmented, leading to a decrease in the distribution of cropland. In addition, it is expected that the landscape of high-suitability areas will become more fragmented and the quality of the landscape will decline in the future. This research provides a scientific basis for understanding the response of Phyllostachys edulis to climate change, and also provides theoretical guidance and data support for the management and planning of bamboo forest ecosystems, which will help in managing bamboo forest resources rationally and balancing carbon sequestration and biodiversity conservation.

Cooling Energy Challenges in Residential Buildings During Heat Waves: Urban Heat Island Impacts in a Hot-Humid City

Ignoring Urban Heat Island (UHI) effects may lead to an underestimation of the building cooling demand. This study investigates the impact of the UHI on the cooling demand in hot-humid cities, employing the Local Climate Zones (LCZs) classification framework combined with the Urban Weather Generator (UWG) model to simulate UHI effects and improve building performance simulations. The primary aim of this research is to quantify the influence of different LCZs within urban environments on variations in the cooling energy demand, particularly during heat waves, and to explore how these effects can be incorporated into building energy models. The findings reveal significant discrepancies in both the average and peak cooling demand when UHI effects are ignored, especially during nighttime. The most intense UHI effect was observed in LCZ 2.1, characterized by compact mid-rise and high-rise buildings, leading to a cooling demand increase of more than 20% compared to suburban data during the heat waves. Additionally, building envelope thermal performance was found to influence cooling demand variability, with improved thermal properties reducing energy consumption and stabilizing demand. This research contributes to the theoretical understanding of how urban microclimates affect building energy consumption by integrating LCZ classification with UHI simulation, offering a more accurate approach for building energy predictions. Practically, it highlights the importance of incorporating LCZs into building energy simulations and provides a framework that can be adapted to cities with different climatic conditions, urban forms, and development patterns. This methodology can be generalized to regions other than hot-humid areas, offering insights for improving energy efficiency, mitigating UHI effects, and guiding urban planning strategies to reduce the building energy demand in diverse environments.

Changes in agrochemical properties of meadow chernozem-like soil under prolonged exposure to agrogenic factors in grain-soybean crop rotation

In a long-term stationary experiment to study the fertilizer system in crop rotation, established in 1962–1964 on meadow chernozem-like soil in the southern natural and climatic zone of the Amur region, the influence of prolonged use of mineral and organo-mineral fertilizer systems on the agrochemical properties of meadow chernozem-like soil in relation to the level of crop yield in crop rotation was studied. The use of mineral fertilizers alone and together with organic ones provided an increase in the content of mobile phosphorus in the soil by 2.0–2.5 times, its mobility by 2.9–3.5 times relative to control. The long-term use of the organo-mineral fertilizer system led to an increase in the humus content by 0.69% and the preservation of acidity indicators at the initial level, while the application of only mineral fertilizers increased the hydrolytic and metabolic acidity. Wheat yield when applying N30 against the background of prolonged application of fertilizers to the 12th rotation of the crop rotation increased by 0.58 t/ha relative to the control, with its aftereffect – by 0.30 t/ha. At the same time, the yield of soybeans was 2.42–2.62 t/ha. It was found that the productivity of crop rotation was determined by 73% by changes in humus content, soil acid content and mobile P2O5 content in the 0–20 cm soil layer. The relationship of crop rotation productivity with humus content was weak (β = 0.26), hydrolytic acidity – medium reverse (β = –0.57), metabolic acidity – strong reverse (β = –0.81) and phosphorus content – strong (β = 0.84). The values of p-levels and Student coefficients indicated the fact that hydrolytic and metabolic acidity, the content of mobile phosphorus were statistically significant variables.

Impact of Building Orientation on Energy Performance of Residential Buildings in Various Cities Across Afghanistan

Building or solar orientation, a key architectural design parameter, significantly influences energy consumption in buildings. Optimizing building orientation to harness passive solar benefits is a fundamental and cost-effective measure in designing energy-efficient buildings. However, the optimal orientation varies based on geographical location, climatic conditions, and building type. Notably, Afghanistan’s building sector currently lacks tailored energy efficiency regulations. Therefore, this study investigates the impact of building orientation on the energy performance of residential buildings across nine cities in Afghanistan, each characterized by distinct climatic conditions and geographic locations, employing BEoptTM energy simulation software. The findings reveal diverse optimal orientations, dividing the country into three distinct climatic zones: subarctic (optimal orientation: south-southeast), continental (optimal orientation: south), and hot-arid (optimal orientation: north). The optimal orientations in these regions yield potential energy savings ranging from 25.6% to 48.9% compared to the least efficient orientations. These insights are critical for establishing location-specific building regulations in Afghanistan, promoting energy-efficient design, and addressing the country’s current trend of unsustainable development.

IMERG V07B and V06B: A Comparative Study of Precipitation Estimates Across South America with a Detailed Evaluation of Brazilian Rainfall Patterns

Satellite-based precipitation products (SPPs) are essential for climate monitoring, especially in regions with sparse observational data. This study compares the performance of the latest version (V07B) and its predecessor (V06B) of the Integrated Multi-satellitE Retrievals for GPM (IMERG) across South America and the adjacent oceans. It focuses on evaluating their accuracy under different precipitation regimes in Brazil using 22 years of IMERG Final data (2000–2021), aggregated into seasonal totals (summer, autumn, winter, and spring). The observations used for the evaluation were organized into 0.1° × 0.1° grid points to match IMERG’s spatial resolution. The analysis was restricted to grid points containing at least one rain gauge, and in cases where multiple gauges were present within a grid point the average value was used. The evaluation metrics included the Root Mean Square Error (RMSE) and categorical indices. The results reveal that while both versions effectively capture major precipitation systems such as the mesoscale convective system (MCS), South Atlantic Convergence Zone (SACZ), and Intertropical Convergence Zone (ITCZ), significant discrepancies emerge in high-rainfall areas, particularly over oceans and tropical zones. Over the continent, however, these discrepancies are reduced due to the correction of observations in the final version of IMERG. A comprehensive analysis of the RMSE across Brazil, both as a whole and within the five analyzed regions, without differentiating precipitation classes, demonstrates that version V07B effectively reduces errors compared to version V06B. The analysis of statistical indices across Brazil’s five regions highlights distinct performance patterns between IMERG versions V06B and V07B, driven by regional and seasonal precipitation characteristics. V07B demonstrates a superior performance, particularly in regions with intense rainfall (R1, R2, and R5), showing a reduced RMSE and improved categorical indices. These advancements are linked to V07B’s reduced overestimation in cold-top cloud regions, although both versions consistently overestimate at rain/no-rain thresholds and for light rainfall. However, in regions prone to underestimation, such as the interior of the Northeastern region (R3) during winter, and the northeastern coast (R4) during winter and spring, V07B exacerbates these issues, highlighting challenges in accurately estimating precipitation from warm-top cloud systems. This study concludes that while V07B exhibits notable advancements, further enhancements are needed to improve accuracy in underperforming regions, specifically those influenced by warm-cloud precipitation systems.

Study of the Biogas Ebullition from Lacustrine Carbonate Enriched and Black Silt Bottom Sediments

The greenhouse effect, which is also promoted by naturally occurring biogas ebullition fluxes (released via bubbles), generated by the decomposition of organic matter in carbonate-enriched and black silt sediments, has been analyzed. This study is based on results obtained using passive gas collectors at different parts of eutrophic Lake Juodis, located in a temperate climate zone in the vicinity of Vilnius (Lithuania). The measured annual biogas (containing about 60% of biomethane) ebullition fluxes from carbonate-enriched sediments and black silt sediments were 16.9–23.0 L/(m2∙y) and 38.5–43.2 L/(m2∙y), respectively. This indicates that the gas fluxes from carbonate sediments were almost twice as low as those from black silt sediments. Oxygen, produced by the photosynthetic activity of green algae in the near-surface water and sediments, helps to retain carbonates in the sediments by preventing their dissolution. In turn, the calcite coating on sediment particles partially preserves organic matter from decomposition, reducing the effective thickness of the sediment layer generating biogas. The characteristic vertical distribution profile of 137Cs activity, with sharp peaks in sediments, suggests that generated biogas bubbles move to the surface of the sediments forming vertical channels by pushing sediment particles asides without noticeably mixing them vertically. This examination showed that factors such as abundance of carbonates in the sediments may result in a significant reduction in biogas generation and emissions from the lake sediments.

Explore the operational performance of phase change radiation terminal heating system in different heating zones of China

IntroductionHeating is one of the main factors leading to high energy consumption and serious carbon emissions in buildings. The clean heating system formed by the coupling of phase change building maintenance structure and solar heating system can improve the thermal storage density of the building maintenance structure, while reducing energy consumption in winter while maintaining a comfortable room temperature through stable energy security.MethodsTherefore, a phase change radiation terminal heating (PCRTH) system with the phase change radiation module as the terminal and the solar energy and air energy as the clean heat source is established in this study. Nanjing, Tianjin and Shenyang in China were selected as the study zones which correspond to the hot summer and cold winter zone, the cold zone and the severe cold zone respectively. The operational effect of the PCRTH system in different climate zones was studied, and the parameters of the PCRTH system were optimized by the GenOpt program combined with Hooke-Jeeves optimization algorithm.ResultsThe analysis results show that the cascade phase change radiation terminals in the three zones reduced room temperature fluctuation, energy consumption and carbon dioxide emissions, but the heating cost was higher. After the Hooke-Jeeves optimization algorithm was used to optimize the PCRTH system parameters in three zones, the PCRTH system heating cost was reduced, and the PCRTH system energy consumption and PCRTH system carbon dioxide emissions were further reduced.DiscussionTherefore, the building heating system composed of PCM maintenance structure and renewable energy has great application advantages in maintaining a comfortable room temperature and improving heating system energy conservation and environmental protection.

Research on Climate Drivers of Ecosystem Services’ Value Loss Offset in the Qinghai–Tibet Plateau Based on Explainable Deep Learning

As one of the highest and most ecologically vulnerable regions in the world, the Qinghai–Tibet Plateau (QTP) presents significant challenges for the application of existing ecosystem service value (ESV) assessment models due to its extreme climate changes and unique plateau environment. Current models often fail to adequately account for the complex climate variability and topographical features of the QTP, making accurate assessments of ESV loss deviations difficult. To address these challenges, this study focuses on the QTP and employs a modified ESV loss deviation model, integrated with explainable deep learning techniques (LSTM-SHAP), to quantify and analyze ESV loss deviations and their climate drivers from 1990 to 2030. The results show that (1) between 1990 and 2020, the offset index in the eastern QTP consistently remained low, indicating significant deviations. Since 2010, low-value clusters in the western region have significantly increased, reflecting a widening range of ecological damage caused by ESV losses, with no marked improvement from 2020 to 2030. (2) SHAP value analysis identified key climate drivers, including temperature seasonality, diurnal temperature variation, and precipitation patterns, which exhibit nonlinear impacts and threshold effects on ESV loss deviation. (3) In the analysis of nonlinear relationships among key climate drivers, the interaction between diurnal temperature range and precipitation in wet seasons demonstrated significant effects, indicating that the synergistic action of temperature variation and precipitation patterns is critical to ecosystem stability. Furthermore, the complex nonlinear interactions between climate factors exacerbated the volatility of ESV loss deviations, particularly under extreme climate conditions. The 2030 forecast highlights that wet season precipitation and annual rainfall will become key factors driving changes in ESV loss deviation. By combining explainable deep learning methods, this study advances the understanding of the relationship between climate drivers and ecosystem service losses, providing scientific insights for ecosystem protection and sustainable management in the Qinghai–Tibet Plateau.

Impact of water deficit on the anatomical structure of more productive and less productive cashew trees (Anacardium occidentale L.) in Côte d’Ivoire

This study aimed to understand the mechanism of resilience of the anatomical tissues of organs of the cashew tree in water deficit in the different climatic zones of Côte d'Ivoire. To achieve this, samples of leaves and roots were taken from 55 cashew trees considered high producers (APHP) and 164 neighboring less productive trees (non-APHP) during the dry and rainy seasons. The technique of double staining with green-carmino made it possible to obtain anatomical sections of transversely cut samples under an optical microscope. The thicknesses and surface areas of the sections were measured using Image J software. The thickness of the leaves parenchymas of APHP trees did not show any variation according to the season while the stomatal density increased during the dry season. The thickness of the leaves cortical and medullary parenchymas of non-APHP trees did not show any variation according to the season too but the non-APHPs’ palisade parenchyma thickness increased while their lacunar parenchyma thickness decreased from 37 ± 1.5 mm to 36 ± 3.6 mm during the dry season. The thickness of leaves’ both sides epidermis increased while the thickness of xylem bundles decreased during the dry season to both APHP and non-APHP trees. The number of the roots’ xylem vessels of APHP trees increased from 11 to 27 vessels/mm2 while those of non-APHP trees increased from 15 to 41 vessels/mm2 during the rainy season. The surface area of the midrib medullary parenchyma of APHP trees increased from 4300 ± 837 mm2 to 5800 ± 412 mm2 while those of non-APHP trees increased from 3400 ± 809 mm2 to 5200 ± 993 mm2 during the dry season. The thicknesses of the tissues of APHPs remained greater than those of non-APHPs, regardless of the sampling season.

A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

Mosquitoes (Diptera: <i>Culicidae</i>) are vectors of vector-borne infections in South Vietnam (materials of the spring expedition 2024)

BACKGROUND: Blood-sucking mosquitoes are carriers of many human vector-borne diseases caused by viruses, bacteria, protozoa and helminths. There are the results of entomological studies of the Joint Russian-Vietnamese Tropical Research and Technology Center. AIM: is to study the generic and species composition of mosquitoes in South Vietnam before the rainy season, when mosquito activity is low. MATERIALS AND METHODS: The collection of arthropods was carried out from May 12 to 26, 2024 in two regions of South Vietnam: the coastal mangrove reserve in the Can Gio area of Ho Chi Minh City, as well as in the Bu Gia Map Reserve of Binh Phuoc province. Imago was collected by exhusters “on themselves” and from feeders, entomological nets from plants, as well as inside and outside residential and outbuildings. The larvae were collected by filtering water samples from natural and artificial reservoirs where mosquitoes lay eggs. Arthropods were identified by morphological features. RESULTS: The analysis of the collected material in two regions of South Vietnam showed that before the rainy season, mosquitoes of the genus Culex predominate 90.7%, mosquitoes of the genus Anopheles and Aedes account for 6.1% and 3.2%, respectively. CONCLUSION: Thus, in South Vietnam, at the end of the “dry season”, mosquitoes of the genus Culex predominate, adapted to development in conditions of reduced breeding sites. The study of the mechanisms of functioning of parasitic systems involving blood-sucking mosquitoes requires further research with the expansion of the research area. It is advisable to conduct entomological monitoring in various landscape and climatic zones during different periods of the epidemic season.

Design Optimization of Energy-Efficient Residential Buildings in Morocco

In this paper, an optimization-based analysis approach is presented to cost-effectively improve the energy efficiency of residential buildings in Morocco. This study introduces a unique focus on the Moroccan context, where a comprehensive application of energy efficiency optimization has not yet been undertaken. This analysis considers the interactive effects among various energy efficiency measures to determine optimal combinations for designing high-energy performance, as well as net-zero energy, residential buildings for six climate zones in Morocco. In particular, the design analysis approach combines a whole-building simulation with the sequential search technique, providing a novel, integrated cost–benefit analysis that minimizes lifecycle costs (LCC) while maximizing energy savings for each climate zone. This study also includes an unprecedented comparison of optimized designs, reference designs, and current Moroccan building regulations (RTCM), highlighting potential improvements to the existing regulatory framework. While the sequential search method has been applied elsewhere, its specific application to achieve net-zero energy homes in the Moroccan context with comparable LCC is a new contribution. The analysis results show that houses in Morocco can be cost-effectively designed to achieve annual energy savings of 51% for Zone 1, 53% for Zone 2, 60% for Zone 3, 67% for Zone 4, 54% for Zone 5, and 56% for Zone 6 compared to the current construction practices considered as reference designs. Moreover, the results indicate that houses can reach net-zero energy building designs with almost the same LCC as the reference design cases for all the climate zones in Morocco.

Retrofit Analysis of Exterior Windows for Large Office Buildings in Different Climate Zones of China

In the energy-saving retrofit of existing buildings, investors are particularly concerned about the energy-saving performance of exterior windows and the payback period of additional costs. This study evaluates representative cities in four different climate zones in China to simulate the energy consumption of large office buildings after replacing different glass windows and conducting energy-saving and economic feasibility assessments. The research method includes the following steps: First, a baseline model of large office buildings in four cities was established using AutoBPS and OpenStudio. Then, the baseline and retrofit models of replacing glass windows were simulated using the EnergyPlus V9.3.0 to obtain multiple hourly energy consumption results. The commercial electricity and gas prices in the four cities were adjusted to calculate the total cost within 20 years after replacing different types of windows. Using the discounted payback period (DPP), net present value (NPV), and profitability index (PI) as evaluation indicators, a feasibility analysis was conducted in the four regions to evaluate the economic feasibility of replacing building windows. The simulation results show that considering economic feasibility and meeting energy-saving standards, it is more economical to choose windows with moderate U-value and SHGC value in the four regions than to choose windows with the smallest U-value and SHGC value, and that both energy savings and economic benefits are closely related to building age, with older buildings (especially those in Changsha and Shenzhen) showing greater benefits. Furthermore, the optimal window types in the four cities determined in this study can recover the investment cost within the window life, with Harbin (SC), Beijing (C), Changsha (HC), and Shenzhen (HW) with the payback period of 6.60, 15.66, 10.16, and 11.42 years, respectively. The research model established in this study provides a useful evaluation path for selecting windows for the energy-saving retrofit of large office buildings in cities in different climate zones and provides data support for the decision making of energy-saving retrofit investors.

Relative humidity prediction across the Indian subcontinent using Kumaraswamy distribution based non-Gaussian model.

Relative humidity (RH) significantly influences various aspects of human life, including agriculture, weather prediction, indoor air quality, and energy consumption. Its intricate non-linear behavior poses a significant challenge for accurate estimation. In the context of Indian climate change, precise forecasting of RH is vital for agriculture and weather prediction. This study proposes a new non-Gaussian approach, the Kumaraswamy seasonal autoregressive moving average (KSARMA) model, for RH prediction across India's five climatic zones (hot-dry, warm-humid, moderate, cold, and composite). Analyzing monthly RH data from 1981 to 2021, model selection was based on diagnostic analysis and Akaike's information criterion (AIC), with parameter estimation utilizing conditional maximum likelihood estimators (CMLE). The KSARMA model demonstrated superior predictive accuracy compared to other models (e.g., multilayer perceptron, SARIMA, Holt-Winter, and SARMA) across all climatic zones, except the hot-dry zone, as supported by error metrics including RMSE (0.04-0.12), MAE (0.03-0.1), SMAPE (0.04-0.2), and MASE (0.5-.08).

Decoding Carbon Footprints: How U.S. Climate Zones Shape Building Emissions

The construction industry accounts for over 40% of carbon emissions in the United States, with embodied carbon—emissions associated with building materials and construction processes—remaining underexplored, particularly regarding the impact of location and climate. This study addresses this gap by investigating the influence of different climate zones on the embodied carbon emissions of residential buildings. Using Building Information Modeling (BIM), 3D models were developed based on the 2021 International Energy Conservation Code (IECC) and International Residential Code (IRC). A lifecycle assessment (LCA) was conducted using Environmental Product Declarations (EPDs) to evaluate the embodied carbon of building materials during the product stage. The findings reveal that buildings in colder climates exhibit higher embodied carbon emissions, ranging from 25,768 kgCO2e in Zone 1 to 40,129 kgCO2e in Zone 8, due to increased insulation requirements. Exterior walls and roofs were identified as significant contributors, comprising up to 34% of total emissions. Sensitivity analysis further indicates that the window-to-wall ratio and interior wall design substantially affect embodied carbon, with baseline emissions around 170 kgCO2e/m2 in warm areas and 255 kgCO2e/m2 in cold areas. These results establish a baseline for lifecycle embodied carbon values across different climate zones in the United States and align with international standards. This study provides valuable insights for policymakers and designers, offering data to inform effective carbon reduction strategies and optimize building designs for sustainability.

Components of High-Yielding Cotton Grown in Rain-Fed Conditions in the Brazilian Cerrado

Brazil leads globally in achieving high lint yields for rain-fed cotton in large-scale fields, with about 92% of its cotton area unirrigated. This study hypothesized that cotton could achieve high yields when favorable climate conditions and management practices favor high fruit load. The objective was to analyze the impact of these factors on cotton yields by examining two commercial fields in Brazil in the same climatic zone (Aw, Koppen)—one in Sapezal (SPZ) and the other in Riachão das Neves (RN). The SPZ field (cv. TMG 47B2RF) spanned 20 hectares, while the RN field (cv. FM 974GLT) covered 90 hectares. The soils of both fields were classified as oxisols, with SPZ possessing a clayey texture and RN a sandy loam texture. The findings indicate that the high lint cotton yields—3111 kg·ha⁻1 in SPZ and 3239 kg·ha⁻1 in RN—were achieved through a combination of ideal weather conditions, high-quality soil, and effective management practices, which favored boll retention, and an optimal plant architecture with short stature (<1.1 m), 19–22 nodes, and ~165 bolls m−2. Boll weights averaged 1.85–1.91 g of lint, and fruit retention rates were 61.6% in SPZ and 66.2% in RN. The study reveals a significant yield gap compared to Brazil’s average lint cotton yield (~1900 kg·ha⁻1) and other high-yield commercial fields (~3500–3900 kg·ha⁻1 of lint). The results underscore that bridging this gap—ranging from 1200 to 2000 kg·ha⁻1—could enhance the sustainability of cotton farming in Brazil by maximizing existing cultivated areas. Ultimately, the insights from this study highlight the role of combining climate suitability, management practices, and soil quality improvement to achieve higher cotton productivity and reduce environmental pressures from agricultural expansion.