Atmospheric phenomena are physical phenomena resulting from the correlation of atmospheric parameters of natural origin. They are associated with climatic storms and include lightning, thunder, global warming, wind, e...Atmospheric phenomena are physical phenomena resulting from the correlation of atmospheric parameters of natural origin. They are associated with climatic storms and include lightning, thunder, global warming, wind, evaporation, rain, clouds, and snow. The formation and evolution of these phenomena remain complex according to their natural reference parameters. The numerical models defined in this study are equations based on models of atmospheric parameters. Applied in the atmosphere, they yield the equation of the key atmospheric phenomena. The distribution of these phenomena across the entire planet is the origin of the formation of climatic regions. Indeed, the constants obtained are 275.16 km/s for the speed of lightning, 3.99 GJ for the discharge energy of a thunderbolt, 276.15˚K for the temperature of global warming, 3.993 Km/h for the formation speed of winds and cyclones, 2.9963 Km/h for the speed of evaporation, 278.16˚K for the formation of rain, 274.1596˚K for the formation of clouds, and 274.1632˚K for snow formation. Moreover, this research conducts an analytical study approach to the phenomenon of climate change in the current era of industrialization, specifically analyzing the direct effects of global warming on atmospheric phenomena. Thus, with a temperature of 53.45˚C, global warming is considered maximal and will lead to very abundant rain and snow precipitations with maximum PW at 12.5 and 11.1 g/cm2 of water, surface water evaporation fluxes significantly above normal at a speed of 6.55 Km/h, increasingly violent winds at speeds far exceeding 5.43 Km/h, and catastrophic climatic effects. In summary, the aim of this research is to define the main natural phenomena associated with global climatic storms and to study the real impact of climate change on Earth.展开更多
Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model o...Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .展开更多
This study aims to assess the synergies and trade-offs of regulating ecosystem services. Ecosystem services are non-linearly interconnected and changes in one service can positively or negatively affect another. We ev...This study aims to assess the synergies and trade-offs of regulating ecosystem services. Ecosystem services are non-linearly interconnected and changes in one service can positively or negatively affect another. We evaluated ecosystem services based on biophysical indicators using an expert scoring system that determines the corresponding soil functions and is part of the existing databases available in Slovakia. This methodological combination enabled us to provide unique mapping and assessment of ecosystem services within Slovakia. Correlation analysis between individual regulating ecosystem services and climate regions, slope, texture, and altitude confirm the statistically significant influence of climate and slope in all agricultural land, arable land, and grassland ecosystems. Statistically significant synergistic effects were established between the regulation of the water regime and the regulation of soil erosion within each climate region, apart from the very warm climate region. Only in a very warm climate region was potential of regulating ecosystem services mutually beneficial for soil erosion control and soil cleaning potential (immobilization of inorganic pollutants).展开更多
This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while ...This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.展开更多
The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in N...The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.展开更多
Cymbidium(Orchidaceae:Epidendroideae),with around 60 species,is widely-distributed across Southeast Asia,providing a nice system for studying the processes that underlie patterns of biodiversity in the region.However,...Cymbidium(Orchidaceae:Epidendroideae),with around 60 species,is widely-distributed across Southeast Asia,providing a nice system for studying the processes that underlie patterns of biodiversity in the region.However,phylogenetic relationships of Cymbidium have not been well resolved,hampering investigations of species diversification and the biogeographical history of this genus.In this study,we construct a plastome phylogeny of 56 Cymbidium species,with four well-resolved major clades,which provides a framework for biogeographical and diversification rate analyses.Molecular dating and biogeographical analyses show that Cymbidium likely originated in the region spanning northern IndoBurma to the eastern Himalayas during the early Miocene(~21.10 Ma).It then rapidly diversified into four major clades in East Asia within approximately a million years during the middle Miocene.Cymbidium spp.migration to the adjacent regions(Borneo,Philippines,and Sulawesi)primarily occurred during the Pliocene-Pleistocene period.Our analyses indicate that the net diversification rate of Cymbidium has decreased since its origin,and is positively associated with changes in temperature and monsoon intensity.Favorable hydrothermal conditions brought by monsoon intensification in the early Miocene possibly contributed to the initial rapid diversification,after which the net diversification rate was reduced with the cooling climate after the middle Miocene.The transition from epiphytic to terrestrial habits may have enabled adaptation to cooler environments and colonization of northern niches,yet without a significant effect on diversification rates.This study provides new insights into how monsoon activity and temperature changes affected the diversification dynamics of plants in Southeast Asia.展开更多
To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simu...To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.展开更多
This paper provides a systematic evaluation of the ability of 12 Earth System Models(ESMs)participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)to simulate the spatial inhomogeneity of the atmospher...This paper provides a systematic evaluation of the ability of 12 Earth System Models(ESMs)participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)to simulate the spatial inhomogeneity of the atmospheric carbon dioxide(CO_(2))concentration.The multi-model ensemble mean(MME)can reasonably simulate the increasing trend of CO_(2) concentration from 1850 to 2014,compared with the observation data from the Scripps CO_(2) Program and CMIP6 prescribed data,and improves upon the CMIP5 MME CO_(2) concentration(which is overestimated after 1950).The growth rate of CO_(2) concentration in the northern hemisphere(NH)is higher than that in the southern hemisphere(SH),with the highest growth rate in the mid-latitudes of the NH.The MME can also reasonably simulate the seasonal amplitude of CO_(2) concentration,which is larger in the NH than in the SH and grows in amplitude after the 1950s(especially in the NH).Although the results of the MME are reasonable,there is a large spread among ESMs,and the difference between the ESMs increases with time.The MME results show that regions with relatively large CO_(2) concentrations(such as northern Russia,eastern China,Southeast Asia,the eastern United States,northern South America,and southern Africa)have greater seasonal variability and also exhibit a larger inter-model spread.Compared with CMIP5,the CMIP6 MME simulates an average spatial distribution of CO_(2) concentration that is much closer to the site observations,but the CMIP6-inter-model spread is larger.The inter-model differences of the annual means and seasonal cycles of atmospheric CO_(2) concentration are both attributed to the differences in natural sources and sinks of CO_(2) between the simulations.展开更多
Ecological stability is a core issue in ecological research and holds significant implications forhumanity. The increased frequency and intensity of drought and wet climate events resulting from climatechange pose a m...Ecological stability is a core issue in ecological research and holds significant implications forhumanity. The increased frequency and intensity of drought and wet climate events resulting from climatechange pose a major threat to global ecological stability. Variations in stability among different ecosystemshave been confirmed, but it remains unclear whether there are differences in stability within the sameterrestrial vegetation ecosystem under the influence of climate events in different directions and intensities.China's grassland ecosystem includes most grassland types and is a good choice for studying this issue.This study used the Standardized Precipitation Evapotranspiration Index-12 (SPEI-12) to identify thedirections and intensities of different types of climate events, and based on Normalized DifferenceVegetation Index (NDVI), calculated the resistance and resilience of different grassland types for 30consecutive years from 1990 to 2019 (resistance and resilience are important indicators to measurestability). Based on a traditional regression model, standardized methods were integrated to analyze theimpacts of the intensity and duration of drought and wet events on vegetation stability. The resultsshowed that meadow steppe exhibited the highest stability, while alpine steppe and desert steppe had thelowest overall stability. The stability of typical steppe, alpine meadow, temperate meadow was at anintermediate level. Regarding the impact of the duration and intensity of climate events on vegetationecosystem stability for the same grassland type, the resilience of desert steppe during drought was mainlyaffected by the duration. In contrast, the impact of intensity was not significant. However, alpine steppewas mainly affected by intensity in wet environments, and duration had no significant impact. Ourconclusions can provide decision support for the future grassland ecosystem governance.展开更多
It is commonly believed that the atmosphere is decoupled from the solid Earth.Thus,it is difficult for the seismic wave energy inside the Earth to propagate into the atmosphere,and atmospheric pressure wave signals ex...It is commonly believed that the atmosphere is decoupled from the solid Earth.Thus,it is difficult for the seismic wave energy inside the Earth to propagate into the atmosphere,and atmospheric pressure wave signals excited by earthquakes are unlikely to exist in atmospheric observations.An increasing number of studies have shown that earthquakes,volcanoes,and tsunamis can perturb the Earth's atmosphere due to various coupling effects.However,the observations mainly focus on acoustic waves with periods of less than 10 min and inertial gravity waves with periods of greater than 1 h.There are almost no clear observations of gravity waves that coincide with observations of low-frequency signals of the Earth's free oscillation frequency band within 1 h.This paper investigates atmospheric gravity wave signals within1 h of surface-atmosphere observations using the periodogram method based on seismometer and microbarometer observations from the global seismic network before and after the July 29,2021 M_(w)8.2 Alaska earthquake in the United States.The numerical results show that the atmospheric gravity wave signals with frequencies similar to those of the Earth's free oscillations _(0)S_(2) and _(0)T_(2) can be detected in the microbaro meter observations.The results con firm the existence of atmospheric gravity waves,indicating that the atmosphere and the solid Earth are not decoupled within this frequency band and that seismic wave energy excited by earthquakes can propagate from the interior of the Earth to the atmosphere and enhance the atmospheric gravity wave signals within 1 h.展开更多
Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of...Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.展开更多
A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Ni...A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.展开更多
Using the observation data in Yongxing Island,South China Sea(SCS)from December 2013 to November 2018,the multiple time scales variation of atmospheric CO_(2)and CH_(4)were analyzed to understand their temporal variat...Using the observation data in Yongxing Island,South China Sea(SCS)from December 2013 to November 2018,the multiple time scales variation of atmospheric CO_(2)and CH_(4)were analyzed to understand their temporal variation characteristics and controlling factors.The regional-averaged background mole fractions of CO_(2)and CH_(4)both show a single-period sinusoidal variation with a lower value at noon and a higher value in the wee hours.In the seasonal scale,they exhibited a significant seasonal difference with higher values in winter and lower values in summer.In the annual scale,CO_(2)and CH_(4)both show an increasing trend,with an annual growth rate of approximately 3.2 ppm and 12 ppb,respectively.The annual growth rate at this site was higher than the global average.The change in atmospheric CO_(2)and CH_(4)in Yongxing Island was probably caused by the higher emission of the surrounding areas and the airflows driven by monsoon.Hopefully,the long-term and high-resolution greenhouse gases(GHGs)dataset will aid relevent researchers and decision-makers in performing more in-depth studies for GHG sources in order to derive effective strategies.展开更多
To study the atmospheric aging of acrylic coatings,a two-year aging exposure experiment was conducted in 13 representative climatic environments in China.An atmospheric aging evaluation model of acrylic coatings was d...To study the atmospheric aging of acrylic coatings,a two-year aging exposure experiment was conducted in 13 representative climatic environments in China.An atmospheric aging evaluation model of acrylic coatings was developed based on aging data including11 environmental factors from 567 cities.A hybrid method of random forest and Spearman correlation analysis was used to reduce the redundancy and multicollinearity of the data set by dimensionality reduction.A semi-supervised collaborative trained regression model was developed with the environmental factors as input and the low-frequency impedance modulus values of the electrochemical impedance spectra of acrylic coatings in 3.5wt%NaCl solution as output.The model improves accuracy compared to supervised learning algorithms model(support vector machines model).The model provides a new method for the rapid evaluation of the aging performance of acrylic coatings,and may also serve as a reference to evaluate the aging performance of other organic coatings.展开更多
Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major...Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major source of nutrient return.To model the litterfall production using climatic variables and assess the nutrient return in 14-year-old Eucalyptus grandis and Pinus taeda stands,we measured litter production over 2 years,using conical litter traps,and monitored climatic variables.Mean temperature,accumulated precipitation,and mean maximum vapor pres-sure deficit at the seasonal level influenced litterfall produc-tion by E.grandis;seasonal accumulated precipitation and mean maximum temperature affected litterfall by P.taeda.The regression tree modeling based on these climatic vari-ables had great accuracy and predictive power for E.grandis(N=33;MAE(mean absolute error)=0.65;RMSE(root mean square error)=0.91;R^(2)=0.71)and P.taeda(N=108;MAE=1.50;RMSE=1.59;R^(2)=0.72).The nutrient return followed a similar pattern to litterfall deposition,as well as the order of importance of macronutrients(E.grandis:Ca>N>K>Mg>P;P.taeda:N>Ca>K>Mg>P)and micronutrients(E.grandis and P.taeda:Mn>Fe>Zn>Cu)in both species.This study constitutes a first approximation of factors that affect litterfall and nutrient return in these systems.展开更多
Climate change studies are diverse with no single study giving a comprehensive review of climate change impacts,adaptation strategies,and policy development in West Africa.The unavailability of an all-inclusive study ...Climate change studies are diverse with no single study giving a comprehensive review of climate change impacts,adaptation strategies,and policy development in West Africa.The unavailability of an all-inclusive study to serve as a guide for practitioners affects the effectiveness of climate change adaptation strategies proposed and adopted in the West African sub-region.The purpose of this study was to review the impacts of climate change risks on the crop,fishery,and livestock sectors,as well as the climate change adaptation strategies and climate-related policies aimed at helping to build resilient agricultural production systems in West Africa.The review process followed a series of rigorous stages until the final selection of 56 articles published from 2009 to 2023.Generally,the results highlighted the adverse effects of climate change risks on food security.We found a continuous decline in food crop production.Additionally,the livestock sector experienced morbidity and mortality,as well as reduction in meat and milk production.The fishery sector recorded loss of fingerlings,reduction in fish stocks,and destruction of mariculture and aquaculture.In West Africa,climate-smart agriculture technologies,physical protection of fishing,and inclusion of gender perspectives in programs appear to be the major adaptation strategies.The study therefore recommends the inclusion of ecosystem and biodiversity restoration,weather insurance,replacement of unsafe vessels,and strengthening gender equality in all climate change mitigation programs,as these will help to secure enough food for present and future generations.展开更多
Togo is facing significant climate challenges that have profound consequences for its environment, economy, and population. This study provides an overview of various climate phenomena affecting Togo and highlights po...Togo is facing significant climate challenges that have profound consequences for its environment, economy, and population. This study provides an overview of various climate phenomena affecting Togo and highlights potential adaptation strategies. We used the inclusion and exclusion criteria (PRISMA) to search both French and English articles on climate change-related disaster risk events in Togo through Google Scholar, Directory of Open Access Journals (DOAJ), and PubMed databases using the keywords “Climate Change”, “Floods”, “Drought”, “Coastal erosion”, “High winds”, “Epidemy”, Heatwaves”, and “Air pollution”. Twenty-five articles from 2000-2023 were included in this study after applying different criteria. Droughts, floods, coastal erosion, food and crop productivity loss, heatwaves, spread of vector-borne diseases, air pollution, and high winds are among the climate phenomena discussed. These challenges are driven by climate change, altering precipitation patterns, increasing temperatures, and rising sea levels. Drought, floods, coastal erosion, loss of food and crop productivity, spread of vector-borne diseases, air pollution and heatwaves are the most climate risks experienced by Togo. Drought contributes to decreased plant cover, water scarcity, and changes in the water and energy balance. Floods cause property damage, health risks, and disruptions to livelihoods. Coastal erosion threatens coastal communities, infrastructure, and ecosystems. Adaptation strategies include early warning systems, improved water management, sustainable agriculture, urban and health planning, and greenhouse gas emissions reduction. Drought-resistant crops, mosquito control, and clean energy adoption are essential.展开更多
Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostat...Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.展开更多
This study focuses on air quality in southern Benin in order to show public authorities what the Beninese populations are exposed to for efficient decision-making. Two sampling campaigns were carried out, one in the w...This study focuses on air quality in southern Benin in order to show public authorities what the Beninese populations are exposed to for efficient decision-making. Two sampling campaigns were carried out, one in the wet period and the other in the dry season. The measurements were taken using a monitor called an “Air Quality Monitor”. For data processing, the multiple comparison methods of Dun (1961) and the Wilcoxon test were used. To maintain legitimacy, all spatial data were included in the official cartographic repository of Benin: WGS 1984, Transverse Mercator Universe Projection (UTM), Zone 31 North. The Moran statistic was used to measure the levels of spatial autocorrelation of the variables studied and to test the significance. In order to locate the spatial subsets, the local spatial association indices of Anselin Local Moran and Getis-Ord, Gi* were used. In terms of results, on the 13 monitoring sites and the 8 parameters chosen to determine air quality, we do not note any significant inter-seasonal difference. Of the eight parameters, only three parameters present spatial autocorrelation leading to predictions of ambient air quality over the entire study area based on the distance separating the points, namely, PM<sub>2.5</sub>, PM<sub>10</sub> and ambient air quality index (AQI). The localities affected by atmospheric pollution in South Benin are located in the south-western part of Benin, headed by Cotonou, which is heavily polluted by CO<sub>2</sub>, TCOV, PM<sub>10</sub> and PM<sub>2.5</sub>.展开更多
Climate change has been a global pandemic with its adverse impacts affecting environments and livelihoods. This has been largely attributed to anthropogenic activities which generate large amounts of Green House Gases...Climate change has been a global pandemic with its adverse impacts affecting environments and livelihoods. This has been largely attributed to anthropogenic activities which generate large amounts of Green House Gases (GHGs), notably carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) among others. In the Upper East of Ghana, climate change manifests in erratic rainfalls, drought, high temperatures, high wind speeds, high intensity rainfall, windstorms, flooding, declining vegetation cover, perennial devastating bushfires etc. Practices such as burning farm residues, use of dung as fuel for cooking, excessive application of nitrogenous fertilizers, and deforestation that are prevalent in the region exacerbate the situation. Although, efforts made by governmental and none-governmental organizations to mitigate climate change through afforestation, agroforestry and promotion of less fuelwood consuming cook stoves, land management practices antagonize these efforts as more CO2 is generated than the carrying capacity of vegetation in the region. Research findings have established the role of trees and soil in carbon sequestration in mitigating climate. However, there is limited knowledge on how the vegetation and soil in agroforestry interplay in mitigation climate change. It is against this background that this review seeks to investigate how vegetation and soil in an agroforestry interact synergistically to sequester carbon and contribute to mitigating climate change in Upper East region of Ghana. In this review, it was discovered soil stored more carbon than vegetation in an agroforestry system and is much effective in mitigating climate change. It was found out that in order to make soil and vegetation in an agroforestry system interact synergistically to effectively mitigate climate change, Climate Smart Agriculture practice which integrates trees, and perennials crops effectively mitigates climate. The review concluded that tillage practices that ensure retention and storage of soil organic carbon (SOC) could be much effective in carbon sequestration in the Savannah zones and could be augmented with vegetation to synergistically mitigate climate change in the Upper East region of Ghana.展开更多
文摘Atmospheric phenomena are physical phenomena resulting from the correlation of atmospheric parameters of natural origin. They are associated with climatic storms and include lightning, thunder, global warming, wind, evaporation, rain, clouds, and snow. The formation and evolution of these phenomena remain complex according to their natural reference parameters. The numerical models defined in this study are equations based on models of atmospheric parameters. Applied in the atmosphere, they yield the equation of the key atmospheric phenomena. The distribution of these phenomena across the entire planet is the origin of the formation of climatic regions. Indeed, the constants obtained are 275.16 km/s for the speed of lightning, 3.99 GJ for the discharge energy of a thunderbolt, 276.15˚K for the temperature of global warming, 3.993 Km/h for the formation speed of winds and cyclones, 2.9963 Km/h for the speed of evaporation, 278.16˚K for the formation of rain, 274.1596˚K for the formation of clouds, and 274.1632˚K for snow formation. Moreover, this research conducts an analytical study approach to the phenomenon of climate change in the current era of industrialization, specifically analyzing the direct effects of global warming on atmospheric phenomena. Thus, with a temperature of 53.45˚C, global warming is considered maximal and will lead to very abundant rain and snow precipitations with maximum PW at 12.5 and 11.1 g/cm2 of water, surface water evaporation fluxes significantly above normal at a speed of 6.55 Km/h, increasingly violent winds at speeds far exceeding 5.43 Km/h, and catastrophic climatic effects. In summary, the aim of this research is to define the main natural phenomena associated with global climatic storms and to study the real impact of climate change on Earth.
文摘Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .
文摘This study aims to assess the synergies and trade-offs of regulating ecosystem services. Ecosystem services are non-linearly interconnected and changes in one service can positively or negatively affect another. We evaluated ecosystem services based on biophysical indicators using an expert scoring system that determines the corresponding soil functions and is part of the existing databases available in Slovakia. This methodological combination enabled us to provide unique mapping and assessment of ecosystem services within Slovakia. Correlation analysis between individual regulating ecosystem services and climate regions, slope, texture, and altitude confirm the statistically significant influence of climate and slope in all agricultural land, arable land, and grassland ecosystems. Statistically significant synergistic effects were established between the regulation of the water regime and the regulation of soil erosion within each climate region, apart from the very warm climate region. Only in a very warm climate region was potential of regulating ecosystem services mutually beneficial for soil erosion control and soil cleaning potential (immobilization of inorganic pollutants).
基金the National Key R&D Program of China(No.2021YFB3701705).
文摘This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.
基金supported by the Open Research Fund of TPESER(Grant No.TPESER202205)the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0101)。
文摘The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.
基金supported by grants from the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB31000000)The 14th Five-Year Plan of the Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences (XTBG-1450101)+3 种基金the Science and Technology Basic Resources Investigation Program of China (2021FY100200)the Key Basic Research Program of Yunnan Province,China (202101BC070003)the Yunnan Revitalization Talent Support Program"Young Talent"and"Innovation Team"ProjectsEcological and Environmental Conservation Program from the Department of Ecology and Environment of Yunnan Province。
文摘Cymbidium(Orchidaceae:Epidendroideae),with around 60 species,is widely-distributed across Southeast Asia,providing a nice system for studying the processes that underlie patterns of biodiversity in the region.However,phylogenetic relationships of Cymbidium have not been well resolved,hampering investigations of species diversification and the biogeographical history of this genus.In this study,we construct a plastome phylogeny of 56 Cymbidium species,with four well-resolved major clades,which provides a framework for biogeographical and diversification rate analyses.Molecular dating and biogeographical analyses show that Cymbidium likely originated in the region spanning northern IndoBurma to the eastern Himalayas during the early Miocene(~21.10 Ma).It then rapidly diversified into four major clades in East Asia within approximately a million years during the middle Miocene.Cymbidium spp.migration to the adjacent regions(Borneo,Philippines,and Sulawesi)primarily occurred during the Pliocene-Pleistocene period.Our analyses indicate that the net diversification rate of Cymbidium has decreased since its origin,and is positively associated with changes in temperature and monsoon intensity.Favorable hydrothermal conditions brought by monsoon intensification in the early Miocene possibly contributed to the initial rapid diversification,after which the net diversification rate was reduced with the cooling climate after the middle Miocene.The transition from epiphytic to terrestrial habits may have enabled adaptation to cooler environments and colonization of northern niches,yet without a significant effect on diversification rates.This study provides new insights into how monsoon activity and temperature changes affected the diversification dynamics of plants in Southeast Asia.
基金supported by the Chinese-Norwegian Collaboration Projects within Climate Systems jointly funded by the National Key Research and Development Program of China (Grant No.2022YFE0106800)the Research Council of Norway funded project MAPARC (Grant No.328943)+2 种基金the support from the Research Council of Norway funded project BASIC (Grant No.325440)the Horizon 2020 project APPLICATE (Grant No.727862)High-performance computing and storage resources were performed on resources provided by Sigma2 - the National Infrastructure for High-Performance Computing and Data Storage in Norway (through projects NS8121K,NN8121K,NN2345K,NS2345K,NS9560K,NS9252K,and NS9034K)。
文摘To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.
基金supported by the National Natural Science Foundation of China(Grant No.42230608)the UK-China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund.
文摘This paper provides a systematic evaluation of the ability of 12 Earth System Models(ESMs)participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)to simulate the spatial inhomogeneity of the atmospheric carbon dioxide(CO_(2))concentration.The multi-model ensemble mean(MME)can reasonably simulate the increasing trend of CO_(2) concentration from 1850 to 2014,compared with the observation data from the Scripps CO_(2) Program and CMIP6 prescribed data,and improves upon the CMIP5 MME CO_(2) concentration(which is overestimated after 1950).The growth rate of CO_(2) concentration in the northern hemisphere(NH)is higher than that in the southern hemisphere(SH),with the highest growth rate in the mid-latitudes of the NH.The MME can also reasonably simulate the seasonal amplitude of CO_(2) concentration,which is larger in the NH than in the SH and grows in amplitude after the 1950s(especially in the NH).Although the results of the MME are reasonable,there is a large spread among ESMs,and the difference between the ESMs increases with time.The MME results show that regions with relatively large CO_(2) concentrations(such as northern Russia,eastern China,Southeast Asia,the eastern United States,northern South America,and southern Africa)have greater seasonal variability and also exhibit a larger inter-model spread.Compared with CMIP5,the CMIP6 MME simulates an average spatial distribution of CO_(2) concentration that is much closer to the site observations,but the CMIP6-inter-model spread is larger.The inter-model differences of the annual means and seasonal cycles of atmospheric CO_(2) concentration are both attributed to the differences in natural sources and sinks of CO_(2) between the simulations.
基金the National Natural Science Foundation of China(42271289).
文摘Ecological stability is a core issue in ecological research and holds significant implications forhumanity. The increased frequency and intensity of drought and wet climate events resulting from climatechange pose a major threat to global ecological stability. Variations in stability among different ecosystemshave been confirmed, but it remains unclear whether there are differences in stability within the sameterrestrial vegetation ecosystem under the influence of climate events in different directions and intensities.China's grassland ecosystem includes most grassland types and is a good choice for studying this issue.This study used the Standardized Precipitation Evapotranspiration Index-12 (SPEI-12) to identify thedirections and intensities of different types of climate events, and based on Normalized DifferenceVegetation Index (NDVI), calculated the resistance and resilience of different grassland types for 30consecutive years from 1990 to 2019 (resistance and resilience are important indicators to measurestability). Based on a traditional regression model, standardized methods were integrated to analyze theimpacts of the intensity and duration of drought and wet events on vegetation stability. The resultsshowed that meadow steppe exhibited the highest stability, while alpine steppe and desert steppe had thelowest overall stability. The stability of typical steppe, alpine meadow, temperate meadow was at anintermediate level. Regarding the impact of the duration and intensity of climate events on vegetationecosystem stability for the same grassland type, the resilience of desert steppe during drought was mainlyaffected by the duration. In contrast, the impact of intensity was not significant. However, alpine steppewas mainly affected by intensity in wet environments, and duration had no significant impact. Ourconclusions can provide decision support for the future grassland ecosystem governance.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB41000000)the National Natural Science Foundation of China(Grant No.42174101,41974023)+1 种基金the Open Fund of Hubei Luojia Laboratory(Grant No.S22H640201)(Germany)The Offshore International Science and Technology Cooperation Center of Frontier Technology of Geodesy。
文摘It is commonly believed that the atmosphere is decoupled from the solid Earth.Thus,it is difficult for the seismic wave energy inside the Earth to propagate into the atmosphere,and atmospheric pressure wave signals excited by earthquakes are unlikely to exist in atmospheric observations.An increasing number of studies have shown that earthquakes,volcanoes,and tsunamis can perturb the Earth's atmosphere due to various coupling effects.However,the observations mainly focus on acoustic waves with periods of less than 10 min and inertial gravity waves with periods of greater than 1 h.There are almost no clear observations of gravity waves that coincide with observations of low-frequency signals of the Earth's free oscillation frequency band within 1 h.This paper investigates atmospheric gravity wave signals within1 h of surface-atmosphere observations using the periodogram method based on seismometer and microbarometer observations from the global seismic network before and after the July 29,2021 M_(w)8.2 Alaska earthquake in the United States.The numerical results show that the atmospheric gravity wave signals with frequencies similar to those of the Earth's free oscillations _(0)S_(2) and _(0)T_(2) can be detected in the microbaro meter observations.The results con firm the existence of atmospheric gravity waves,indicating that the atmosphere and the solid Earth are not decoupled within this frequency band and that seismic wave energy excited by earthquakes can propagate from the interior of the Earth to the atmosphere and enhance the atmospheric gravity wave signals within 1 h.
基金Under the auspices of National Natural Science Foundation of China(No.52279016,51909106,51879108,42002247,41471160)Natural Science Foundation of Guangdong Province,China(No.2020A1515011038,2020A1515111054)+1 种基金Special Fund for Science and Technology Development in 2016 of Department of Science and Technology of Guangdong Province,China(No.2016A020223007)the Project of Jinan Science and Technology Bureau(No.2021GXRC070)。
文摘Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.
基金supported by the National Natural Science Foundation of China(NSFCGrant No.42275061)+3 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)the Laoshan Laboratory(Grant No.LSKJ202202404)the NSFC(Grant No.42030410)the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology.
文摘A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.
基金supported by the National Natural Science Foundation of China(No.41907180).
文摘Using the observation data in Yongxing Island,South China Sea(SCS)from December 2013 to November 2018,the multiple time scales variation of atmospheric CO_(2)and CH_(4)were analyzed to understand their temporal variation characteristics and controlling factors.The regional-averaged background mole fractions of CO_(2)and CH_(4)both show a single-period sinusoidal variation with a lower value at noon and a higher value in the wee hours.In the seasonal scale,they exhibited a significant seasonal difference with higher values in winter and lower values in summer.In the annual scale,CO_(2)and CH_(4)both show an increasing trend,with an annual growth rate of approximately 3.2 ppm and 12 ppb,respectively.The annual growth rate at this site was higher than the global average.The change in atmospheric CO_(2)and CH_(4)in Yongxing Island was probably caused by the higher emission of the surrounding areas and the airflows driven by monsoon.Hopefully,the long-term and high-resolution greenhouse gases(GHGs)dataset will aid relevent researchers and decision-makers in performing more in-depth studies for GHG sources in order to derive effective strategies.
基金the National Key R&D Program of China(2023YFB3812901)the Postdoctoral Fellowship Program of CPSF(No.GZC20230239)+1 种基金the China Postdoctoral Science Foundation(No.2023M740219)the National Natural Science Foundation of China(No.22209094)。
文摘To study the atmospheric aging of acrylic coatings,a two-year aging exposure experiment was conducted in 13 representative climatic environments in China.An atmospheric aging evaluation model of acrylic coatings was developed based on aging data including11 environmental factors from 567 cities.A hybrid method of random forest and Spearman correlation analysis was used to reduce the redundancy and multicollinearity of the data set by dimensionality reduction.A semi-supervised collaborative trained regression model was developed with the environmental factors as input and the low-frequency impedance modulus values of the electrochemical impedance spectra of acrylic coatings in 3.5wt%NaCl solution as output.The model improves accuracy compared to supervised learning algorithms model(support vector machines model).The model provides a new method for the rapid evaluation of the aging performance of acrylic coatings,and may also serve as a reference to evaluate the aging performance of other organic coatings.
基金funded by Lumin S.A. and the Agencia Nacional de Investigación e Innovación (ANII)[POS_NAC_2016_1_130479]
文摘Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major source of nutrient return.To model the litterfall production using climatic variables and assess the nutrient return in 14-year-old Eucalyptus grandis and Pinus taeda stands,we measured litter production over 2 years,using conical litter traps,and monitored climatic variables.Mean temperature,accumulated precipitation,and mean maximum vapor pres-sure deficit at the seasonal level influenced litterfall produc-tion by E.grandis;seasonal accumulated precipitation and mean maximum temperature affected litterfall by P.taeda.The regression tree modeling based on these climatic vari-ables had great accuracy and predictive power for E.grandis(N=33;MAE(mean absolute error)=0.65;RMSE(root mean square error)=0.91;R^(2)=0.71)and P.taeda(N=108;MAE=1.50;RMSE=1.59;R^(2)=0.72).The nutrient return followed a similar pattern to litterfall deposition,as well as the order of importance of macronutrients(E.grandis:Ca>N>K>Mg>P;P.taeda:N>Ca>K>Mg>P)and micronutrients(E.grandis and P.taeda:Mn>Fe>Zn>Cu)in both species.This study constitutes a first approximation of factors that affect litterfall and nutrient return in these systems.
文摘Climate change studies are diverse with no single study giving a comprehensive review of climate change impacts,adaptation strategies,and policy development in West Africa.The unavailability of an all-inclusive study to serve as a guide for practitioners affects the effectiveness of climate change adaptation strategies proposed and adopted in the West African sub-region.The purpose of this study was to review the impacts of climate change risks on the crop,fishery,and livestock sectors,as well as the climate change adaptation strategies and climate-related policies aimed at helping to build resilient agricultural production systems in West Africa.The review process followed a series of rigorous stages until the final selection of 56 articles published from 2009 to 2023.Generally,the results highlighted the adverse effects of climate change risks on food security.We found a continuous decline in food crop production.Additionally,the livestock sector experienced morbidity and mortality,as well as reduction in meat and milk production.The fishery sector recorded loss of fingerlings,reduction in fish stocks,and destruction of mariculture and aquaculture.In West Africa,climate-smart agriculture technologies,physical protection of fishing,and inclusion of gender perspectives in programs appear to be the major adaptation strategies.The study therefore recommends the inclusion of ecosystem and biodiversity restoration,weather insurance,replacement of unsafe vessels,and strengthening gender equality in all climate change mitigation programs,as these will help to secure enough food for present and future generations.
文摘Togo is facing significant climate challenges that have profound consequences for its environment, economy, and population. This study provides an overview of various climate phenomena affecting Togo and highlights potential adaptation strategies. We used the inclusion and exclusion criteria (PRISMA) to search both French and English articles on climate change-related disaster risk events in Togo through Google Scholar, Directory of Open Access Journals (DOAJ), and PubMed databases using the keywords “Climate Change”, “Floods”, “Drought”, “Coastal erosion”, “High winds”, “Epidemy”, Heatwaves”, and “Air pollution”. Twenty-five articles from 2000-2023 were included in this study after applying different criteria. Droughts, floods, coastal erosion, food and crop productivity loss, heatwaves, spread of vector-borne diseases, air pollution, and high winds are among the climate phenomena discussed. These challenges are driven by climate change, altering precipitation patterns, increasing temperatures, and rising sea levels. Drought, floods, coastal erosion, loss of food and crop productivity, spread of vector-borne diseases, air pollution and heatwaves are the most climate risks experienced by Togo. Drought contributes to decreased plant cover, water scarcity, and changes in the water and energy balance. Floods cause property damage, health risks, and disruptions to livelihoods. Coastal erosion threatens coastal communities, infrastructure, and ecosystems. Adaptation strategies include early warning systems, improved water management, sustainable agriculture, urban and health planning, and greenhouse gas emissions reduction. Drought-resistant crops, mosquito control, and clean energy adoption are essential.
基金supported by the National Science Foundation of China(Grant No.42230606)。
文摘Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.
文摘This study focuses on air quality in southern Benin in order to show public authorities what the Beninese populations are exposed to for efficient decision-making. Two sampling campaigns were carried out, one in the wet period and the other in the dry season. The measurements were taken using a monitor called an “Air Quality Monitor”. For data processing, the multiple comparison methods of Dun (1961) and the Wilcoxon test were used. To maintain legitimacy, all spatial data were included in the official cartographic repository of Benin: WGS 1984, Transverse Mercator Universe Projection (UTM), Zone 31 North. The Moran statistic was used to measure the levels of spatial autocorrelation of the variables studied and to test the significance. In order to locate the spatial subsets, the local spatial association indices of Anselin Local Moran and Getis-Ord, Gi* were used. In terms of results, on the 13 monitoring sites and the 8 parameters chosen to determine air quality, we do not note any significant inter-seasonal difference. Of the eight parameters, only three parameters present spatial autocorrelation leading to predictions of ambient air quality over the entire study area based on the distance separating the points, namely, PM<sub>2.5</sub>, PM<sub>10</sub> and ambient air quality index (AQI). The localities affected by atmospheric pollution in South Benin are located in the south-western part of Benin, headed by Cotonou, which is heavily polluted by CO<sub>2</sub>, TCOV, PM<sub>10</sub> and PM<sub>2.5</sub>.
文摘Climate change has been a global pandemic with its adverse impacts affecting environments and livelihoods. This has been largely attributed to anthropogenic activities which generate large amounts of Green House Gases (GHGs), notably carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) among others. In the Upper East of Ghana, climate change manifests in erratic rainfalls, drought, high temperatures, high wind speeds, high intensity rainfall, windstorms, flooding, declining vegetation cover, perennial devastating bushfires etc. Practices such as burning farm residues, use of dung as fuel for cooking, excessive application of nitrogenous fertilizers, and deforestation that are prevalent in the region exacerbate the situation. Although, efforts made by governmental and none-governmental organizations to mitigate climate change through afforestation, agroforestry and promotion of less fuelwood consuming cook stoves, land management practices antagonize these efforts as more CO2 is generated than the carrying capacity of vegetation in the region. Research findings have established the role of trees and soil in carbon sequestration in mitigating climate. However, there is limited knowledge on how the vegetation and soil in agroforestry interplay in mitigation climate change. It is against this background that this review seeks to investigate how vegetation and soil in an agroforestry interact synergistically to sequester carbon and contribute to mitigating climate change in Upper East region of Ghana. In this review, it was discovered soil stored more carbon than vegetation in an agroforestry system and is much effective in mitigating climate change. It was found out that in order to make soil and vegetation in an agroforestry system interact synergistically to effectively mitigate climate change, Climate Smart Agriculture practice which integrates trees, and perennials crops effectively mitigates climate. The review concluded that tillage practices that ensure retention and storage of soil organic carbon (SOC) could be much effective in carbon sequestration in the Savannah zones and could be augmented with vegetation to synergistically mitigate climate change in the Upper East region of Ghana.
