The Earth's climate operates as a complex,dynamically interconnected system,driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback loops.This study employs a theoretical framework and the Eigen Microstate(EM)approach of statistical physics to examine global surface temperature variations since 1948,as revealed by a global reanalysis.We identified EMs significantly correlated with key climate phenomena such as the global monsoon system,tropical climates,and El Niño.Our analysis reveals that these EMs have increasingly influenced global surface temperature variations over recent decades,highlighting the critical roles of hemispheric differences,land-sea contrasts,and tropical climate fluctuations in a warming world.Additionally,we used model simulations from more than 10 Coupled Model Intercomparison Project Phase 6(CMIP6)under three future climate scenarios to perform a comparative analysis of the changes in each EM contribution.The results indicate that under future warming scenarios,tropical climate fluctuations will become increasingly dominant,while traditional hemispheric and monsoonal patterns may decline.This shift underscores the importance of understanding tropical dynamics and their impact on global climate from a physics-based perspective.Our study provides a new perspective on understanding and addressing global climate change,enhancing the theoretical foundation of this critical field,and yielding findings with significant practical implications for improving climate models and developing effective mitigation and adaptation strategies.
Hua TuShang WangJun MengYongwen ZhangXiaosong ChenDeliang ChenJingfang Fan
Climate change is getting worse and worse,and we're seeing moreextreme(极端的)weather.This is causing(导致)a big challenge.Nowthe question is,what should we do?
Climate change is becoming a major issue for agriculture and the well-being of farmers. The objective of this article is to identify and analyze the production factors that may influence the competitiveness level of agricultural operations, as well as to establish a structural and functional typology of these farms. Using Principal component analysis (PCA) combined with hierarchical ascending classification (HAC) on 250 farmers, the study was able to set farms typology. Furthermore, variance analysis and econometric models (linear et quadratic) were also used for in-depth analysis. The results show the existence of three groups of farm (GA, GB, GC): GA (19.7%), GB (65.3%), and GC (15%). Drought spells and flood are the main climatic risks affecting rain-fed farm operations. For irrigated crops such as rice, the major constraints remain bird attacks, the invasion of pests and nematodes. Climate variability significantly increases the prevalence of morbidities in the region by raising the number of inactive individuals. This significantly and differentially affects the outcomes of these assets. Health expenditures represent a significant share (GB: 12% and GC: 11%) and a non-negligible share (GA: 8.4%). However, larger participations (GC) show better economic performance due to economies of scale, but all categories would benefit from adopting appropriate strategies to reduce losses and increase their resilience.
In this study, we focused on describing the trends of Extreme Precipitation Indices (EPI) in Senegal and analyzing the significant links between their variability and key climatic factors such as the El Niño-Southern Oscillation Index (ONI), the Land-Ocean Temperature Index (LOTI), and the Land Surface Temperature Index (LST). Based on a century of daily rainfall data from various Senegalese stations, this study utilized twelve (12) EPIs calculated according to the definitions of the Expert Team on Climate Change Detection and Indices (ETCCDI). To analyze the temporal variation characteristics of extreme precipitation, the Mann-Kendall (MK) test was employed to perform a uniformity test on the precipitation data series. A dependence method through differentiation was used to remove data trends and observe correlations between the climate change indices ONI, LOTI, LST, and EPIs. An approach based on lagged correlations between the ONI index and the EPIs was applied to evaluate the predictability of extreme precipitation patterns in Senegal. Trend analysis indicates a significant decrease in total precipitation and frequency and intensity indices in most stations, while duration indices show no clear trend. Regarding their interannual variability, the analysis shows negative correlations between ONI and total precipitation, consistent with the known influence of ENSO on Sahel precipitation. Correlations with LOTI and LST indices, on the other hand, suggest that the Clausius-Clapeyron theory does not hold at Senegal’s latitudes, but that adjacent Atlantic ocean warming influence is crucial in modulating extreme precipitation patterns. Finally, on the predictability of extreme precipitation, the study shows a significant signal up to three months in advance with ENSO for 58% of the EPIs and up to two months in advance for 90% of the EPIs.
Moussa DiakhatéKhadidiatou Ina ManeAbdou Lahat DiengAïssatou BadjiMamadou NdiayeDahirou WaneAmadou Thierno Gaye
In Niger, farms have been facing negative effects of climate change for several decades. The objective of this work is to assess the vulnerability of farms in Tillabery department by proposing an adaptation approach. A five-step method and descriptive analysis were used on a sample of 250 farmers. The degree of damage caused by pests and crop diseases is significant, with respective proportions of 52.50% and 40.40%. It appears that the main climate risk factors for vulnerability are droughts, floods, soil degradation, and pest invasions. Additionally, the average level of exposure to agricultural operations is very high, with an index of 0.6. The sensitivity index remained constant in the range of 0.3 to 0.6 and is significant (reaching an index of 0.8). However, 61.2% of farms have a medium level of vulnerability and 33.3% have a high vulnerability to the effects of climate change. Nonetheless, a concerning trend regarding the vulnerability of farms has been observed. To assist policymakers and development actors in improving the vulnerability level of these production units, four phases of action are proposed: a diagnostic phase, evaluation, estimation of adaptation needs, implementation, and proper monitoring of actions.
Idrissa Saidou MahamadouYacouba Ali RazinatouSoumana Boubacar
Because of their effect on climate,carbon dioxide(CO_(2)),methane(CH_(4)),nitrous oxide(N_(2)O),and dimethylsulfide(DMS)are collectively designated as climate-relevant gases(CRGs).CO_(2),CH_(4),and N_(2)O are greenhouse gases contributing to global warming(positive climate feedback).Conversely,DMS is involved in the generation of cloud condensation nuclei,thus in the formation of clouds that cool the boundary layer by reflecting incoming solar radiation(negative climate feedback).Despite their scarcity,field observations and model results have demonstrated the essential role of polar oceans in the budget of CRGs.For example,the Southern Ocean represents a substantial CO_(2)sink but a source of N_(2)O and DMS,thereby exerting variable feedback on climate change.Unfortunately,because of the severe environmental conditions at polar latitudes,substantial knowledge gaps remain,for example on the mechanisms underlying CRGs formation or on the strength and distribution of their sources and sinks in the Southern and Arctic Oceans.Here,we review the most recent research results on the distribution,production-loss processes,and abundance variations of CRGs in the polar oceans.We list the remaining knowledge gaps and propose future directions of research on CRGs in the polar oceans,as a useful reference for future studies.
