2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.

Discovery of the Significant Impacts of Swell Propagation on Global Wave Climate Change

This study compared the differences in the wave climate in the South China Sea and North Indian Ocean under these two datasets:ERA-40 wave reanalysis and Mei’s hindcast wave data.In the numerical calculation of regional ocean waves,the wave climate characteristics exhibited significant bias if the influence of external swells(swells from afar)was not fully considered,which may provide an incorrect basis for global climate change analysis.1)The trends of the significant wave height(SWH)obtained from the two datasets showed significant differences,such as those of the Bay of Bengal and the Java Sea in June-July-August.For the past 45 years,SWH from ERA-40(SWH-ERA)exhibited a significant annual increase in low-latitude waters of the North Indian Ocean(0.2-0.6 cm yr^(-1))and South China Sea(0.2-0.8 cm yr^(-1)).2)In the Bay of Bengal,the SWH-ERA in each month was generally 0.5 m higher than the SWH from Mei’s hindcast wave data(SWH-Mei)and can reach 1.0 m higher in some months.3)In the Bay of Bengal,SWH-ERA and SWH-Mei increased significantly at annual rates of 0.13 and 0.27 cm yr^(-1),respectively.This increasing trend was mainly reflected after 1978.SWH-ERA showed a trough in 1975(1.33 m)and a crest in 1992(1.83 m),which were not reflected in SWH-Mei.

Habitable Land Will Soon Become the World’s Scarcest Resource: Why Appalachia Should Choose Climate Change Havens over Millionaire Estates and Golf Courses

This research advocates for the construction of Climate Change Haven Communities across the Appalachian Region. The proposed development plan can be extended to the northern tier states across the US and also to the northern and mountainous regions of Europe and Asia. We present an analogy to the earlier climate change period of the Last Glacial Maximum/“Ice Age” in which these same northern regions of the planet were covered in ice sheets making them uninhabitable for most humans and many plant and animal species. In some significant ways, the Ice Age scenario can be a reverse-model for our current climate crisis. We also advocate strongly for the prevention of upscale real estate development projects in these same regions of the globe, as these will foreclose the possibility of safely sheltering the millions of persons who will be displaced by climate change over the next 5 to 10 years.

The Global Energy and Water Exchanges(GEWEX)Project in Central Asia:The Case for a Regional Hydroclimate Project

Central Asia consists of the former Soviet Republics,Kazakhstan,Kyrgyz Republic,Tajikistan,Turkmenistan,and Uzbekistan.The region’s climate is continental,mostly semi-arid to arid.Agriculture is a significant part of the region’s economy.By its nature of intensive water use,agriculture is extremely vulnerable to climate change.Population growth and irrigation development have significantly increased the demand for water in the region.Major climate change issues include melting glaciers and a shrinking snowpack,which are the foundation of the region’s water resources,and a changing precipitation regime.Most glaciers are located in Kyrgyzstan and Tajikistan,leading to transboundary water resource issues.Summer already has extremely high temperatures.Analyses indicate that Central Asia has been warming and precipitation might be increasing.The warming is expected to increase,but its spatial and temporal distribution depends upon specific global scenarios.Projections of future precipitation show significant uncertainties in type,amount,and distribution.Regional Hydroclimate Projects(RHPs)are an approach to studying these issues.Initial steps to develop an RHP began in 2021 with a widely distributed online survey about these climate issues.It was followed up with an online workshop and then,in 2023,an in-person workshop,held in Tashkent,Uzbekistan.Priorities for the Global Energy and Water Exchanges(GEWEX)project for the region include both observations and modeling,as well as development of better and additional precipitation observations,all of which are topics for the next workshop.A well-designed RHP should lead to reductions in critical climate uncertainties in policy-relevant timeframes that can influence decisions on necessary investments in climate adaptation.

Sedimentological evidence of climate-tectonic interaction in the upper Satluj catchment of NW Himalaya

Quaternary valley fill deposits in the Upper Satluj Valley of NW Himalaya act as archives of changing climate-tectonic dynamics in a region.Quaternary landforms help in decoding the relationship between climate and tectonics.Kinnaur region is traversed by several active faults and thrusts such as the Kaurik-Chango Fault(KCF)and Sangla Detachment(SD),thereby making upper Satluj Valley tectonically active.Morphotectonic parameters such as width of valley floor(Vfw),Normalized Steepness Index(KSn)and geomorphological evidences such as the presence of huge strath terraces,narrowing of the river valley and palaeolake deposits point towards the tectonically active nature of the terrain.This arid,high elevation region is also climatically sensitive as it falls in a transient climatic zone which receives rainfall only during abnormal monsoon months.Excessive rainfall causes outburst floods,a common phenomenon in the area due to the blocking of headwater in the upper reaches of the Satluj valley.As a result,the Quaternary sequence is modified from time to time.The transition from hypo concentrated deposits to channel deposits and ponding events are prominent in the depositional sequence,resulting from a response to climate.The studied Quaternary sediments reveal that the Trans-Himalayan region of the upper Satluj valley is affected by tectonic-climate variability,making it vulnerable to geohazards.

Cameroon Climate Predictions Using the SARIMA-LSTM Machine Learning Model: Adjustment of a Climate Model for the Sudano-Sahelian Zone of Cameroon

It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.

Toward a Learnable Climate Model in the Artificial Intelligence Era

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

A Systematic Literature Review of the Impact of Climate Change on Menopause: Altering the Age, Severity of Symptoms and Long-Term Effects

Objective: This systematic review investigates the impact of climate change on menopause, focusing on the correlation between geographical location—considering altitude, temperature, humidity, and annual temperature range—and women’s menopausal experiences. This study aims to interpret how these environmental factors influence the age of onset, severity of symptoms such as hot flushes and night sweats, and other long-term effects of menopause. Understanding these relationships addresses a significant gap in current knowledge and could guide future public health strategies. Methods: Through a comprehensive analysis of three cross-continental studies involving 1500 postmenopausal women from Spain, South American countries (Ecuador, Panama, Chile), various climates in Türkiye (Black Sea, Mediterranean, Continental), and the United Arab Emirates (UAE), this review evaluates diverse environmental impacts. Studies were selected based on their methodological rigor, geographical diversity, and focus on the unique and personal experiences of menopause. Data was collected via questionnaires and routine medical checkups, analyzing demographic, lifestyle, mood, symptom severity, and onset age variables. Results: Preliminary analysis indicates that 52.5% of participants from Spanish-speaking countries and the UAE reported vasomotor symptoms, with those in higher temperatures and lower altitudes experiencing exacerbated symptoms. Notably, Mediterranean climates were associated with an earlier menopause onset. Seasonal changes had minimal impact across all regions, suggesting lifestyle and other environmental factors play a more significant role. Conclusions: The findings highlight a clear link between climate-related geographical factors and the menopausal experience. Women in warmer, lower-altitude regions suffer more severe symptoms, while those in Mediterranean climates face earlier onset. The absence of significant seasonal variations across the studies underscores the predominance of lifestyle and environmental factors over purely climatic conditions. These insights pave the way for targeted interventions and support the need for further public health research into the complex interactions between climate change and menopause.

Climate and topography regulate the spatial pattern of soil salinization and its effects on shrub community structure in Northwest China

Soil salinization may affect biodiversity and species composition,leading to changes in the plant community structure.However,few studies have explored the spatial pattern of soil salinization and its effects on shrub community structure at the ecosystem scale.Therefore,we conducted a transect sampling of desert shrublands in Northwest China during the growing season(June–September)in 2021.Soil salinization(both the degree and type),shrub community structure(e.g.,shrub density and height),and biodiversity parameters(e.g.,Simpson diversity,Margalf abundance,Shannon-Wiener diversity,and Pielou evenness indices)were used to assess the effects of soil salinization on shrub community structure.The results showed that the primary degree of soil salinization in the study area was light salinization,with the area proportion of 69.8%.Whereas the main type of soil salinization was characterized as sulfate saline soil,also accounting for 69.8%of the total area.Notably,there was a significant reduction in the degree of soil salinization and a shift in the type of soil salinization from chloride saline soil to sulfate saline soil,with an increase in longitude.Regional mean annual precipitation(MAP),mean annual evapotranspiration(MAE),elevation,and slope significantly contributed to soil salinization and its geochemical differentiation.As soil salinization intensified,shrub community structure displayed increased diversity and evenness,as indicated by the increases in the Simpson diversity,Shannon-Wiener diversity,and Pielou evenness indices.Moreover,the succulent stems and leaves of Chenopodiaceae and Tamaricaceae exhibited clear advantages under these conditions.Furthermore,regional climate and topography,such as MAP,MAE,and elevation,had greater effects on the distribution of shrub plants than soil salinization.These results provide a reference for the origin and pattern of soil salinization in drylands and their effects on the community structure of halophyte shrub species.

Litter production and leaf nutrient concentration and remobilization in response to climate seasonality in the central Amazon

Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seasonality remain largely unknown for the central Amazon.This study meas-ured litterfall production,leaf nutrient remobilization,and leaf area index on a forest plateau in the central Amazon.Litterfall was measured at monthly intervals during 2014,while nitrogen,phosphorus,potassium,calcium and mag-nesium concentrations of leaf litter and canopy leaves were measured in the dry and rainy seasons,and remobilization rates determined.Leaf area index was also recorded in the dry and rainy seasons.Monthly litterfall varied from 33.2(in the rainy season)to 87.6 g m^(-2) in the dry season,while leaf area index increased slightly in the rainy season.Climatic seasonality had no effect on concentrations of nitrogen,calcium,and magnesium,whereas phosphorous and potassium responded to rainfall seasonality oppositely.While phosphorous increased,potassium decreased during the dry season.Over seasons,nitrogen,potassium,and phosphorous decreased in leaf litter;calcium increased in leaf litter,while magnesium remained unaffected with leaf aging.Regardless,the five nutrients had similar remobilization rates over the year.The absence of climate seasonality on nutrient remobilization suggests that the current length of the dry season does not alter nutrient remobilization rates but this may change as dry periods become more prolonged in the future due to climate change.

Application of Predictive Model for Efficient Cassava (Manihot esculenta Crantz) Yield in the Face of Climate Variability in Enugu State, Nigeria

Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate variability incidence which can be communicated to local farmers by agro-meteorological extension officers, research on crops that can grow with little or no rain, planning irrigation scheme, and improving tree planting culture in the study area.

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.

Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model

Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.

Projected impacts of climate change on the habitat of Xerophyta species in Africa

Climate change poses a serious long-term threat to biodiversity.To effectively reduce biodiversity loss,conservationists need to have a thorough understanding of the preferred habitats of species and the variables that affect their distribution.Therefore,predicting the impact of climate change on speciesappropriate habitats may help mitigate the potential threats to biodiversity distribution.Xerophyta,a monocotyledonous genus of the family Velloziaceae is native to mainland Africa,Madagascar,and the Arabian Peninsula.The key drivers of Xerophyta habitat distribution and preference are unknown.Using 308 species occurrence data and eight environmental variables,the MaxEnt model was used to determine the potential distribution of six Xerophyta species in Africa under past,current and future climate change scenarios.The results showed that the models had a good predictive ability(Area Under the Curve and True Skill Statistics values for all SDMs were more than 0.902),indicating high accuracy in forecasting the potential geographic distribution of Xerophyta species.The main bioclimatic variables that impacted potential distributions of most Xerophyta species were mean temperature of the driest quarter(Bio9)and precipitation of the warmest quarter(Bio18).According to our models,tropical Africa has zones of moderate and high suitability for Xerophyta taxa,which is consistent with the majority of documented species localities.The habitat suitability of the existing range of the Xerophyta species varied based on the climate scenario,with most species experiencing a range loss greater than the range gain regardless of the climate scenario.The projected spatiotemporal patterns of Xerophyta species help guide recommendations for conservation efforts.

Effect of Supplementary Irrigation on the Yield of Sorghum (Sorghum bicolor L. Moench) in the Context of Climate Change in the Dry Savannahs of Togo

Under the current context of climate change, supplementary irrigation may be needed for crop production resilience. We determined the effects of supplementary irrigation on sorghum grain yield in the dry Savannah region of Togo. A two-year trial was conducted in a controlled environment at AREJ, an agro-ecological center in Cinkassé. The plant material was sorghum variety Sorvato 28. The experimental design was a Completely Randomized Block with three replications and three treatments as follows: T0 control plot (rainfed conditions);T1 (supplementary irrigation from flowering to grain filling stage) and T2 (supplementary irrigation from planting to grain filling stage). Two irrigation techniques (furrow and Californian system) were used under each watering treatment. The results showed that irrigation technique significantly affected panicle length with no effect on 1000 grains mass. Panicle length and grain yields varied from 15.59 to 25.71 cm and 0.0 to 2.06 t∙h−1, respectively, with the highest values (25.66 cm and 2.06 t∙h−1, respectively) under the T2 treatment with the California system-based supplementary irrigation. The comparison of results obtained on treatment T0 and T2, shows that supplementary irrigation increased the yields by at least 68.62%. Supplementary irrigation during sowing and growing season (T2) improved sorghum yields in the dry savannahs of Togo, with a better performance of the California irrigation system.

The Cloud Model for Climate Change

In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model. Some interesting observations are revealed. The IPCC model equated average temperatures with average energy fluxes, which can cause significant errors. The model assumed that all energy fluxes remained constant, and the Earth emitted infrared radiation as if it were a blackbody. Neither of those conditions exists. The IPCC’s definition of Climate Change only includes events caused by human actions, excluding most causes. Satellite data aimed at the tops of clouds may have inferred a high Greenhouse Gas absorption flux. The model showed more energy coming from the atmosphere than absorbed from the sun, which may have caused a violation of the First and Second Laws of Thermodynamics. There were unexpectedly large gaps in the satellite data that aligned with various absorption bands of Greenhouse Gases, possibly caused by photon scattering associated with re-emissions. Based on science, we developed a cloud-based climate model that complied with the Radiation Laws and the First and Second Laws of Thermodynamics. The Cloud Model showed that 81.3% of the outgoing reflected and infrared radiation was applicable to the clouds and water vapor. In comparison, the involvement of CO2 was only 0.04%, making it too minuscule to measure reliably.

Stability assessment of tree ring growth of Pinus armandii Franch in response to climate change based on slope directions at the Lubanling in the Funiu Mountains,China

Global warming will affect growth strategies and how trees will adapt.To compare the response of tree radial growth to climate warming in different slope directions,samples of Pinus armandii Franch were collected and tree-ring chronologies developed on northern and western slopes from the Lubanling in the Funiu Mountains.Correlation analyses showed that two chronologies were mainly limited by temperatures in the previous June-August and the com-bination of temperatures and moisture in the current May-July.The difference of the climate response to slopes was small but not negligible.Radial growth of the LBLO1 site on the northern slope was affected by the combined maximum and minimum temperatures,while that of the LBLO2 site was affected by maximum temperatures.With regards to moisture,radial growth of the trees on the north slope was influenced by the relative humidity in the current May-July,while on the western slope,it was affected by the relative humidity in the previous June-August,the current May-July and the precipitation in the current May-July.With the change in climate,the effects of the main limiting factors on growth on different slopes were visible to a certain extent,but the differences in response of trees on different slopes gradually decreased,which might be caused by factors such as different slope directions and the change in diurnal temperature range.These results may provide information for forest protection and ecological construction in this region,and a scientific reference for future climate reconstruction.

Stability assessment of tree ring growth of Pinus armandii Franch in response to climate change based on slope directions at the Lubanling in the Funiu Mountains,China

Global warming will affect growth strategies and how trees will adapt.To compare the response of tree radial growth to climate warming in different slope directions,samples of Pinus armandii Franch were collected and treering chronologies developed on northern and western slopes from the Lubanling in the Funiu Mountains.Correlation analyses showed that two chronologies were mainly limited by temperatures in the previous June–August and the combination of temperatures and moisture in the current May–July.The difference of the climate response to slopes was small but not negligible.Radial growth of the LBL01 site on the northern slope was affected by the combined maximum and minimum temperatures,while that of the LBL02 site was affected by maximum temperatures.With regards to moisture,radial growth of the trees on the north slope was influenced by the relative humidity in the current May–July,while on the western slope,it was affected by the relative humidity in the previous June–August,the current May–July and the precipitation in the current May–July.With the change in climate,the effects of the main limiting factors on growth on different slopes were visible to a certain extent,but the differences in response of trees on different slopes gradually decreased,which might be caused by factors such as different slope directions and the change in diurnal temperature range.These results may provide information for forest protection and ecological construction in this region,and a scientific reference for future climate reconstruction.

The Role of Certificates and Labels for Cocoa in the Face of Climate Change: A Scientific Review

Climate change threatens cocoa quality, raising concerns regarding sustainable premium cocoa production. Evaluating the effectiveness of certification standards is imperative to address this concern effectively. A multi-stage method was employed for a systematic review of 39 peer-reviewed articles to highlight the impacts of climate change on the biophysical environment of cocoa and its implications for adapting Geographical Indications (GIs). Additionally, a comprehensive review was conducted on climate-relevant standards of certificates in Ecuador, Indonesia, and Ghana. The findings of this study provide practical insights into possible difficulties that cocoa-producing countries may encounter in maintaining the distinctive flavours and quality trademarks of cocoa in the face of changing climate. Moreover, the findings emphasize the need for producer countries to prioritize viable adaptation and product differentiation strategies that meet sustainable marketing standards to protect GIs or place-based intellectual property. Furthermore, the findings indicate certificates require effective multi-level climate change management and environmental-social-governance principles that promote scientifically proven mitigation strategies, such as increasing soil organic carbon, zero deforestation, and reducing emissions while striving to leverage local adaptation policies to reduce location-specific vulnerability. Finally, certificates can accelerate the expansion, intensification, and redistribution of sustainable production for gains that outweigh the inconveniences caused by climate change.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.