Climate Phenomena Research Articles

Early 20th century Southern Hemisphere cooling

Abstract. Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW.

Enhancing Global Food Security: Opportunities for the American Meteorological Society

Abstract Food security is a key pillar of environmental security yet remains one of the world’s greatest challenges. Its obverse, food insecurity, negatively impacts health and well-being, drives mass migration, and undermines national security and global sustainable development. Ensuring food security is a delicate balance of myriad concerns within the atmospheric and Earth sciences, agronomy and agriculture engineering, social sciences, economics, monitoring, and policymaking. A Food Security Presidential Session at the American Meteorological Society’s (AMS) 2022 Annual Meeting brought together experts across disciplines to tackle issues at the nexus of weather, climate, and food security. The starkest takeaway was the realization that, despite its importance and clear roles for the atmospheric and climate sciences, food security has not been a focus for the AMS community. The aim of this paper is to build on the perspectives shared by this expert panel and to identify overlapping issues and key points of intersection between the food-security community and AMS. We examine 1) the interactions between weather, climate, and the food system and how they influence food security; 2) the time and spatial scales of food security decision support that match weather and climate phenomena; 3) the role of both providers and users of information as well as decision-makers in improving research to operations for food security; and 4) the opportunities for the AMS community to address food security. We conclude that, moving forward, the AMS community is well-positioned to scale up its engagement across the global food system to address existing scientific needs and technology gaps to improve global food security.

The sampling method for optimal precursors of El Niño–Southern Oscillation events

Abstract. The El Niño–Southern Oscillation (ENSO) is a significant climate phenomenon that appears periodically in the tropical Pacific. The intermediate coupled ocean–atmosphere Zebiak–Cane (ZC) model is the first and classical one designed to numerically forecast the ENSO events. Traditionally, the conditional nonlinear optimal perturbation (CNOP) approach has been used to capture optimal precursors in practice. In this paper, based on state-of-the-art statistical machine learning techniques1, we investigate the sampling algorithm proposed in Shi and Sun (2023) to obtain optimal precursors via the CNOP approach in the ZC model. For the ZC model, or more generally, the numerical models with a large number O(104−105) of degrees of freedom, the numerical performance, regardless of the statically spatial patterns and the dynamical nonlinear time evolution behaviors as well as the corresponding quantities and indices, shows the high efficiency of the sampling method compared to the traditional adjoint method. The sampling algorithm does not only reduce the gradient (first-order information) to the objective function value (zeroth-order information) but also avoids the use of the adjoint model, which is hard to develop in the coupled ocean–atmosphere models and the parameterization models. In addition, based on the key characteristic that the samples are independently and identically distributed, we can implement the sampling algorithm by parallel computation to shorten the computation time. Meanwhile, we also show in the numerical experiments that the important features of optimal precursors can still be captured even when the number of samples is reduced sharply.

Potential of Nature-Based Solutions to Diminish Urban Heat Island Effects and Improve Outdoor Thermal Comfort in Summer: Case Study of Matadero Madrid

Urban heat island effects and climate change are climatic phenomena responsible for periods of extreme heat in summer which severely impact citizens’ well-being and health. In this alarming context which questions the livability of our cities, Nature-Based Solutions (NBSs) are considered an unavoidable component of the complex strategy in diminishing urban temperatures. The present work aims to show the relevance of NBSs in urban temperature regulation through the estimation of their potential to improve outdoor thermal comfort of the heritage site Matadero Madrid. To this end, this article evaluates the effects of a scenario combining different solutions including NBSs and identifies which solutions are the most effective. The results show that this scenario has an impact on direct solar radiation and wind speed but does not affect air temperature and relative humidity. Furthermore, even if this scenario combining a fabric canopy, tree canopy, and green area significantly improves thermal conditions, it does not allow us to reach an optimal level of thermal comfort for visitors. To consider the implementation of more meaningful interventions, existing legal, administrative, and cultural limitations of the case study should be omitted. This would enable us to identify which restrictions could be adapted, thus unlocking the adaptation potential of Matadero Madrid.

Quantifying High-Temperature and Drought Stress Effects on Soybean Growth and Yield in the Western Guanzhong Plain

High-temperature and drought events significantly impact crop growth and development. In the soybean-producing region of the Guanzhong Plain in China, understanding the dynamics of these climatic phenomena is vital for soybean yield preservation. Through a fixed-position observation experiment that analyzed four growth stages, nine agronomic traits, and soybean yield per unit area from 1998 to 2023, this research evaluated the characteristics of high-temperature and drought processes in various growth stages. It also examined the influence of high-temperature processes, drought processes, and their combined effects on agronomic traits and yield. The results indicate the following: (1) High temperature was a constant factor during the soybean growth period, with temperature-related indices markedly surpassing those related to drought. Notably, the occurrence of high-temperature and drought events was more prevalent during the flowering–podding stage than at the podding or grain-filling stages. (2) High temperature profoundly affected soybean yield components, primarily through a decrease in the number of grains per plant during the flowering–podding stage, subsequently impacting the grain weight per plant and yield. In years with extremely high temperatures, the soybean plant height was reduced by 6.1 to 15 cm, the main stem node number decreased by 0.1 to 2.9, the branch number decreased by 0.2 to 0.6, the number of pods per plant decreased by 4.8 to 13.7, the number of grains per pod decreased by 0.1 to 0.3, the number of grains per plant decreased by 13.5 to 32.6, the grain weight per plant decreased by 3.8 to 6.9 g, and the 100-grain weight decreased by 0.1 to 4.5 g. The common impact of high temperature combined with drought processes in different growth stages was reflected in the reduction in the number of branches by 0.1 to 1.4 and the reduction in the number of grains per pod by 0.02 to 13.7. This study underscores the importance of addressing the quantitative effects of climate change and extreme weather on soybean yield, which could help to develop effective adaptation and mitigation strategies.

On The Interannual Variability of Indonesian Monsoon Rainfall (IMR): A Literature Review of The Role of its External Forcing

The IMR variability is notorious for its hydrometeorological disasters. This paper examines recent studies on IMR and the main factors controlling its variability. The focus of this study is to investigate the impact of the atmosphere-ocean interaction that acts as the external forcing of IMR in the tropical Indian and Pacific Oceans. Specifically, the study will examine the influence of two climate phenomena, namely the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) and their interdecadal changes associated Pacific Decadal Oscillation (PDO), on the IMR. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Furthermore, data sets (such as rainfall, wind field, and SST) spanning 1990-2020 were used to verify the key findings. In general, this study concludes that the majority of the authors coincided with the following conclusion: ENSO and IOD events impact IMR by changing its amplitude, duration, intensity, and frequency of mean and extreme rainfall. Additionally, it has been shown that their impacts on IMR are most substantial during the dry seasons, specifically in June, July, and August (JJA), and not as strong as during the wet seasons, specifically in December, January, and February (DJF). Spatially, the effects of ENSO and IOD on IMR variability are clearly found more eastward and westward of the region, respectively. The expansions towards the east and west directions were facilitated by the displacement of the ascending and descending of Walker circulation patterns in the Indonesian region, respectively. Given the interannual fluctuations in IMR, caused mainly by ocean-atmosphere interactions, the knowledge gap of atmospheric factors like the Quasi-Biennial Oscillation (QBO) must be investigated in the future, as suggested by previous research and our preliminary study.

Food system futures in Finland: How do experts evaluate changes in resilience up to 2030?

Food security has received much attention since sudden shocks like Covid-19 and the Russian invasion of Ukraine. Resilience to sudden changes and disruptions is called for to maintain food availability in societies. In this study, potential disruptions and changes in the Finnish food system’s operating environment were evaluated. We focused on two future challenges: 1) what key disruptions will confront the food system until 2030; and 2) how will the Finnish food system change based on the experts’ views, and what measures will develop resilience up to 2030? We used the Delphi technique for data gathering. According to the results, the most significant shock at all three levels, national, EU, and global, was the disruptions caused by climate change (the increase in extreme climate and weather phenomena). An increase in the efficient recycling of nutrients was seen as most desirable, and an increase in the costs associated with recovery from disturbances and shocks was seen as most likely. Reducing inputs’ dependence on imports was seen as a key measure for developing resilience. Two constructed scenarios were presented, which highlight the determinants and uncertainties in the development of resilience in Finland.

Long-term responses of maar lakes water level to climate and groundwater variability in central Mexico

Besides water level (WL) variability, several lakes worldwide have shown water level decline trends and total desiccation. In maar lakes, there is paleoenvironmental evidence of water level responses to climate and groundwater inflow changes; however, historical studies are scarce. Understanding the relative contributions of natural variability and anthropogenic impacts to the decline of lakes' water level is fundamental to preserving these ecosystems. In this study, we developed a conceptual baseline of the response of tropical maar lakes to climate and groundwater variability at different time scales in near natural conditions. The four analyzed maar lakes are in a semiarid, endorheic basin in central Mexico and the study time frame (1959 to 1992) includes a historical period before direct human impact. We analyzed the effects of meteorological records, large-scale climate phenomena indices (ENSO, PDO, and AMO), and regional groundwater levels on WL datasets using multiple linear regression models, trend analysis and cross correlations. WL responded to meteorological seasonality and climate variability indices. All lakes lost more water to evaporation than they gained from precipitation, which partially explains long-term WL declines. Regional groundwater levels decreased, suggesting a reduction of groundwater inflow to the lakes, which contributed to WL declines. The latter may reflect a lagged effect of long-term recharge decrease, probably due to long-term climate change in the region since the formation of the lakes evidenced in previous studies. The results add to evidence of water level declines caused by groundwater-mediated natural variability, warning about how this process is being exacerbated by anthropic activities under the context of global change.

Diatom-based indications of an environmental regime shift and droughts associated with seasonal monsoons during the Holocene in Biển Hồ maar lake, the Central Highlands, Vietnam

The interactions of the different monsoon systems across Southeast Asia create extreme climate phenomena. Central Vietnam, located near the centre of this transitional region, has encountered numerous effects. As a result, its sediments from lakes or speleothems are valuable archives for interpreting past climate variability. However, there is still a lack of high-resolution paleoenvironmental and palaeoclimatic reconstructions during the Holocene in Vietnam. Our study presents a paleoenvironmental diatom-based record of sediment cores collected from Biển Hồ maar lake (14°03′N, 108°00′E) in the Central Highlands of Vietnam covering nearly the entire Holocene. Based on changes in diatom assemblages in the sediment sequence, we identified two periods of the Early Holocene (~11,700–7800 cal BP) and the Mid- to Late-Holocene (~7800–360 cal BP), which mark a remarkable shift in the environment around Biển Hồ. Alternations of key diatom species during the Early Holocene indicate intensity variations between water-mixing and thermal stratification mechanisms in meso-eutrophic conditions. During the Mid- to Late-Holocene, the complete dominance of Aulacoseira granulata var. granulata implies year-round destratification and intense mixing of the lake water column in a permanently eutrophic environment. Its morphological variability reveals intervals of dry environmental conditions driven by pronounced droughts across the Asian continent.

Climate Change Impacts on Human Health

Our environment provides us with natural resources that are important for our survival and livelihoods. The Earth’s species are dependent on the ecosystem service functions of our planet which is driven by climate stability. Health is a very important aspect and is most essential for life. Health is directly related to the nature of the environment, weather and climate. Changes in weather and climate have influenced the health of human populations in the past and caused several epidemics. Weather and climate can affect the distribution and survival of several arthropods, such as mosquitoes or mammals that are vectors for various diseases. Recently many people in Kerala and some parts of South India were affected by the West Nile virus which is attributed to the changing weather and vector borne influences. This fever is a mosquito-borne zoonotic disease and is caused by the flavivirus — West Nile Virus. The state of Kerala was on high alert as a seven year old boy from Mallapuram died in Kozikode due to the virus. In the same way, the water quality can be impacted giving rise to health problems. We are observing changes in the frequency and severity of weather and climate phenomena. This is seen as heavy rains, droughts, and also extreme cold or hot temperatures in different geographical regions. All this can lead to new climate-related health threats. Therefore, climate variability can pose threats to human health in several ways. The impacts of climate change are already being witnessed and will further increase in the coming decades. It may also lead to several emerging infectious diseases. Scientists study the exposure pathways in humans and animals for understanding the impacts of climate change on health. This involves conducting studies over time and in different locations, among different communities. In this research paper will discuss about the various impacts of climate change on human health.

CLIMATE PLANNING AND LOCAL GOVERNMENT: ACTORS AND CLIMATE CHANGE MEASURES

Urban development based on anthropogenic systems led to evident urban transformations on a global and local scale. Climate change is the product of these transformations, characterized by weather patterns and ecological systems alterations. These alterations cause impacts on urban dynamics, which generate severe social consequences. It becomes imperative to assume the inevitability of the climate phenomenon and adopt a new management model with adaptation and mitigation actions. The research addresses the climatic phenomenon in Ecuador, specifically in the urban area of Riobamba, emphasizing its planning instruments. The objective is to recognize the scope of local instruments and plans related to climate change and to identify actors involved through a map of actors according to their level of engagement and support for climate change action. The research contemplates a descriptive methodology with a qualitative approach using theoretical and argumentative techniques. The research considers documentary and fieldwork through methods such as documentary analysis, unstructured observation, in-depth interviews with strategic actors, case studies, and self-completed perception surveys of available subjects, corresponding to an exploratory and descriptive level. The results show that the local government did not consider initiatives aimed at climate planning and, despite programs and projects that seek to solve environmental problems, they need to be developed in detail or linked as measures against climate change.

Development of an evaluation indicator for highway climate change adaptation projects based on analytical hierarchy process in South Korea

AbstractOwing to climate change, abnormal climate phenomena occur frequently, damaging aging highway facilities. Therefore, it is necessary to develop adaptation projects for highway systems. Adaptation projects focus on mitigating the impact of climate change on highway facilities and enabling safe use. The present study aims to develop quantified evaluation indicators that are necessary for planning and selecting appropriate climate change adaptation projects. By analysing previous studies, the most important factors to be considered in the evaluation process of climate change adaptation projects were defined, and 20 preliminary evaluation indicators were divided into three layers. A feasibility study for each class was performed on the preliminary evaluation indicators by an expert panel; 16 evaluation indicators were selected through a feasibility study, and the weight of each indicator was calculated using the analytical hierarchy process (AHP) method. The priority of the evaluation indicators was service improvement through adaptation projects (weight 8.76), cost reduction and job creation (weight 8.46), and climate change impact reduction and vulnerability reduction (weight 8.31). These quantified evaluation indicators can help organizations that manage highways respond to climate change and establish adaptation projects.

Upper thermal tolerance and population implications for the Magdalena River stingray Potamotrygon magdalenae.

Knowledge of thermal tolerance limits provides important clues to the capacity of a species to withstand acute and chronic thermal changes. Climate models predict the increase and intensification of events such as heat waves, therefore understanding the upper thermal limits that a species can tolerate has become of utmost importance. We measured the upper thermal tolerance of the endemic Magdalena river stingray Potamotrygon magdalenae acclimated to experimental conditions, and then used critical thermal methodology to find the temperature at which an organism reaches a critical endpoint where locomotory activity becomes disorganized and the animal loses its ability to escape from conditions that will promptly lead to its death. We also describe the behavioral response of individuals to acute thermal stress and infer the possible consequences of temperature increases in the habitats of P. magdalenae populations. There were no significant differences between sexes in temperature tolerance or behavior. The critical thermal maximum (39°C) was 5.9°C above the maximum recorded temperature for the study area. Although P. magdalenae was tolerant to high temperature and currently is not living at its upper thermal limit, its survival in Guarinocito Pond will be threatened if temperatures continue to increase, considering the warming scenarios predicted for tropical regions due to climate change, even including short-term climate phenomena such as El Niño.

Refugees, Climate Litigation in the Global South and Climate Change: Facing the Gap in the Protection of Climate Refugees in International Law

Climate change, as the main catalyst for catastrophes in this century, is closely linked to large groups of human beings in forced displacement. This group, called climate migrants - people who, against their will, have to leave their places of origin due to climate phenomena. However, this group of human beings, which tends to expand expressively in the coming decades, reaching somewhere between 200 million to 1.2 billion people by 2050, still does not enjoy specific protection, for what they could be considered: refugees. Despite this, the recognition of this category of migrants as refugees is of immediate importance, due to the need for protection, which has not yet been reflected in international law. Thus, at the moment, what advances have been achieved regarding the protection of climate “refugees” and regarding the evolution of the use of the expression? The present work is developed through bibliographic and documentary research as a research technique, and the analytical-deductive method for analyzing information. In this context, climate strategic litigation, a mechanism through which climate impacts on human rights can be claimed in international courts, could be a possible short-term solution to the legislative gap for refugee protection.

Responses of annual streamflow variability to annual precipitation, extreme climate events and large-scale climate phenomena in the Qinghai-Tibet Plateau

Solar activity and large-scale climate phenomena have significant effects on extreme climate events and streamflow variability. As the roof of the world and the water tower of Asia, the Qinghai-Tibet Plateau (QTP) is highly sensitive to climate change. Therefore, it is of great significance to study the relationship between extreme hydrometeorological events of the QTP and climate change for global hydroclimate research. In this study, we analyzed the spatiotemporal variation and significant oscillation period of several hydrometeorological variables such as extreme precipitation indices (EPIs), extreme temperature indices (ETIs) and annual streamflow variability based on the observation data of hydrometeorological stations in the QTP during 1962–2019 using Sen’s slope estimator, Mann-Kendall test and continuous wavelet analysis (CWT). And the teleconnection patterns and the lead-lag relationship between annual precipitation, extreme climate events, multiple nonstationary climate mode and annual streamflow were evaluated using wavelet coherence (WTC). The results show that the climate of the QTP has been wetter and warmer in the past 58 years. The annual streamflow of several natural rivers in the QTP mainly show an increasing trend over the last 60 years. The annual streamflow of natural river (except Yellow River) increases significantly in three-rivers headwater region, and the rivers in the northeast and northwest also show a significant increase trend, but there is no significant change in the natural river streamflow in the south of QTP. In addition, the annual streamflow of natural rivers had significant periodicities in the bands of 2–4 years, 4–7 years and 7–11 years. The significant coherence of WTC spectra between annual precipitation and streamflow indicate that precipitation is the main reason for annual streamflow variation in the QTP. The variation of extreme climate events significantly regulates the regional annual streamflow. All EPIs except consecutive dry days show an in-phase correlation with annual streamflow of most headwater. Annual streamflow of Naijin River is positively and negatively correlated with extreme warm and extreme cold, respectively, and has a clearer lead-lag relationship than that with EPIs. Annual streamflow of headwater has higher correlations with EI Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) than with sunspot number (SSN). Solar activity may first affect ENSO and PDO, and then this effect is transferred sequentially to the hydrological cycle of the QTP by SSN-modulated PDO and PDO-SSN co-modulated ENSO. It is of great significance to investigate the response of streamflow variation to annual precipitation, extreme climate events and large-scale climate phenomena for water resources management, flood control, ecosystem restoration, and the well-being of surrounding residents and sustainable development in the QTP.

The Effect of Geoclimatic Factors on the Distribution of Paracoccidioidomycosis in Mato Grosso do Sul, Brazil.

The incidence of paracoccidioidomycosis (PCM) varies in Latin America, and it is influenced by environmental factors. This study evaluated the distribution of PCM acute/subacute form (AF) cases and their correlation with geoclimatic factors in the Mato Grosso do Sul (MS) state. The study included 81 patients diagnosed with the PCM/AF at the University Hospital of the Federal University of Mato Grosso do Sul between January 1980 and February 2022. Geographic coordinates, health microregion of patient's residence, compensated average temperature, relative air humidity (RH), El Niño Southern Oscillation (ENSO), and average global temperature were analyzed. The highest incidence was observed in the Aquidauana (7/100,000 inhabitants), while Campo Grande, the state's capital, had the highest number (n = 34; 42.4%) and density (4.4 cases/km2) of cases. The number of cases increased during extended periods of the El Niño phenomenon. A positive correlation was found between higher RH and PCM/AF cases. Most PCM/AF cases were found in areas with loamy soils and RH ranging from 60.8 to 73.6%. In MS, the health microregions of PCM/AF patients are characterized by deforestation for agricultural and pasture use, coupled with loamy soils and specific climatic phenomena leading to higher soil humidity.

Enhancing ENSO predictions with self-attention ConvLSTM and temporal embeddings

El Niño-Southern Oscillation (ENSO), a cyclic climate phenomenon spanning interannual and decadal timescales, exerts substantial impacts on the global weather patterns and ecosystems. Recently, deep learning has brought considerable advances in the accurate prediction of ENSO occurrence. However, the current models are insufficient to characterize the evolutionary behavior of the ENSO, particularly lacking comprehensive modeling of local-range and longrange spatiotemporal interdependencies, and the incorporation of calendar monthly and seasonal properties. To make up this gap, we propose a Two-Stage SpatioTemporal (TSST) autoregressive model that couples the meteorological factor prediction with ENSO indicator prediction. The first stage predicts the meteorological time series by leveraging self-attention ConvLSTM network which captures both the local and the global spatial-temporal dependencies. The temporal embeddings of calendar months and seasonal information are further incorporated to preserves repeatedly-occurring-yet-hidden patterns in meteorological series. The second stage uses multiple layers to extract higher level of features from predicted meteorological factors progressively to generate ENSO indicators. The results demonstrate that our model outperforms the state-of-the-art ENSO prediction models, effectively predicting ENSO up to 24 months and mitigating the spring predictability barrier.

A new tool for studying seasonality and spatio-temporal structure of ENSO cycles in data and ESM simulations

Abstract In this work, we present a new diagnostic tool for El Niño Southern Oscillation (ENSO) simulations in Earth System Models (ESMs) based on the analysis of upper ocean heat content data. It allows us to identify the seasonally dependent structure of temperature anomalies in the equatorial Pacific Ocean in the form of a dominant spatio-temporal pattern. We demonstrate the results of applying a tool to analysis of real data as well as climate simulations in two versions of the Institute of Numerical Mathematics ESM. We find that the latest version of the model, with improved parameterizations of clouds, large-scale condensation, and aerosols, provides significantly better reproduction of ENSO-related structure of anomalies, as well as the phase locking of ENSO to the annual cycle. We recommend to use the tool for diagnostic analysis of ESMs regarding simulation of climate phenomena with strong seasonality.

Relationship between chlorophyll-a, rainfall, and climate phenomena in tropical archipelagic estuarine waters

Similar to many estuaries worldwide with sources receiving nitrogen and phosphorus, i.e., nutrients, from point and diffuse sources, the waters in Jakarta Bay, Musi Estuary, and Rokan Estuary in Indonesia are facing negative impacts on water quality and ecosystems, i.e., eutrophication, because of rapid urbanization and human activities. The transport of nutrients through rivers and tributaries depends on rainfall and climate phenomena, ultimately dictating chlorophyll-a (Chl-a) concentrations and trophic levels in estuaries. The relationship between trophic level, Chl-a concentration, rainfall, and climate phenomena was explored in this study by examining monthly Chl-a concentrations from 2003 to 2021 in the three estuaries. Remote sensing Chl-a concentrations data from the NASA Aqua MODIS mission was subjected to Geographic Information System (GIS) and statistical analyses. The dynamic fluctuations of Chl-a concentrations in all estuaries showed eutrophic zones appearing at specific times, influenced by local rainfalls and their patterns. The first principal components of the Empirical Orthogonal Function (EOF) analysis of Chl-a concentration anomalies showed significant correlations with rainfall anomalies and the Indian Ocean Dipole (IOD) index. These relationships exhibited distinct patterns influenced by unique climate factors in each estuary. The study highlights the crucial role of wide-area continuous monitoring and early warning systems, facilitated by satellite remote sensing, in preserving the health of coastal ecosystems. The findings also offer valuable insights for designing future monitoring programs and targeted conservation efforts.

Retaining Short‐Term Variability Reduces Mean State Biases in Wind Stress Overriding Simulations

AbstractPositive feedbacks in climate processes can make it difficult to identify the primary drivers of climate phenomena. Some recent global climate model (GCM) studies address this issue by controlling the wind stress felt by the surface ocean such that the atmosphere and ocean become mechanically decoupled. Most mechanical decoupling studies have chosen to override wind stress with an annual climatology. In this study we introduce an alternative method of interannually varying overriding which maintains higher frequency momentum forcing of the surface ocean. Using a GCM (NCAR CESM1), we then assess the size of the biases associated with these two methods of overriding by comparing with a freely evolving control integration. We find that overriding with a climatology creates sea surface temperature (SST) biases throughout the global oceans on the order of ±1°C. This is substantially larger than the biases introduced by interannually varying overriding, especially in the tropical Pacific. We attribute the climatological overriding SST biases to a lack of synoptic and subseasonal variability, which causes the mixed layer to be too shallow throughout the global surface ocean. This shoaling of the mixed layer reduces the effective heat capacity of the surface ocean such that SST biases excite atmospheric feedbacks. These results have implications for the reinterpretation of past climatological wind stress overriding studies: past climate signals attributed to momentum coupling may in fact be spurious responses to SST biases.