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Article

Stefano Tibaldi and Franco Molteni

The atmospheric circulation in the mid-latitudes of both hemispheres is usually dominated by westerly winds and by planetary-scale and shorter-scale synoptic waves, moving mostly from west to east. A remarkable and frequent exception to this “usual” behavior is atmospheric blocking. Blocking occurs when the usual zonal flow is hindered by the establishment of a large-amplitude, quasi-stationary, high-pressure meridional circulation structure which “blocks” the flow of the westerlies and the progression of the atmospheric waves and disturbances embedded in them. Such blocking structures can have lifetimes varying from a few days to several weeks in the most extreme cases. Their presence can strongly affect the weather of large portions of the mid-latitudes, leading to the establishment of anomalous meteorological conditions. These can take the form of strong precipitation episodes or persistent anticyclonic regimes, leading in turn to floods, extreme cold spells, heat waves, or short-lived droughts. Even air quality can be strongly influenced by the establishment of atmospheric blocking, with episodes of high concentrations of low-level ozone in summer and of particulate matter and other air pollutants in winter, particularly in highly populated urban areas. Atmospheric blocking has the tendency to occur more often in winter and in certain longitudinal quadrants, notably the Euro-Atlantic and the Pacific sectors of the Northern Hemisphere. In the Southern Hemisphere, blocking episodes are generally less frequent, and the longitudinal localization is less pronounced than in the Northern Hemisphere. Blocking has aroused the interest of atmospheric scientists since the middle of the last century, with the pioneering observational works of Berggren, Bolin, Rossby, and Rex, and has become the subject of innumerable observational and theoretical studies. The purpose of such studies was originally to find a commonly accepted structural and phenomenological definition of atmospheric blocking. The investigations went on to study blocking climatology in terms of the geographical distribution of its frequency of occurrence and the associated seasonal and inter-annual variability. Well into the second half of the 20th century, a large number of theoretical dynamic works on blocking formation and maintenance started appearing in the literature. Such theoretical studies explored a wide range of possible dynamic mechanisms, including large-amplitude planetary-scale wave dynamics, including Rossby wave breaking, multiple equilibria circulation regimes, large-scale forcing of anticyclones by synoptic-scale eddies, finite-amplitude non-linear instability theory, and influence of sea surface temperature anomalies, to name but a few. However, to date no unique theoretical model of atmospheric blocking has been formulated that can account for all of its observational characteristics. When numerical, global short- and medium-range weather predictions started being produced operationally, and with the establishment, in the late 1970s and early 1980s, of the European Centre for Medium-Range Weather Forecasts, it quickly became of relevance to assess the capability of numerical models to predict blocking with the correct space-time characteristics (e.g., location, time of onset, life span, and decay). Early studies showed that models had difficulties in correctly representing blocking as well as in connection with their large systematic (mean) errors. Despite enormous improvements in the ability of numerical models to represent atmospheric dynamics, blocking remains a challenge for global weather prediction and climate simulation models. Such modeling deficiencies have negative consequences not only for our ability to represent the observed climate but also for the possibility of producing high-quality seasonal-to-decadal predictions. For such predictions, representing the correct space-time statistics of blocking occurrence is, especially for certain geographical areas, extremely important.

Article

Shuiqing Yin and Deliang Chen

Weather generators (WGs) are stochastic models that can generate synthetic climate time series of unlimited length and having statistical properties similar to those of observed time series for a location or an area. WGs can infill missing data, extend the length of climate time series, and generate meteorological conditions for unobserved locations. Since the 1990s WGs have become an important spatial-temporal statistical downscaling methodology and have been playing an increasingly important role in climate-change impact assessment. Although the majority of the existing WGs have focused on simulation of precipitation for a single site, more and more WGs considering correlations among multiple sites, and multiple variables, including precipitation and nonprecipitation variables such as temperature, solar radiation, wind, humidity, and cloud cover have been developed for daily and sub-daily scales. Various parametric, semi-parametric and nonparametric WGs have shown the ability to represent the mean, variance, and autocorrelation characteristics of climate variables at different scales. Two main methodologies including change factor and conditional WGs on large-scale dynamical and thermal dynamical weather states have been developed for applications under a changing climate. However, rationality and validity of assumptions underlining both methodologies need to be carefully checked before they can be used to project future climate change at local scale. Further, simulation of extreme values by the existing WGs needs to be further improved. WGs assimilating multisource observations from ground observations, reanalysis, satellite remote sensing, and weather radar for the continuous simulation of two-dimensional climate fields based on the mixed physics-based and stochastic approaches deserve further efforts. An inter-comparison project on a large ensemble of WG methods may be helpful for the improvement of WGs. Due to the applied nature of WGs, their future development also requires inputs from decision-makers and other relevant stakeholders.

Article

Since the dawn of the digital computing age in the mid-20th century, computers have been used as virtual laboratories for the study of atmospheric phenomena. The first simulations of thunderstorms captured only their gross features, yet required the most advanced computing hardware of the time. The following decades saw exponential growth in computational power that was, and continues to be, exploited by scientists seeking to answer fundamental questions about the internal workings of thunderstorms, the most devastating of which cause substantial loss of life and property throughout the world every year. By the mid-1970s, the most powerful computers available to scientists contained, for the first time, enough memory and computing power to represent the atmosphere containing a thunderstorm in three dimensions. Prior to this time, thunderstorms were represented primarily in two dimensions, which implicitly assumed an infinitely long cloud in the missing dimension. These earliest state-of-the-art, fully three-dimensional simulations revealed fundamental properties of thunderstorms, such as the structure of updrafts and downdrafts and the evolution of precipitation, while still only roughly approximating the flow of an actual storm due computing limitations. In the decades that followed these pioneering three-dimensional thunderstorm simulations, new modeling approaches were developed that included more accurate ways of representing winds, temperature, pressure, friction, and the complex microphysical processes involving solid, liquid, and gaseous forms of water within the storm. Further, these models also were able to be run at a resolution higher than that of previous studies due to the steady growth of available computational resources described by Moore’s law, which observed that computing power doubled roughly every two years. The resolution of thunderstorm models was able to be increased to the point where features on the order of a couple hundred meters could be resolved, allowing small but intense features such as downbursts and tornadoes to be simulated within the parent thunderstorm. As model resolution increased further, so did the amount of data produced by the models, which presented a significant challenge to scientists trying to compare their simulated thunderstorms to observed thunderstorms. Visualization and analysis software was developed and refined in tandem with improved modeling and computing hardware, allowing the simulated data to be brought to life and allowing direct comparison to observed storms. In 2019, the highest resolution simulations of violent thunderstorms are able to capture processes such as tornado formation and evolution which are found to include the aggregation of many small, weak vortices with diameters of dozens of meters, features which simply cannot not be simulated at lower resolution.

Article

The factors that determine individual perceptions of climate change have been a focus of social science research for many years. An array of studies have found that individual-level characteristics, such as partisan affiliation, ideological beliefs, educational attainment, and race, affect one’s views on the existence of global warming, as well as the levels of concern regarding this matter. But in addition to the individual-level attributes that have been shown to affect perceptions of climate change, a growing body of literature has found that individual experiences with weather can shape a variety of views and beliefs that individuals maintain regarding climate change. These studies indicate that direct experiences with extreme weather events and abnormal seasonal temperature and precipitation levels can affect the likelihood that an individual will perceive global warming to be occurring, and in some cases their policy preferences for addressing the problem. The emerging literature on this relationship indicates that individuals are more likely to express skepticism regarding the existence of global warming when experiencing below average temperatures or above average snowfall in the period preceding an interview on their views. Conversely, higher temperatures and various extreme weather events can elevate acceptance of global warming’s existence. A number of studies also find that individuals are more likely to report weather conditions such as drought and extreme heat affected their acceptance of global warming when such conditions were occurring in their region. For example, the severe drought that has encompassed much of the western United States between 2005 and 2016 has increasingly been cited by residents of the region as the primary reason for their belief that climate change is occurring. What remains unclear at this point is whether the weather conditions are actually changing opinions regarding climate change or if the preexisting opinions are causing individuals to see the weather events in a manner consistent with those opinions. Notably, the relationship between weather experiences and beliefs regarding climate change appear to be multidirectional in nature. Numerous studies have found that not only do weather experiences shape the views of individuals regarding global warming, but also individuals’ views on the existence of global warming can affect their perceptions of the weather that they have experienced. In particular, recent research has shown that individuals who are skeptical about the existence of global warming are less likely to report the weather recorded in their area accurately than individuals who believe global warming is happening.

Article

Jürgen Scheffran, Peter Michael Link, and Janpeter Schilling

Climate change was conceived as a “risk multiplier” that could exacerbate security risks and conflicts in fragile regions and hotspots where poverty, violence, injustice, and social insecurity are prevalent. The linkages have been most extensively studied for the African continent, which is affected by both climate change and violent conflict. Together with other drivers, climate change can undermine human security and livelihoods of vulnerable communities in Africa through different pathways. These include variability in temperature and precipitation; weather extremes and natural disasters, such as floods and droughts; resource problems through water scarcity, land degradation, and food insecurity; forced migration and farmer–herder conflict; and infrastructure for transport, water, and energy supply. Through these channels, climate change may contribute to humanitarian crises and conflict, subject to local conditions for the different regions of Africa. While a number of statistical studies find no significant link between reduced precipitation and violent conflict in Africa, several studies do detect such a link, mostly in interaction with other issues. The effects of climate change on resource conflicts are often indirect, complex, and linked to political, economic, and social conflict factors, including social inequalities, low economic development, and ineffective institutions. Regions dependent on rainfed agriculture are more sensitive to civil conflict following droughts. Rising food prices can contribute to food insecurity and violence. Water scarcity and competition in river basins are partly associated with low-level conflicts, depending on socioeconomic variables and management practices. Another conflict factor in sub-Saharan Africa are shifting migration routes of herders who need grazing land to avoid livestock losses, while farmers depend on land for growing their harvest. Empirical findings reach no consensus on how climate vulnerability and violence interact with environmental migration, which also could be seen as an adaptation measure strengthening community resilience. Countries with a low human development index (HDI) are particularly vulnerable to the double exposure to natural disasters and armed conflict. Road and water infrastructures influence the social and political consequences of climate stress. The high vulnerabilities and low adaptive capacities of many African countries may increase the probability of violent conflicts related to climate change impacts.

Article

Throughout history human societies have been shaped and sculpted by the weather conditions that they faced. More than just the physical parameters imposed by the weather itself, how individuals, communities, and whole societies have imagined and understood the weather has influenced many facets of human activity, from agriculture to literary culture. Whether through direct lived experiences, oral traditions and stories, or empirical scientific data these different ways of understanding meteorological conditions have served a multitude of functions in society, from the pragmatic to the moral. While developments made in the scientific understanding of the atmosphere over the last 300 years have been demonstrably beneficial to most communities, their rapid onset and spread across different societies often came at the expense of older ways of knowing. Therefore, the late 20th century turn to emphasizing the importance of and interrogating and incorporating of traditional ecological knowledge within meteorological frameworks and discourses was essential. This scholarly research, underway across a number of disciplines across the humanities and beyond, not only aides the top-down integration and reach of mitigation and adaptation plans in response to the threat posed by anthropogenic climate change; it also enables the bottom-up flow of forgotten or overlooked knowledge, which helps to refine and improve our scientific understanding of global environmental systems.

Article

Mehmet Ali Uzelgun and Ümit Şahin

The case of Turkey provides some insight into the socio-political and communicative processes taking place at the periphery of global climate governance efforts. Turkey’s 12-year delayed entry into the United Nations Framework Convention on Climate Change regime (in 2004) and its being one of the last signatories to the Kyoto Protocol (in 2009) has hampered climate-relevant efforts in the country in many ways. This includes institutionalization at national and local levels, the development of relevant national policies, and communication activities. Climate change communication activities in Turkey can be divided into two major categories: the earlier advocacy activities, and the period of mass communication. The earlier activist or advocacy group communication efforts began around 2000, and have contributed significantly to mainstreaming climate change. Paralleling the government’s position towards the issue in many ways, the national-level media activities have remained nominal until 2007, when escalating local weather extremes were widely associated with climate change. Research in climate change communication in Turkey commenced only recently. Although the studies are limited both in scope and quantity, existing evidence suggests that 2007 was crucial in setting the terms of the debate in the country. Mobilizations at both international and national levels in 2009 made that year another landmark for climate change communication and policy in Turkey. International organizations and governance agencies have also taken active roles in both communication and research activities, and in the translation of governance tools developed at the international level to the national level. A review of the above-mentioned efforts suggests that a bottom-up direction of climate change communication efforts, and a minority-influence framework—in which minor advocacy and expert groups are supported by global policy norms and scientific knowledge in taking the issue to the national agenda—may be useful in understanding the dynamics taking place in industrializing countries such as Turkey.

Article

C.J.C. Reason

Southern Africa extends from the equator to about 34°S and is essentially a narrow, peninsular land mass bordered to its south, west, and east by oceans. Its termination in the mid-ocean subtropics has important consequences for regional climate, since it allows the strongest western boundary current in the world ocean (warm Agulhas Current) to be in close proximity to an intense eastern boundary upwelling current (cold Benguela Current). Unlike other western boundary currents, the Agulhas retroflects south of the land mass and flows back into the South Indian Ocean, thereby leading to a large area of anomalously warm water south of South Africa which may influence storm development over the southern part of the land mass. Two other unique regional ocean features imprint on the climate of southern Africa—the Angola-Benguela Frontal Zone (ABFZ) and the Seychelles-Chagos thermocline ridge (SCTR). The former is important for the development of Benguela Niños and flood events over southwestern Africa, while the SCTR influences Madden-Julian Oscillation and tropical cyclone activity in the western Indian Ocean. In addition to South Atlantic and South Indian Ocean influences, there are climatic implications of the neighboring Southern Ocean. Along with Benguela Niños, the southern African climate is strongly impacted by ENSO and to lesser extent by the Southern Annular Mode (SAM) and sea-surface temperature (SST) dipole events in the Indian and South Atlantic Oceans. The regional land–sea distribution leads to a highly variable climate on a range of scales that is still not well understood due to its complexity and its sensitivity to a number of different drivers. Strong and variable gradients in surface characteristics exist not only in the neighboring oceans but also in several aspects of the land mass, and these all influence the regional climate and its interactions with climate modes of variability. Much of the interior of southern Africa consists of a plateau 1 to 1.5 km high and a narrow coastal belt that is particularly mountainous in South Africa, leading to sharp topographic gradients. The topography is able to influence the track and development of many weather systems, leading to marked gradients in rainfall and vegetation across southern Africa. The presence of the large island of Madagascar, itself a region of strong topographic and rainfall gradients, has consequences for the climate of the mainland by reducing the impact of the moist trade winds on the Mozambique coast and the likelihood of tropical cyclone landfall there. It is also likely that at least some of the relativity aridity of the Limpopo region in northern South Africa/southern Zimbabwe results from the location of Madagascar in the southwestern Indian Ocean. While leading to challenges in understanding its climate variability and change, the complex geography of southern Africa offers a very useful test bed for improving the global models used in many institutions for climate prediction. Thus, research into the relative shortcomings of the models in the southern African region may lead not only to better understanding of southern African climate but also to enhanced capability to predict climate globally.

Article

The history of the Russian Magneto-Meteorological Observatory (RMMO) in Beijing has not been extensively researched. Sources for this information are Russian (the Russian State Historical Archive, Saint Petersburg Branch of the Archive of the Academy of Sciences, Russian National Library) and Chinese (the First Historical Archive of Beijing, the Library of the Shanghai Zikavey Observatory) archives. These archival materials can be scientifically and methodologically analyzed. At the beginning of the 18th century, the Russian Orthodox Mission (ROM) was founded in the territory of Beijing. Existing until 1955, the ROM performed an important role in the development of Russian–Chinese relations. Russian scientists could only work in Beijing through the ROM due to China’s policy of fierce self-isolation. The ROM became the center of Chinese academic studies and the first training school for Russian sinologists. From its very beginning, it was considered not only a church or diplomatic mission but a research center in close cooperation with the Russian Academy of Sciences. In this context, the RMMO made important weather investigations in China and the Far East in the 19th century. The RMMO, as well as its branch stations in China and Mongolia, part of a scientific network, represented an important link between Europe and Asia and was probably the largest geographical scientific network in the world at that time.

Article

Annick Terpstra and Shun-ichi Watanabe

Polar lows are intense maritime mesoscale cyclones developing in both hemispheres poleward of the main polar front. These rapidly developing severe storms are accompanied by strong winds, heavy precipitation (hail and snow), and rough sea states. Polar lows can have significant socio-economic impact by disrupting human activities in the maritime polar regions, such as tourism, fisheries, transportation, research activities, and exploration of natural resources. Upon landfall, they quickly decay, but their blustery winds and substantial snowfall affect the local communities in coastal regions, resulting in airport-closure, transportation breakdown and increased avalanche risk. Polar lows are primarily a winter phenomenon and tend to develop during excursions of polar air masses, originating from ice-covered areas, over the adjacent open ocean. These so-called cold-air outbreaks are driven by the synoptic scale atmospheric configuration, and polar lows usually develop along air-mass boundaries associated with these cold-air outbreaks. Local orographic features and the sea-ice configuration also play prominent roles in pre-conditioning the environment for polar low development. Proposed dynamical pathways for polar low development include moist baroclinic instability, symmetric convective instability, and frontal instability, but verification of these mechanisms is limited due to sparse observations and insufficient resolution of reanalysis data. Maritime areas with a frequent polar low presence are climatologically important regions for the global ocean circulation, hence local changes in energy exchange between the atmosphere and ocean in these regions potentially impacts the global climate system. Recent research indicates that the enhanced heat and momentum exchange by mesoscale cyclones likely has a pronounced impact on ocean heat transport by triggering deep water formation in the ocean and by modifying horizontal mixing in the atmosphere. Since the beginning of the satellite-era a steady decline of sea-ice cover in the Northern Hemisphere has expanded the ice-free polar regions, and thus the areas for polar low development, yet the number of polar lows is projected to decline under future climate scenarios.

Article

Global climate models are our main tool to generate quantitative climate projections, but these models do not resolve the effects of complex topography, regional scale atmospheric processes and small-scale extreme events. To understand potential regional climatic changes, and to provide information for regional-scale impact modeling and adaptation planning, downscaling approaches have been developed. Regional climate change modeling, even though it is still a matter of basic research and questioned by many researchers, is urged to provide operational results. One major downscaling class is statistical downscaling, which exploits empirical relationships between larger-scale and local weather. The main statistical downscaling approaches are perfect prog (often referred to as empirical statistical downscaling), model output statistics (which is typically some sort of bias correction), and weather generators. Statistical downscaling complements or adds to dynamical downscaling and is useful to generate user-tailored local-scale information, or to efficiently generate regional scale information about mean climatic changes from large global climate model ensembles. Further research is needed to assess to what extent the assumptions underlying statistical downscaling are met in typical applications, and to develop new methods for generating spatially coherent projections, and for including process-understanding in bias correction. The increasing resolution of global climate models will improve the representation of downscaling predictors and will, therefore, make downscaling an even more feasible approach that will still be required to tailor information for users.

Article

Rasmus Benestad

What are the local consequences of a global climate change? This question is important for proper handling of risks associated with weather and climate. It also tacitly assumes that there is a systematic link between conditions taking place on a global scale and local effects. It is the utilization of the dependency of local climate on the global picture that is the backbone of downscaling; however, it is perhaps easiest to explain the concept of downscaling in climate research if we start asking why it is necessary. Global climate models are our best tools for computing future temperature, wind, and precipitation (or other climatological variables), but their limitations do not let them calculate local details for these quantities. It is simply not adequate to interpolate from model results. However, the models are able to predict large-scale features, such as circulation patterns, El Niño Southern Oscillation (ENSO), and the global mean temperature. The local temperature and precipitation are nevertheless related to conditions taking place over a larger surrounding region as well as local geographical features (also true, in general, for variables connected to weather/climate). This, of course, also applies to other weather elements. Downscaling makes use of systematic dependencies between local conditions and large-scale ambient phenomena in addition to including information about the effect of the local geography on the local climate. The application of downscaling can involve several different approaches. This article will discuss various downscaling strategies and methods and will elaborate on their rationale, assumptions, strengths, and weaknesses. One important issue is the presence of spontaneous natural year-to-year variations that are not necessarily directly related to the global state, but are internally generated and superimposed on the long-term climate change. These variations typically involve phenomena such as ENSO, the North Atlantic Oscillation (NAO), and the Southeast Asian monsoon, which are nonlinear and non-deterministic. We cannot predict the exact evolution of non-deterministic natural variations beyond a short time horizon. It is possible nevertheless to estimate probabilities for their future state based, for instance, on projections with models run many times with slightly different set-up, and thereby to get some information about the likelihood of future outcomes. When it comes to downscaling and predicting regional and local climate, it is important to use many global climate model predictions. Another important point is to apply proper validation to make sure the models give skillful predictions. For some downscaling approaches such as regional climate models, there usually is a need for bias adjustment due to model imperfections. This means the downscaling doesn’t get the right answer for the right reason. Some of the explanations for the presence of biases in the results may be different parameterization schemes in the driving global and the nested regional models. A final underlying question is: What can we learn from downscaling? The context for the analysis is important, as downscaling is often used to find answers to some (implicit) question and can be a means of extracting most of the relevant information concerning the local climate. It is also important to include discussions about uncertainty, model skill or shortcomings, model validation, and skill scores.

Article

In the years following the Second World War, the U.S. government played a prominent role in the support of basic scientific research. The National Science Foundation (NSF) was created in 1950 with the primary mission of supporting fundamental science and engineering, excluding medical sciences. Over the years, the NSF has operated from the “bottom up,” keeping close track of research around the United States and the world while maintaining constant contact with the research community to identify ever-moving horizons of inquiry. In the 1950s the field of meteorology was something of a poor cousin to the other branches of science; forecasting was considered more of trade than a discipline founded on sound theoretical foundations. Realizing the importance of the field to both the economy and national security, the NSF leadership made a concerted effort to enhance understanding of the global atmospheric circulation. The National Center for Atmospheric Research (NCAR) was established to complement ongoing research efforts in academic institutions; it has played a pivotal role in providing observational and modeling tools to the emerging cadre of researchers in the disciplines of meteorology and atmospheric sciences. As understanding of the predictability of the coupled atmosphere-ocean system grew, the field of climate science emerged as a natural outgrowth of meteorology, oceanography, and atmospheric sciences. The NSF played a leading role in the implementation of major international programs such as the International Geophysical Year (IGY), the Global Weather Experiment, the World Ocean Circulation Experiment (WOCE) and Tropical Ocean Global Atmosphere (TOGA). Through these programs, understanding of the coupled climate system comprising atmosphere, ocean, land, ice-sheet, and sea ice greatly improved. Consistent with its mission, the NSF supported projects that advanced fundamental knowledge of forcing and feedbacks in the coupled atmosphere-ocean-land system. Research projects have included theoretical, observational, and modeling studies of the following: the general circulation of the stratosphere and troposphere; the processes that govern climate; the causes of climate variability and change; methods of predicting climate variations; climate predictability; development and testing of parameterization of physical processes; numerical methods for use in large-scale climate models; the assembly and analysis of instrumental and/or modeled climate data; data assimilation studies; and the development and use of climate models to diagnose and simulate climate variability and change. Climate scientists work together on an array of topics spanning time scales from the seasonal to the centennial. The NSF also supports research on the natural evolution of the earth’s climate on geological time scales with the goal of providing a baseline for present variability and future trends. The development of paleoclimate data sets has resulted in longer term data for evaluation of model simulations, analogous to the evaluation using instrumental observations. This has enabled scientists to create transformative syntheses of paleoclimate data and modeling outcomes in order to understand the response of the longer-term and higher magnitude variability of the climate system that is observed in the geological records. The NSF will continue to address emerging issues in climate and earth-system science through balanced investments in transformative ideas, enabling infrastructure and major facilities to be developed.

Article

Situated at the southern edge of the Tibetan Plateau (TP), the Hindu-Kush-Himalayas-Gangetic (HKHG) region is under the clear and present danger of climate change. Flash-flood, landslide, and debris flow caused by extreme precipitation, as well as rapidly melting glaciers, threaten the water resources and livelihood of more than 1.2 billion people living in the region. Rapid industrialization and increased populations in recent decades have resulted in severe atmospheric and environmental pollution in the region. Because of its unique topography and dense population, the HKHG is not only a major source of pollution aerosol emissions, but also a major receptor of large quantities of natural dust aerosols transported from the deserts of West Asia and the Middle East during the premonsoon and early monsoon season (April–June). The dust aerosols, combined with local emissions of light-absorbing aerosols, that is, black carbon (BC), organic carbon (OC), and mineral dust, can (a) provide additional powerful heating to the atmosphere and (b) allow more sunlight to penetrate the snow layer by darkening the snow surface. Both effects will lead to accelerated melting of snowpack and glaciers in the HKHG region, amplifying the greenhouse warming effect. In addition, these light-absorbing aerosols can interact with monsoon winds and precipitation, affecting extreme precipitation events in the HKHG, as well as weather variability and climate change over the TP and the greater Asian monsoon region.

Article

Japan is one of the world’s leading marine fishing nations in globalized industrial fisheries, yet the mainstay of the national fishing industry continues to be small-scale fisheries with their own set of cultural and environmental heritage. The cultural tradition of the Japanese fishing communities still preserves the various ways of understanding local weather, which are mainly based on landscape perception and forecasting knowledge. The prediction of weather conditions for a given location and time is part of a long-established historical tradition related to the need for an “easy” understanding of the climatic and maritime environment. It encompasses a variety of practical experiences, skillful reasoning strategies, and cultural values concerning indigenous environmental knowledge, decision-making strategies, and habitual applications of knowledge in everyday life. Japanese traditional forecasting culture interfaces with modern meteorological forecasting technologies to generate a hybrid knowledge, and offers an example of the complex dialogue between global science and local science. Specifically, interpretations and meteorological observations of local weather are modes of everyday engagement with the weather that exhibit a highly nuanced ecological sophistication and continue to offer a critical discourse on the cultural, environmental, and social context of Japanese small-scale fisheries. Indigenous weather understanding is bound up with community-based cultural heritage—religious traditions, meteorological classifications, proverbs, traditional forecasting models, and selective incorporation or rejection of scientific forecasting data—that offers a general overview of the interaction between community know-how, sensory experience, skills, and cultural practices.