While climate change has become one of the most pressing issues around the world, adapting to it from a long-term perspective is extraordinarily challenging due to the significant spatial variations of climatic changes (e.g., different magnitudes of temperature increases from low- to high-latitude regions, precipitation increases in wet regions versus decreases in dry areas) as well as the wide variety of consequences caused by these changes (e.g., unexpected long-lasting droughts versus more frequent floods). In order to support informed decision making and resilient engineering planning under future climate change, it is extremely important to develop reliable and high-resolution climate scenarios to facilitate the exploration of all possible changes to regional climatology and to quantify the potential climate risks to human society and natural systems.
Although global climate models (GCMs) have been widely used to develop future climate scenarios, their outputs are usually too coarse to be suitable for driving impact models which require finer-resolution projections at both spatial and temporal scales. Besides, there are a wide variety of uncertainties in future climate projections which are caused by different choices of greenhouse gas emissions scenarios, GCM structure, parameterization schemes, etc. These challenges are among the most urgent issues to be addressed for climate change impact assessment and adaptation studies. High-resolution regional climate models, statistical downscaling, and advanced data analytical techniques are critically important to address these challenges, yet they are not well explored due to the research gaps among climate physicists, climate modellers, climate impacts modellers, and climate data users.
This Research Topic aims to capture recent advances in regional climate modelling and data analysis in support of developing high-resolution climate scenarios and assessing regional climate change impacts. Original Research and Review articles in regional climate modelling and statistical downscaling, climate data analysis and application, climate change impact assessment and adaptation in different fields (e.g., water, agriculture, fisheries, energy, indigenous communities, ecology, health, cities, etc.) are particularly welcome. Submissions of Perspectives, Opinions, Commentary, and Data Reports are also welcome.
Potential topics include but are not limited to the following:
• Regional climate modelling and statistical downscaling;
• Climate data analysis and visualization;
• Climate uncertainty quantification and risk assessment;
• Hydroclimate modelling and flooding risk assessment;
• Climate change impact assessment; and
• Application of new technologies for climate adaptation.
While climate change has become one of the most pressing issues around the world, adapting to it from a long-term perspective is extraordinarily challenging due to the significant spatial variations of climatic changes (e.g., different magnitudes of temperature increases from low- to high-latitude regions, precipitation increases in wet regions versus decreases in dry areas) as well as the wide variety of consequences caused by these changes (e.g., unexpected long-lasting droughts versus more frequent floods). In order to support informed decision making and resilient engineering planning under future climate change, it is extremely important to develop reliable and high-resolution climate scenarios to facilitate the exploration of all possible changes to regional climatology and to quantify the potential climate risks to human society and natural systems.
Although global climate models (GCMs) have been widely used to develop future climate scenarios, their outputs are usually too coarse to be suitable for driving impact models which require finer-resolution projections at both spatial and temporal scales. Besides, there are a wide variety of uncertainties in future climate projections which are caused by different choices of greenhouse gas emissions scenarios, GCM structure, parameterization schemes, etc. These challenges are among the most urgent issues to be addressed for climate change impact assessment and adaptation studies. High-resolution regional climate models, statistical downscaling, and advanced data analytical techniques are critically important to address these challenges, yet they are not well explored due to the research gaps among climate physicists, climate modellers, climate impacts modellers, and climate data users.
This Research Topic aims to capture recent advances in regional climate modelling and data analysis in support of developing high-resolution climate scenarios and assessing regional climate change impacts. Original Research and Review articles in regional climate modelling and statistical downscaling, climate data analysis and application, climate change impact assessment and adaptation in different fields (e.g., water, agriculture, fisheries, energy, indigenous communities, ecology, health, cities, etc.) are particularly welcome. Submissions of Perspectives, Opinions, Commentary, and Data Reports are also welcome.
Potential topics include but are not limited to the following:
• Regional climate modelling and statistical downscaling;
• Climate data analysis and visualization;
• Climate uncertainty quantification and risk assessment;
• Hydroclimate modelling and flooding risk assessment;
• Climate change impact assessment; and
• Application of new technologies for climate adaptation.