Pub Date : 2023-04-18DOI: 10.1088/2752-5295/accdf9
K. Novick, M. Barnes
Widespread shifts in land cover and land management (LCLM) are being incentivized as tools to mitigate climate change, creating an urgent need for prognostic assessments of how LCLM impacts surface energy balance and temperature. Historically, observational studies have tended to focus on how LCLM impacts surface temperature (T surf), usually at annual timescales. However, understanding the potential for LCLM change to confer climate adaptation benefits, or to produce unintended adverse consequences, requires careful consideration of impacts on both T surf and the near-surface air temperature (T a,local) when they are most consequential for ecosystem and societal well-being (e.g. on hot summer days). Here, long-term data from 130 AmeriFlux towers distributed between 19–71 °N are used to systematically explore LCLM impacts on both T surf and T a,local, with an explicit focus on midday summer periods when adaptive cooling is arguably most needed. We observe profound impacts of LCLM on T surf at midday, frequently amounting to differences of 10 K or more from one site to the next. LCLM impacts on T a,local are smaller but still significant, driving variation of 5–10 K across sites. The magnitude of LCLM impacts on both T surf and T a,local is not well explained by plant functional type, climate regime, or albedo; however, we show that LCLM shifts that enhance ET or increase canopy height are likely to confer a local mid-day cooling benefit for both T surf and T a,local most of the time. At night, LCLM impacts on temperature are much smaller, such that averaging across the diurnal cycle will underestimate the potential for land cover to mediate microclimate when the consequences for plant and human well-being are most stark. Finally, during especially hot periods, land cover impacts on T a,local and T surf are less coordinated, and ecosystems that tend to cool the air during normal conditions may have a diminished capacity to do so when it is very hot. We end with a set of practical recommendations for future work evaluating the biophysical impacts and adaptation potential of LCLM shifts.
{"title":"A practical exploration of land cover impacts on surface and air temperature when they are most consequential","authors":"K. Novick, M. Barnes","doi":"10.1088/2752-5295/accdf9","DOIUrl":"https://doi.org/10.1088/2752-5295/accdf9","url":null,"abstract":"Widespread shifts in land cover and land management (LCLM) are being incentivized as tools to mitigate climate change, creating an urgent need for prognostic assessments of how LCLM impacts surface energy balance and temperature. Historically, observational studies have tended to focus on how LCLM impacts surface temperature (T surf), usually at annual timescales. However, understanding the potential for LCLM change to confer climate adaptation benefits, or to produce unintended adverse consequences, requires careful consideration of impacts on both T surf and the near-surface air temperature (T a,local) when they are most consequential for ecosystem and societal well-being (e.g. on hot summer days). Here, long-term data from 130 AmeriFlux towers distributed between 19–71 °N are used to systematically explore LCLM impacts on both T surf and T a,local, with an explicit focus on midday summer periods when adaptive cooling is arguably most needed. We observe profound impacts of LCLM on T surf at midday, frequently amounting to differences of 10 K or more from one site to the next. LCLM impacts on T a,local are smaller but still significant, driving variation of 5–10 K across sites. The magnitude of LCLM impacts on both T surf and T a,local is not well explained by plant functional type, climate regime, or albedo; however, we show that LCLM shifts that enhance ET or increase canopy height are likely to confer a local mid-day cooling benefit for both T surf and T a,local most of the time. At night, LCLM impacts on temperature are much smaller, such that averaging across the diurnal cycle will underestimate the potential for land cover to mediate microclimate when the consequences for plant and human well-being are most stark. Finally, during especially hot periods, land cover impacts on T a,local and T surf are less coordinated, and ecosystems that tend to cool the air during normal conditions may have a diminished capacity to do so when it is very hot. We end with a set of practical recommendations for future work evaluating the biophysical impacts and adaptation potential of LCLM shifts.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117264847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-14DOI: 10.1088/2752-5295/accd0e
J. Prochaska, C. Beaulieu, K. Giamalaki
We introduce a new methodology to study marine heat waves (MHWs), extreme events in the sea surface temperature (SST) of the global ocean. Motivated by previously large and impactful MHWs and by theoretical expectation that the dominant heating processes coherently affect large regions of the ocean, we introduce a methodology from computer vision to construct marine heat wave systems (MWHSs) – the collation of SST extrema in dimensions of area and time. We identify 649 475 MHWSs in the 37 year period (1983–2019) of daily SST records and find that the duration tdur (days), maximum area Amax (km2), and total ‘volume’ VMHWS (days km2) for the majority of MHWSs are well-described by power-law distributions: tdur−3,Amax−2 and VMHWS−2 . These characteristics confirm SST extrema exhibit strong spatial coherence that define the formation and evolution of MHWs. Furthermore, the most severe MHWSs deviate from these power-laws and are the dominant manifestation of MHWs: extrema in ocean heating are driven by the ∼200 systems with largest area and duration. We further demonstrate that the previously purported rise in the incidence of MHW events over the past decade is only significant in these severe systems. A change point analysis reveals a rapid increase in days under a severe MHW in most regions of the global ocean over the period of 2000–2005. Understanding the origin and impacts of MHWs in the current and future ocean, therefore, should focus on the production and evolution of the largest-scale and longest-duration heating phenomena.
{"title":"The rapid rise of severe marine heat wave systems","authors":"J. Prochaska, C. Beaulieu, K. Giamalaki","doi":"10.1088/2752-5295/accd0e","DOIUrl":"https://doi.org/10.1088/2752-5295/accd0e","url":null,"abstract":"We introduce a new methodology to study marine heat waves (MHWs), extreme events in the sea surface temperature (SST) of the global ocean. Motivated by previously large and impactful MHWs and by theoretical expectation that the dominant heating processes coherently affect large regions of the ocean, we introduce a methodology from computer vision to construct marine heat wave systems (MWHSs) – the collation of SST extrema in dimensions of area and time. We identify 649 475 MHWSs in the 37 year period (1983–2019) of daily SST records and find that the duration tdur (days), maximum area Amax (km2), and total ‘volume’ VMHWS (days km2) for the majority of MHWSs are well-described by power-law distributions: tdur−3,Amax−2 and VMHWS−2 . These characteristics confirm SST extrema exhibit strong spatial coherence that define the formation and evolution of MHWs. Furthermore, the most severe MHWSs deviate from these power-laws and are the dominant manifestation of MHWs: extrema in ocean heating are driven by the ∼200 systems with largest area and duration. We further demonstrate that the previously purported rise in the incidence of MHW events over the past decade is only significant in these severe systems. A change point analysis reveals a rapid increase in days under a severe MHW in most regions of the global ocean over the period of 2000–2005. Understanding the origin and impacts of MHWs in the current and future ocean, therefore, should focus on the production and evolution of the largest-scale and longest-duration heating phenomena.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128133745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-14DOI: 10.1088/2752-5295/accd0f
W. Guan, Lung-Chuang Wang
The formation mechanism responsible for the leading mode of the subseasonal variability of wintertime surface air temperature (SAT) over Eurasia is investigated. The leading SAT mode over Eurasia is characterized by a triple pattern with strong cold anomalies centered over northern Eurasia and weaker warm anomalies over the Arctic and East Asia, respectively, which has a deep barotropic structure and extends from the surface to the upper troposphere. It is tightly coupled to a wave-like atmospheric circulation, which stretches from the North Atlantic to East Asia and resembles the Scandinavia teleconnection pattern. Its formation mechanism is further revealed through the analysis of the temperature budget. The atmospheric circulation-induced horizontal advection is found to be the primary driver of the cold anomalies over northern Eurasia associated with the leading SAT mode in two steps. First, the advection of the climatological temperature by the mode-associated meridional wind anomalies triggers the cooling in the western part of Eurasia. Second, the advection of the above cold anomalies by background westerly winds from west Eurasia to the east further redistributes the cold anomalies. The meridional and zonal advection eventually causes the mode-associated strong cold anomalies over northern Eurasia.
{"title":"Mechanism of the wintertime subseasonal surface air temperature variability over Eurasia","authors":"W. Guan, Lung-Chuang Wang","doi":"10.1088/2752-5295/accd0f","DOIUrl":"https://doi.org/10.1088/2752-5295/accd0f","url":null,"abstract":"The formation mechanism responsible for the leading mode of the subseasonal variability of wintertime surface air temperature (SAT) over Eurasia is investigated. The leading SAT mode over Eurasia is characterized by a triple pattern with strong cold anomalies centered over northern Eurasia and weaker warm anomalies over the Arctic and East Asia, respectively, which has a deep barotropic structure and extends from the surface to the upper troposphere. It is tightly coupled to a wave-like atmospheric circulation, which stretches from the North Atlantic to East Asia and resembles the Scandinavia teleconnection pattern. Its formation mechanism is further revealed through the analysis of the temperature budget. The atmospheric circulation-induced horizontal advection is found to be the primary driver of the cold anomalies over northern Eurasia associated with the leading SAT mode in two steps. First, the advection of the climatological temperature by the mode-associated meridional wind anomalies triggers the cooling in the western part of Eurasia. Second, the advection of the above cold anomalies by background westerly winds from west Eurasia to the east further redistributes the cold anomalies. The meridional and zonal advection eventually causes the mode-associated strong cold anomalies over northern Eurasia.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"2573 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128787606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-11DOI: 10.1088/2752-5295/accbe2
Anhelina Zapolska, M. Vrac, A. Quiquet, T. Extier, Frank Arthur, H. Renssen, D. Roche
Climate model simulations are inherently biased. It is a notably difficult problem when dealing with climate impact assessments and model-data integration. This is especially true when looking at derived quantities such as biomes, where not only climate but also vegetation dynamics biases come into play. To overcome such difficulties, we evaluate the performance of an existing methodology to correct climate model outputs, applied here for the first time to long past climate conditions. The proposed methodology relies on the ‘Cumulative Distribution Function-transform’ (CDF-t) technique, which allows to account for climate change within the bias-correction procedure. The results are evaluated in two independent ways: (i) using forward modelling, so that model results are directly comparable to reconstructed vegetation distribution; (ii) using climatic reconstructions based on an inverse modelling approach. The modelling is performed using the intermediate complexity model iLOVECLIM in the standard global and interactively downscaled over the Europe version. The combined effects of dynamical downscaling and bias correction resulted in significantly stronger agreement between the simulated results and pollen-based biome reconstructions (BIOME6000) for the pre-industrial (0.18 versus 0.44) and mid-Holocene (MH) (0.31 versus 0.40). Higher correlation is also observed between statistically modelled global gridded potential natural distribution and modelled biomes (0.36 versus 0.41). Similarly, we find higher correlation between the reconstructed and the modelled temperatures for the MH (0.02 versus 0.21). No significant difference is found for the Last Glacial Maximum when using temperature reconstructions, due to the low number of data points available. Our findings show that the application of the CDF-t method on simulated climate variables enables us to simulate palaeoclimate and vegetation distribution in better agreement with independent reconstructions.
气候模式模拟具有固有的偏见。在处理气候影响评估和模式数据整合时，这是一个非常困难的问题。在观察诸如生物群落之类的衍生数量时尤其如此，在这些数量中，不仅气候偏差，植被动态偏差也会起作用。为了克服这些困难，我们评估了一种修正气候模式输出的现有方法的性能，该方法首次应用于长期过去的气候条件。所提出的方法依赖于“累积分布函数变换”(CDF-t)技术，该技术允许在偏差校正过程中考虑气候变化。结果以两种独立的方式进行评估:(i)使用正演模拟，使模型结果与重建的植被分布直接比较;(ii)利用基于逆模拟方法的气候重建。建模是使用标准全球和交互式缩小欧洲版本的中间复杂性模型iLOVECLIM进行的。在动态降尺度和偏置校正的共同作用下，模拟结果与基于花粉的生物群系重建(BIOME6000)在工业化前(0.18 vs 0.44)和全新世中期(MH) (0.31 vs 0.40)的一致性显著增强。在统计模拟的全球网格化潜在自然分布与模拟的生物群系之间也观察到较高的相关性(0.36 vs 0.41)。同样，我们发现重建的和模拟的MH温度之间有更高的相关性(0.02对0.21)。由于可用的数据点较少，末次盛冰期的温度重建没有发现显著差异。研究结果表明，CDF-t方法在模拟气候变量上的应用使我们能够更好地模拟古气候和植被分布，并与独立重建结果相吻合。
{"title":"Improving biome and climate modelling for a set of past climate conditions: evaluating bias correction using the CDF-t approach","authors":"Anhelina Zapolska, M. Vrac, A. Quiquet, T. Extier, Frank Arthur, H. Renssen, D. Roche","doi":"10.1088/2752-5295/accbe2","DOIUrl":"https://doi.org/10.1088/2752-5295/accbe2","url":null,"abstract":"Climate model simulations are inherently biased. It is a notably difficult problem when dealing with climate impact assessments and model-data integration. This is especially true when looking at derived quantities such as biomes, where not only climate but also vegetation dynamics biases come into play. To overcome such difficulties, we evaluate the performance of an existing methodology to correct climate model outputs, applied here for the first time to long past climate conditions. The proposed methodology relies on the ‘Cumulative Distribution Function-transform’ (CDF-t) technique, which allows to account for climate change within the bias-correction procedure. The results are evaluated in two independent ways: (i) using forward modelling, so that model results are directly comparable to reconstructed vegetation distribution; (ii) using climatic reconstructions based on an inverse modelling approach. The modelling is performed using the intermediate complexity model iLOVECLIM in the standard global and interactively downscaled over the Europe version. The combined effects of dynamical downscaling and bias correction resulted in significantly stronger agreement between the simulated results and pollen-based biome reconstructions (BIOME6000) for the pre-industrial (0.18 versus 0.44) and mid-Holocene (MH) (0.31 versus 0.40). Higher correlation is also observed between statistically modelled global gridded potential natural distribution and modelled biomes (0.36 versus 0.41). Similarly, we find higher correlation between the reconstructed and the modelled temperatures for the MH (0.02 versus 0.21). No significant difference is found for the Last Glacial Maximum when using temperature reconstructions, due to the low number of data points available. Our findings show that the application of the CDF-t method on simulated climate variables enables us to simulate palaeoclimate and vegetation distribution in better agreement with independent reconstructions.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123360180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-11DOI: 10.1088/2752-5295/accbe1
S. Dee, A. Bailey, J. L. Conroy, A. Atwood, S. Stevenson, J. Nusbaumer, D. Noone
The hydrologic cycle is a fundamental component of the climate system with critical societal and ecological relevance. Yet gaps persist in our understanding of water fluxes and their response to increased greenhouse gas forcing. The stable isotope ratios of oxygen and hydrogen in water provide a unique opportunity to evaluate hydrological processes and investigate their role in the variability of the climate system and its sensitivity to change. Water isotopes also form the basis of many paleoclimate proxies in a variety of archives, including ice cores, lake and marine sediments, corals, and speleothems. These records hold most of the available information about past hydrologic variability prior to instrumental observations. Water isotopes thus provide a ‘common currency’ that links paleoclimate archives to modern observations, allowing us to evaluate hydrologic processes and their effects on climate variability on a wide range of time and length scales. Building on previous literature summarizing advancements in water isotopic measurements and modeling and describe water isotopic applications for understanding hydrological processes, this topical review reflects on new insights about climate variability from isotopic studies. We highlight new work and opportunities to enhance our understanding and predictive skill and offer a set of recommendations to advance observational and model-based tools for climate research. Finally, we highlight opportunities to better constrain climate sensitivity and identify anthropogenically-driven hydrologic changes within the inherently noisy background of natural climate variability.
{"title":"Water isotopes, climate variability, and the hydrological cycle: recent advances and new frontiers","authors":"S. Dee, A. Bailey, J. L. Conroy, A. Atwood, S. Stevenson, J. Nusbaumer, D. Noone","doi":"10.1088/2752-5295/accbe1","DOIUrl":"https://doi.org/10.1088/2752-5295/accbe1","url":null,"abstract":"The hydrologic cycle is a fundamental component of the climate system with critical societal and ecological relevance. Yet gaps persist in our understanding of water fluxes and their response to increased greenhouse gas forcing. The stable isotope ratios of oxygen and hydrogen in water provide a unique opportunity to evaluate hydrological processes and investigate their role in the variability of the climate system and its sensitivity to change. Water isotopes also form the basis of many paleoclimate proxies in a variety of archives, including ice cores, lake and marine sediments, corals, and speleothems. These records hold most of the available information about past hydrologic variability prior to instrumental observations. Water isotopes thus provide a ‘common currency’ that links paleoclimate archives to modern observations, allowing us to evaluate hydrologic processes and their effects on climate variability on a wide range of time and length scales. Building on previous literature summarizing advancements in water isotopic measurements and modeling and describe water isotopic applications for understanding hydrological processes, this topical review reflects on new insights about climate variability from isotopic studies. We highlight new work and opportunities to enhance our understanding and predictive skill and offer a set of recommendations to advance observational and model-based tools for climate research. Finally, we highlight opportunities to better constrain climate sensitivity and identify anthropogenically-driven hydrologic changes within the inherently noisy background of natural climate variability.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115579076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-11DOI: 10.1088/2752-5295/accbe3
M. Karami, T. Koenigk, B. Tremblay
The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km2 per decade in the 1980s and accelerating to ∼−0.47 million km2 per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.
{"title":"Variability modes of September Arctic sea ice: drivers and their contributions to sea ice trend and extremes","authors":"M. Karami, T. Koenigk, B. Tremblay","doi":"10.1088/2752-5295/accbe3","DOIUrl":"https://doi.org/10.1088/2752-5295/accbe3","url":null,"abstract":"The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km2 per decade in the 1980s and accelerating to ∼−0.47 million km2 per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127282279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-06DOI: 10.1088/2752-5295/accb03
Asif Ishtiaque
Farmers in the US are adopting a range of strategies to deal with climate change impacts, from changing planting dates to using advanced technologies. Studies on farmers’ adaptation in US agriculture focus on a variety of topics and provide an understanding of how farmers adapt to climate change impacts, which adaptation strategies offer better outcomes, and what challenges need to be addressed for effective adaptations. Nevertheless, we lack a comprehensive view of adaptation studies focusing on US farmers’ adaptations. A review of adaptation studies in US agriculture context will help us to understand current adaptation research trends and realize future research potential. To fulfill this gap, this study systematically reviewed peer-reviewed studies on adaptation to climate change in US agriculture. A systematic search on the Web of Science and Google Scholar platforms generated 95 articles for final review. These studies were categorized under five themes based on their topical relevance: (i) reporting on-farm adaptations, (ii) exploring potential adaptations, (iii) evaluating specific adaptations, (iv) challenges of adaptations, and (v) perceptions toward adaptations. A skewed distribution of studies under these themes has been observed; a majority of the studies focused on evaluating specific adaptations (47%) followed by exploring potential adaptations (22%), while reporting on-farm adaptations (17%), challenges of adaptations (6%), and perception towards adaptations (8%) received less attention. In this article, key findings under each theme are presented and some areas for future research focus are discussed. These findings indicate the need for more attention to documenting on-farm adaptation strategies and the associated challenges while emphasizing other themes.
美国农民正在采取一系列策略来应对气候变化的影响，从改变种植日期到使用先进技术。对美国农业中农民适应的研究侧重于各种主题，并提供了对农民如何适应气候变化影响的理解，哪些适应策略可以提供更好的结果，以及为了有效适应需要解决哪些挑战。然而，我们缺乏以美国农民适应为重点的适应研究的全面观点。回顾美国农业环境下的适应研究，有助于我们了解当前的适应研究趋势和认识未来的研究潜力。为了填补这一空白，本研究系统地回顾了美国农业适应气候变化的同行评议研究。在Web of Science和b谷歌Scholar平台上进行系统搜索，得出95篇文章供最终评审。这些研究根据其主题相关性分为五个主题:(i)报告农场适应性，(ii)探索潜在适应性，(iii)评估特定适应性，(iv)适应性的挑战，以及(v)对适应性的看法。观察到这些主题下的研究分布有偏差;大多数研究侧重于评估特定的适应(47%)，其次是探索潜在的适应(22%)，而报告农场适应(17%)、适应的挑战(6%)和对适应的看法(8%)得到的关注较少。在本文中，介绍了每个主题下的主要发现，并讨论了未来研究的重点领域。这些发现表明，在强调其他主题的同时，需要更多地关注记录农场适应策略和相关挑战。
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Pub Date : 2023-04-06DOI: 10.1088/2752-5295/accb02
M. Dannenberg, M. Johnston
The El Niño–Southern Oscillation (ENSO) affects many climatic controls on vegetation activity, driving interannual variation in timing (phenology) and magnitude of terrestrial carbon uptake. However, the climatic effects of ENSO can differ for sea surface temperature (SST) anomalies primarily centered in the eastern vs. central Pacific (EP and CP, respectively). Here, we examine the extent to which EP and CP SST anomalies affect Northern Hemisphere photosynthetic seasonality and whether their effects differ. Using two decades of satellite near-infrared reflectance of vegetation (NIRv) and FLUXNET2015 gross primary production, we estimated annual 0.05° start and end of growing season timing corresponding to the onset and offset of photosynthetic activity, as well as peak NIRv magnitude as a proxy for peak growing season productivity. We find that correlations between Northern Hemisphere photosynthetic timing/magnitude and ENSO differ for EP- and CP-centered SST anomalies, though in many regions the effects and differences between them are quite small. Warmer SSTs generally led to an earlier start of the photosynthetic season, especially in North America and parts of Eurasia. However, the magnitude (and even direction) of the relationships between start of season and SST differed for CP- and EP-dominated events. Correlations of both peak NIRv magnitude and end of season timing with ENSO tended to be smaller in magnitude and more regionally idiosyncratic, though with strong evidence of different effects of CP and EP SSTs. In southern North America, CP SSTs (but not EP SSTs) were positively associated with peak NIRv, while in boreal regions of North America and Eurasia, CP SSTs were negatively associated with peak NIRv (despite small positive associations with EP SSTs). Differences between the effects of EP and CP SST anomalies suggest that short-term vegetation forecasts based on aggregate ENSO indices could be improved by separately considering the EP and CP components.
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Pub Date : 2023-04-06DOI: 10.1088/2752-5295/accb01
Pelin Kınay, Xander Wang, P. Augustine, Margaret Augustine
While evidence of Indigenous Peoples’ climate knowledge and adaptation practices is readily available in Canada, regional variations are poorly understood, and proper representation and recognition in academic and planning contexts is scarce. Much less still is known about the health and environmental impacts of climate change on these communities. This review sought to report and assess the evidence of such impacts on Indigenous Peoples in Atlantic Canada over the past two decades. Current published studies focused on Indigenous Peoples’ knowledge and perceptions and highlight government policy for adaptation measurements. We systematically searched publications between January 2002 and March 2022 from the Web of Science, PubMed, Google Scholar, and Science Direct databases, screening for (1) environmental and (2) health impacts of climate change on Indigenous Peoples. Fifty-six articles were selected and thoroughly reviewed using the GRADE approach to assess the quality of the evidence. The quality of evidence ranged from low to moderate, and the evidentiary foundation for links between climate change and health effects was weak. We thus find an opportunity for future research to focus on climate-related effects on the health and lands of Indigenous Peoples within Atlantic Canada, especially concerning impacts on mental health.
虽然加拿大很容易获得土著人民气候知识和适应实践的证据，但对区域差异的了解很少，而且在学术和规划背景下缺乏适当的代表性和认可。人们对气候变化对这些社区的健康和环境影响知之甚少。这次审查试图报告和评估过去二十年来对加拿大大西洋地区土著人民的这种影响的证据。目前发表的研究侧重于土著人民的知识和观念，并强调政府的适应措施政策。我们系统地检索了2002年1月至2022年3月期间来自Web of Science、PubMed、Google Scholar和Science Direct数据库的出版物，筛选(1)气候变化对土著人民的环境和(2)健康影响。我们选择了56篇文章，并使用GRADE方法对其进行了全面的审查，以评估证据的质量。证据质量从低到中等不等，气候变化与健康影响之间存在联系的证据基础薄弱。因此，我们发现未来的研究有机会侧重于气候对加拿大大西洋地区土著人民健康和土地的影响，特别是对心理健康的影响。
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Pub Date : 2023-03-22DOI: 10.1088/2752-5295/acc67e
Shuang Ma, Lifen Jiang, R. Wilson, J. Chanton, S. Niu, C. Iversen, A. Malhotra, Jiang Jiang, Yuanyuan Huang, Xingjie Lu, Z. Shi, F. Tao, Junyi Liang, D. Ricciuto, P. Hanson, Yiqi Luo
Peatlands contain one-third of global soil carbon (C), but the responses of peatland ecosystems to long-term warming are not well understood. Here, we pursue an emergent understanding of warming effects on ecosystem C fluxes at peatlands by constraining a process-oriented model, the terrestrial ECOsystem model, with observational data from a long-term warming experiment at the Spruce and Peatland Responses Under Changing Environments site. Model-based assessments show that ecosystem-level photosynthesis and autotrophic respiration exhibited significant thermal acclimation, with temperature sensitivities being linearly decreased with warming. Using the thermal-acclimated parameter values, simulated gross primary production, net primary production, and plant autotrophic respiration (R a), were all lower than those simulated with non-thermal acclimated parameter values. In contrast, ecosystem respiration simulated with thermal acclimated parameter values was higher than that simulated with non-thermal acclimated parameter values. Net ecosystem CO2 exchange was much higher after constraining model parameters with observational data from the warming treatments, releasing C at a rate of 28.3 g C m−2 yr−1 °C−1. Our data-model integration study suggests that peatlands are likely to release more C than previously estimated. Earth system models may overestimate C uptake by peatlands under warming if physiological thermal acclimation of plants is not incorporated. Thus, it is critical to consider the long-term physiological thermal acclimation of plants in the models to better predict global C dynamics under future climate and their feedback to climate change.
泥炭地含有全球三分之一的土壤碳(C)，但泥炭地生态系统对长期变暖的反应尚未得到很好的理解。在这里，我们通过约束一个面向过程的模式，即陆地生态系统模式，利用在变化环境下云杉和泥炭地响应的长期变暖实验的观测数据，寻求对泥炭地生态系统C通量的变暖效应的新兴理解。基于模型的评估表明，生态系统水平的光合作用和自养呼吸表现出显著的热驯化，温度敏感性随变暖线性降低。利用热驯化参数值模拟的总初级生产量、净初级生产量和植物自养呼吸(R a)均低于非热驯化参数值的模拟结果。与此相反，热驯化参数值模拟的生态系统呼吸高于非热驯化参数值模拟的生态系统呼吸。在用增温处理的观测数据约束模型参数后，生态系统净CO2交换要高得多，释放C的速率为28.3 g C m−2 yr−1°C−1。我们的数据模型整合研究表明，泥炭地释放的碳可能比之前估计的要多。如果不考虑植物的生理热适应，地球系统模型可能会高估变暖条件下泥炭地对碳的吸收。因此，在模型中考虑植物的长期生理热适应对于更好地预测未来气候下全球碳动态及其对气候变化的反馈至关重要。
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