Pub Date : 2023-06-16DOI: 10.1088/2752-5295/acdf0f
Chen Zhang, W. Tung, W. Cleveland
We present the Arctic atmospheric river (AR) climatology based on twelve sets of labels derived from ERA5 and MERRA-2 reanalyses for 1980–2019. The ARs were identified and tracked in the 3-hourly reanalysis data with a multifactorial approach based on either atmospheric column-integrated water vapor (IWV) or integrated water vapor transport (IVT) exceeding one of the three climate thresholds (75th, 85th, and 95th percentiles). Time series analysis of the AR event counts from the AR labels showed overall upward trends from the mid-1990s to 2019. The 75th IVT- and IWV-based labels, as well as the 85th IWV-based labels, are likely more sensitive to Arctic surface warming, therefore, detected some broadening of AR-affected areas over time, while the rest of the labels did not. Spatial exploratory analysis of these labels revealed that the AR frequency of occurrence maxima shifted poleward from over-land in 1980–1999 to over the Arctic Ocean and its outlying Seas in 2000–2019. Regions across the Atlantic, the Arctic, to the Pacific Oceans trended higher AR occurrence, surface temperature, and column-integrated moisture. Meanwhile, ARs were increasingly responsible for the rising moisture transport into the Arctic. Even though the increase of Arctic AR occurrence was primarily associated with long-term Arctic surface warming and moistening, the effects of changing atmospheric circulation could stand out locally, such as on the Pacific side over the Chukchi Sea. The changing teleconnection patterns strongly modulated AR activities in time and space, with prominent anomalies in the Arctic-Pacific sector during the latest decade. Besides, the extreme events identified by the 95th-percentile labels displayed the most significant changes and were most influenced by the teleconnection patterns. The twelve Arctic AR labels and the detailed graphics in the atlas can help navigate the uncertainty of detecting and quantifying Arctic ARs and their associated effects in current and future studies.
{"title":"Climatology and decadal changes of Arctic atmospheric rivers based on ERA5 and MERRA-2","authors":"Chen Zhang, W. Tung, W. Cleveland","doi":"10.1088/2752-5295/acdf0f","DOIUrl":"https://doi.org/10.1088/2752-5295/acdf0f","url":null,"abstract":"We present the Arctic atmospheric river (AR) climatology based on twelve sets of labels derived from ERA5 and MERRA-2 reanalyses for 1980–2019. The ARs were identified and tracked in the 3-hourly reanalysis data with a multifactorial approach based on either atmospheric column-integrated water vapor (IWV) or integrated water vapor transport (IVT) exceeding one of the three climate thresholds (75th, 85th, and 95th percentiles). Time series analysis of the AR event counts from the AR labels showed overall upward trends from the mid-1990s to 2019. The 75th IVT- and IWV-based labels, as well as the 85th IWV-based labels, are likely more sensitive to Arctic surface warming, therefore, detected some broadening of AR-affected areas over time, while the rest of the labels did not. Spatial exploratory analysis of these labels revealed that the AR frequency of occurrence maxima shifted poleward from over-land in 1980–1999 to over the Arctic Ocean and its outlying Seas in 2000–2019. Regions across the Atlantic, the Arctic, to the Pacific Oceans trended higher AR occurrence, surface temperature, and column-integrated moisture. Meanwhile, ARs were increasingly responsible for the rising moisture transport into the Arctic. Even though the increase of Arctic AR occurrence was primarily associated with long-term Arctic surface warming and moistening, the effects of changing atmospheric circulation could stand out locally, such as on the Pacific side over the Chukchi Sea. The changing teleconnection patterns strongly modulated AR activities in time and space, with prominent anomalies in the Arctic-Pacific sector during the latest decade. Besides, the extreme events identified by the 95th-percentile labels displayed the most significant changes and were most influenced by the teleconnection patterns. The twelve Arctic AR labels and the detailed graphics in the atlas can help navigate the uncertainty of detecting and quantifying Arctic ARs and their associated effects in current and future studies.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123514541","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 : 2023-06-06DOI: 10.1088/2752-5295/acd6af
G. Persad, B. Samset, L. Wilcox, R. Allen, M. Bollasina, B. Booth, C. Bonfils, Tom Crocker, M. Joshi, M. Lund, K. Marvel, J. Merikanto, K. Nordling, Sabine Undorf, D. V. van Vuuren, D. Westervelt, Alcide Zhao
Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.
{"title":"Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments","authors":"G. Persad, B. Samset, L. Wilcox, R. Allen, M. Bollasina, B. Booth, C. Bonfils, Tom Crocker, M. Joshi, M. Lund, K. Marvel, J. Merikanto, K. Nordling, Sabine Undorf, D. V. van Vuuren, D. Westervelt, Alcide Zhao","doi":"10.1088/2752-5295/acd6af","DOIUrl":"https://doi.org/10.1088/2752-5295/acd6af","url":null,"abstract":"Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121244474","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 : 2023-06-01DOI: 10.1088/2752-5295/acd5f4
J. Doelman, W. Verhagen, E. Stehfest, D. V. van Vuuren
Peatlands only cover a small fraction of the global land surface (∼3%) but store large amounts of carbon (∼600 GtC). Drainage of peatlands for agriculture results in the decomposition of organic matter, leading to greenhouse gas (GHG) emissions. As a result, degraded peatlands are currently responsible for 2%–3% of global anthropogenic emissions. Preventing further degradation of peatlands and restoration (i.e. rewetting) are therefore important for climate change mitigation. In this study, we show that land-use change in three SSP scenarios with optimistic, recent trends, and pessimistic assumptions leads to peatland degradation between 2020 and 2100 ranging from −7 to +10 Mha (−23% to +32%), and a continuation or even an increase in annual GHG emissions (−0.1 to +0.4 GtCO2-eq yr−1). In default mitigation scenarios without a specific focus on peatlands, peatland degradation is reduced due to synergies with forest protection and afforestation policies. However, this still leaves large amounts of GHG emissions from degraded peatlands unabated, causing cumulative CO2 emissions from 2020 to 2100 in an SSP2-1.5 °C scenario of 73 GtCO2. In a mitigation scenario with dedicated peatland restoration policy, GHG emissions from degraded peatlands can be reduced to nearly zero without major effects on projected land-use dynamics. This underlines the opportunity of peatland protection and restoration for climate change mitigation and the need to synergistically combine different land-based mitigation measures. Peatland location and extent estimates vary widely in the literature; a sensitivity analysis implementing various spatial estimates shows that especially in tropical regions degraded peatland area and peatland emissions are highly uncertain. The required protection and mitigation efforts are geographically unequally distributed, with large concentrations of peatlands in Russia, Europe, North America and Indonesia (33% of emission reductions are located in Indonesia). This indicates an important role for only a few countries that have the opportunity to protect and restore peatlands with global benefits for climate change mitigation.
{"title":"The role of peatland degradation, protection and restoration for climate change mitigation in the SSP scenarios","authors":"J. Doelman, W. Verhagen, E. Stehfest, D. V. van Vuuren","doi":"10.1088/2752-5295/acd5f4","DOIUrl":"https://doi.org/10.1088/2752-5295/acd5f4","url":null,"abstract":"Peatlands only cover a small fraction of the global land surface (∼3%) but store large amounts of carbon (∼600 GtC). Drainage of peatlands for agriculture results in the decomposition of organic matter, leading to greenhouse gas (GHG) emissions. As a result, degraded peatlands are currently responsible for 2%–3% of global anthropogenic emissions. Preventing further degradation of peatlands and restoration (i.e. rewetting) are therefore important for climate change mitigation. In this study, we show that land-use change in three SSP scenarios with optimistic, recent trends, and pessimistic assumptions leads to peatland degradation between 2020 and 2100 ranging from −7 to +10 Mha (−23% to +32%), and a continuation or even an increase in annual GHG emissions (−0.1 to +0.4 GtCO2-eq yr−1). In default mitigation scenarios without a specific focus on peatlands, peatland degradation is reduced due to synergies with forest protection and afforestation policies. However, this still leaves large amounts of GHG emissions from degraded peatlands unabated, causing cumulative CO2 emissions from 2020 to 2100 in an SSP2-1.5 °C scenario of 73 GtCO2. In a mitigation scenario with dedicated peatland restoration policy, GHG emissions from degraded peatlands can be reduced to nearly zero without major effects on projected land-use dynamics. This underlines the opportunity of peatland protection and restoration for climate change mitigation and the need to synergistically combine different land-based mitigation measures. Peatland location and extent estimates vary widely in the literature; a sensitivity analysis implementing various spatial estimates shows that especially in tropical regions degraded peatland area and peatland emissions are highly uncertain. The required protection and mitigation efforts are geographically unequally distributed, with large concentrations of peatlands in Russia, Europe, North America and Indonesia (33% of emission reductions are located in Indonesia). This indicates an important role for only a few countries that have the opportunity to protect and restore peatlands with global benefits for climate change mitigation.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133284416","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 : 2023-05-25DOI: 10.1088/2752-5295/acd8e3
S. Muñoz, S. Dee, X. Luo, M. R. Haider, M. O'Donnell, B. Parazin, J. Remo
The Mississippi River represents a major commercial waterway, and periods of anomalously low river levels disrupt riverine transport. These low-flow events occur periodically, with a recent event in the fall of 2022 slowing barge traffic and generating sharp increases in riverine transportation costs. Here we combine instrumental river gage observations from the lower Mississippi River with output from the Community Earth System Model v2 Large Ensemble (LENS2) to evaluate historical trends and future projections of Mississippi River low streamflow extremes, place the 2022 low-flow event in a broader temporal context, and assess the hydroclimatic mechanisms that mediate the occurrence of low-flows. We show that the severity and duration of low-flow events gradually decreased between 1950 and 1980 coincident with the establishment of artificial reservoirs. In the context of the last ∼70 years, the 2022 low-flow event was less severe in terms of stage or discharge minima than other low-flow events of the mid- and late-20th century. Model simulations from the LENS2 dataset show that, under a moderate-high emissions scenario (SSP3-7.0), the severity and duration of low-flow events is projected to decrease through to the end of the 21st century. Finally, we use the large sample size afforded by the LENS2 dataset to show that low-flow events on the Mississippi River are associated with cold tropical Pacific forcing (i.e. La Niña conditions), providing support for the hypothesis that the El Niño-Southern Oscillation plays a critical role in mediating Mississippi River discharge extremes. We anticipate that our findings describing the trends in and hydroclimatic mechanisms of Mississippi River low-flow occurrence will aid water resource managers to reduce the negative impacts of low water levels on riverine transport.
{"title":"Mississippi River low-flows: context, causes, and future projections","authors":"S. Muñoz, S. Dee, X. Luo, M. R. Haider, M. O'Donnell, B. Parazin, J. Remo","doi":"10.1088/2752-5295/acd8e3","DOIUrl":"https://doi.org/10.1088/2752-5295/acd8e3","url":null,"abstract":"The Mississippi River represents a major commercial waterway, and periods of anomalously low river levels disrupt riverine transport. These low-flow events occur periodically, with a recent event in the fall of 2022 slowing barge traffic and generating sharp increases in riverine transportation costs. Here we combine instrumental river gage observations from the lower Mississippi River with output from the Community Earth System Model v2 Large Ensemble (LENS2) to evaluate historical trends and future projections of Mississippi River low streamflow extremes, place the 2022 low-flow event in a broader temporal context, and assess the hydroclimatic mechanisms that mediate the occurrence of low-flows. We show that the severity and duration of low-flow events gradually decreased between 1950 and 1980 coincident with the establishment of artificial reservoirs. In the context of the last ∼70 years, the 2022 low-flow event was less severe in terms of stage or discharge minima than other low-flow events of the mid- and late-20th century. Model simulations from the LENS2 dataset show that, under a moderate-high emissions scenario (SSP3-7.0), the severity and duration of low-flow events is projected to decrease through to the end of the 21st century. Finally, we use the large sample size afforded by the LENS2 dataset to show that low-flow events on the Mississippi River are associated with cold tropical Pacific forcing (i.e. La Niña conditions), providing support for the hypothesis that the El Niño-Southern Oscillation plays a critical role in mediating Mississippi River discharge extremes. We anticipate that our findings describing the trends in and hydroclimatic mechanisms of Mississippi River low-flow occurrence will aid water resource managers to reduce the negative impacts of low water levels on riverine transport.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128086911","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 : 2023-05-19DOI: 10.1088/2752-5295/acd714
J. Risbey, Damien B Irving, D. Squire, R. Matear, D. Monselesan, M. Pook, N. Ramesh, D. Richardson, C. Tozer
The record-shattering hot day in the Pacific Northwest in June 2021 is used to motivate a study of record-shattering temperature extremes in a very large hindcast ensemble. The hottest days in the Pacific Northwest in the large ensemble have similar large scale and synoptic patterns to those associated with the observed event. From the perspective of a fixed location, the hottest ensemble days are acutely sensitive to the chance sequencing of a dry period with a precisely positioned weather pattern. These days are thus rare and require very large samples (tens of thousands of years) to capture. The enduring nature of record-shattering heat records can be understood through this lens of weather ‘noise’ and sampling. When a record-shattering event occurs due to chance alignment of weather systems in the optimal configuration, any small sample of years subsequent to the (very unlikely) record event has an extremely low chance of finding yet another chance extreme. While warming of the baseline climate can narrow the gap between more regular extremes and record-shattering extremes, this can take many decades depending on the pace of climate change. Climate models are unlikely to capture record-shattering extremes at fixed locations given by observations unless the model samples are large enough to provide enough weather outcomes to include the optimal weather alignments. This underscores the need to account for sampling in assessing models and changes in weather-sensitive extremes. In particular, climate models are not necessarily deficient in representing extremes if that assessment is based on their absence in undersize samples.
{"title":"A large ensemble illustration of how record-shattering heat records can endure","authors":"J. Risbey, Damien B Irving, D. Squire, R. Matear, D. Monselesan, M. Pook, N. Ramesh, D. Richardson, C. Tozer","doi":"10.1088/2752-5295/acd714","DOIUrl":"https://doi.org/10.1088/2752-5295/acd714","url":null,"abstract":"The record-shattering hot day in the Pacific Northwest in June 2021 is used to motivate a study of record-shattering temperature extremes in a very large hindcast ensemble. The hottest days in the Pacific Northwest in the large ensemble have similar large scale and synoptic patterns to those associated with the observed event. From the perspective of a fixed location, the hottest ensemble days are acutely sensitive to the chance sequencing of a dry period with a precisely positioned weather pattern. These days are thus rare and require very large samples (tens of thousands of years) to capture. The enduring nature of record-shattering heat records can be understood through this lens of weather ‘noise’ and sampling. When a record-shattering event occurs due to chance alignment of weather systems in the optimal configuration, any small sample of years subsequent to the (very unlikely) record event has an extremely low chance of finding yet another chance extreme. While warming of the baseline climate can narrow the gap between more regular extremes and record-shattering extremes, this can take many decades depending on the pace of climate change. Climate models are unlikely to capture record-shattering extremes at fixed locations given by observations unless the model samples are large enough to provide enough weather outcomes to include the optimal weather alignments. This underscores the need to account for sampling in assessing models and changes in weather-sensitive extremes. In particular, climate models are not necessarily deficient in representing extremes if that assessment is based on their absence in undersize samples.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121256278","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 : 2023-05-12DOI: 10.1088/2752-5295/acd4da
É. Blanc, Ilan Noy
We estimate the impact of precipitation extremes on the productivity of agricultural land parcels in New Zealand using satellite data. This type of post-disaster damage assessment aims to allow for the quantification of disaster damage when an on-the-ground assessment of damage is too costly or too difficult to conduct. It can also serve as a retroactive data collection tool for disaster loss databases where data collection did not happen at the time. We use satellite-derived observations of terrestrial vegetation (the enhanced vegetation index (EVI)) over the growing season, with data at the land parcel level identifying five land use types (annual and perennial crops, and three types of pasture), and with precipitation records, which we use to identify both excessively dry (drought) and excessively wet (flood) episodes. Using regression analyses, we examine whether these precipitation extremes had an observable impact on agricultural productivity. We find statistically significant declines in agricultural productivity that are associated with both droughts and floods. The average impact of these events is usually less than 1%, but the impacts are quite heterogeneous across years and across regions, with some parcels experiencing a much more significant decline in the EVI. We also identify several impact patterns related to the varying drought and flood vulnerability of the analysed land use types.
{"title":"Impacts of droughts and floods on agricultural productivity in New Zealand as measured from space","authors":"É. Blanc, Ilan Noy","doi":"10.1088/2752-5295/acd4da","DOIUrl":"https://doi.org/10.1088/2752-5295/acd4da","url":null,"abstract":"We estimate the impact of precipitation extremes on the productivity of agricultural land parcels in New Zealand using satellite data. This type of post-disaster damage assessment aims to allow for the quantification of disaster damage when an on-the-ground assessment of damage is too costly or too difficult to conduct. It can also serve as a retroactive data collection tool for disaster loss databases where data collection did not happen at the time. We use satellite-derived observations of terrestrial vegetation (the enhanced vegetation index (EVI)) over the growing season, with data at the land parcel level identifying five land use types (annual and perennial crops, and three types of pasture), and with precipitation records, which we use to identify both excessively dry (drought) and excessively wet (flood) episodes. Using regression analyses, we examine whether these precipitation extremes had an observable impact on agricultural productivity. We find statistically significant declines in agricultural productivity that are associated with both droughts and floods. The average impact of these events is usually less than 1%, but the impacts are quite heterogeneous across years and across regions, with some parcels experiencing a much more significant decline in the EVI. We also identify several impact patterns related to the varying drought and flood vulnerability of the analysed land use types.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115754824","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 : 2023-04-21DOI: 10.1088/2752-5295/accf30
F. Lehner, C. Deser
Adaptation to climate change has now become a necessity for many regions. Yet, adaptation planning at regional scales over the next few decades is challenging given the contingencies originating from a combination of different sources of climate projection uncertainty, chief among them internal variability. Here, we review the causes and consequences of internal climate variability, how it can be quantified and accounted for in uncertainty assessments, and what research questions remain most pertinent to better understand its predictive limits and consequences for science and society. This perspective argues for putting internal variability into the spotlight of climate adaptation science and intensifying collaborations between the climate modeling and application communities.
{"title":"Origin, importance, and predictive limits of internal climate variability","authors":"F. Lehner, C. Deser","doi":"10.1088/2752-5295/accf30","DOIUrl":"https://doi.org/10.1088/2752-5295/accf30","url":null,"abstract":"Adaptation to climate change has now become a necessity for many regions. Yet, adaptation planning at regional scales over the next few decades is challenging given the contingencies originating from a combination of different sources of climate projection uncertainty, chief among them internal variability. Here, we review the causes and consequences of internal climate variability, how it can be quantified and accounted for in uncertainty assessments, and what research questions remain most pertinent to better understand its predictive limits and consequences for science and society. This perspective argues for putting internal variability into the spotlight of climate adaptation science and intensifying collaborations between the climate modeling and application communities.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134262129","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 : 2023-04-21DOI: 10.1088/2752-5295/accf2e
Akshay Rajeev, V. Mishra
Tropical cyclones (TCs) cause compound extremes of rainfall and wind gust. However, their occurrence and impacts on India still need to be better understood. Using ERA5 reanalysis and cyclone eAtlas, we examine the compound extremes of precipitation and wind gust driven by TCs that made landfall over India during 1981–2021. Based on the joint return period of compound extremes, the five worst TCs occurred in May 1990, May 1999, May 2010 (Laila), October 2014 (Hudhud), and May 2020 (Amphan). A majority of TCs during 1981–2021 originated from the Bay of Bengal (BoB) and only a few from the Arabian Sea (AS). While the frequency of all the TCs has either declined or remained stable in the North Indian Ocean (NIO, BoB, AS) during 1981–2021, the frequency of TCs with compound extremes has increased by about three-fold during the most recent decade (2011–2021). Compound extremes driven by TCs affect large regions along the coast and risk infrastructure and human lives. The frequency of TCs with large area of impact (greater than 200 000 km2) compound wind and precipitation extreme extent exhibits a three-fold rise during 1981–2021, indicating an increase in the hazard associated with the compound extremes driven by TCs in India.
{"title":"Increasing risk of compound wind and precipitation extremes due to tropical cyclones in India","authors":"Akshay Rajeev, V. Mishra","doi":"10.1088/2752-5295/accf2e","DOIUrl":"https://doi.org/10.1088/2752-5295/accf2e","url":null,"abstract":"Tropical cyclones (TCs) cause compound extremes of rainfall and wind gust. However, their occurrence and impacts on India still need to be better understood. Using ERA5 reanalysis and cyclone eAtlas, we examine the compound extremes of precipitation and wind gust driven by TCs that made landfall over India during 1981–2021. Based on the joint return period of compound extremes, the five worst TCs occurred in May 1990, May 1999, May 2010 (Laila), October 2014 (Hudhud), and May 2020 (Amphan). A majority of TCs during 1981–2021 originated from the Bay of Bengal (BoB) and only a few from the Arabian Sea (AS). While the frequency of all the TCs has either declined or remained stable in the North Indian Ocean (NIO, BoB, AS) during 1981–2021, the frequency of TCs with compound extremes has increased by about three-fold during the most recent decade (2011–2021). Compound extremes driven by TCs affect large regions along the coast and risk infrastructure and human lives. The frequency of TCs with large area of impact (greater than 200 000 km2) compound wind and precipitation extreme extent exhibits a three-fold rise during 1981–2021, indicating an increase in the hazard associated with the compound extremes driven by TCs in India.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126586909","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 : 2023-04-21DOI: 10.1088/2752-5295/accf2d
S. Plecha, A. Teles-Machado, R. Tomé, P. Mateus
Numerous processes affecting coastal ocean dynamics and water properties occur at the air-sea interface as a result of wind blowing on the ocean surface. In Earth system research, it is crucial to appropriately characterize the ocean surface wind (OSW) field because of its significance in many academic and economic activities. This study aimed to evaluate the accuracy of the most recent OSW datasets based on numerical modeling and remote sensing products in estimating in situ observations along the Atlantic coast of the Iberian Peninsula. The results are three-fold: (1) when high temporal resolutions are not necessary, remote sensing products are an excellent choice because they provide reliable OSW estimates; (2) for analyses that require high temporal resolution, numerical weather models are the best choice because they can statistically reproduce the main trend; (3) fifth generation of European ReAnalysis (ERA5) showed that, despite having a lower spatial resolution than the dynamically downscaled weather research and forecasting simulation, it captures the spatial and temporal dynamics and variability of coastal winds and may be used as forcing of the atmosphere-ocean interface modeling without compromising its accuracy.
{"title":"Offshore wind data assessment near the Iberian Peninsula over the last 25 years","authors":"S. Plecha, A. Teles-Machado, R. Tomé, P. Mateus","doi":"10.1088/2752-5295/accf2d","DOIUrl":"https://doi.org/10.1088/2752-5295/accf2d","url":null,"abstract":"Numerous processes affecting coastal ocean dynamics and water properties occur at the air-sea interface as a result of wind blowing on the ocean surface. In Earth system research, it is crucial to appropriately characterize the ocean surface wind (OSW) field because of its significance in many academic and economic activities. This study aimed to evaluate the accuracy of the most recent OSW datasets based on numerical modeling and remote sensing products in estimating in situ observations along the Atlantic coast of the Iberian Peninsula. The results are three-fold: (1) when high temporal resolutions are not necessary, remote sensing products are an excellent choice because they provide reliable OSW estimates; (2) for analyses that require high temporal resolution, numerical weather models are the best choice because they can statistically reproduce the main trend; (3) fifth generation of European ReAnalysis (ERA5) showed that, despite having a lower spatial resolution than the dynamically downscaled weather research and forecasting simulation, it captures the spatial and temporal dynamics and variability of coastal winds and may be used as forcing of the atmosphere-ocean interface modeling without compromising its accuracy.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121659517","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 : 2023-04-21DOI: 10.1088/2752-5295/accf2f
N. Diffenbaugh, E. Barnes, P. Keys
Although achieving net-zero emissions is very likely to stabilize the long-term global temperature, the possibility of continued warming and extreme events could cause those efforts to be perceived as a failure if there is an expectation that stabilizing global temperature will also stabilize local and regional climate. Leveraging decarbonization scenarios from multiple global climate models, we find that much of the world faces >30% probability of decadal warming after net-zero CO2 emissions are achieved, with most areas exhibiting sustained probability of extreme hot and wet events. Further, substantial fractions of the global population and gross domestic product could experience post-net-zero warming, including hundreds of millions of people and trillions of dollars in the United States, China and India during the decade following net-zero. This likelihood suggests that some of the most populous, wealthy, and powerful regions may experience climatic conditions that could be perceived—at least in the near-term—to indicate that climate stabilization policies have failed, highlighting the importance of adaptation for ensuring that communities are prepared for the climate variations that will inevitably occur during and after decarbonization.
{"title":"Probability of continued local-scale warming and extreme events during and after decarbonization","authors":"N. Diffenbaugh, E. Barnes, P. Keys","doi":"10.1088/2752-5295/accf2f","DOIUrl":"https://doi.org/10.1088/2752-5295/accf2f","url":null,"abstract":"Although achieving net-zero emissions is very likely to stabilize the long-term global temperature, the possibility of continued warming and extreme events could cause those efforts to be perceived as a failure if there is an expectation that stabilizing global temperature will also stabilize local and regional climate. Leveraging decarbonization scenarios from multiple global climate models, we find that much of the world faces >30% probability of decadal warming after net-zero CO2 emissions are achieved, with most areas exhibiting sustained probability of extreme hot and wet events. Further, substantial fractions of the global population and gross domestic product could experience post-net-zero warming, including hundreds of millions of people and trillions of dollars in the United States, China and India during the decade following net-zero. This likelihood suggests that some of the most populous, wealthy, and powerful regions may experience climatic conditions that could be perceived—at least in the near-term—to indicate that climate stabilization policies have failed, highlighting the importance of adaptation for ensuring that communities are prepared for the climate variations that will inevitably occur during and after decarbonization.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129252435","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}
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