Pub Date : 2024-02-29DOI: 10.1088/2752-5295/ad2eb2
N. Ritzhaupt, D. Maraun
Extreme precipitation can lead to severe environmental and economic impacts. Thus, future changes in extreme precipitation and their uncertainties are of major interest. Changes in extreme precipitation can be decomposed into thermodynamic (temperature-related) and dynamic (vertical velocity related) contributions with a scaling approach for extreme precipitation. Applying this approach to the global climate model ensembles CMIP5 and CMIP6, we decompose projection uncertainties of extremes in daily precipitation into uncertainties of thermodynamic and dynamic changes. We analyze regional patterns of the total uncertainties in extreme precipitation projections, as well as the thermodynamic and dynamic contributions to these uncertainties. Total uncertainties relative to the projected multi model mean are dominated by the dynamical contributions, and are large over the tropics and subtropics, but smaller over the high and mid-latitudes. Uncertainties in the thermodynamic contribution are generally small. From CMIP5 to CMIP6, uncertainties in thermodynamic and dynamic changes are slightly reduced in the high and mid-latitudes, while there is a substantial reduction of the uncertainties of the dynamic changes in the tropics and subtropics.
{"title":"State-of-the-art climate models reduce dominant dynamical uncertainty in projections of extreme precipitation","authors":"N. Ritzhaupt, D. Maraun","doi":"10.1088/2752-5295/ad2eb2","DOIUrl":"https://doi.org/10.1088/2752-5295/ad2eb2","url":null,"abstract":"\u0000 Extreme precipitation can lead to severe environmental and economic impacts. Thus, future changes in extreme precipitation and their uncertainties are of major interest. Changes in extreme precipitation can be decomposed into thermodynamic (temperature-related) and dynamic (vertical velocity related) contributions with a scaling approach for extreme precipitation. Applying this approach to the global climate model ensembles CMIP5 and CMIP6, we decompose projection uncertainties of extremes in daily precipitation into uncertainties of thermodynamic and dynamic changes. We analyze regional patterns of the total uncertainties in extreme precipitation projections, as well as the thermodynamic and dynamic contributions to these uncertainties. Total uncertainties relative to the projected multi model mean are dominated by the dynamical contributions, and are large over the tropics and subtropics, but smaller over the high and mid-latitudes. Uncertainties in the thermodynamic contribution are generally small. From CMIP5 to CMIP6, uncertainties in thermodynamic and dynamic changes are slightly reduced in the high and mid-latitudes, while there is a substantial reduction of the uncertainties of the dynamic changes in the tropics and subtropics.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"16 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140409728","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 : 2024-02-22DOI: 10.1088/2752-5295/ad2c0e
L. Andreasen, Joona Cornér, Peter Abbott, Victoria A. Sinclair, Felix Riede, C. Timmreck
Explosive volcanic eruptions are well known to influence Earth’s temperature. Changes in Earth’s temperature can affect temperature gradients which in turn could affect the isentropic slope and hence Northern Hemisphere high and mid- latitude weather. Yet, the possible influence of volcanic eruptions on these atmospheric circulation patterns and the potential spatial extent are not well understood. To address this issue, we pursue two independent lines of evidence. Firstly, we simulate volcanic eruptions with the MPI-ESM1.2 Earth System Model and use the TRACK algorithm to explore how extra-tropical cyclone frequency is affected in the model experiments. Secondly, we query the Greenland ice core NEEM-2011-S1 for indications of increased Northern Hemisphere extra-tropical cyclone frequency correlating with evidence for explosive volcanism by comparing the storm proxies sodium (Na) and calcium (Ca); with the eruption proxy sulphur (S). Both the model and proxy evidence suggest that large explosive volcanic eruptions increase storminess around the location of the ice core. Furthermore, the simulations indicate that the number of extra-tropical cyclones increases in the subtropics and at high latitudes, while they decrease in the mid-latitudes. A detailed interrogation of the simulated eruptions reveals that increases in cyclone frequency are linked to steepening of the isentropic slope due to a larger meridional temperature gradient and to a lower tropopause. The steepening is driven by a combination of warming of the tropical stratosphere from absorption of longwave radiation by volcanic aerosols and surface cooling due to the scattering of sunlight by the same aerosols, whereas the lower tropopause may be attributed to a warmer stratosphere.
{"title":"Changes in Northern Hemisphere extra-tropicalcyclone frequency following volcanic eruptions","authors":"L. Andreasen, Joona Cornér, Peter Abbott, Victoria A. Sinclair, Felix Riede, C. Timmreck","doi":"10.1088/2752-5295/ad2c0e","DOIUrl":"https://doi.org/10.1088/2752-5295/ad2c0e","url":null,"abstract":"\u0000 Explosive volcanic eruptions are well known to influence Earth’s temperature. Changes in Earth’s temperature can affect temperature gradients which in turn could affect the isentropic slope and hence Northern Hemisphere high and mid- latitude weather. Yet, the possible influence of volcanic eruptions on these atmospheric circulation patterns and the potential spatial extent are not well understood. To address this issue, we pursue two independent lines of evidence. Firstly, we simulate volcanic eruptions with the MPI-ESM1.2 Earth System Model and use the TRACK algorithm to explore how extra-tropical cyclone frequency is affected in the model experiments. Secondly, we query the Greenland ice core NEEM-2011-S1 for indications of increased Northern Hemisphere extra-tropical cyclone frequency correlating with evidence for explosive volcanism by comparing the storm proxies sodium (Na) and calcium (Ca); with the eruption proxy sulphur (S). Both the model and proxy evidence suggest that large explosive volcanic eruptions increase storminess around the location of the ice core. Furthermore, the simulations indicate that the number of extra-tropical cyclones increases in the subtropics and at high latitudes, while they decrease in the mid-latitudes. A detailed interrogation of the simulated eruptions reveals that increases in cyclone frequency are linked to steepening of the isentropic slope due to a larger meridional temperature gradient and to a lower tropopause. The steepening is driven by a combination of warming of the tropical stratosphere from absorption of longwave radiation by volcanic aerosols and surface cooling due to the scattering of sunlight by the same aerosols, whereas the lower tropopause may be attributed to a warmer stratosphere.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"66 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140439828","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 : 2024-02-12DOI: 10.1088/2752-5295/ad285a
Anna S. Jensen, K. Rittger, M. Raleigh
The seasonal mountain snowpack of the western U.S. (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODSCAG/MODDRFS) from 2001-2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (March 1st - June 30th) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.
{"title":"Spatio-temporal patterns and trends in MODIS-retrieved radiative forcing by snow impurities over the Western U.S. from 2001 - 2022","authors":"Anna S. Jensen, K. Rittger, M. Raleigh","doi":"10.1088/2752-5295/ad285a","DOIUrl":"https://doi.org/10.1088/2752-5295/ad285a","url":null,"abstract":"\u0000 The seasonal mountain snowpack of the western U.S. (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODSCAG/MODDRFS) from 2001-2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (March 1st - June 30th) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"137 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139842756","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 : 2024-02-12DOI: 10.1088/2752-5295/ad285a
Anna S. Jensen, K. Rittger, M. Raleigh
The seasonal mountain snowpack of the western U.S. (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODSCAG/MODDRFS) from 2001-2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (March 1st - June 30th) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.
{"title":"Spatio-temporal patterns and trends in MODIS-retrieved radiative forcing by snow impurities over the Western U.S. from 2001 - 2022","authors":"Anna S. Jensen, K. Rittger, M. Raleigh","doi":"10.1088/2752-5295/ad285a","DOIUrl":"https://doi.org/10.1088/2752-5295/ad285a","url":null,"abstract":"\u0000 The seasonal mountain snowpack of the western U.S. (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODSCAG/MODDRFS) from 2001-2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (March 1st - June 30th) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"18 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783062","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 : 2024-01-26DOI: 10.1088/2752-5295/ad22ec
H. Ghasemifard, Pieter Groenemeijer, T. Púčik, Francesco Battaglioli
We study the role of changes in circulation type frequency on the evolution of summertime thunderstorm and large hail frequency across Europe since 1950 until 2020 to find out if they are responsible for the changes that an additive regression model (AR-CHaMo) predicts to have happened. To define circulation types, the 500 hPa geopotential height anomaly field on each day was clustered into 14 distinct patterns using principal component analysis and k-means clustering. We show that lightning and hail occurrence, both observed and modelled by AR-CHaMo, strongly depend on the circulation type, with a higher frequency observed in poleward flow downstream of a trough and on the lee side of mountains. AR-CHaMo predicts strong increases in hail frequency across central parts of Europe to have occurred in the 1950-2020 period. During this period, changes in circulation type frequency are small and only significant for 2 of the 14 clusters. The trends in both lightning and hail frequency to be expected if they were solely determined by circulation patterns, are small, with typical values of 1 – 3 % per decade relative to the mean, whereas the trends expected by AR-CHaMo are on the order of 4 – 10% in most areas. Across many regions, the sign of the changes does not agree in sign, in particular across European Russia where circulation types have become more favorable for lightning and hail, but a decreasing probability was modelled by AR-CHaMo. We conclude that changing circulation types are, in general, not responsible for changes in thunderstorm and hail frequency, which included the strong increase of conditions favorable for large hail in central Europe.
{"title":"Do changing circulation types raise the frequency of summertime thunderstorms and large hail in Europe?","authors":"H. Ghasemifard, Pieter Groenemeijer, T. Púčik, Francesco Battaglioli","doi":"10.1088/2752-5295/ad22ec","DOIUrl":"https://doi.org/10.1088/2752-5295/ad22ec","url":null,"abstract":"\u0000 We study the role of changes in circulation type frequency on the evolution of summertime thunderstorm and large hail frequency across Europe since 1950 until 2020 to find out if they are responsible for the changes that an additive regression model (AR-CHaMo) predicts to have happened. To define circulation types, the 500 hPa geopotential height anomaly field on each day was clustered into 14 distinct patterns using principal component analysis and k-means clustering. We show that lightning and hail occurrence, both observed and modelled by AR-CHaMo, strongly depend on the circulation type, with a higher frequency observed in poleward flow downstream of a trough and on the lee side of mountains. AR-CHaMo predicts strong increases in hail frequency across central parts of Europe to have occurred in the 1950-2020 period. During this period, changes in circulation type frequency are small and only significant for 2 of the 14 clusters. The trends in both lightning and hail frequency to be expected if they were solely determined by circulation patterns, are small, with typical values of 1 – 3 % per decade relative to the mean, whereas the trends expected by AR-CHaMo are on the order of 4 – 10% in most areas. Across many regions, the sign of the changes does not agree in sign, in particular across European Russia where circulation types have become more favorable for lightning and hail, but a decreasing probability was modelled by AR-CHaMo. We conclude that changing circulation types are, in general, not responsible for changes in thunderstorm and hail frequency, which included the strong increase of conditions favorable for large hail in central Europe.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"15 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139594305","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 : 2024-01-26DOI: 10.1088/2752-5295/ad22eb
Lin Shi, Adam R. Brandt, Dan Iancu, Katharine J. Mach, Christopher Field, Mu-Jung Cho, Michelle Ng, Kyung Jin (Sarah) Chey, Nilam Ram, Tom Robinson, Byron Reeves
Information and communications technology (ICT) has become an indispensable part of our lives. Prior research on climate impact of ICT devices and services climate impact have largely focused on the embodied carbon emissions using life cycle assessment (LCA) and energy modeling frameworks. These perspectives view mainly emphasize the carbon emissions associated with the construction and distribution of digital devices along production supply chains. However, the carbon emissions monitored or facilitated by digital device use is largely under studied. In this study, we propose the concept of Digital Use Supply Chains (DUSC) as an orthogonal dimension of digital devices’ life cycle. DUSC refers to the production activities and resource consumption recorded or induced using digital devices. We propose a framework to quantify digital behaviors related greenhouse gas emissions through use of the Screenomics paradigm, where users’ digital screen data are unobtrusively collected moment-by-moment. Through Screenomics’ granular recording of users’ digital behavior, we evaluate behavior-based greenhouse gas emissions traced by the digital devices. The DUSC concept connects individual’s digital behaviors to their global climate change impact, contributing to a more nuanced and complete evaluation of the climate impacts of the digital economy. Our case study indicates the estimated scale of the greenhouse gas emissions linking to digital activities is 3 orders of magnitude higher than the emissions associated with the devices life cycle alone. DUSC could enable climate change mitigation at a meaningful, actionable level through personalized educational or behavior change programs. It also facilitates novel data-driven feedback loops that may provide digital device users with insights into their personal climate impacts. Recognition and future studies of DUSC could accelerate the quantification and standardization of a “carbon handprint” of digital devices and create positive climate impacts from digital products and services.
{"title":"Climate impacts of digital use supply chains","authors":"Lin Shi, Adam R. Brandt, Dan Iancu, Katharine J. Mach, Christopher Field, Mu-Jung Cho, Michelle Ng, Kyung Jin (Sarah) Chey, Nilam Ram, Tom Robinson, Byron Reeves","doi":"10.1088/2752-5295/ad22eb","DOIUrl":"https://doi.org/10.1088/2752-5295/ad22eb","url":null,"abstract":"\u0000 Information and communications technology (ICT) has become an indispensable part of our lives. Prior research on climate impact of ICT devices and services climate impact have largely focused on the embodied carbon emissions using life cycle assessment (LCA) and energy modeling frameworks. These perspectives view mainly emphasize the carbon emissions associated with the construction and distribution of digital devices along production supply chains. However, the carbon emissions monitored or facilitated by digital device use is largely under studied. In this study, we propose the concept of Digital Use Supply Chains (DUSC) as an orthogonal dimension of digital devices’ life cycle. DUSC refers to the production activities and resource consumption recorded or induced using digital devices. We propose a framework to quantify digital behaviors related greenhouse gas emissions through use of the Screenomics paradigm, where users’ digital screen data are unobtrusively collected moment-by-moment. Through Screenomics’ granular recording of users’ digital behavior, we evaluate behavior-based greenhouse gas emissions traced by the digital devices. The DUSC concept connects individual’s digital behaviors to their global climate change impact, contributing to a more nuanced and complete evaluation of the climate impacts of the digital economy. Our case study indicates the estimated scale of the greenhouse gas emissions linking to digital activities is 3 orders of magnitude higher than the emissions associated with the devices life cycle alone. DUSC could enable climate change mitigation at a meaningful, actionable level through personalized educational or behavior change programs. It also facilitates novel data-driven feedback loops that may provide digital device users with insights into their personal climate impacts. Recognition and future studies of DUSC could accelerate the quantification and standardization of a “carbon handprint” of digital devices and create positive climate impacts from digital products and services.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"46 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139594990","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 : 2024-01-17DOI: 10.1088/2752-5295/ad1fd7
A. Hinzmann, T. Moelg, Matthias H Braun, N. Cullen, Douglas R Hardy, Georg Kaser, R. Prinz
Over recent decades, the retreat of Kilimanjaro’s glaciers has been portrayed as a beacon of climate change. The decline in glacier area within the 20th century, however, is evident for all tropical glaciers in East Africa, including those of Mount Kenya and the Rwenzori Range. Being mainly controlled by high-altitude hygric seasonality, these glaciers are par-ticularly valuable indicators of tropical climate variability and climate change. More recent studies have focused on Kilimanjaro and Mount Kenya but the Rwenzori Range has not been considered for nearly two decades, which introduces an uncertainty about the remaining glacierization in East Africa. Therefore, the present study provides insights into the most recent glacier extents of all three mountain regions using a manual, multitemporal analysis of high-resolution satellite images for the years 2021/2022. Accordingly, the glacierization in East Africa is estimated to be 1.36 km2, with a glacier area of 0.98 km2 on Kilimanjaro, 0.069 km2 on Mount Kenya and 0.38 km2 in the Rwenzori Range. The uncertainty is deter-mined to be smaller than 12 %. Compared to previous estimations, the overall area has de-clined by more than a half of its early 21st century extent. These recent results demonstrate the continuing influence of retreat processes, which were found to be driven by Indian Ocean warming and high-elevation snowfall changes in previous studies.
{"title":"Tropical glacier loss in East Africa: recent areal extents on Kilimanjaro, Mount Kenya, and in the Rwenzori Range from high-resolution remote sensing data","authors":"A. Hinzmann, T. Moelg, Matthias H Braun, N. Cullen, Douglas R Hardy, Georg Kaser, R. Prinz","doi":"10.1088/2752-5295/ad1fd7","DOIUrl":"https://doi.org/10.1088/2752-5295/ad1fd7","url":null,"abstract":"\u0000 Over recent decades, the retreat of Kilimanjaro’s glaciers has been portrayed as a beacon of climate change. The decline in glacier area within the 20th century, however, is evident for all tropical glaciers in East Africa, including those of Mount Kenya and the Rwenzori Range. Being mainly controlled by high-altitude hygric seasonality, these glaciers are par-ticularly valuable indicators of tropical climate variability and climate change. More recent studies have focused on Kilimanjaro and Mount Kenya but the Rwenzori Range has not been considered for nearly two decades, which introduces an uncertainty about the remaining glacierization in East Africa. Therefore, the present study provides insights into the most recent glacier extents of all three mountain regions using a manual, multitemporal analysis of high-resolution satellite images for the years 2021/2022. Accordingly, the glacierization in East Africa is estimated to be 1.36 km2, with a glacier area of 0.98 km2 on Kilimanjaro, 0.069 km2 on Mount Kenya and 0.38 km2 in the Rwenzori Range. The uncertainty is deter-mined to be smaller than 12 %. Compared to previous estimations, the overall area has de-clined by more than a half of its early 21st century extent. These recent results demonstrate the continuing influence of retreat processes, which were found to be driven by Indian Ocean warming and high-elevation snowfall changes in previous studies.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"113 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139616343","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 : 2024-01-16DOI: 10.1088/2752-5295/ad1f40
Zachary Kaufman, N. Feldl, Claudie Beaulieu
In recent decades, Arctic-amplified warming and sea-ice loss coincided with a prolonged wintertime Eurasian cooling trend. This observed Warm Arctic-Cold Eurasia pattern has occasionally been attributed to sea-ice forced changes in the midlatitude atmospheric circulation, implying an anthropogenic cause. However, comprehensive climate change simulations do not produce Eurasian cooling, instead suggesting a role for unforced atmospheric variability. This study seeks to clarify the source of this model-observation discrepancy by developing a statistical approach that enables direct comparison of Arctic-midlatitude interactions. In both historical simulations and observations, we first identify Ural blocking as the primary causal driver of sea ice, temperature, and circulation anomalies consistent with the Warm Arctic-Cold Eurasia pattern. Next, we quantify distinct transient responses to this Ural blocking, which explain the model-observation discrepancy in historical Eurasian temperature. Observed 1988-2012 Eurasian cooling occurs in response to a pronounced positive trend in Ural sea-level pressure, temporarily masking long-term midlatitude warming. This observed sea-level pressure trend lies at the outer edge of simulated variability in a fully coupled large ensemble, where smaller sea-level pressure trends have little impact on the ensemble mean temperature trend over Eurasia. Accounting for these differences bring observed and simulated trends into remarkable agreement. Finally, we quantify the influence of sea-ice loss on the magnitude of the observed Ural sea-level pressure trend, an effect that is absent in historical simulations. These results illustrate that sea-ice loss and tropospheric variability can both play a role in producing Eurasian cooling. Furthermore, by conducting a direct model-observation comparison, we reveal a key difference in the causal structures characterizing the Warm Arctic-Cold Eurasia Pattern, which will guide ongoing efforts to explain the lack of Eurasian cooling in climate change simulations.
{"title":"Warm Arctic-cold Eurasia pattern driven by atmospheric blocking in models and observations","authors":"Zachary Kaufman, N. Feldl, Claudie Beaulieu","doi":"10.1088/2752-5295/ad1f40","DOIUrl":"https://doi.org/10.1088/2752-5295/ad1f40","url":null,"abstract":"\u0000 In recent decades, Arctic-amplified warming and sea-ice loss coincided with a prolonged wintertime Eurasian cooling trend. This observed Warm Arctic-Cold Eurasia pattern has occasionally been attributed to sea-ice forced changes in the midlatitude atmospheric circulation, implying an anthropogenic cause. However, comprehensive climate change simulations do not produce Eurasian cooling, instead suggesting a role for unforced atmospheric variability. This study seeks to clarify the source of this model-observation discrepancy by developing a statistical approach that enables direct comparison of Arctic-midlatitude interactions. In both historical simulations and observations, we first identify Ural blocking as the primary causal driver of sea ice, temperature, and circulation anomalies consistent with the Warm Arctic-Cold Eurasia pattern. Next, we quantify distinct transient responses to this Ural blocking, which explain the model-observation discrepancy in historical Eurasian temperature. Observed 1988-2012 Eurasian cooling occurs in response to a pronounced positive trend in Ural sea-level pressure, temporarily masking long-term midlatitude warming. This observed sea-level pressure trend lies at the outer edge of simulated variability in a fully coupled large ensemble, where smaller sea-level pressure trends have little impact on the ensemble mean temperature trend over Eurasia. Accounting for these differences bring observed and simulated trends into remarkable agreement. Finally, we quantify the influence of sea-ice loss on the magnitude of the observed Ural sea-level pressure trend, an effect that is absent in historical simulations. These results illustrate that sea-ice loss and tropospheric variability can both play a role in producing Eurasian cooling. Furthermore, by conducting a direct model-observation comparison, we reveal a key difference in the causal structures characterizing the Warm Arctic-Cold Eurasia Pattern, which will guide ongoing efforts to explain the lack of Eurasian cooling in climate change simulations.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139618196","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 : 2024-01-16DOI: 10.1088/2752-5295/ad1f41
Paul Ayodele Adigun, Emmanuel Owoicho Abah, Oluwaseun David Ajileye
Heatwaves in Africa are expected to increase in frequency, magnitude, and duration. This is significant because the health burden is only expected to worsen as heatwaves intensify. Inadequate knowledge of the climate's impact on health in developing nations such as Africa makes safeguarding the health of vulnerable groups at risk challenging. In this study we quantify possible role of human activity in heatwave intensification during the historical period, and project the future risk of heat-related mortality in Africa under two representative Concentration Pathways (RCP26) and (RCP60). Heatwaves are measured using the Excess Heat Factor (EHF); the daily minimum (Tn) and maximum (Tx) are used to compute the EHF index; by averaging the day's Tx and Tn. Two heat factors, significance (EHIsig) and acclimatization (EHIaccl) are combined in the EHF to quantify the total excess heat. Our results confirm that the recent intensification of heatwaves over Africa during the historical period is attributable atmospheric greenhouse gas forcing and changes in land use. The Return event highlights the potential future escalation of heatwave conditions brought on by climate change and socioeconomic variables. RCP26 indicates a substantial rise in heat-related mortality, with an increase from about 9,000 deaths per year in the historical period to approximately 23,000 deaths per year at the end of the 21st century. Similarly, the RCP60 showed an even more significant increase, with heat-related deaths increasing to about 43,000 annually. This study highlights the potentially growing risk of intensifying heatwaves in Africa under different emission scenarios. It projects a significant increase in heatwave magnitude, duration, frequency, and heat-related mortality. Africa's low adaptive capacity will amplify the impact, emphasizing the need for emissions reduction and effective adaptation measures.
{"title":"Intensifying human-driven heatwaves characteristics and heat related mortality over Africa","authors":"Paul Ayodele Adigun, Emmanuel Owoicho Abah, Oluwaseun David Ajileye","doi":"10.1088/2752-5295/ad1f41","DOIUrl":"https://doi.org/10.1088/2752-5295/ad1f41","url":null,"abstract":"\u0000 Heatwaves in Africa are expected to increase in frequency, magnitude, and duration. This is significant because the health burden is only expected to worsen as heatwaves intensify. Inadequate knowledge of the climate's impact on health in developing nations such as Africa makes safeguarding the health of vulnerable groups at risk challenging. In this study we quantify possible role of human activity in heatwave intensification during the historical period, and project the future risk of heat-related mortality in Africa under two representative Concentration Pathways (RCP26) and (RCP60). Heatwaves are measured using the Excess Heat Factor (EHF); the daily minimum (Tn) and maximum (Tx) are used to compute the EHF index; by averaging the day's Tx and Tn. Two heat factors, significance (EHIsig) and acclimatization (EHIaccl) are combined in the EHF to quantify the total excess heat. Our results confirm that the recent intensification of heatwaves over Africa during the historical period is attributable atmospheric greenhouse gas forcing and changes in land use. The Return event highlights the potential future escalation of heatwave conditions brought on by climate change and socioeconomic variables. RCP26 indicates a substantial rise in heat-related mortality, with an increase from about 9,000 deaths per year in the historical period to approximately 23,000 deaths per year at the end of the 21st century. Similarly, the RCP60 showed an even more significant increase, with heat-related deaths increasing to about 43,000 annually. This study highlights the potentially growing risk of intensifying heatwaves in Africa under different emission scenarios. It projects a significant increase in heatwave magnitude, duration, frequency, and heat-related mortality. Africa's low adaptive capacity will amplify the impact, emphasizing the need for emissions reduction and effective adaptation measures.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140505976","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 : 2024-01-08DOI: 10.1088/2752-5295/ad1c45
P. Pfleiderer, C. Schleussner, Jana Sillmann
Without stringent reductions in emission of greenhouse gases in the coming years, an exceedance of the 1.5C temperature limit is increasingly likely. This has given rise to so-called temperature overshoot scenarios, in which the global mean surface air temperature exceeds a certain limit (i.e. 1.5C above pre- industrial levels) before bringing temperatures back below that limit. Despite their prominence in the climate mitigation literature, the implications of an overshoot for local climate impacts is still understudied. Here we present a comprehensive analysis of implications of an overshoot for regional temperature and precipitation changes as well as climate extremes indices. Based on a multi-model comparison from the Coupled Model Intercomparison Project (CMIP6) we find that temperature changes are largely reversible in many regions, but also report significant land-ocean and latitudinal differences after an overshoot. For precipitation, the emerging picture is less clear. In many regions the drying or wetting trend is continued throughout the overshoot irrespective of a change in the global mean temperature trend with resulting consequences for extreme precipitation. Taken together, our results indicate that even under a reversal of global mean temperature increase, regional climate changes may only be partially reversed in the decades after peak warming. We thus provide further evidence that overshooting of a warming level implies considerable risks on the regional level.
{"title":"Limited reversal of regional climate signals in overshoot scenarios","authors":"P. Pfleiderer, C. Schleussner, Jana Sillmann","doi":"10.1088/2752-5295/ad1c45","DOIUrl":"https://doi.org/10.1088/2752-5295/ad1c45","url":null,"abstract":"\u0000 Without stringent reductions in emission of greenhouse gases in the coming years, an exceedance of the 1.5C temperature limit is increasingly likely. This has given rise to so-called temperature overshoot scenarios, in which the global mean surface air temperature exceeds a certain limit (i.e. 1.5C above pre- industrial levels) before bringing temperatures back below that limit. Despite their prominence in the climate mitigation literature, the implications of an overshoot for local climate impacts is still understudied. Here we present a comprehensive analysis of implications of an overshoot for regional temperature and precipitation changes as well as climate extremes indices. Based on a multi-model comparison from the Coupled Model Intercomparison Project (CMIP6) we find that temperature changes are largely reversible in many regions, but also report significant land-ocean and latitudinal differences after an overshoot. For precipitation, the emerging picture is less clear. In many regions the drying or wetting trend is continued throughout the overshoot irrespective of a change in the global mean temperature trend with resulting consequences for extreme precipitation. Taken together, our results indicate that even under a reversal of global mean temperature increase, regional climate changes may only be partially reversed in the decades after peak warming. We thus provide further evidence that overshooting of a warming level implies considerable risks on the regional level.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"46 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139446154","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：