Pub Date : 2024-07-09DOI: 10.1175/bams-d-23-0098.1
Solomon Bililign, Steven S. Brown, Daniel M. Westervelt, Rajesh Kumar, Wenfu Tang, Frank Flocke, William Vizuete, Kassahun Ture, Francis D. Pope, Belay Demoz, Akua Asa-Awuku, Pieternel F. Levelt, Egide Kalisa, Garima Raheja, Alex Ndyabakira, Michael J. Gatari
Abstract Air pollution in Africa is a significant public health issue responsible for 1.1 million premature deaths annually. Sub-Saharan Africa has the highest rate of population growth and urbanization of any region in the world, with substantial potential for future emissions growth and worsening air quality. Accurate and extensive observations of meteorology and atmospheric composition have underpinned successful air pollution mitigation strategies in the Global North, yet Africa in general, and East Africa in particular, remain among the most sparsely observed regions in the world. This paper is based on the discussion of these issues during two international workshops, one held virtually in the U.S. in July 2021 and one in Kigali, Rwanda in January 2023. The workshops were designed to develop a measurement, capacity building and collaboration strategy to improve air quality relevant measurements, modeling, and data availability in East Africa. This paper frames the relevant scientific needs and describes the requirements for training and infrastructure development for an integrated observing and modeling strategy that includes partnerships between East African scientists and organizations and their counterparts in the developed world.
{"title":"East African Megacity Air Quality: Rationale and Framework for a Measurement and Modeling Program","authors":"Solomon Bililign, Steven S. Brown, Daniel M. Westervelt, Rajesh Kumar, Wenfu Tang, Frank Flocke, William Vizuete, Kassahun Ture, Francis D. Pope, Belay Demoz, Akua Asa-Awuku, Pieternel F. Levelt, Egide Kalisa, Garima Raheja, Alex Ndyabakira, Michael J. Gatari","doi":"10.1175/bams-d-23-0098.1","DOIUrl":"https://doi.org/10.1175/bams-d-23-0098.1","url":null,"abstract":"Abstract Air pollution in Africa is a significant public health issue responsible for 1.1 million premature deaths annually. Sub-Saharan Africa has the highest rate of population growth and urbanization of any region in the world, with substantial potential for future emissions growth and worsening air quality. Accurate and extensive observations of meteorology and atmospheric composition have underpinned successful air pollution mitigation strategies in the Global North, yet Africa in general, and East Africa in particular, remain among the most sparsely observed regions in the world. This paper is based on the discussion of these issues during two international workshops, one held virtually in the U.S. in July 2021 and one in Kigali, Rwanda in January 2023. The workshops were designed to develop a measurement, capacity building and collaboration strategy to improve air quality relevant measurements, modeling, and data availability in East Africa. This paper frames the relevant scientific needs and describes the requirements for training and infrastructure development for an integrated observing and modeling strategy that includes partnerships between East African scientists and organizations and their counterparts in the developed world.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"27 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1175/bams-d-24-0157.1
Laura Brewington, Chelsey Bryson, Abby Frazier, Victoria W. Keener, John J. Marra, Erbai X. Matsutaro, Kikuko Mochimaru, Paula Moehlenkamp
"A Climate Services Dialog to Build Sector-Based Climate Early Warning Systems in the Republic of Palau" published on 09 Jul 2024 by American Meteorological Society.
{"title":"A Climate Services Dialog to Build Sector-Based Climate Early Warning Systems in the Republic of Palau","authors":"Laura Brewington, Chelsey Bryson, Abby Frazier, Victoria W. Keener, John J. Marra, Erbai X. Matsutaro, Kikuko Mochimaru, Paula Moehlenkamp","doi":"10.1175/bams-d-24-0157.1","DOIUrl":"https://doi.org/10.1175/bams-d-24-0157.1","url":null,"abstract":"\"A Climate Services Dialog to Build Sector-Based Climate Early Warning Systems in the Republic of Palau\" published on 09 Jul 2024 by American Meteorological Society.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"46 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-08DOI: 10.1175/bams-d-23-0179.1
Jianping Duan, Haoxin Zhang, Dongnan Jian, Cunde Xiao, Fengqi Hao, Hongzhou Zhu, Fraser C. Lott, Peter A. Stott
Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations suggest that the extremely warm August over the Tibetan Plateau in 2022 could not occur without human influences, which corresponds to a new normal during 2070–2100.
{"title":"Influences of Anthropogenic Forcing on the Exceptionally Warm August 2022 over the Eastern Tibetan Plateau","authors":"Jianping Duan, Haoxin Zhang, Dongnan Jian, Cunde Xiao, Fengqi Hao, Hongzhou Zhu, Fraser C. Lott, Peter A. Stott","doi":"10.1175/bams-d-23-0179.1","DOIUrl":"https://doi.org/10.1175/bams-d-23-0179.1","url":null,"abstract":"Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations suggest that the extremely warm August over the Tibetan Plateau in 2022 could not occur without human influences, which corresponds to a new normal during 2070–2100.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"55 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
"Attribution of the Extreme 2022 Summer Drought along the Yangtze River Valley in China Based on Detection and Attribution System of Chinese Academy of Sciences" published on 03 Jul 2024 by American Meteorological Society.
{"title":"Attribution of the Extreme 2022 Summer Drought along the Yangtze River Valley in China Based on Detection and Attribution System of Chinese Academy of Sciences","authors":"Lixia Zhang, Tianjun Zhou, Xing Zhang, Wenxia Zhang, Lijuan Li, Laurent Li","doi":"10.1175/bams-d-23-0258.1","DOIUrl":"https://doi.org/10.1175/bams-d-23-0258.1","url":null,"abstract":"\"Attribution of the Extreme 2022 Summer Drought along the Yangtze River Valley in China Based on Detection and Attribution System of Chinese Academy of Sciences\" published on 03 Jul 2024 by American Meteorological Society.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"26 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1175/bams-d-24-0071.1
Craig Earl-Spurr, Sébastien Langlade, Daniel Krahenbuhl, Sim D. Aberson, Manola Brunet, Johnny Chan, Chris Fogarty, Christopher W. Landsea, Blair Trewin, Christopher Velden, Robert C. Balling, Randall S. Cerveny
Abstract A World Meteorological Organization team has evaluated 2023's Tropical Cyclone Freddy's duration of 36.0 days (with 10-min average wind-speeds of 30 kt or higher) as the world record for longest tropical cyclone duration.
{"title":"New WMO Certified Tropical Cyclone Duration Extreme: TC Freddy (04 February to 14 March 2023) Lasting for 36.0 days","authors":"Craig Earl-Spurr, Sébastien Langlade, Daniel Krahenbuhl, Sim D. Aberson, Manola Brunet, Johnny Chan, Chris Fogarty, Christopher W. Landsea, Blair Trewin, Christopher Velden, Robert C. Balling, Randall S. Cerveny","doi":"10.1175/bams-d-24-0071.1","DOIUrl":"https://doi.org/10.1175/bams-d-24-0071.1","url":null,"abstract":"Abstract A World Meteorological Organization team has evaluated 2023's Tropical Cyclone Freddy's duration of 36.0 days (with 10-min average wind-speeds of 30 kt or higher) as the world record for longest tropical cyclone duration.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"162 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1175/bams-d-23-0252.1
Michelle L. L’Heureux, Daniel S. Harnos, Emily Becker, Brian Brettschneider, Mingyue Chen, Nathaniel C. Johnson, Arun Kumar, Michael K. Tippett
Abstract Did the strong 2023–24 El Niño live up to the hype? While climate prediction is inherently probabilistic, many users compare El Niño events against a deterministic map of expected impacts (e.g., wetter or drier regions). Here, using this event as a guide, we show that no El Niño perfectly matches the ideal image and that observed anomalies will only partially match what was anticipated. In fact, the degree to which the climate anomalies match the expected ENSO impacts tends to scale with the strength of the event. The 2023–24 event generally matched well with ENSO expectations around the United States. However, this will not always be the case, as the analysis shows larger deviations from the historical ENSO pattern of impacts are commonplace, with some climate variables more prone to inconsistencies (e.g., temperature) than others (e.g., precipitation). Users should incorporate this inherent uncertainty in their risk and decision-making analysis.
{"title":"How Well Do Seasonal Climate Anomalies Match Expected El Niño-Southern Oscillation (ENSO) Impacts?","authors":"Michelle L. L’Heureux, Daniel S. Harnos, Emily Becker, Brian Brettschneider, Mingyue Chen, Nathaniel C. Johnson, Arun Kumar, Michael K. Tippett","doi":"10.1175/bams-d-23-0252.1","DOIUrl":"https://doi.org/10.1175/bams-d-23-0252.1","url":null,"abstract":"Abstract Did the strong 2023–24 El Niño live up to the hype? While climate prediction is inherently probabilistic, many users compare El Niño events against a deterministic map of expected impacts (e.g., wetter or drier regions). Here, using this event as a guide, we show that no El Niño perfectly matches the ideal image and that observed anomalies will only partially match what was anticipated. In fact, the degree to which the climate anomalies match the expected ENSO impacts tends to scale with the strength of the event. The 2023–24 event generally matched well with ENSO expectations around the United States. However, this will not always be the case, as the analysis shows larger deviations from the historical ENSO pattern of impacts are commonplace, with some climate variables more prone to inconsistencies (e.g., temperature) than others (e.g., precipitation). Users should incorporate this inherent uncertainty in their risk and decision-making analysis.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"80 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1175/bams-d-24-0145.1
Valerio Lembo, Simona Bordoni, Emanuele Bevacqua, Daniela I. V. Domeisen, Christian L. E. Franzke, Vera M. Galfi, Chaim Garfinkel, Christian I. Grams, Assaf Hochman, Roshan Jha, Kai Kornhuber, Frank Kwasniok, Valerio Lucarini, Gabriele Messori, Duncan Pappert, Iago Perez-Fernandez, Jacopo Riboldi, Emmanuele Russo, Tiffany A. Shaw, Iana Strigunova, Felix Strnad, Pascal Yiou, Nedjeljka Zagar
Abstract What: A workshop on Rossby waves, heatwaves and compound extreme events was co-organized by the Institute for Atmospheric Sciences and Climate (ISAC) of the National Research Council of Italy (CNR) and the University of Trento, Italy. The workshop gathered experts from different fields, such as extreme events analysis, atmospheric dynamics, climate modeling, Numerical Weather Prediction, with the aim to discuss state-of-the-art research, open challenges, and stimulate networking across different communities. When: 28-30th November 2023. Where: CNR Research Area, Bologna, Italy.
{"title":"Dynamics, statistics and predictability of Rossby waves, heatwaves and spatially compounded extreme events","authors":"Valerio Lembo, Simona Bordoni, Emanuele Bevacqua, Daniela I. V. Domeisen, Christian L. E. Franzke, Vera M. Galfi, Chaim Garfinkel, Christian I. Grams, Assaf Hochman, Roshan Jha, Kai Kornhuber, Frank Kwasniok, Valerio Lucarini, Gabriele Messori, Duncan Pappert, Iago Perez-Fernandez, Jacopo Riboldi, Emmanuele Russo, Tiffany A. Shaw, Iana Strigunova, Felix Strnad, Pascal Yiou, Nedjeljka Zagar","doi":"10.1175/bams-d-24-0145.1","DOIUrl":"https://doi.org/10.1175/bams-d-24-0145.1","url":null,"abstract":"Abstract What: A workshop on Rossby waves, heatwaves and compound extreme events was co-organized by the Institute for Atmospheric Sciences and Climate (ISAC) of the National Research Council of Italy (CNR) and the University of Trento, Italy. The workshop gathered experts from different fields, such as extreme events analysis, atmospheric dynamics, climate modeling, Numerical Weather Prediction, with the aim to discuss state-of-the-art research, open challenges, and stimulate networking across different communities. When: 28-30th November 2023. Where: CNR Research Area, Bologna, Italy.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"46 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-19DOI: 10.1175/bams-d-23-0227.1
Ligia Bernardet, Lisa Bengtsson, Patrick A. Reinecke, Fanglin Yang, Man Zhang, Kyle Hall, James Doyle, Matus Martini, Grant Firl, Lulin Xue
Abstract The Common Community Physics Package (CCPP) is a state-of-the-art infrastructure designed to facilitate community-wide development of atmospheric physics parameterizations, support their interoperability among different modeling centers, and enable the transition of research to operations in NWP and climate modeling. The CCPP consists of two elements: the Physics (a repository of parameterizations) and the Framework (an infrastructure for interfacing the parameterizations with host models). The CCPP is a community resource: its latest release has 23 primary parameterizations, which can be organized into six supported suites. It is distributed with a single-column model to facilitate physics development and experimentation. The Developmental Testbed Center provides support to users and developers. A key aspect of the CCPP is its interoperability, that is, its ability to be used by multiple host models. This enables synergistic collaboration among groups dispersed over various institutions and working on various models. In this article we provide an overview of the CCPP and how it is being used in two leading modeling systems. The CCPP is part of the Unified Forecast System (UFS), is included in the NOAA operational Hurricane Analysis and Forecast System (HAFS) version one, and is slated for use in all upcoming NOAA global and limited-area UFS applications for operations. Similarly, the CCPP has been integrated into the Navy Environmental Prediction System Using a Nonhydrostatic Engine (NEPTUNE) model and is undergoing testing for upcoming transition to operations. These experiences make physics interoperability a reality and open the doors for much broader collaborative efforts on ESM development.
{"title":"Common Community Physics Package: Fostering Collaborative Development in Physical Parameterizations and Suites","authors":"Ligia Bernardet, Lisa Bengtsson, Patrick A. Reinecke, Fanglin Yang, Man Zhang, Kyle Hall, James Doyle, Matus Martini, Grant Firl, Lulin Xue","doi":"10.1175/bams-d-23-0227.1","DOIUrl":"https://doi.org/10.1175/bams-d-23-0227.1","url":null,"abstract":"Abstract The Common Community Physics Package (CCPP) is a state-of-the-art infrastructure designed to facilitate community-wide development of atmospheric physics parameterizations, support their interoperability among different modeling centers, and enable the transition of research to operations in NWP and climate modeling. The CCPP consists of two elements: the Physics (a repository of parameterizations) and the Framework (an infrastructure for interfacing the parameterizations with host models). The CCPP is a community resource: its latest release has 23 primary parameterizations, which can be organized into six supported suites. It is distributed with a single-column model to facilitate physics development and experimentation. The Developmental Testbed Center provides support to users and developers. A key aspect of the CCPP is its interoperability, that is, its ability to be used by multiple host models. This enables synergistic collaboration among groups dispersed over various institutions and working on various models. In this article we provide an overview of the CCPP and how it is being used in two leading modeling systems. The CCPP is part of the Unified Forecast System (UFS), is included in the NOAA operational Hurricane Analysis and Forecast System (HAFS) version one, and is slated for use in all upcoming NOAA global and limited-area UFS applications for operations. Similarly, the CCPP has been integrated into the Navy Environmental Prediction System Using a Nonhydrostatic Engine (NEPTUNE) model and is undergoing testing for upcoming transition to operations. These experiences make physics interoperability a reality and open the doors for much broader collaborative efforts on ESM development.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"343 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1175/bams-d-23-0214.1
Christopher P. McKay, Mateo N. Cintron
Abstract The thermal equator (also known as the heat equator) is the circumplanetary set of points that represent the highest mean annual temperature at each longitude. Recent high precision global datasets for Earth and Mars provide a basis for a detailed calculation of the thermal equator on these worlds. On Earth, the temperature values that comprise the thermal equator range from 25.85° to 34.75°C, with a mean of 27.75° ± 1.3°C, and extends in latitude as high as 20°N in Mexico and 29.3°N in the Indian subcontinent. The maximum southern extent is 20°S in Australia. On Mars, lacking oceans, the thermal equator takes a simpler track and is roughly parallel to the equator, and displaced 5°–10°S. However, there is a region of longitude on Mars where the thermal equator becomes bimodal with a northern branch centered at 10°N and a southern branch centered at 20°S.
{"title":"The Thermal Equator on Earth and Mars","authors":"Christopher P. McKay, Mateo N. Cintron","doi":"10.1175/bams-d-23-0214.1","DOIUrl":"https://doi.org/10.1175/bams-d-23-0214.1","url":null,"abstract":"Abstract The thermal equator (also known as the heat equator) is the circumplanetary set of points that represent the highest mean annual temperature at each longitude. Recent high precision global datasets for Earth and Mars provide a basis for a detailed calculation of the thermal equator on these worlds. On Earth, the temperature values that comprise the thermal equator range from 25.85° to 34.75°C, with a mean of 27.75° ± 1.3°C, and extends in latitude as high as 20°N in Mexico and 29.3°N in the Indian subcontinent. The maximum southern extent is 20°S in Australia. On Mars, lacking oceans, the thermal equator takes a simpler track and is roughly parallel to the equator, and displaced 5°–10°S. However, there is a region of longitude on Mars where the thermal equator becomes bimodal with a northern branch centered at 10°N and a southern branch centered at 20°S.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"42 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1175/bams-d-22-0244.1
Alexander P. Trishchenko, Calin Ungureanu
Abstract A novel satellite image processing technique was utilized to produce an annual time series of the Minimum Snow/Ice (MSI) extent over the entire Greenland landmass for the period 2000-2022. The information was derived from the Moderate Resolution Imaging Spectroradiometer 10-day clear-sky composites over the April-September period. The data products were generated from 250-m swath imagery. The annual aggregates were downscaled to a 150-m grid for consistency with data on margins of Greenland available from the Geological Survey of Denmark and Greenland (GEUS), and the Greenland Ice Mapping Project. Inter-annual variations in the MSI extent were derived and analyzed for each of the seven major glacier basins in Greenland split into the main ice sheet, represented by a static map, and the peripheral areas from which all variations originated. Four of the seven regions demonstrated statistically significant negative trends in the MSI extent. The entire Greenland area also showed a declining snow/ice extent although this was not statistically significant. The region-wide and peripheral snow/ice extent varied from a minimum of 1.807 × 106 km2 (1.449 × 105 km2 for peripheral areas) observed in 2012 to a maximum of 1.860 × 106 km2 (1.977 × 105 km2) observed in 2006 with an average value of 1.829 × 106 km2 (1.664 × 105 km2). The derived MSI variations showed statistically significant correlation with the near-surface 2- m air temperature from the ERA5 Land reanalysis and Greenland ice mass balance from GEUS for all catchments, with correlation coefficients for the entire area equal to −0.74 and 0.53, respectively. The mapping of many peripheral glaciers and ice shelves included in the glaciology databases and utilized for the IPCC reporting is not always consistent with our results and requires improvement, especially in the coastal areas.
{"title":"Annual Minimum Snow/Ice Extent Variations over Greenland since 2000: Ice Sheet, Peripheral Areas, and Relation to Ice Mass Balance","authors":"Alexander P. Trishchenko, Calin Ungureanu","doi":"10.1175/bams-d-22-0244.1","DOIUrl":"https://doi.org/10.1175/bams-d-22-0244.1","url":null,"abstract":"Abstract A novel satellite image processing technique was utilized to produce an annual time series of the Minimum Snow/Ice (MSI) extent over the entire Greenland landmass for the period 2000-2022. The information was derived from the Moderate Resolution Imaging Spectroradiometer 10-day clear-sky composites over the April-September period. The data products were generated from 250-m swath imagery. The annual aggregates were downscaled to a 150-m grid for consistency with data on margins of Greenland available from the Geological Survey of Denmark and Greenland (GEUS), and the Greenland Ice Mapping Project. Inter-annual variations in the MSI extent were derived and analyzed for each of the seven major glacier basins in Greenland split into the main ice sheet, represented by a static map, and the peripheral areas from which all variations originated. Four of the seven regions demonstrated statistically significant negative trends in the MSI extent. The entire Greenland area also showed a declining snow/ice extent although this was not statistically significant. The region-wide and peripheral snow/ice extent varied from a minimum of 1.807 × 106 km2 (1.449 × 105 km2 for peripheral areas) observed in 2012 to a maximum of 1.860 × 106 km2 (1.977 × 105 km2) observed in 2006 with an average value of 1.829 × 106 km2 (1.664 × 105 km2). The derived MSI variations showed statistically significant correlation with the near-surface 2- m air temperature from the ERA5 Land reanalysis and Greenland ice mass balance from GEUS for all catchments, with correlation coefficients for the entire area equal to −0.74 and 0.53, respectively. The mapping of many peripheral glaciers and ice shelves included in the glaciology databases and utilized for the IPCC reporting is not always consistent with our results and requires improvement, especially in the coastal areas.","PeriodicalId":9464,"journal":{"name":"Bulletin of the American Meteorological Society","volume":"75 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141259457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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