2026
|
Emma A. Blackford; Madeline R. Magee; Paul Block: Predicting Oxythermal Stress Conditions for Coldwater Fish in a Northern Wisconsin Lake. In: Environmental Modeling & Assessment, 2026. @article{Blackford2026,
title = {Predicting Oxythermal Stress Conditions for Coldwater Fish in a Northern Wisconsin Lake},
author = {Emma A. Blackford and Madeline R. Magee and Paul Block},
url = {https://link-springer-com.ezproxy.library.wisc.edu/article/10.1007/s10666-026-10115-8},
doi = {10.1007/s10666-026-10115-8},
year = {2026},
date = {2026-04-11},
urldate = {2026-04-11},
journal = {Environmental Modeling & Assessment},
abstract = {This study combines long-term lake water quality data with statistical modeling to predict coldwater fish habitat conditions from a season-ahead lead. We select a case-study lake in Northern Wisconsin with forty-two years of biological, chemical, and physical data to calculate three summertime oxythermal stress metrics for cisco (Coregonus artedi) conditioned on bi-weekly temperature and dissolved oxygen profiles. Significant intra-and-interannual variability are identified in seasonal oxythermal habitat conditions. Springtime global and local climate variables generally indicate a stronger relationship than within lake variables when correlated with summertime oxythermal habitat, suggesting a potentially robust link between climate patterns and lake water quality in Wisconsin. Leveraging both climate and within lake springtime observations, a principal component regression approach was applied to probabilistically predict summertime oxythermal stress metrics. Models showed skillful prediction of multiple oxythermal habitat metrics across summer months of highest stress, with the best fitting model achieving R2 = 0.42 and RPSS = 0.55. We conclude that characterization and tailored season-ahead prediction of oxythermal habitat conditions may provide prospects for proactive lake management in support of coldwater fish habitat.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study combines long-term lake water quality data with statistical modeling to predict coldwater fish habitat conditions from a season-ahead lead. We select a case-study lake in Northern Wisconsin with forty-two years of biological, chemical, and physical data to calculate three summertime oxythermal stress metrics for cisco (Coregonus artedi) conditioned on bi-weekly temperature and dissolved oxygen profiles. Significant intra-and-interannual variability are identified in seasonal oxythermal habitat conditions. Springtime global and local climate variables generally indicate a stronger relationship than within lake variables when correlated with summertime oxythermal habitat, suggesting a potentially robust link between climate patterns and lake water quality in Wisconsin. Leveraging both climate and within lake springtime observations, a principal component regression approach was applied to probabilistically predict summertime oxythermal stress metrics. Models showed skillful prediction of multiple oxythermal habitat metrics across summer months of highest stress, with the best fitting model achieving R2 = 0.42 and RPSS = 0.55. We conclude that characterization and tailored season-ahead prediction of oxythermal habitat conditions may provide prospects for proactive lake management in support of coldwater fish habitat. |
Richard B. Rood; Joshua Winslow; Rachel Kelly; Michael Notaro; Laura Briley; Eva Gnegy; Karlie Wells; Haochen Ye; Sarah Hutchinson: Objective determination of the presence of lake-effect zones in climate models. In: Journal of Great Lakes Research, vol. 52, iss. 2, no. 102750, 2026, ISSN: 0380-1330. @article{Rood2026b,
title = {Objective determination of the presence of lake-effect zones in climate models},
author = {Richard B. Rood and Joshua Winslow and Rachel Kelly and Michael Notaro and Laura Briley and Eva Gnegy and Karlie Wells and Haochen Ye and Sarah Hutchinson},
url = {https://www.sciencedirect.com/science/article/pii/S0380133026000109},
doi = {10.1016/j.jglr.2026.102750},
issn = {0380-1330},
year = {2026},
date = {2026-03-22},
journal = {Journal of Great Lakes Research},
volume = {52},
number = {102750},
issue = {2},
abstract = {In this study, we use K-means clustering to develop a methodology to determine the presence of lake-effect precipitation zones in model simulations of the Laurentian Great Lakes Basin. Our goal is to have a quick evaluation method that can identify if the qualitative representation of precipitation is improving as modeling technology advances. We use two regional climate model ensembles (North American Coordinated Regional Downscaling Experiment and the International Centre for Theoretical Physics’ Regional Climate Model 4 as coupled to a 1D lake model with some modified at the University of Wisconsin-Madison). University of Delaware (UDel) observational monthly winter precipitation data from the basin are compared to the model ensemble simulations over the climatology period of 1980–1999 using an object-based K-means cluster analysis and performance tools from the METplus evaluation package. Lake-effect zones are present by visual inspection in the Udel observations, and a choice of four clusters represents lake-effect zones in the observations across the basin. For the model simulations, it is not possible at the basin scale to identify the lake-effect zones visually. The application of the K-means clusters at the basin scales extracts geographical features in the correct locations; however, the features are biased compared with observations. The analysis is repeated at the sub-basin scale, and the lake-effect zones are revealed well enough to provide insights into model performance. The high sensitivity of the K-means cluster analysis to the domain size, regional, basin-scale, and sub-basin scale, is greater than expected. However, it reveals important aspects of the performance of present-generation simulations. The paper discusses the K-means cluster analysis and its performance metrics provided by METplus, systematic simulation bias at the basin and regional scale, and representation of lake-effect zones by model ensemble members at the sub-basin scale. We conclude that the clustering techniques could quicken the identification of lake-effect zones; however, significant reduction of simulation bias is needed to improve the representation of lake-effect zones prior to detailed scientific investigation and application to regional climate adaptation applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this study, we use K-means clustering to develop a methodology to determine the presence of lake-effect precipitation zones in model simulations of the Laurentian Great Lakes Basin. Our goal is to have a quick evaluation method that can identify if the qualitative representation of precipitation is improving as modeling technology advances. We use two regional climate model ensembles (North American Coordinated Regional Downscaling Experiment and the International Centre for Theoretical Physics’ Regional Climate Model 4 as coupled to a 1D lake model with some modified at the University of Wisconsin-Madison). University of Delaware (UDel) observational monthly winter precipitation data from the basin are compared to the model ensemble simulations over the climatology period of 1980–1999 using an object-based K-means cluster analysis and performance tools from the METplus evaluation package. Lake-effect zones are present by visual inspection in the Udel observations, and a choice of four clusters represents lake-effect zones in the observations across the basin. For the model simulations, it is not possible at the basin scale to identify the lake-effect zones visually. The application of the K-means clusters at the basin scales extracts geographical features in the correct locations; however, the features are biased compared with observations. The analysis is repeated at the sub-basin scale, and the lake-effect zones are revealed well enough to provide insights into model performance. The high sensitivity of the K-means cluster analysis to the domain size, regional, basin-scale, and sub-basin scale, is greater than expected. However, it reveals important aspects of the performance of present-generation simulations. The paper discusses the K-means cluster analysis and its performance metrics provided by METplus, systematic simulation bias at the basin and regional scale, and representation of lake-effect zones by model ensemble members at the sub-basin scale. We conclude that the clustering techniques could quicken the identification of lake-effect zones; however, significant reduction of simulation bias is needed to improve the representation of lake-effect zones prior to detailed scientific investigation and application to regional climate adaptation applications. |
2025
|
Benjamin J. Smith; Till J. W. Wagner; Hilary A. Dugan; Grace M. Wilkinson; Lucas K. Zoet; Nimish Pujara; Jennifer A. Franck: How Ice Composition Controls Radiatively Driven Convection under Lake Ice. In: Geophysical Research Letters, vol. 52, iss. 19, 2025. @article{Smith2025,
title = {How Ice Composition Controls Radiatively Driven Convection under Lake Ice},
author = {Benjamin J. Smith and Till J. W. Wagner and Hilary A. Dugan and Grace M. Wilkinson and Lucas K. Zoet and Nimish Pujara and Jennifer A. Franck},
doi = {10.1029/2025GL117454},
year = {2025},
date = {2025-10-07},
urldate = {2025-10-07},
journal = {Geophysical Research Letters},
volume = {52},
issue = {19},
abstract = {Light transmission through the ice cover of lakes can heat near-surface waters and result in radiatively driven convection (RDC), a prominent source of under-ice water motion in spring. We investigate the impact of ice composition on the under-ice water column using fully resolved two-dimensional numerical simulations of the water that account for light attenuation by both ice and water. Increasing the amount of opaque white ice (relative to that of transparent black ice) decreases thermal forcing of the water and delays Rayleigh-Taylor instabilities and convective mixing. Other key environmental factors include the attenuation length scale of light and initial stratification of the water column. We determine whether and when (a) the water column first becomes unstable and (b) RDC is initiated. Notably, RDC is delayed by a period of growth of a gravitationally unstable layer. These findings have implications for the cycling of nutrients and gases, and wider ecosystem dynamics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Light transmission through the ice cover of lakes can heat near-surface waters and result in radiatively driven convection (RDC), a prominent source of under-ice water motion in spring. We investigate the impact of ice composition on the under-ice water column using fully resolved two-dimensional numerical simulations of the water that account for light attenuation by both ice and water. Increasing the amount of opaque white ice (relative to that of transparent black ice) decreases thermal forcing of the water and delays Rayleigh-Taylor instabilities and convective mixing. Other key environmental factors include the attenuation length scale of light and initial stratification of the water column. We determine whether and when (a) the water column first becomes unstable and (b) RDC is initiated. Notably, RDC is delayed by a period of growth of a gravitationally unstable layer. These findings have implications for the cycling of nutrients and gases, and wider ecosystem dynamics. |
John DelPizzo; William J. Baule; Lara Tobias-Tarsh; Michael Notaro; Richard B. Rood: Climatology and Recent Changes in the Occurrence of Freezing Rain throughout the Laurentian Great Lakes Region. In: Journal of Applied Meteorology and Climatology, vol. 64, iss. 10, pp. 1395-1409, 2025. @article{DelPizzo2025,
title = {Climatology and Recent Changes in the Occurrence of Freezing Rain throughout the Laurentian Great Lakes Region},
author = {John DelPizzo and William J. Baule and Lara Tobias-Tarsh and Michael Notaro and Richard B. Rood},
url = {https://journals.ametsoc.org/view/journals/apme/64/10/JAMC-D-24-0204.1.xml},
doi = {10.1175/JAMC-D-24-0204.1},
year = {2025},
date = {2025-10-01},
urldate = {2025-10-01},
journal = {Journal of Applied Meteorology and Climatology},
volume = {64},
issue = {10},
pages = {1395-1409},
abstract = {Freezing rain (FZRA) events have expensive and sometimes deadly effects on major population centers in the Great Lakes region (GLR) of North America. This paper investigates changes in the spatiotemporal nature of FZRA. The work extends the spatial and temporal record of a previously published, but now dated, Great Lakes FZRA climatology (1976–90) to analyze trends and their underlying reasons by utilizing observations made through 2020. To isolate regional trends and determine changes in the synoptic-scale processes driving them, a k-means objective clustering algorithm is applied to pressure anomaly maps and records of FZRA observations to create three archetypal synoptic weather patterns associated with FZRA. A northward shift in FZRA incidence is found across the GLR on an annual basis, with an increase in FZRA occurrence in January and April and a decrease during March. Regionally, the largest trends were a decrease since 1979 throughout Pennsylvania, upstate New York, and the St. Lawrence Lowlands of Canada and an increase in the southern reach of Manitoba, Ontario, and Quebec and the low-lying Atlantic Coastal Plain of New York. The geographic location of the low three synoptic patterns associated with FZRA events remained similar between 1979 and 1999 and 2000–20, though changes to their intensity allowed for enhanced warm air advection. We suggest that this, combined with rising temperatures in a nonstationary climate and a subtle northward shift in some cyclones, was responsible for an observed northward shift in FZRA.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Freezing rain (FZRA) events have expensive and sometimes deadly effects on major population centers in the Great Lakes region (GLR) of North America. This paper investigates changes in the spatiotemporal nature of FZRA. The work extends the spatial and temporal record of a previously published, but now dated, Great Lakes FZRA climatology (1976–90) to analyze trends and their underlying reasons by utilizing observations made through 2020. To isolate regional trends and determine changes in the synoptic-scale processes driving them, a k-means objective clustering algorithm is applied to pressure anomaly maps and records of FZRA observations to create three archetypal synoptic weather patterns associated with FZRA. A northward shift in FZRA incidence is found across the GLR on an annual basis, with an increase in FZRA occurrence in January and April and a decrease during March. Regionally, the largest trends were a decrease since 1979 throughout Pennsylvania, upstate New York, and the St. Lawrence Lowlands of Canada and an increase in the southern reach of Manitoba, Ontario, and Quebec and the low-lying Atlantic Coastal Plain of New York. The geographic location of the low three synoptic patterns associated with FZRA events remained similar between 1979 and 1999 and 2000–20, though changes to their intensity allowed for enhanced warm air advection. We suggest that this, combined with rising temperatures in a nonstationary climate and a subtle northward shift in some cyclones, was responsible for an observed northward shift in FZRA. |
G. Aaron Alexander; Daniel B. Wright; Carolyn B. Voter; Steven P. Loheide II: City-scale evaluation of urban ecohydrologic processes on surface energy balances, heat, and humidity. In: Urban Climate, vol. 63, no. 102596, 2025, ISSN: 2212-0955. @article{Alexander2025,
title = {City-scale evaluation of urban ecohydrologic processes on surface energy balances, heat, and humidity},
author = {G. Aaron Alexander and Daniel B. Wright and Carolyn B. Voter and Steven P. Loheide II},
url = {https://www-sciencedirect-com.ezproxy.library.wisc.edu/science/article/pii/S2212095525003128},
doi = {10.1016/j.uclim.2025.102596},
issn = {2212-0955},
year = {2025},
date = {2025-09-13},
urldate = {2025-09-13},
journal = {Urban Climate},
volume = {63},
number = {102596},
abstract = {Urban regions substantially modify both surface energy and hydrologic cycles. Despite the linkage between urban hydrology and energy cycles, modern coupled land-atmosphere models do not represent common urban hydrologic features like runoff routing from impervious to pervious surfaces or tree canopy that shades pavements. We compare three urban surface models in the Weather and Research Forecasting model across multiple hydrometeorological events in Milwaukee, Wisconsin: a widely used slab urban model (Noah-MP Bulk Parameterization; Typical), multiple land covers per grid cell (Noah-MP Mosaic; Mosaic), and a model which adds sub-grid water transfers between land cover types (Noah-MP HUE; HUE). Inclusion of urban hydrology and vegetation (HUE) increases albedo and emissivity, reducing available energy in our study region. Ambient soil moisture conditions cause divergent responses in HUE simulations: warming when soil water is limited and cooling when ample soil water is available for evapotranspiration. Comparison against observed 2m air temperature and specific humidity show increased skill in the HUE model simulations, especially compared to the Typical model. Noah-MP HUE presents a stride in understanding how urban hydrology influences city-scale meteorology and a pathway to examine urban hydrologic greening initiatives more wholistically in regional atmospheric models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Urban regions substantially modify both surface energy and hydrologic cycles. Despite the linkage between urban hydrology and energy cycles, modern coupled land-atmosphere models do not represent common urban hydrologic features like runoff routing from impervious to pervious surfaces or tree canopy that shades pavements. We compare three urban surface models in the Weather and Research Forecasting model across multiple hydrometeorological events in Milwaukee, Wisconsin: a widely used slab urban model (Noah-MP Bulk Parameterization; Typical), multiple land covers per grid cell (Noah-MP Mosaic; Mosaic), and a model which adds sub-grid water transfers between land cover types (Noah-MP HUE; HUE). Inclusion of urban hydrology and vegetation (HUE) increases albedo and emissivity, reducing available energy in our study region. Ambient soil moisture conditions cause divergent responses in HUE simulations: warming when soil water is limited and cooling when ample soil water is available for evapotranspiration. Comparison against observed 2m air temperature and specific humidity show increased skill in the HUE model simulations, especially compared to the Typical model. Noah-MP HUE presents a stride in understanding how urban hydrology influences city-scale meteorology and a pathway to examine urban hydrologic greening initiatives more wholistically in regional atmospheric models. |
Yu-Shen Lin; Shih-Yu Lee; Feng He; Huang-Hsiung Hsu; Yue-Gau Chen: Potential Processes of Two-Phase AMOC Recovery After the Younger Dryas in the TraCE-21K-II Simulation. In: Geophysical Research Letters, vol. 52, iss. 17, 2025. @article{Lin2025b,
title = {Potential Processes of Two-Phase AMOC Recovery After the Younger Dryas in the TraCE-21K-II Simulation},
author = {Yu-Shen Lin and Shih-Yu Lee and Feng He and Huang-Hsiung Hsu and Yue-Gau Chen},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025GL117250},
doi = {10.1029/2025GL117250},
year = {2025},
date = {2025-08-30},
urldate = {2025-08-30},
journal = {Geophysical Research Letters},
volume = {52},
issue = {17},
abstract = {A two-phase recovery of the Atlantic Meridional Overturning Circulation (AMOC) is revealed following the abrupt cessation of freshwater forcing (FWF) input at the end of the Younger Dryas in the TraCE-21K-II simulation. This staged AMOC reactivation is attributed to changes in sea surface salinity (SSS) pattern in the North Atlantic Ocean. The first recovery phase is mainly due to the termination of FWF; however, the increasing SSS through hemispheric-scale northward transport of salty water is partially suppressed by melting water from high-latitude regions, resulting in a subsequent oscillation in the AMOC strength. The second recovery phase is primarily linked to the sea ice retreat in the Greenland–Iceland–Norwegian Seas, which reinitiates the SSS transport through the Norwegian Current. Exploring such model characteristics in simulating the surface oceanic processes may improve our understanding of the AMOC's response to FWF.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A two-phase recovery of the Atlantic Meridional Overturning Circulation (AMOC) is revealed following the abrupt cessation of freshwater forcing (FWF) input at the end of the Younger Dryas in the TraCE-21K-II simulation. This staged AMOC reactivation is attributed to changes in sea surface salinity (SSS) pattern in the North Atlantic Ocean. The first recovery phase is mainly due to the termination of FWF; however, the increasing SSS through hemispheric-scale northward transport of salty water is partially suppressed by melting water from high-latitude regions, resulting in a subsequent oscillation in the AMOC strength. The second recovery phase is primarily linked to the sea ice retreat in the Greenland–Iceland–Norwegian Seas, which reinitiates the SSS transport through the Norwegian Current. Exploring such model characteristics in simulating the surface oceanic processes may improve our understanding of the AMOC's response to FWF. |
Marissa Weiss; Addie Rose Holland; Anthony W. D'Amato; Linda A. Deegan; William H. Farmer; Christopher Hoving; Ambarish V. Karmalkar; Alexander Latzka; Madeline Magee; Peter B. McIntyre; Toni Lyn Morelli; Michael Notaro; Nancy Olmstead; Richard N. Palmer; Nancy Pau; Rosalind Renfrew; Christine A. Ribic; John Sheppard; Michelle D. Staudinger; Benjamin Zuckerberg; Bethany A. Bradley: Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation. In: BioScience, vol. 75, iss. 10, pp. 842–855, 2025. @article{Weiss2025b,
title = {Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation},
author = {Marissa Weiss and Addie Rose Holland and Anthony W. D'Amato and Linda A. Deegan and William H. Farmer and Christopher Hoving and Ambarish V. Karmalkar and Alexander Latzka and Madeline Magee and Peter B. McIntyre and Toni Lyn Morelli and Michael Notaro and Nancy Olmstead and Richard N. Palmer and Nancy Pau and Rosalind Renfrew and Christine A. Ribic and John Sheppard and Michelle D. Staudinger and Benjamin Zuckerberg and Bethany A. Bradley},
url = {https://academic.oup.com/bioscience/article/75/10/842/8205518},
doi = {10.1093/biosci/biaf087},
year = {2025},
date = {2025-07-17},
urldate = {2025-07-17},
journal = {BioScience},
volume = {75},
issue = {10},
pages = {842–855},
abstract = {The rapid pace of climate change demands changes in management practices. Despite abundant climate adaptation research, the implementation of climate adaptation can lag in the management space. In the present article, we argue that relationship-centered engagement—establishing and maintaining relationships among researchers and natural resource managers—is critical for bridging the research–management gap. We evaluated researcher–manager partnerships within the US Northeast Climate Adaptation Science Center and identified three cultural shifts that institutions, funders, researchers, and managers could adopt to boost the odds of translating findings into action: acknowledging and supporting the central role of relationships in creating and implementing actionable science, lengthening funding timelines to better support establishing and maintaining relationships, and aligning institutional rewards to support relationship building. A renewed focus on relationships can lead to more diverse and effective partnerships that bridge knowledge to practice and hasten adaptation to climate change.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The rapid pace of climate change demands changes in management practices. Despite abundant climate adaptation research, the implementation of climate adaptation can lag in the management space. In the present article, we argue that relationship-centered engagement—establishing and maintaining relationships among researchers and natural resource managers—is critical for bridging the research–management gap. We evaluated researcher–manager partnerships within the US Northeast Climate Adaptation Science Center and identified three cultural shifts that institutions, funders, researchers, and managers could adopt to boost the odds of translating findings into action: acknowledging and supporting the central role of relationships in creating and implementing actionable science, lengthening funding timelines to better support establishing and maintaining relationships, and aligning institutional rewards to support relationship building. A renewed focus on relationships can lead to more diverse and effective partnerships that bridge knowledge to practice and hasten adaptation to climate change. |
Pengfei Xue; Chenfu Huang; Yafang Zhong; Michael Notaro; Miraj B. Kayastha; Xing Zhou; Chuyan Zhao; Christa Peters-Lidard; Carlos Cruz; Eric Kemp: Enhancing winter climate simulations of the Great Lakes: insights from a new coupled lake–ice–atmosphere (CLIAv1) system on the importance of integrating 3D hydrodynamics with a regional climate model. In: GeoScientific Model Development, vol. 18, iss. 13, pp. 4293–4316, 2025. @article{Xue2025b,
title = {Enhancing winter climate simulations of the Great Lakes: insights from a new coupled lake–ice–atmosphere (CLIAv1) system on the importance of integrating 3D hydrodynamics with a regional climate model},
author = {Pengfei Xue and Chenfu Huang and Yafang Zhong and Michael Notaro and Miraj B. Kayastha and Xing Zhou and Chuyan Zhao and Christa Peters-Lidard and Carlos Cruz and Eric Kemp},
url = {https://gmd.copernicus.org/articles/18/4293/2025/},
doi = {10.5194/gmd-18-4293-2025},
year = {2025},
date = {2025-07-16},
urldate = {2025-07-16},
journal = {GeoScientific Model Development},
volume = {18},
issue = {13},
pages = {4293–4316},
abstract = {The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States due to their vast thermal inertia, moisture source potential, and complex heat and moisture flux dynamics. This study presents a newly developed coupled lake–ice–atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA) Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulations of the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 demonstrates superior performance in reproducing observed lake surface temperatures (LSTs), ice cover distribution, and the vertical thermal structure of the Great Lakes compared to the NU-WRF model coupled with the default 1D Lake Ice Snow and Sediment Simulator (LISSS). CLIAv1 also enhances the simulation of over-lake atmospheric conditions, including air temperature, wind speed, and sensible and latent heat fluxes, underscoring the importance of resolving complex lake dynamics for reliable regional Earth system projections. More importantly, the key contribution of this study is the identification of critical physical processes that influence lake thermal structure and ice cover – processes that are missed by 1D lake models but effectively resolved by 3D lake models. Through process-oriented numerical experiments, we identify key 3D hydrodynamic processes – ice transport, heat advection, and shear production in turbulence – that explain the superiority of 3D lake models to 1D lake models, particularly in cold season performance and lake–atmosphere interactions. Critically, all three of these processes are dynamically linked to water currents – spatially and temporally evolving flow fields that are structurally absent in 1D models. This study aims to advance our understanding of the physical mechanisms that underlie the fundamental differences between 3D and 1D lake models in simulating key hydrodynamic processes during the winter season, and it offers generalized insights that are not constrained by specific model configurations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States due to their vast thermal inertia, moisture source potential, and complex heat and moisture flux dynamics. This study presents a newly developed coupled lake–ice–atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA) Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulations of the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 demonstrates superior performance in reproducing observed lake surface temperatures (LSTs), ice cover distribution, and the vertical thermal structure of the Great Lakes compared to the NU-WRF model coupled with the default 1D Lake Ice Snow and Sediment Simulator (LISSS). CLIAv1 also enhances the simulation of over-lake atmospheric conditions, including air temperature, wind speed, and sensible and latent heat fluxes, underscoring the importance of resolving complex lake dynamics for reliable regional Earth system projections. More importantly, the key contribution of this study is the identification of critical physical processes that influence lake thermal structure and ice cover – processes that are missed by 1D lake models but effectively resolved by 3D lake models. Through process-oriented numerical experiments, we identify key 3D hydrodynamic processes – ice transport, heat advection, and shear production in turbulence – that explain the superiority of 3D lake models to 1D lake models, particularly in cold season performance and lake–atmosphere interactions. Critically, all three of these processes are dynamically linked to water currents – spatially and temporally evolving flow fields that are structurally absent in 1D models. This study aims to advance our understanding of the physical mechanisms that underlie the fundamental differences between 3D and 1D lake models in simulating key hydrodynamic processes during the winter season, and it offers generalized insights that are not constrained by specific model configurations. |
Mohammad Abbasian; Daniel B. Wright; Michael Notaro; Steve Vavrus; Daniel J. Vimont: Flood frequency sampling error: insights from regional analysis, stochastic storm transposition, and physics-based modeling. In: Journal of Hydrology, vol. 662 Part A, no. 133802, 2025. @article{Abbasian2025b,
title = {Flood frequency sampling error: insights from regional analysis, stochastic storm transposition, and physics-based modeling},
author = {Mohammad Abbasian and Daniel B. Wright and Michael Notaro and Steve Vavrus and Daniel J. Vimont},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0022169425011400?via%3Dihub},
doi = {10.1016/j.jhydrol.2025.133802},
year = {2025},
date = {2025-07-12},
urldate = {2025-07-12},
journal = {Journal of Hydrology},
volume = {662 Part A},
number = {133802},
abstract = {Flood Frequency Analysis (FFA) typically involves fitting a probability distribution to Annual Maximum Peaks (AMPs) to estimate peak flow quantiles. While flood frequency sampling error due to small sample sizes is a well-recognized issue, this study highlights that, as flood data records lengthen, sampling error can remain as a concern. We examine the Kickapoo watershed in the north-central United States, where at-site FFA is susceptible to significant sampling errors despite a relatively long record of flood observations (90 years). We leverage a combination of at-site and regional statistical analyses of AMPs and watershed characteristics, Bulletin 17C guidelines, and a process-driven FFA approach to gain insights into flood extremes, flood frequency, and sampling errors. The process-based FFA integrates stochastic storm transposition with Monte Carlo physics-based hydrologic modeling. It employs the WRF-Hydro hydrologic model and a process-based calibration approach with Fusion, a new high-resolution forcing dataset over the continental United States. We demonstrate that three exceptionally large events, with a combined likelihood of occurrence of less than 2%, significantly affect extreme quantiles and their confidence intervals. Further, we show that while Kickapoo’s physiographic characteristics differ somewhat from neighboring watersheds, these extremes are also shaped by remarkable precipitation variability, contributing to sampling errors. While sample size has traditionally been the focal issue of sampling error, this research underscores additional factors: rare and extreme events and hydroclimate variability. It also highlights how regional analyses and advanced physics-based modeling techniques help improve understanding of flood extremes and frequency.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Flood Frequency Analysis (FFA) typically involves fitting a probability distribution to Annual Maximum Peaks (AMPs) to estimate peak flow quantiles. While flood frequency sampling error due to small sample sizes is a well-recognized issue, this study highlights that, as flood data records lengthen, sampling error can remain as a concern. We examine the Kickapoo watershed in the north-central United States, where at-site FFA is susceptible to significant sampling errors despite a relatively long record of flood observations (90 years). We leverage a combination of at-site and regional statistical analyses of AMPs and watershed characteristics, Bulletin 17C guidelines, and a process-driven FFA approach to gain insights into flood extremes, flood frequency, and sampling errors. The process-based FFA integrates stochastic storm transposition with Monte Carlo physics-based hydrologic modeling. It employs the WRF-Hydro hydrologic model and a process-based calibration approach with Fusion, a new high-resolution forcing dataset over the continental United States. We demonstrate that three exceptionally large events, with a combined likelihood of occurrence of less than 2%, significantly affect extreme quantiles and their confidence intervals. Further, we show that while Kickapoo’s physiographic characteristics differ somewhat from neighboring watersheds, these extremes are also shaped by remarkable precipitation variability, contributing to sampling errors. While sample size has traditionally been the focal issue of sampling error, this research underscores additional factors: rare and extreme events and hydroclimate variability. It also highlights how regional analyses and advanced physics-based modeling techniques help improve understanding of flood extremes and frequency.
|
Rudradutt Thaker; Stephen J. Vavrus; Christine A. Shields; Alice K. DuVivier; Michelle Maclennan; Marika M. Holland; Laura Landrum: Arctic Atmospheric Rivers in a Changing Climate and the Impacts on Sea Ice. In: JGR-Atmospheres, vol. 130, iss. 10, 2025. @article{Thaker2025b,
title = {Arctic Atmospheric Rivers in a Changing Climate and the Impacts on Sea Ice},
author = {Rudradutt Thaker and Stephen J. Vavrus and Christine A. Shields and Alice K. DuVivier and Michelle Maclennan and Marika M. Holland and Laura Landrum},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042521},
doi = {10.1029/2024JD042521},
year = {2025},
date = {2025-05-15},
urldate = {2025-05-15},
journal = {JGR-Atmospheres},
volume = {130},
issue = {10},
abstract = {Atmospheric rivers (ARs) transport heat and moisture from lower latitudes to the Arctic, contributing to sea ice loss. As climate warming and sea ice decline continue, understanding how Arctic ARs evolve is essential. While studies suggest an increase in Arctic ARs and storms, a comprehensive understanding of their changing behavior, seasonal patterns, and sea ice impacts remains incomplete. This study investigates the changing dynamics of Arctic ARs in response to a warming climate, examining the drivers of these changes and their impact on sea ice. Using the Community Earth System Model, Version 2 (CESM2), we find CESM2 effectively simulates Arctic ARs compared to ERA5. To analyze ARs under different climate conditions, we apply three detection methods: using present climate thresholds, scaling thresholds with projected future moisture changes, and calculating unique thresholds for each decade. Our results show increased AR frequency and intensity in the future, with changes strongly influenced by the chosen AR definition. Depending on the method, we find that AR frequency increases range from 30%–50% up to 400%, or even show decreases in some regions. During fall and winter, the North Atlantic experiences increased AR frequency, while more intense ARs occur in the North Pacific during summer. We also explore the effects of future ARs on sea ice, finding a net increase in sea ice loss, particularly in winter and spring. The extent of sea ice loss is highly sensitive to the AR detection method used.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Atmospheric rivers (ARs) transport heat and moisture from lower latitudes to the Arctic, contributing to sea ice loss. As climate warming and sea ice decline continue, understanding how Arctic ARs evolve is essential. While studies suggest an increase in Arctic ARs and storms, a comprehensive understanding of their changing behavior, seasonal patterns, and sea ice impacts remains incomplete. This study investigates the changing dynamics of Arctic ARs in response to a warming climate, examining the drivers of these changes and their impact on sea ice. Using the Community Earth System Model, Version 2 (CESM2), we find CESM2 effectively simulates Arctic ARs compared to ERA5. To analyze ARs under different climate conditions, we apply three detection methods: using present climate thresholds, scaling thresholds with projected future moisture changes, and calculating unique thresholds for each decade. Our results show increased AR frequency and intensity in the future, with changes strongly influenced by the chosen AR definition. Depending on the method, we find that AR frequency increases range from 30%–50% up to 400%, or even show decreases in some regions. During fall and winter, the North Atlantic experiences increased AR frequency, while more intense ARs occur in the North Pacific during summer. We also explore the effects of future ARs on sea ice, finding a net increase in sea ice loss, particularly in winter and spring. The extent of sea ice loss is highly sensitive to the AR detection method used. |
Hesam Salmabadi; Mohsen Saeedi; Michael Notaro; Alexandre Roy: Dust transport pathways from the Mesopotamian Marshes. In: Aeolian Research, vol. 73, 2025. @article{Salmabadi2025,
title = {Dust transport pathways from the Mesopotamian Marshes},
author = {Hesam Salmabadi and Mohsen Saeedi and Michael Notaro and Alexandre Roy},
doi = {10.1016/j.aeolia.2025.100975},
year = {2025},
date = {2025-04-24},
urldate = {2025-04-24},
journal = {Aeolian Research},
volume = {73},
abstract = {The Mesopotamian Marshes, located in southern Iraq and southwestern Iran, represent one of the world’s largest wetland ecosystems. These marshlands have undergone significant degradation primarily due to anthropogenic activities, including extensive dam construction, oil extraction, and political conflicts, transforming vast areas into potential dust sources. This study investigates the wind climatology over the marshes and analyzes the long-range transport pathways of dust originating from the region using forward air-parcel trajectories generated with the HYSPLIT model from 2000 to 2023, with each trajectory calculated over an 8-day period. Through trajectory clustering, we identified four primary transport pathways with distinct seasonal patterns. The dominant pathway (35%) follows the Shamal winds southeastward across the Persian Gulf, particularly active in summer and spring. A second pathway (35%) curves southwestward toward Africa, while a third (19%) moves northeastward toward the Caspian Sea and Kazakhstan during non-summer seasons. The fourth pathway (11%) represents high-altitude transport via mid-tropospheric westerlies, potentially reaching East Asia. Meteorological analysis suggests that dust emission potential is active year-round and is highest during summer. Summer is characterized by high temperatures (seasonal mean of 38.8 degree C), no precipitation, and the highest seasonal mean wind speeds (5.31 ms^-1). These findings provide crucial insights into the spatial extent and seasonal variability of dust transport from the Mesopotamian Marshes, demonstrating their far-reaching impact on air quality, ecosystems, and climate in regions as distant as East Asia and North Africa, highlighting the need for targeted conservation to mitigate environmental impacts posed by dust from these degraded wetlands.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Mesopotamian Marshes, located in southern Iraq and southwestern Iran, represent one of the world’s largest wetland ecosystems. These marshlands have undergone significant degradation primarily due to anthropogenic activities, including extensive dam construction, oil extraction, and political conflicts, transforming vast areas into potential dust sources. This study investigates the wind climatology over the marshes and analyzes the long-range transport pathways of dust originating from the region using forward air-parcel trajectories generated with the HYSPLIT model from 2000 to 2023, with each trajectory calculated over an 8-day period. Through trajectory clustering, we identified four primary transport pathways with distinct seasonal patterns. The dominant pathway (35%) follows the Shamal winds southeastward across the Persian Gulf, particularly active in summer and spring. A second pathway (35%) curves southwestward toward Africa, while a third (19%) moves northeastward toward the Caspian Sea and Kazakhstan during non-summer seasons. The fourth pathway (11%) represents high-altitude transport via mid-tropospheric westerlies, potentially reaching East Asia. Meteorological analysis suggests that dust emission potential is active year-round and is highest during summer. Summer is characterized by high temperatures (seasonal mean of 38.8 degree C), no precipitation, and the highest seasonal mean wind speeds (5.31 ms^-1). These findings provide crucial insights into the spatial extent and seasonal variability of dust transport from the Mesopotamian Marshes, demonstrating their far-reaching impact on air quality, ecosystems, and climate in regions as distant as East Asia and North Africa, highlighting the need for targeted conservation to mitigate environmental impacts posed by dust from these degraded wetlands. |
Fujung Tsai; Yu-Chen Chien; Wei-Nai Chen; Michael Notaro; Hung-Yu Chen; Neng-Huei Lin; Po-Chun Hsu; Yu-Chi Lin: Source and Transport of Dust to the North Pacific: Observations and Analysis From a High Mountain. In: JGR-Atmospheres, 2025. @article{Tsai2025b,
title = {Source and Transport of Dust to the North Pacific: Observations and Analysis From a High Mountain},
author = {Fujung Tsai and Yu-Chen Chien and Wei-Nai Chen and Michael Notaro and Hung-Yu Chen and Neng-Huei Lin and Po-Chun Hsu and Yu-Chi Lin},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042415},
doi = {10.1029/2024JD042415},
year = {2025},
date = {2025-03-12},
urldate = {2025-03-12},
journal = {JGR-Atmospheres},
abstract = {Dust transported to the North Pacific originates not only from East Asian sources but also from non-East Asian sources, providing important marine nutrients to the open ocean. This study analyzes the sources, transport routes, and dust concentrations during 13 North Pacific events in 2010 observed at Mt. Lulin on the Northwest Pacific margin. In addition to aerosol measurements, surface weather data, space lidar observations, MERRA-2 reanalysis data, and trajectory simulations were used. The results show that, during transport to the Pacific, dust from North Africa and the Middle East first moves northeast to Central Asia (30–55°N) and ascends to 200–400 hPa before crossing East Asia. In contrast, dust from the Taklamakan Desert in East Asia rises to 300–400 hPa before being transported eastward. As these dust sources descend into East Asia, they often mix with dust from the Gobi Desert. Indian dust travels zonally eastward at altitudes of 600–800 hPa over Southeast Asia without mixing. In the northwest Pacific, reanalysis data show that while dust is concentrated near the surface, maximum outflow to the Pacific occurs at 400 hPa in the mid-latitudes due to strong westerlies. Trajectory analysis combined with observations suggests that this high-altitude transport includes dust from the Sahara, Arabia, and Taklamakan deserts. At Mt. Lulin along the subtropical coast of East Asia, measured dust concentrations during dust events range from 15 to 39 μg m−3, while the annual average is close to 5 μg m−3, accounting for 42% of the aerosol concentration over the high mountain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dust transported to the North Pacific originates not only from East Asian sources but also from non-East Asian sources, providing important marine nutrients to the open ocean. This study analyzes the sources, transport routes, and dust concentrations during 13 North Pacific events in 2010 observed at Mt. Lulin on the Northwest Pacific margin. In addition to aerosol measurements, surface weather data, space lidar observations, MERRA-2 reanalysis data, and trajectory simulations were used. The results show that, during transport to the Pacific, dust from North Africa and the Middle East first moves northeast to Central Asia (30–55°N) and ascends to 200–400 hPa before crossing East Asia. In contrast, dust from the Taklamakan Desert in East Asia rises to 300–400 hPa before being transported eastward. As these dust sources descend into East Asia, they often mix with dust from the Gobi Desert. Indian dust travels zonally eastward at altitudes of 600–800 hPa over Southeast Asia without mixing. In the northwest Pacific, reanalysis data show that while dust is concentrated near the surface, maximum outflow to the Pacific occurs at 400 hPa in the mid-latitudes due to strong westerlies. Trajectory analysis combined with observations suggests that this high-altitude transport includes dust from the Sahara, Arabia, and Taklamakan deserts. At Mt. Lulin along the subtropical coast of East Asia, measured dust concentrations during dust events range from 15 to 39 μg m−3, while the annual average is close to 5 μg m−3, accounting for 42% of the aerosol concentration over the high mountain. |
C. C. Zimmerman; T. J. W. Wagner; E. A. Maroon; D. E. McNamara: Slowed Response of Atlantic Meridional Overturning Circulation Not a Robust Signal of Collapse. In: Geophysical Research Letters, 2025. @article{Zimmerman2025,
title = {Slowed Response of Atlantic Meridional Overturning Circulation Not a Robust Signal of Collapse},
author = {C. C. Zimmerman and T. J. W. Wagner and E. A. Maroon and D. E. McNamara},
doi = {10.1029/2024gl112415},
year = {2025},
date = {2025-01-24},
urldate = {2025-01-24},
journal = {Geophysical Research Letters},
abstract = {Using an idealized model of the Atlantic meridional overturning circulation (AMOC), we test whether changes in the statistical properties of an AMOC time series can reveal Critical Slowing Down (CSD) and serve as early warnings of an upcoming critical transition. We calculate CSD indicators for simulations across varying parameter regimes, investigating the system's steady‐state dynamical structure and its evolution under gradual climate forcing. We find that the modeled AMOC features bistability for relatively weak gyre salinity exchange, but no bistability when the gyres are sufficiently strong. However, CSD indicators consistently warn of a collapse across the gyre strength parameter space, even when no bifurcations occur, thus raising false alarms. We argue that CSD should be applied cautiously in systems where the dynamical structure and physical response to forcing are not fully known (such as the AMOC), specifically where it is not a priori clear whether the system is in a multistable regime.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Using an idealized model of the Atlantic meridional overturning circulation (AMOC), we test whether changes in the statistical properties of an AMOC time series can reveal Critical Slowing Down (CSD) and serve as early warnings of an upcoming critical transition. We calculate CSD indicators for simulations across varying parameter regimes, investigating the system's steady‐state dynamical structure and its evolution under gradual climate forcing. We find that the modeled AMOC features bistability for relatively weak gyre salinity exchange, but no bistability when the gyres are sufficiently strong. However, CSD indicators consistently warn of a collapse across the gyre strength parameter space, even when no bifurcations occur, thus raising false alarms. We argue that CSD should be applied cautiously in systems where the dynamical structure and physical response to forcing are not fully known (such as the AMOC), specifically where it is not a priori clear whether the system is in a multistable regime. |
Nicolas B. Sartore; Till J. W. Wagner; Matthew R. Siegfried; Nimish Pujara; Lucas K. Zoet: Wave erosion, frontal bending, and calving at Ross Ice Shelf. In: The Cryosphere, vol. 19, iss. 1, pp. 249–265, 2025. @article{Sartore2025,
title = {Wave erosion, frontal bending, and calving at Ross Ice Shelf},
author = {Nicolas B. Sartore and Till J. W. Wagner and Matthew R. Siegfried and Nimish Pujara and Lucas K. Zoet},
doi = {10.5194/tc-19-249-2025},
year = {2025},
date = {2025-01-20},
urldate = {2025-01-20},
journal = {The Cryosphere},
volume = {19},
issue = {1},
pages = {249–265},
abstract = {Ice shelf calving constitutes roughly half of the total mass loss from the Antarctic ice sheet. Although much attention is paid to calving of giant tabular icebergs, these events are relatively rare. Here, we investigate the role of frontal melting and stresses at the ice shelf front in driving bending and calving on the scale of ∼100 m, perpendicular to the ice edge. We focus in particular on how buoyant underwater “feet” that protrude beyond the above-water ice cliff may cause tensile stresses at the base of the ice. Indirect and anecdotal observations of such feet at the Ross Ice Shelf front suggest that the resulting bending may be widespread and can trigger calving. We consider satellite observations together with an elastic beam model and a parameterization of wave erosion to better understand the dynamics at the ice shelf front. Our results suggest that on average frontal ablation rather consistently accounts for 20±5 m yr−1 of ice loss at Ross Ice Shelf, likely mostly due to wave erosion and smaller-scale, 𝒪(100 m), foot-induced calving. This constitutes only ∼2 % of the total frontal mass loss (since near-front ice velocities are ∼1000 m yr−1). Observational evidence suggests that sporadic larger events can skew this rate (we document one foot-induced calving event of size ∼1 km). Stresses from foot-induced bending are likely not sufficient to initiate crevassing but rather act to propagate existing crevasses. In addition, our results support recent findings by Buck (2024) that additional bending moments, likely due to temperature gradients in the ice, may play a role in driving frontal deflections. The highly variable environment, irregularity of pre-existing crevasse spacing, and complex rheology of the ice continue to pose challenges in better constraining the drivers behind the observed deformations and resulting calving rates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ice shelf calving constitutes roughly half of the total mass loss from the Antarctic ice sheet. Although much attention is paid to calving of giant tabular icebergs, these events are relatively rare. Here, we investigate the role of frontal melting and stresses at the ice shelf front in driving bending and calving on the scale of ∼100 m, perpendicular to the ice edge. We focus in particular on how buoyant underwater “feet” that protrude beyond the above-water ice cliff may cause tensile stresses at the base of the ice. Indirect and anecdotal observations of such feet at the Ross Ice Shelf front suggest that the resulting bending may be widespread and can trigger calving. We consider satellite observations together with an elastic beam model and a parameterization of wave erosion to better understand the dynamics at the ice shelf front. Our results suggest that on average frontal ablation rather consistently accounts for 20±5 m yr−1 of ice loss at Ross Ice Shelf, likely mostly due to wave erosion and smaller-scale, 𝒪(100 m), foot-induced calving. This constitutes only ∼2 % of the total frontal mass loss (since near-front ice velocities are ∼1000 m yr−1). Observational evidence suggests that sporadic larger events can skew this rate (we document one foot-induced calving event of size ∼1 km). Stresses from foot-induced bending are likely not sufficient to initiate crevassing but rather act to propagate existing crevasses. In addition, our results support recent findings by Buck (2024) that additional bending moments, likely due to temperature gradients in the ice, may play a role in driving frontal deflections. The highly variable environment, irregularity of pre-existing crevasse spacing, and complex rheology of the ice continue to pose challenges in better constraining the drivers behind the observed deformations and resulting calving rates. |
2024
|
Igor V. Polyakov; Thomas J. Ballinger; James E. Overland; Stephen J. Vavrus; Seth L. Danielson; Rick Lader; Uma S. Bhatt; Amy S. Hendricks; Franz J. Mueter: Atmospheric Pressure Rivalry Between the Arctic and Northern Pacific: Implications for Alaskan Climate Variability. In: International Journal of Climatology, 2024. @article{Polyakov2024,
title = {Atmospheric Pressure Rivalry Between the Arctic and Northern Pacific: Implications for Alaskan Climate Variability},
author = {Igor V. Polyakov and Thomas J. Ballinger and James E. Overland and Stephen J. Vavrus and Seth L. Danielson and Rick Lader and Uma S. Bhatt and Amy S. Hendricks and Franz J. Mueter},
doi = {https://doi.org/10.1002/joc.8638},
year = {2024},
date = {2024-10-23},
journal = { International Journal of Climatology},
abstract = {Located at the confluence of the Arctic and North Pacific and with Alaska at its heart, the Pacific Arctic Region (PAR) is a unique and interconnected regional climate system. Significant climatic changes in the PAR are described by a novel, mobile monthly Alaska Arctic Front (AAF) index, which is defined by sea level pressure differences between the migratory cores of the Beaufort High and Aleutian Low. Regional climate variability associated with the AAF shows prominent decadal signatures that are driven by the opposing effects of the North Pacific and the Arctic atmospheric pressure fields. Low AAF (negative phase) is dominated by North Pacific forcing, whereas high AAF (positive phase) is dominated by Arctic atmospheric processes. The recent (2011–2021) negative AAF phase, which is associated with the westward displacement of Aleutian Low explaining stronger northward winds and enhanced water transport northward through Bering Strait, is conducive to increased oceanic heat and freshwater content, reduced regional sea ice cover in the PAR, and to the expansion of Pacific species into the Arctic. These factors are all indicators of the Pacification of the Arctic Ocean, a key feature of climate change related to progression of anomalous Pacific water masses and biota into the polar basins. It is not yet clear if or when the recent phase of decadal variability will change and alter the rate of Pacification of the Arctic climate system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Located at the confluence of the Arctic and North Pacific and with Alaska at its heart, the Pacific Arctic Region (PAR) is a unique and interconnected regional climate system. Significant climatic changes in the PAR are described by a novel, mobile monthly Alaska Arctic Front (AAF) index, which is defined by sea level pressure differences between the migratory cores of the Beaufort High and Aleutian Low. Regional climate variability associated with the AAF shows prominent decadal signatures that are driven by the opposing effects of the North Pacific and the Arctic atmospheric pressure fields. Low AAF (negative phase) is dominated by North Pacific forcing, whereas high AAF (positive phase) is dominated by Arctic atmospheric processes. The recent (2011–2021) negative AAF phase, which is associated with the westward displacement of Aleutian Low explaining stronger northward winds and enhanced water transport northward through Bering Strait, is conducive to increased oceanic heat and freshwater content, reduced regional sea ice cover in the PAR, and to the expansion of Pacific species into the Arctic. These factors are all indicators of the Pacification of the Arctic Ocean, a key feature of climate change related to progression of anomalous Pacific water masses and biota into the polar basins. It is not yet clear if or when the recent phase of decadal variability will change and alter the rate of Pacification of the Arctic climate system. |
Hong Wang; Zhisheng An; Xu Zhang; Peixian Shu; Feng He; Weiguo Liu; Hongxuan Lu; Guodong Ming; Lin Liu; Weijian Zhou: Westerly and Laurentide ice sheet fluctuations during the last glacial maximum. In: npj Climate and Atmospheric Science, vol. 7, pp. 213, 2024. @article{Wang2024,
title = {Westerly and Laurentide ice sheet fluctuations during the last glacial maximum},
author = {Hong Wang and Zhisheng An and Xu Zhang and Peixian Shu and Feng He and Weiguo Liu and Hongxuan Lu and Guodong Ming and Lin Liu and Weijian Zhou},
doi = {https://doi.org/10.1038/s41612-024-00760-9},
year = {2024},
date = {2024-09-10},
urldate = {2024-09-10},
journal = {npj Climate and Atmospheric Science},
volume = {7},
pages = {213},
abstract = {The last glacial maximum (LGM) is widely acknowledged as the most recent cold period representing maximum global ice conditions. However, substantial warming is observed over Northern Hemisphere. Here, we show that the LGM climate shifted from very cold to fairly warm, followed by less cold conditions in the early Heinrich Stadial 1 (HS1) phases. Our synthesis of accurate AMS 14C dates refines the exact timing of Laurentide Ice Sheet (LIS) advances during the early LGM/HS1, constraining the chronology of the LIS decay during the late LGM. The summertime soil temperatures near ice fronts were found to increase by 1.3 °C from the early to late LGM and to decrease by 0.5 °C to the early HS1 phases, consistent with the cold-warm-cool climate patterns. The early/late LGM and early HS1 climates are found to be characterized by frequent cold/warm summers and cold winters since the world’s largest LIS began to decay.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The last glacial maximum (LGM) is widely acknowledged as the most recent cold period representing maximum global ice conditions. However, substantial warming is observed over Northern Hemisphere. Here, we show that the LGM climate shifted from very cold to fairly warm, followed by less cold conditions in the early Heinrich Stadial 1 (HS1) phases. Our synthesis of accurate AMS 14C dates refines the exact timing of Laurentide Ice Sheet (LIS) advances during the early LGM/HS1, constraining the chronology of the LIS decay during the late LGM. The summertime soil temperatures near ice fronts were found to increase by 1.3 °C from the early to late LGM and to decrease by 0.5 °C to the early HS1 phases, consistent with the cold-warm-cool climate patterns. The early/late LGM and early HS1 climates are found to be characterized by frequent cold/warm summers and cold winters since the world’s largest LIS began to decay. |
Shaun R. Eaves; Andrew N. Mackintosh; Joel B. Pedro; Helen C. Bostock; Matthew T. Ryan; Kevin P. Norton; Bruce W. Hayward; Brian M. Anderson; Feng He; Richard S. Jones; Andrew M. Lorrey; Rewi M. Newnham; Stephen G. Tims; Marcus J. Vandergoes: Coupled atmosphere-ocean response of the southwest Pacific to deglacial changes in Atlantic meridional overturning circulation Author links open overlay panel. In: Earth and Planetary Science Letters, vol. 641, pp. 118802, 2024. @article{Eaves2024,
title = {Coupled atmosphere-ocean response of the southwest Pacific to deglacial changes in Atlantic meridional overturning circulation Author links open overlay panel},
author = {Shaun R. Eaves and Andrew N. Mackintosh and Joel B. Pedro and Helen C. Bostock and Matthew T. Ryan and Kevin P. Norton and Bruce W. Hayward and Brian M. Anderson and Feng He and Richard S. Jones and Andrew M. Lorrey and Rewi M. Newnham and Stephen G. Tims and Marcus J. Vandergoes},
doi = {https://doi.org/10.1016/j.epsl.2024.118802},
year = {2024},
date = {2024-09-01},
journal = {Earth and Planetary Science Letters},
volume = {641},
pages = {118802},
abstract = {The last glacial termination was characterised by millennial-scale episodes of warming and cooling that appear offset between the hemispheres. It has been proposed that this bi-polar seesaw is the result of climate system feedbacks. A key debate, which remains unresolved, concerns the relative roles of the atmosphere and oceans in transmitting these climate responses between the hemispheres. In this study we present quantitative climate proxy data to show that air temperatures in New Zealand, as recorded by mountain glaciers, tracked millennial-scale warming and cooling of local surface temperatures of the adjacent Tasman Sea throughout the last glacial termination. Both realms were dominated by warming between 18 ka and 12 ka, interrupted by a multi-centennial to millennial-scale cooling event centred on 14 ka, coincident with the Antarctic Cold Reversal. Reconciling our climate proxy evidence with a transient climate model simulation of the glacial termination, we find that the timing and amplitude of temperature changes are consistent with changing Atlantic meridional overturning circulation (AMOC). The southwest Pacific region displays a particularly sensitive response to AMOC intensity changes, despite its far-field situation from the North Atlantic. This sensitivity represents the combined impact of fast-acting oceanic teleconnections and regional atmosphere-ocean response associated with changes to the southern westerly winds. Our findings highlight that recent hypotheses promoting the role of southern westerlies as a critical component of deglaciation may be complementary to, rather than competitive with, the bipolar seesaw paradigm.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The last glacial termination was characterised by millennial-scale episodes of warming and cooling that appear offset between the hemispheres. It has been proposed that this bi-polar seesaw is the result of climate system feedbacks. A key debate, which remains unresolved, concerns the relative roles of the atmosphere and oceans in transmitting these climate responses between the hemispheres. In this study we present quantitative climate proxy data to show that air temperatures in New Zealand, as recorded by mountain glaciers, tracked millennial-scale warming and cooling of local surface temperatures of the adjacent Tasman Sea throughout the last glacial termination. Both realms were dominated by warming between 18 ka and 12 ka, interrupted by a multi-centennial to millennial-scale cooling event centred on 14 ka, coincident with the Antarctic Cold Reversal. Reconciling our climate proxy evidence with a transient climate model simulation of the glacial termination, we find that the timing and amplitude of temperature changes are consistent with changing Atlantic meridional overturning circulation (AMOC). The southwest Pacific region displays a particularly sensitive response to AMOC intensity changes, despite its far-field situation from the North Atlantic. This sensitivity represents the combined impact of fast-acting oceanic teleconnections and regional atmosphere-ocean response associated with changes to the southern westerly winds. Our findings highlight that recent hypotheses promoting the role of southern westerlies as a critical component of deglaciation may be complementary to, rather than competitive with, the bipolar seesaw paradigm. |
Brooke Snoll; Ruza Ivanovic; Lauren Gregoire; Sam Sherriff-Tadano; Laurie Menviel; Takashi Obase; Ayako Abe-Ouchi; Nathaelle Bouttes; Chengfei He; Feng He; Marie Kapsch; Uwe Mikolajewicz; Juan Muglia; Paul Valdes: A multi-model assessment of the early last deglaciation (PMIP4 LDv1): a meltwater perspective. In: Climate of the Past , vol. 20, iss. 4, pp. 789-815, 2024. @article{Snoll2024,
title = {A multi-model assessment of the early last deglaciation (PMIP4 LDv1): a meltwater perspective},
author = {Brooke Snoll and Ruza Ivanovic and Lauren Gregoire and Sam Sherriff-Tadano and Laurie Menviel and Takashi Obase and Ayako Abe-Ouchi and Nathaelle Bouttes and Chengfei He and Feng He and Marie Kapsch and Uwe Mikolajewicz and Juan Muglia and Paul Valdes},
doi = {10.5194/cp-20-789-2024},
year = {2024},
date = {2024-04-05},
urldate = {2024-04-05},
journal = {Climate of the Past },
volume = {20},
issue = {4},
pages = {789-815},
abstract = {The last deglaciation (∼20–11 ka BP) is a period of a major, long-term climate transition from a glacial to interglacial state that features multiple centennial- to decadal-scale abrupt climate variations whose root cause is still not fully understood. To better understand this time period, the Paleoclimate Modelling Intercomparison Project (PMIP) has provided a framework for an internationally coordinated endeavour in simulating the last deglaciation whilst encompassing a broad range of models. Here, we present a multi-model intercomparison of 17 transient simulations of the early part of the last deglaciation (∼20–15 ka BP) from nine different climate models spanning a range of model complexities and uncertain boundary conditions and forcings. The numerous simulations available provide the opportunity to better understand the chain of events and mechanisms of climate changes between 20 and 15 ka BP and our collective ability to simulate them. We conclude that the amount of freshwater forcing and whether it follows the ice sheet reconstruction or induces an inferred Atlantic meridional overturning circulation (AMOC) history, heavily impacts the deglacial climate evolution for each simulation rather than differences in the model physics. The course of the deglaciation is consistent between simulations except when the freshwater forcing is above 0.1 Sv – at least 70 % of the simulations agree that there is warming by 15 ka BP in most places excluding the location of meltwater input. For simulations with freshwater forcings that exceed 0.1 Sv from 18 ka BP, warming is delayed in the North Atlantic and surface air temperature correlations with AMOC strength are much higher. However, we find that the state of the AMOC coming out of the Last Glacial Maximum (LGM) also plays a key role in the AMOC sensitivity to model forcings. In addition, we show that the response of each model to the chosen meltwater scenario depends largely on the sensitivity of the model to the freshwater forcing and other aspects of the experimental design (e.g. CO2 forcing or ice sheet reconstruction). The results provide insight into the ability of our models to simulate the first part of the deglaciation and how choices between uncertain boundary conditions and forcings, with a focus on freshwater fluxes, can impact model outputs. We can use these findings as helpful insight in the design of future simulations of this time period.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The last deglaciation (∼20–11 ka BP) is a period of a major, long-term climate transition from a glacial to interglacial state that features multiple centennial- to decadal-scale abrupt climate variations whose root cause is still not fully understood. To better understand this time period, the Paleoclimate Modelling Intercomparison Project (PMIP) has provided a framework for an internationally coordinated endeavour in simulating the last deglaciation whilst encompassing a broad range of models. Here, we present a multi-model intercomparison of 17 transient simulations of the early part of the last deglaciation (∼20–15 ka BP) from nine different climate models spanning a range of model complexities and uncertain boundary conditions and forcings. The numerous simulations available provide the opportunity to better understand the chain of events and mechanisms of climate changes between 20 and 15 ka BP and our collective ability to simulate them. We conclude that the amount of freshwater forcing and whether it follows the ice sheet reconstruction or induces an inferred Atlantic meridional overturning circulation (AMOC) history, heavily impacts the deglacial climate evolution for each simulation rather than differences in the model physics. The course of the deglaciation is consistent between simulations except when the freshwater forcing is above 0.1 Sv – at least 70 % of the simulations agree that there is warming by 15 ka BP in most places excluding the location of meltwater input. For simulations with freshwater forcings that exceed 0.1 Sv from 18 ka BP, warming is delayed in the North Atlantic and surface air temperature correlations with AMOC strength are much higher. However, we find that the state of the AMOC coming out of the Last Glacial Maximum (LGM) also plays a key role in the AMOC sensitivity to model forcings. In addition, we show that the response of each model to the chosen meltwater scenario depends largely on the sensitivity of the model to the freshwater forcing and other aspects of the experimental design (e.g. CO2 forcing or ice sheet reconstruction). The results provide insight into the ability of our models to simulate the first part of the deglaciation and how choices between uncertain boundary conditions and forcings, with a focus on freshwater fluxes, can impact model outputs. We can use these findings as helpful insight in the design of future simulations of this time period. |
Yanyan Yu; Jie Yu snd Haibin Wu; Feng He; Stephen J. Vavrus; Amber Johnson; Wenchao Zhang; Qin Li; Zhengtang Guo: Asynchronous Holocene human population changes in north and south China as related to animal resource utilization. In: Global and Planetary Change, vol. 235, iss. 0921-8181, pp. 104403, 2024. @article{Yu2024,
title = {Asynchronous Holocene human population changes in north and south China as related to animal resource utilization},
author = {Yanyan Yu and Jie Yu snd Haibin Wu and Feng He and Stephen J. Vavrus and Amber Johnson and Wenchao Zhang and Qin Li and Zhengtang Guo},
doi = {10.1016/j.gloplacha.2024.104403},
year = {2024},
date = {2024-04-01},
urldate = {2024-04-01},
journal = {Global and Planetary Change},
volume = {235},
issue = {0921-8181},
pages = {104403},
abstract = {During the Holocene, rich Neolithic and Bronze cultures developed in the middle and lower reaches of Yellow River valley (north China) and Yangtze River valley (south China), making them the core areas of past human activities. Thus, it is important to reveal the process and driving mechanism of regional population change. Agriculture development has always been taken as the key driver of population changes, and current studies mainly focus on the role that cultivation played, however, it is still unclear if animal resource utilization also contributed to regional population changes. Here, the spatiotemporal changes of population and domestic animal utilization levels in north and south China from 10 to 2 ka BP have been reconstructed based on 27,935 archaeological sites and faunal remains data from 94 sites, respectively, and the change in potential wild animal resources has been simulated by the Minimum Terrestrial Resource Model (MTRM). The results show asynchronous changes of population occurred in north and south China during 10–2 ka BP, which were correlated with regional domestic and potential wild animal resource utilization. In north China, more significant population growth corresponded to a greater increase of domestic animal ratios and a sharp decline of potential wild animal resources after 8 ka BP. In south China, less significant population growth was accompanied by a slower increase of domestic animal ratios and stable variations of potential wild animal resources. This research suggests that different changes of potential wild animal resources in north and south China contributed to spatial variations in survival pressure, utilization level of domestic animals, and population growth, which was further determined by asynchronous changes of precipitation in the two regions. This study explains the impact of climate changes on population from a new perspective.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
During the Holocene, rich Neolithic and Bronze cultures developed in the middle and lower reaches of Yellow River valley (north China) and Yangtze River valley (south China), making them the core areas of past human activities. Thus, it is important to reveal the process and driving mechanism of regional population change. Agriculture development has always been taken as the key driver of population changes, and current studies mainly focus on the role that cultivation played, however, it is still unclear if animal resource utilization also contributed to regional population changes. Here, the spatiotemporal changes of population and domestic animal utilization levels in north and south China from 10 to 2 ka BP have been reconstructed based on 27,935 archaeological sites and faunal remains data from 94 sites, respectively, and the change in potential wild animal resources has been simulated by the Minimum Terrestrial Resource Model (MTRM). The results show asynchronous changes of population occurred in north and south China during 10–2 ka BP, which were correlated with regional domestic and potential wild animal resource utilization. In north China, more significant population growth corresponded to a greater increase of domestic animal ratios and a sharp decline of potential wild animal resources after 8 ka BP. In south China, less significant population growth was accompanied by a slower increase of domestic animal ratios and stable variations of potential wild animal resources. This research suggests that different changes of potential wild animal resources in north and south China contributed to spatial variations in survival pressure, utilization level of domestic animals, and population growth, which was further determined by asynchronous changes of precipitation in the two regions. This study explains the impact of climate changes on population from a new perspective. |
Maxwell R. W. Beal; Mutlu Özdoğan; Paul J. Block: A Machine Learning and Remote Sensing-Based Model for Algae Pigment and Dissolved Oxygen Retrieval on a Small Inland Lake. In: Water Resources Research, vol. 60, iss. 3, pp. e2023WR035744, 2024. @article{Beal2024,
title = {A Machine Learning and Remote Sensing-Based Model for Algae Pigment and Dissolved Oxygen Retrieval on a Small Inland Lake},
author = {Maxwell R. W. Beal and Mutlu Özdoğan and Paul J. Block},
doi = {10.1029/2023WR035744},
year = {2024},
date = {2024-02-28},
journal = {Water Resources Research},
volume = {60},
issue = {3},
pages = {e2023WR035744},
abstract = {Excessive algae growth can lead to negative consequences for ecosystem function, economic opportunity, and human and animal health. Due to the cost-effectiveness and temporal availability of satellite imagery, remote sensing has become a powerful tool for water quality monitoring. The use of remotely sensed products to monitor water quality related to algae and cyanobacteria productivity during a bloom event may help inform management strategies for inland waters. To evaluate the ability of satellite imagery to monitor algae pigments and dissolved oxygen conditions in a small inland lake, chlorophyll-a, phycocyanin, and dissolved oxygen concentrations are measured using a YSI EXO2 sonde during Sentinel-2 and Sentinel-3 overpasses from 2019 to 2022 on Lake Mendota, WI. Machine learning methods are implemented with existing algorithms to model chlorophyll-a, phycocyanin, and Pc:Chla. A novel machine learning-based dissolved oxygen modeling approach is developed using algae pigment concentrations as predictors. Best model results based on Sentinel-2 (Sentinel-3) imagery achieved R2 scores of 0.47 (0.42) for chlorophyll-a, 0.69 (0.22) for phycocyanin, and 0.70 (0.41) for Pc:Chla. Dissolved oxygen models achieved an R2 of 0.68 (0.36) when applied to Sentinel-2 (Sentinel-3) imagery, and Pc:Chla is found to be the most important predictive feature. Random forest models are better suited to water quality estimations in this system given built in methods for feature selection and a relatively small data set. Use of these approaches for estimation of Pc:Chla and dissolved oxygen can increase the water quality information extracted from satellite imagery and improve characterization of algae conditions among inland waters.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Excessive algae growth can lead to negative consequences for ecosystem function, economic opportunity, and human and animal health. Due to the cost-effectiveness and temporal availability of satellite imagery, remote sensing has become a powerful tool for water quality monitoring. The use of remotely sensed products to monitor water quality related to algae and cyanobacteria productivity during a bloom event may help inform management strategies for inland waters. To evaluate the ability of satellite imagery to monitor algae pigments and dissolved oxygen conditions in a small inland lake, chlorophyll-a, phycocyanin, and dissolved oxygen concentrations are measured using a YSI EXO2 sonde during Sentinel-2 and Sentinel-3 overpasses from 2019 to 2022 on Lake Mendota, WI. Machine learning methods are implemented with existing algorithms to model chlorophyll-a, phycocyanin, and Pc:Chla. A novel machine learning-based dissolved oxygen modeling approach is developed using algae pigment concentrations as predictors. Best model results based on Sentinel-2 (Sentinel-3) imagery achieved R2 scores of 0.47 (0.42) for chlorophyll-a, 0.69 (0.22) for phycocyanin, and 0.70 (0.41) for Pc:Chla. Dissolved oxygen models achieved an R2 of 0.68 (0.36) when applied to Sentinel-2 (Sentinel-3) imagery, and Pc:Chla is found to be the most important predictive feature. Random forest models are better suited to water quality estimations in this system given built in methods for feature selection and a relatively small data set. Use of these approaches for estimation of Pc:Chla and dissolved oxygen can increase the water quality information extracted from satellite imagery and improve characterization of algae conditions among inland waters. |