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Abstract
Climate change detection and attribution have played a central role in establishing the influence of human activities on climate. Optimal fingerprinting, a linear regression with errors in variables (EIVs), has been widely used in detection and attribution analyses of climate change. The method regresses observed climate variables on the expected climate responses to the external forcings, which are measured with EIVs. The reliability of the method depends critically on proper point and interval estimations of the regression coefficients. The confidence intervals constructed from the prevailing method, total least squares (TLS), have been reported to be too narrow to match their nominal confidence levels. We propose a novel framework to estimate the regression coefficients based on an efficient, bias-corrected estimating equations approach. The confidence intervals are constructed with a pseudo residual bootstrap variance estimator that takes advantage of the available control runs. Our regression coefficient estimator is unbiased, with a smaller variance than the TLS estimator. Our estimation of the sampling variability of the estimator has a low bias compared to that from TLS, which is substantially negatively biased. The resulting confidence intervals for the regression coefficients have coverage rates close to the nominal level, which ensures valid inferences in detection and attribution analyses. In applications to the annual mean near-surface air temperature at the global, continental, and subcontinental scales during 1951–2020, the proposed method led to shorter confidence intervals than those based on TLS in most of the analyses.
Significance Statement
Optimal fingerprinting is an important statistical tool for estimating human influences on the climate and for quantifying the associated uncertainty. Nonetheless, the estimators from the prevailing practice are not as optimal as believed, and their uncertainties are underestimated, both owing to the unreliable estimation of the optimal weight matrix that is critical to the method. Here we propose an estimation method based on the theory of estimating equations; to assess the uncertainty of the resulting estimator, we propose a pseudo bootstrap procedure. Through extensive numerical studies commonly used in statistical investigations, we demonstrate that the new estimator has a smaller mean-square error, and its uncertainty is estimated much closer to the true uncertainty than the prevailing total least squares method.
Abstract
Climate change detection and attribution have played a central role in establishing the influence of human activities on climate. Optimal fingerprinting, a linear regression with errors in variables (EIVs), has been widely used in detection and attribution analyses of climate change. The method regresses observed climate variables on the expected climate responses to the external forcings, which are measured with EIVs. The reliability of the method depends critically on proper point and interval estimations of the regression coefficients. The confidence intervals constructed from the prevailing method, total least squares (TLS), have been reported to be too narrow to match their nominal confidence levels. We propose a novel framework to estimate the regression coefficients based on an efficient, bias-corrected estimating equations approach. The confidence intervals are constructed with a pseudo residual bootstrap variance estimator that takes advantage of the available control runs. Our regression coefficient estimator is unbiased, with a smaller variance than the TLS estimator. Our estimation of the sampling variability of the estimator has a low bias compared to that from TLS, which is substantially negatively biased. The resulting confidence intervals for the regression coefficients have coverage rates close to the nominal level, which ensures valid inferences in detection and attribution analyses. In applications to the annual mean near-surface air temperature at the global, continental, and subcontinental scales during 1951–2020, the proposed method led to shorter confidence intervals than those based on TLS in most of the analyses.
Significance Statement
Optimal fingerprinting is an important statistical tool for estimating human influences on the climate and for quantifying the associated uncertainty. Nonetheless, the estimators from the prevailing practice are not as optimal as believed, and their uncertainties are underestimated, both owing to the unreliable estimation of the optimal weight matrix that is critical to the method. Here we propose an estimation method based on the theory of estimating equations; to assess the uncertainty of the resulting estimator, we propose a pseudo bootstrap procedure. Through extensive numerical studies commonly used in statistical investigations, we demonstrate that the new estimator has a smaller mean-square error, and its uncertainty is estimated much closer to the true uncertainty than the prevailing total least squares method.
Abstract
Extratropical cyclones (ETCs) are a common source of natural hazards, from heavy rain to high winds, and the direction and speed of ETC propagation influence where impacts occur and for how long. Eighteen models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are used to examine the response of Northern Hemisphere ETC propagation to global warming. In winter, simulations show that ETCs become slower over North America and the Arctic but faster over the Pacific Ocean and part of Europe. In summer, storm propagation becomes slightly slower throughout much of the midlatitudes (30°–60°N). Trends in both seasons relate closely to the impact of global warming on upper-level (250 hPa) winds and the 850–250-hPa thickness gradient. Wherever local thickness gradients weaken in the future, ETCs travel more slowly; conversely, wherever they strengthen, ETCs travel more quickly. In contrast to past work, we find that winter storm propagation becomes more zonal over the Pacific and Atlantic Oceans, which may link to decreased atmospheric blocking and less-sinuous flow at 500 hPa. The importance of model projections of the 850–250-hPa thickness gradient for meridionality of ETC propagation remains uncertain for these regions. However, for North America, models that project stronger thickness gradients also project less-sinuous flow and more-zonal ETC propagation. Overall, this work highlights strong regional variation in how the speed and direction of ETC propagation, and the upper-level circulation patterns that govern them, respond to continued warming.
Significance Statement
Extratropical storms are common sources of natural hazards like heavy rain and high winds. In our analysis of projections from 18 climate models, we find that winter storms tend to move more slowly over midlatitude North America and the Arctic as the world warms but move faster over the North Pacific Ocean and part of Europe. Slight slowing of summer storms is projected throughout much of the midlatitudes. When storms move slower, their attendant hazards (like heavy precipitation) last longer for the areas they impact. Further, Atlantic winter storms travel more west to east instead of southwest to northeast, so they impact Iceland less often and the British Isles more often. Changes become more dramatic with each additional degree of global warming.
Abstract
Extratropical cyclones (ETCs) are a common source of natural hazards, from heavy rain to high winds, and the direction and speed of ETC propagation influence where impacts occur and for how long. Eighteen models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are used to examine the response of Northern Hemisphere ETC propagation to global warming. In winter, simulations show that ETCs become slower over North America and the Arctic but faster over the Pacific Ocean and part of Europe. In summer, storm propagation becomes slightly slower throughout much of the midlatitudes (30°–60°N). Trends in both seasons relate closely to the impact of global warming on upper-level (250 hPa) winds and the 850–250-hPa thickness gradient. Wherever local thickness gradients weaken in the future, ETCs travel more slowly; conversely, wherever they strengthen, ETCs travel more quickly. In contrast to past work, we find that winter storm propagation becomes more zonal over the Pacific and Atlantic Oceans, which may link to decreased atmospheric blocking and less-sinuous flow at 500 hPa. The importance of model projections of the 850–250-hPa thickness gradient for meridionality of ETC propagation remains uncertain for these regions. However, for North America, models that project stronger thickness gradients also project less-sinuous flow and more-zonal ETC propagation. Overall, this work highlights strong regional variation in how the speed and direction of ETC propagation, and the upper-level circulation patterns that govern them, respond to continued warming.
Significance Statement
Extratropical storms are common sources of natural hazards like heavy rain and high winds. In our analysis of projections from 18 climate models, we find that winter storms tend to move more slowly over midlatitude North America and the Arctic as the world warms but move faster over the North Pacific Ocean and part of Europe. Slight slowing of summer storms is projected throughout much of the midlatitudes. When storms move slower, their attendant hazards (like heavy precipitation) last longer for the areas they impact. Further, Atlantic winter storms travel more west to east instead of southwest to northeast, so they impact Iceland less often and the British Isles more often. Changes become more dramatic with each additional degree of global warming.
Abstract
In recent years, the Southern Ocean has experienced unprecedented surface warming and sea ice loss—a stark reversal of the sea ice expansion and surface cooling that prevailed over the preceding decades. Here, we examine the mechanisms that led to the abrupt circumpolar surface warming events that occurred in late 2016 and 2019 and assess the role of internal climate variability. A mixed layer heat budget analysis reveals that these recent circumpolar surface warming events were triggered by a weakening of the circumpolar westerlies, which decreased northward Ekman transport and accelerated the seasonal shoaling of the mixed layer. We emphasize the underappreciated effect of the latter mechanism, which played a dominant role and amplified the warming effect of air–sea heat fluxes during months of peak solar insolation. An examination of the CESM1 large ensemble demonstrates that these recent circumpolar warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM), whereby negative SAM in austral spring favors shallower mixed layers and anomalously high summertime SST. A key insight from this analysis is that the seasonal phasing of springtime mixed layer depth shoaling is an important contributor to summertime SST variability in the Southern Ocean. Thus, future Southern Ocean summertime SST extremes will depend on the coevolution of mixed layer depth and surface wind variability.
Significance Statement
This study examines how reductions in the strength of the circumpolar westerlies can produce abrupt and extreme surface warming across the Southern Ocean. A key insight is that the mixed layer temperature is most sensitive to surface wind perturbations in late austral spring, when the regional mixed layer depth and solar insolation approach their respective seasonal minimum and maximum. This heightened surface temperature response to surface wind variability was realized during the austral spring of 2016 and 2019, when a dramatic weakening of the circumpolar westerlies triggered unprecedented warming across the Southern Ocean. In both cases, the anomalously weak circumpolar winds reduced the northward Ekman transport of cool subpolar waters and caused the mixed layer to shoal more rapidly in the spring, with the latter mechanism being more dominant. Using results from an ensemble of coupled climate simulations, we demonstrate that the 2016 and 2019 Southern Ocean warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM). These results suggest that future Southern Ocean surface warming extremes will depend on both the evolution of regional mixed layer depths and interannual wind variability.
Abstract
In recent years, the Southern Ocean has experienced unprecedented surface warming and sea ice loss—a stark reversal of the sea ice expansion and surface cooling that prevailed over the preceding decades. Here, we examine the mechanisms that led to the abrupt circumpolar surface warming events that occurred in late 2016 and 2019 and assess the role of internal climate variability. A mixed layer heat budget analysis reveals that these recent circumpolar surface warming events were triggered by a weakening of the circumpolar westerlies, which decreased northward Ekman transport and accelerated the seasonal shoaling of the mixed layer. We emphasize the underappreciated effect of the latter mechanism, which played a dominant role and amplified the warming effect of air–sea heat fluxes during months of peak solar insolation. An examination of the CESM1 large ensemble demonstrates that these recent circumpolar warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM), whereby negative SAM in austral spring favors shallower mixed layers and anomalously high summertime SST. A key insight from this analysis is that the seasonal phasing of springtime mixed layer depth shoaling is an important contributor to summertime SST variability in the Southern Ocean. Thus, future Southern Ocean summertime SST extremes will depend on the coevolution of mixed layer depth and surface wind variability.
Significance Statement
This study examines how reductions in the strength of the circumpolar westerlies can produce abrupt and extreme surface warming across the Southern Ocean. A key insight is that the mixed layer temperature is most sensitive to surface wind perturbations in late austral spring, when the regional mixed layer depth and solar insolation approach their respective seasonal minimum and maximum. This heightened surface temperature response to surface wind variability was realized during the austral spring of 2016 and 2019, when a dramatic weakening of the circumpolar westerlies triggered unprecedented warming across the Southern Ocean. In both cases, the anomalously weak circumpolar winds reduced the northward Ekman transport of cool subpolar waters and caused the mixed layer to shoal more rapidly in the spring, with the latter mechanism being more dominant. Using results from an ensemble of coupled climate simulations, we demonstrate that the 2016 and 2019 Southern Ocean warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM). These results suggest that future Southern Ocean surface warming extremes will depend on both the evolution of regional mixed layer depths and interannual wind variability.
Abstract
This study examines the characteristics and phase evolution of the quasi-biweekly oscillation of surface sensible heating (SH) over the central-eastern Tibetan Plateau (CETP) during spring. The mechanism connecting CETP SH to spring rainfall in China on the quasi-biweekly time scale is further investigated. Results show that the dominant mode of quasi-biweekly CETP SH presents a monopole pattern, in which the peak leads the maximum of the quasi-biweekly rainfall in the middle and lower reaches of the Yangtze River (MLYR) and South China by approximately 5 and 7 days, respectively. As an upper-level Rossby wave train propagates eastward, an anomalous center of convergence moves to the CETP, which leads to a strong downdraft and reduced cloud cover. The resultant elevated shortwave radiation input and drier soil conditions are favorable for the CETP SH quasi-biweekly oscillation to enter a positive phase. When reaching its peak, the CETP SH efficiently heats the lower atmosphere, resulting in a local updraft. Due to the “SH-driven air pump” effect, abundant water vapor is transported from the oceans to China. A lower-layer southerly anomaly on the east side of the TP develops into an anomalous cyclonic circulation via the effect of topographic friction, which leads to the expansion of the positive potential vorticity anomaly and the maximum of the quasi-biweekly rainfall in the MLYR. Further southeastward propagation of the wave train leads to a shift in the rainfall anomaly center to South China. These findings suggest that the CETP monopole SH warming could be a good indicator for predicting intraseasonal variations in spring rainfall over China.
Abstract
This study examines the characteristics and phase evolution of the quasi-biweekly oscillation of surface sensible heating (SH) over the central-eastern Tibetan Plateau (CETP) during spring. The mechanism connecting CETP SH to spring rainfall in China on the quasi-biweekly time scale is further investigated. Results show that the dominant mode of quasi-biweekly CETP SH presents a monopole pattern, in which the peak leads the maximum of the quasi-biweekly rainfall in the middle and lower reaches of the Yangtze River (MLYR) and South China by approximately 5 and 7 days, respectively. As an upper-level Rossby wave train propagates eastward, an anomalous center of convergence moves to the CETP, which leads to a strong downdraft and reduced cloud cover. The resultant elevated shortwave radiation input and drier soil conditions are favorable for the CETP SH quasi-biweekly oscillation to enter a positive phase. When reaching its peak, the CETP SH efficiently heats the lower atmosphere, resulting in a local updraft. Due to the “SH-driven air pump” effect, abundant water vapor is transported from the oceans to China. A lower-layer southerly anomaly on the east side of the TP develops into an anomalous cyclonic circulation via the effect of topographic friction, which leads to the expansion of the positive potential vorticity anomaly and the maximum of the quasi-biweekly rainfall in the MLYR. Further southeastward propagation of the wave train leads to a shift in the rainfall anomaly center to South China. These findings suggest that the CETP monopole SH warming could be a good indicator for predicting intraseasonal variations in spring rainfall over China.
Abstract
The mass balance of the Antarctic ice sheet is intricately linked to the state of the surrounding atmosphere and ocean. As a direct result, improving projections of future sea level change requires understanding change in the Antarctic atmosphere and Southern Ocean, and the processes that couple these systems. Here, we examine the influence of sea ice cover on the overlying atmosphere and subsequently the surface mass balance (SMB) of the adjacent Antarctic ice sheet. We investigate these processes both over the observational era using the ERA5 atmospheric reanalysis and in ensemble simulations of the Community Earth System Model 2.1 (CESM2) where only sea ice coverage is altered. Comparing extreme high and low sea ice over the satellite era in ERA5 reveals atmospheric and ice sheet SMB anomalies that largely mirror anomalies simulated by CESM2 in response to sea ice loss. Results highlight significant near-surface atmospheric warming in response to sea ice reductions that are particularly pronounced in nonsummer seasons and driven by significant ocean-to-atmosphere turbulent heat fluxes. In areas of sea ice loss, significant ocean surface evaporation increases occur. On the eastern flank of climatological low pressure systems, moisture is readily advected toward the ice sheet, driving positive anomalies in the ice sheet SMB. These results indicate that underestimation of Antarctic sea ice, which is common in many current-generation coupled climate models, may lead to overestimation of the ice sheet SMB and therefore underestimation of Antarctica’s contributions to global sea level.
Significance Statement
The Antarctic ice sheet is the largest potential source of global sea level rise. Its sea level contributions depend in part on how much snow accumulates across its surface. Through observation-incorporating reanalysis data and climate model sensitivity studies, we find that Southern Ocean sea ice coverage exerts an important influence on the near-surface climate and mass balance of the Antarctic ice sheet. Our results show that reductions in Antarctic sea ice promote enhanced ocean surface evaporation and subsequent increases in snowfall across the Antarctic ice sheet. Because current climate models tend to simulate too little Antarctic sea ice, we conclude they may therefore overestimate Antarctic ice sheet snowfall, leading to underprediction of future sea level rise.
Abstract
The mass balance of the Antarctic ice sheet is intricately linked to the state of the surrounding atmosphere and ocean. As a direct result, improving projections of future sea level change requires understanding change in the Antarctic atmosphere and Southern Ocean, and the processes that couple these systems. Here, we examine the influence of sea ice cover on the overlying atmosphere and subsequently the surface mass balance (SMB) of the adjacent Antarctic ice sheet. We investigate these processes both over the observational era using the ERA5 atmospheric reanalysis and in ensemble simulations of the Community Earth System Model 2.1 (CESM2) where only sea ice coverage is altered. Comparing extreme high and low sea ice over the satellite era in ERA5 reveals atmospheric and ice sheet SMB anomalies that largely mirror anomalies simulated by CESM2 in response to sea ice loss. Results highlight significant near-surface atmospheric warming in response to sea ice reductions that are particularly pronounced in nonsummer seasons and driven by significant ocean-to-atmosphere turbulent heat fluxes. In areas of sea ice loss, significant ocean surface evaporation increases occur. On the eastern flank of climatological low pressure systems, moisture is readily advected toward the ice sheet, driving positive anomalies in the ice sheet SMB. These results indicate that underestimation of Antarctic sea ice, which is common in many current-generation coupled climate models, may lead to overestimation of the ice sheet SMB and therefore underestimation of Antarctica’s contributions to global sea level.
Significance Statement
The Antarctic ice sheet is the largest potential source of global sea level rise. Its sea level contributions depend in part on how much snow accumulates across its surface. Through observation-incorporating reanalysis data and climate model sensitivity studies, we find that Southern Ocean sea ice coverage exerts an important influence on the near-surface climate and mass balance of the Antarctic ice sheet. Our results show that reductions in Antarctic sea ice promote enhanced ocean surface evaporation and subsequent increases in snowfall across the Antarctic ice sheet. Because current climate models tend to simulate too little Antarctic sea ice, we conclude they may therefore overestimate Antarctic ice sheet snowfall, leading to underprediction of future sea level rise.
Abstract
The global perspective presented here is built on earlier papers discussing the dynamics of the upper branch of the Hadley cell in the two solsticial seasons. The role of the tropics is made explicit in a conceptual model that is presented and evaluated. The fluctuation of deep tropical convection in longitude and time is seen as crucial. The filamentary outflows from such convective events move westward and across the equator deep into the winter hemisphere. The horizontal tilt of the cross-equatorial flow implies a significant upper-tropospheric flux of westerly momentum from the winter tropics to the summer hemisphere. These properties are related to the cross-equatorial propagation of wave activity triggered by deep tropical convection in the summer hemisphere. The filaments carry with them near-equatorial values of absolute vorticity and potential vorticity. After turning anticyclonically, some filaments move eastward and poleward to the equatorial edge of the winter subtropical jet. There is strong evidence they can interact with the eddies on this jet and enhance their poleward westerly momentum flux. In the global perspective, tropical and extratropical systems and the interaction between them are all important for the dynamics of the upper branch of the Hadley cell.
significance statement
The Hadley cell is the large-scale overturning in the atmosphere with air in the upper troposphere moving from the equatorial region to near 30° in the winter hemisphere. In the standard view it is midlatitude weather systems that are responsible for removing angular momentum from this upper branch of the Hadley cell. Here it is proposed that tropical systems and their interaction with the midlatitude systems are also important. Insight into the role of the tropics in the dynamics of the Hadley cell can be obtained by considering it as the sum of many events of active deep convection occurring in different longitudes and at different times.
Abstract
The global perspective presented here is built on earlier papers discussing the dynamics of the upper branch of the Hadley cell in the two solsticial seasons. The role of the tropics is made explicit in a conceptual model that is presented and evaluated. The fluctuation of deep tropical convection in longitude and time is seen as crucial. The filamentary outflows from such convective events move westward and across the equator deep into the winter hemisphere. The horizontal tilt of the cross-equatorial flow implies a significant upper-tropospheric flux of westerly momentum from the winter tropics to the summer hemisphere. These properties are related to the cross-equatorial propagation of wave activity triggered by deep tropical convection in the summer hemisphere. The filaments carry with them near-equatorial values of absolute vorticity and potential vorticity. After turning anticyclonically, some filaments move eastward and poleward to the equatorial edge of the winter subtropical jet. There is strong evidence they can interact with the eddies on this jet and enhance their poleward westerly momentum flux. In the global perspective, tropical and extratropical systems and the interaction between them are all important for the dynamics of the upper branch of the Hadley cell.
significance statement
The Hadley cell is the large-scale overturning in the atmosphere with air in the upper troposphere moving from the equatorial region to near 30° in the winter hemisphere. In the standard view it is midlatitude weather systems that are responsible for removing angular momentum from this upper branch of the Hadley cell. Here it is proposed that tropical systems and their interaction with the midlatitude systems are also important. Insight into the role of the tropics in the dynamics of the Hadley cell can be obtained by considering it as the sum of many events of active deep convection occurring in different longitudes and at different times.
Abstract
Southeastern Australia experienced an extreme heatwave event from 27 January to 8 February 2009, which culminated in the devastating “Black Saturday” bushfires that led to hundreds of human casualties and major economic losses in the state of Victoria. This study investigates the causes of the heatwave event, its prediction, and the role of anthropogenic climate change using a dynamical subseasonal-to-seasonal (S2S) forecast system. We show that the intense positive temperature anomalies over southeastern Australia were associated with the persistent high pressure system over the Tasman Sea and a low pressure anomaly over southern Australia, which favored horizontal warm-air advection from the lower latitudes to the region. Enhanced convection over the tropical western Pacific and northern Australia due to weak La Niña conditions appear to have played a role in strengthening the high pressure anomalies over the Tasman Sea. The observed climate conditions are largely reproduced in the hindcast of the Australian Community Climate and Earth System Simulator–Seasonal prediction system version 1 (ACCESS-S1). The model skillfully predicts the spatial characteristics and relative intensity of the heatwave event at a 10-day lead time. A climate attribution forecast experiment with low atmospheric CO2 and counterfactual cold ocean–atmospheric initial conditions suggests that the enhanced greenhouse effect contributed about 3°C warming of the predicted event. This study provides an example of how a S2S prediction system can be used not only for multiweek prediction of an extreme event and its climate drivers, but also for the attribution to anthropogenic climate change.
Abstract
Southeastern Australia experienced an extreme heatwave event from 27 January to 8 February 2009, which culminated in the devastating “Black Saturday” bushfires that led to hundreds of human casualties and major economic losses in the state of Victoria. This study investigates the causes of the heatwave event, its prediction, and the role of anthropogenic climate change using a dynamical subseasonal-to-seasonal (S2S) forecast system. We show that the intense positive temperature anomalies over southeastern Australia were associated with the persistent high pressure system over the Tasman Sea and a low pressure anomaly over southern Australia, which favored horizontal warm-air advection from the lower latitudes to the region. Enhanced convection over the tropical western Pacific and northern Australia due to weak La Niña conditions appear to have played a role in strengthening the high pressure anomalies over the Tasman Sea. The observed climate conditions are largely reproduced in the hindcast of the Australian Community Climate and Earth System Simulator–Seasonal prediction system version 1 (ACCESS-S1). The model skillfully predicts the spatial characteristics and relative intensity of the heatwave event at a 10-day lead time. A climate attribution forecast experiment with low atmospheric CO2 and counterfactual cold ocean–atmospheric initial conditions suggests that the enhanced greenhouse effect contributed about 3°C warming of the predicted event. This study provides an example of how a S2S prediction system can be used not only for multiweek prediction of an extreme event and its climate drivers, but also for the attribution to anthropogenic climate change.
Abstract
A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6-μm atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations.
significance statement
Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.
Abstract
A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6-μm atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations.
significance statement
Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.
Abstract
To investigate patterns of horizontal atmospheric latent energy (LE) transport toward the Arctic, we applied the self-organizing maps (SOM) method to the daily vertically integrated horizontal LE flux from ERA5 in winter (January–March) during 1979–2021. A clear picture depicting the LE transport to the Arctic at a synoptic scale then emerged, with four primary transport pathways identified: the northern Europe, the Davis Strait, the Greenland Sea, and the Bering Strait pathways. The four primary pathways occurred at a comparable frequency, and noticeable interannual variability was observed in their time series of frequency during 1979–2021. Further analysis suggested that the northward LE transport through all these pathways is significantly modulated by cyclones, with the northern Europe and the Greenland Sea pathways being mostly affected. Generally, more frequent and stronger cyclones were observed near the entry regions of LE transport compared to other regions. Moreover, this study provides a comprehensive picture of how atmospheric LE transport is related to air temperature, moisture, surface heat flux, and sea ice anomalies over the Arctic Ocean in winter. Through a thermodynamic perspective, we argue that the deleterious impacts of poleward LE transport on Arctic sea ice are to a large extent attributable to the enhanced local atmosphere–ice interactions, which increase downward longwave radiation (DLR) plus turbulent fluxes, consequently warming the surface and promoting the loss of sea ice. According to the quantitative results, among the four primary pathways, LE transport through the Davis Strait and the Greenland Sea could cause the loss of Arctic sea ice most efficiently.
Abstract
To investigate patterns of horizontal atmospheric latent energy (LE) transport toward the Arctic, we applied the self-organizing maps (SOM) method to the daily vertically integrated horizontal LE flux from ERA5 in winter (January–March) during 1979–2021. A clear picture depicting the LE transport to the Arctic at a synoptic scale then emerged, with four primary transport pathways identified: the northern Europe, the Davis Strait, the Greenland Sea, and the Bering Strait pathways. The four primary pathways occurred at a comparable frequency, and noticeable interannual variability was observed in their time series of frequency during 1979–2021. Further analysis suggested that the northward LE transport through all these pathways is significantly modulated by cyclones, with the northern Europe and the Greenland Sea pathways being mostly affected. Generally, more frequent and stronger cyclones were observed near the entry regions of LE transport compared to other regions. Moreover, this study provides a comprehensive picture of how atmospheric LE transport is related to air temperature, moisture, surface heat flux, and sea ice anomalies over the Arctic Ocean in winter. Through a thermodynamic perspective, we argue that the deleterious impacts of poleward LE transport on Arctic sea ice are to a large extent attributable to the enhanced local atmosphere–ice interactions, which increase downward longwave radiation (DLR) plus turbulent fluxes, consequently warming the surface and promoting the loss of sea ice. According to the quantitative results, among the four primary pathways, LE transport through the Davis Strait and the Greenland Sea could cause the loss of Arctic sea ice most efficiently.
Abstract
Atmospheric angular momentum (AAM) is used to study the variability of Earth’s atmospheric circulation during the past 45 years, a time of considerable climate change. Using global AAM, two interdecadal states are defined covering the periods 1977–98 (hereinafter P1) and 1999–2022 (P2). Global AAM decreased from P1 to P2 and was accompanied by weakened subtropical jet streams in both hemispheres, strong convection around the northern Maritime Continent, and a strengthened sea surface temperature (SST) gradient across the tropical Pacific Ocean. The period differences project onto 1) internal interdecadal Pacific variability (IPV), 2) a postulated transient ocean thermostat response to greenhouse gas and aerosol emissions, and 3) circulation anomalies related to the ozone hole. During 1977–2023, the first two processes are forcing the climate toward larger Pacific Ocean SST gradients and a poleward expansion of the Indo-Pacific warm pool (IPWP), especially into the Northern Hemisphere. The ozone hole produces its own distinct pattern of anomalies in the Southern Hemisphere that tend to become persistent in the early 1990s. The zonal and vertical mean AAM variations during P1 have frequent westerly wind anomalies between 40°N and 40°S with poleward propagation on interannual time scales. During P2, the circulation is dominated by subtropical easterly wind anomalies, poleward-shifted jets, and weaker propagation. Locally, the zonal mean anomalies manifest as midlatitude ridges that lead to continental droughts. Case studies illustrate the weakened subtropical jet streams of P2 and examine the factors behind a transition to La Niña in early 2020 that maintains the P2 pattern.
Abstract
Atmospheric angular momentum (AAM) is used to study the variability of Earth’s atmospheric circulation during the past 45 years, a time of considerable climate change. Using global AAM, two interdecadal states are defined covering the periods 1977–98 (hereinafter P1) and 1999–2022 (P2). Global AAM decreased from P1 to P2 and was accompanied by weakened subtropical jet streams in both hemispheres, strong convection around the northern Maritime Continent, and a strengthened sea surface temperature (SST) gradient across the tropical Pacific Ocean. The period differences project onto 1) internal interdecadal Pacific variability (IPV), 2) a postulated transient ocean thermostat response to greenhouse gas and aerosol emissions, and 3) circulation anomalies related to the ozone hole. During 1977–2023, the first two processes are forcing the climate toward larger Pacific Ocean SST gradients and a poleward expansion of the Indo-Pacific warm pool (IPWP), especially into the Northern Hemisphere. The ozone hole produces its own distinct pattern of anomalies in the Southern Hemisphere that tend to become persistent in the early 1990s. The zonal and vertical mean AAM variations during P1 have frequent westerly wind anomalies between 40°N and 40°S with poleward propagation on interannual time scales. During P2, the circulation is dominated by subtropical easterly wind anomalies, poleward-shifted jets, and weaker propagation. Locally, the zonal mean anomalies manifest as midlatitude ridges that lead to continental droughts. Case studies illustrate the weakened subtropical jet streams of P2 and examine the factors behind a transition to La Niña in early 2020 that maintains the P2 pattern.
