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Abstract
This paper introduces a newly compiled set of feature-based climatologies identified from ERA-Interim (1979–2014). Two categories of flow features are considered: (i) Eulerian climatologies of jet streams, tropopause folds, surface fronts, cyclones and anticyclones, blocks, and potential vorticity streamers and cutoffs and (ii) Lagrangian climatologies, based on a large ensemble of air parcel trajectories, of stratosphere–troposphere exchange, warm conveyor belts, and tropical moisture exports. Monthly means of these feature climatologies are openly available at the ETH Zürich web page (http://eraiclim.ethz.ch) and are annually updated. Datasets at higher resolution can be obtained from the authors on request. These feature climatologies allow studying the frequency, variability, and trend of atmospheric phenomena and their interrelationships across temporal scales. To illustrate the potential of this dataset, boreal winter climatologies of selected features are presented and, as a first application, the very unusual Northern Hemispheric winter of 2009/10 is identified as the season when most of the considered features show maximum deviations from climatology. The second application considers dry winters in the western United States and reveals fairly localized anomalies in the eastern North Pacific of enhanced blocking and surface anticyclones and reduced cyclones.
Abstract
This paper introduces a newly compiled set of feature-based climatologies identified from ERA-Interim (1979–2014). Two categories of flow features are considered: (i) Eulerian climatologies of jet streams, tropopause folds, surface fronts, cyclones and anticyclones, blocks, and potential vorticity streamers and cutoffs and (ii) Lagrangian climatologies, based on a large ensemble of air parcel trajectories, of stratosphere–troposphere exchange, warm conveyor belts, and tropical moisture exports. Monthly means of these feature climatologies are openly available at the ETH Zürich web page (http://eraiclim.ethz.ch) and are annually updated. Datasets at higher resolution can be obtained from the authors on request. These feature climatologies allow studying the frequency, variability, and trend of atmospheric phenomena and their interrelationships across temporal scales. To illustrate the potential of this dataset, boreal winter climatologies of selected features are presented and, as a first application, the very unusual Northern Hemispheric winter of 2009/10 is identified as the season when most of the considered features show maximum deviations from climatology. The second application considers dry winters in the western United States and reveals fairly localized anomalies in the eastern North Pacific of enhanced blocking and surface anticyclones and reduced cyclones.
Stratosphere–troposphere exchange (STE) is important for the chemical composition of both the stratosphere and troposphere. Modifications of STE in a changing climate may affect stratospheric ozone depletion and the oxidizing capacity of the troposphere significantly. However, STE is still poorly understood and inadequately quantified, due to the involvement of physical and dynamical processes on local to global scales and to conceptual problems. In this study, a presentday global climatology of STE is developed that is based, from a data standpoint, on 15 yr of global meteorological reanalyses, and, from a conceptual standpoint, on a Lagrangian perspective that considers the pathways of exchange air parcels and their residence times in the troposphere and lowermost stratosphere. To this end, two complementary Lagrangian models are used. Particular consideration is given to “deep” exchange events that, through fast ascent of tropospheric or fast descent of stratospheric air masses, bring into contact air from the (potentially polluted) boundary layer and lower stratosphere. It is shown that they have different characteristics (strongly preferred geographical locations and a pronounced seasonal cycle) from that of the full set of exchange events. This result is important for accurately characterizing the effects of STE. In particular, it can be inferred that the well-documented springtime maximum of surface ozone cannot be explained primarily by STE.
Stratosphere–troposphere exchange (STE) is important for the chemical composition of both the stratosphere and troposphere. Modifications of STE in a changing climate may affect stratospheric ozone depletion and the oxidizing capacity of the troposphere significantly. However, STE is still poorly understood and inadequately quantified, due to the involvement of physical and dynamical processes on local to global scales and to conceptual problems. In this study, a presentday global climatology of STE is developed that is based, from a data standpoint, on 15 yr of global meteorological reanalyses, and, from a conceptual standpoint, on a Lagrangian perspective that considers the pathways of exchange air parcels and their residence times in the troposphere and lowermost stratosphere. To this end, two complementary Lagrangian models are used. Particular consideration is given to “deep” exchange events that, through fast ascent of tropospheric or fast descent of stratospheric air masses, bring into contact air from the (potentially polluted) boundary layer and lower stratosphere. It is shown that they have different characteristics (strongly preferred geographical locations and a pronounced seasonal cycle) from that of the full set of exchange events. This result is important for accurately characterizing the effects of STE. In particular, it can be inferred that the well-documented springtime maximum of surface ozone cannot be explained primarily by STE.
Abstract
Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limited-area numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.
Abstract
Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limited-area numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.
The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.
The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.
Abstract
Between March 15-19, 2022, East Antarctica experienced an exceptional heatwave with widespread 30-40° C temperature anomalies across the ice sheet. In Part I, we assessed the meteorological drivers that generated an intense atmospheric river (AR) which caused these record-shattering temperature anomalies. Here in Part II, we continue our large, collaborative study by analyzing the widespread and diverse impacts driven by the AR landfall.
These impacts included widespread rain and surface melt which was recorded along coastal areas, but this was outweighed by widespread, high snowfall accumulations resulting in a largely positive surface mass balance contribution to the East Antarctic region. An analysis of the surface energy budget indicated that widespread downward longwave radiation anomalies caused by large cloud-liquid water contents along with some scattered solar radiation produced intense surface warming. Isotope measurements of the moisture were highly elevated, likely imprinting a strong signal for past climate reconstructions. The AR event attenuated cosmic ray measurements at Concordia, something previously never observed. Finally, an extratropical cyclone west of the AR landfall likely triggered the final collapse of the critically unstable Conger Ice Shelf while further reducing an already record low sea-ice extent.
Abstract
Between March 15-19, 2022, East Antarctica experienced an exceptional heatwave with widespread 30-40° C temperature anomalies across the ice sheet. In Part I, we assessed the meteorological drivers that generated an intense atmospheric river (AR) which caused these record-shattering temperature anomalies. Here in Part II, we continue our large, collaborative study by analyzing the widespread and diverse impacts driven by the AR landfall.
These impacts included widespread rain and surface melt which was recorded along coastal areas, but this was outweighed by widespread, high snowfall accumulations resulting in a largely positive surface mass balance contribution to the East Antarctic region. An analysis of the surface energy budget indicated that widespread downward longwave radiation anomalies caused by large cloud-liquid water contents along with some scattered solar radiation produced intense surface warming. Isotope measurements of the moisture were highly elevated, likely imprinting a strong signal for past climate reconstructions. The AR event attenuated cosmic ray measurements at Concordia, something previously never observed. Finally, an extratropical cyclone west of the AR landfall likely triggered the final collapse of the critically unstable Conger Ice Shelf while further reducing an already record low sea-ice extent.
Abstract
Between March 15-19, 2022, East Antarctica experienced an exceptional heatwave with widespread 30-40° C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of -9.4° C on March 18 at Concordia Station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an intense atmospheric river advecting subtropical/mid-latitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heatwave’s meteorological drivers, impacts, and historical climate context.
Here we focus on describing those temperature records along with the intricate meteorological drivers that led to the most intense atmospheric river observed over East Antarctica. These efforts describe the Rossby wave activity forced from intense tropical convection over the Indian Ocean. This led to an atmospheric river and warm conveyor belt intensification near the coastline which reinforced atmospheric blocking deep into East Antarctica. The resulting moisture flux and upper-level warm air advection eroded the typical surface temperature inversions over the ice sheet. At the peak of the heatwave, an area of 3.3 million km2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about one hundred years, a closer recurrence of such an event is possible under future climate projections. In a subsequent manuscript, we describe the various impacts this extreme event had on the East Antarctic cryosphere.
Abstract
Between March 15-19, 2022, East Antarctica experienced an exceptional heatwave with widespread 30-40° C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of -9.4° C on March 18 at Concordia Station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an intense atmospheric river advecting subtropical/mid-latitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heatwave’s meteorological drivers, impacts, and historical climate context.
Here we focus on describing those temperature records along with the intricate meteorological drivers that led to the most intense atmospheric river observed over East Antarctica. These efforts describe the Rossby wave activity forced from intense tropical convection over the Indian Ocean. This led to an atmospheric river and warm conveyor belt intensification near the coastline which reinforced atmospheric blocking deep into East Antarctica. The resulting moisture flux and upper-level warm air advection eroded the typical surface temperature inversions over the ice sheet. At the peak of the heatwave, an area of 3.3 million km2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about one hundred years, a closer recurrence of such an event is possible under future climate projections. In a subsequent manuscript, we describe the various impacts this extreme event had on the East Antarctic cryosphere.
