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Abstract
The first campaign-based measurements of virtual temperature in the upper-troposphere and lower-stratosphere (UTLS) region were made with the middle- and upper-atmosphere (MU) radar radio acoustic sounding system (RASS) during 4 days in August 1995. This dataset was examined in order to study high-frequency changes in the stability below 20 km, but especially in the UTLS region. Calculations of the WMO tropopause and cold-point tropopause heights showed the latter to be (1.0 ± 0.6) km higher, where 0.6 km is the standard deviation. A diurnal cycle of temperature and wind dominated the spectra, which was identified as the diurnal solar tide. Its phase maximum occurred in the afternoon between 5 and 15 km and showed upward energy propagation above this height. Changes in the UTLS kinetic energy dissipation rate ε showed significant high-frequency fluctuations embedded within layers that persisted for at least 1 day. Relative to the WMO tropopause height, the median ε increased from (0.5 ± 0.1) × 10−3 m2 s−3 in the upper troposphere to (0.7 ± 0.1) × 10−3 m2 s−3 in the lower stratosphere.
Abstract
The first campaign-based measurements of virtual temperature in the upper-troposphere and lower-stratosphere (UTLS) region were made with the middle- and upper-atmosphere (MU) radar radio acoustic sounding system (RASS) during 4 days in August 1995. This dataset was examined in order to study high-frequency changes in the stability below 20 km, but especially in the UTLS region. Calculations of the WMO tropopause and cold-point tropopause heights showed the latter to be (1.0 ± 0.6) km higher, where 0.6 km is the standard deviation. A diurnal cycle of temperature and wind dominated the spectra, which was identified as the diurnal solar tide. Its phase maximum occurred in the afternoon between 5 and 15 km and showed upward energy propagation above this height. Changes in the UTLS kinetic energy dissipation rate ε showed significant high-frequency fluctuations embedded within layers that persisted for at least 1 day. Relative to the WMO tropopause height, the median ε increased from (0.5 ± 0.1) × 10−3 m2 s−3 in the upper troposphere to (0.7 ± 0.1) × 10−3 m2 s−3 in the lower stratosphere.
Abstract
The very high frequency (VHF) middle and upper atmosphere radar radio acoustic sounding system (MU-RASS) in Shigaraki, Japan, is able to provide tropospheric virtual temperature data with high temporal resolution on the order of a few minutes. The objective of this paper is to test the usefulness of MU-RASS as a tool for examining high-frequency changes in atmospheric stability and its effects on wave and energy propagation. For this study, temperature and wind data below 8-km altitude during a 2-day campaign period in October 2001 were used. A long-lasting inversion layer at 3.5-km altitude dominated the observation period. Large vertical wind perturbations with periods of less than 30 min were observed inside this inversion layer. Wavelet analysis was used to identify the dominant wave period for calculating the wind and temperature variances. The temperature variance characteristics exhibited a combination of the horizontal and vertical wind variance characteristics. In conclusion, the high temporal resolution of the MU-RASS enabled the study of short time-scale wind and temperature perturbations. These perturbations were related to the atmospheric stability, wave propagation, and energy in the troposphere, demonstrating the usefulness of the MU-RASS for this kind of study.
Abstract
The very high frequency (VHF) middle and upper atmosphere radar radio acoustic sounding system (MU-RASS) in Shigaraki, Japan, is able to provide tropospheric virtual temperature data with high temporal resolution on the order of a few minutes. The objective of this paper is to test the usefulness of MU-RASS as a tool for examining high-frequency changes in atmospheric stability and its effects on wave and energy propagation. For this study, temperature and wind data below 8-km altitude during a 2-day campaign period in October 2001 were used. A long-lasting inversion layer at 3.5-km altitude dominated the observation period. Large vertical wind perturbations with periods of less than 30 min were observed inside this inversion layer. Wavelet analysis was used to identify the dominant wave period for calculating the wind and temperature variances. The temperature variance characteristics exhibited a combination of the horizontal and vertical wind variance characteristics. In conclusion, the high temporal resolution of the MU-RASS enabled the study of short time-scale wind and temperature perturbations. These perturbations were related to the atmospheric stability, wave propagation, and energy in the troposphere, demonstrating the usefulness of the MU-RASS for this kind of study.
Abstract
The special observing periods (SOPs) of the Year of Polar Prediction present an opportunity to assess the skill of numerical weather prediction (NWP) models operating over the Antarctic, many of which assimilated additional observations during an SOP to produce some of the most observationally informed model output to date for the Antarctic region and permitting closer examination of model performance under various configurations and parameterizations. This intercomparison evaluates six NWP models spanning global and limited domains, coupled and uncoupled, operating in the Antarctic during the austral summer SOP between 16 November 2018 and 15 February 2019. Model performance varies regionally between each model and parameter; however, the majority of models were found to be warm biased over the continent with respect to ERA5 at analysis, some with biases growing to 3.5 K over land after 48 h. Temperature biases over sea ice were found to be strongly correlated between analysis and 48 h in uncoupled models, but that this correlation can be reduced through coupling to a sea ice model. Surface pressure and 500-hPa geopotential height forecasts and biases were found to be strongly correlated over open ocean in all models, and wind speed forecasts were found to be generally more skillful at higher resolutions with the exception of fast modeled winds over sloping terrain in PolarWRF. Surface sensible and latent heat flux forecasts and biases produced diverse correlations, varying by model, parameter, and gridcell classification. Of the models evaluated, those which couple atmosphere, sea ice, and ocean typically exhibited stronger skill.
Significance Statement
We evaluated the performance of six numerical weather prediction models operating over the Antarctic during the Year of Polar Prediction austral summer special observing period (16 November 2018–15 February 2019). Our analysis found that several models were as much as 3.5 K warmer than the reference analysis (ERA5) at 48 h over land and were strongly correlated over sea ice in uncoupled models; however, this correlation is reduced through coupling to a sea ice model. Surface pressure biases are communicated to the midtroposphere over the ocean at larger spatial scales, while higher resolution showed an increase in positive wind biases at longer forecasts. Surface turbulent heat fluxes produced complex correlations with other forecast parameters, which should be quantified in future studies. Coupled models that included an ocean/sea ice component typically performed better; providing evidence that the inclusion of such components leads to improved model performance, even at short time scales such as these.
Abstract
The special observing periods (SOPs) of the Year of Polar Prediction present an opportunity to assess the skill of numerical weather prediction (NWP) models operating over the Antarctic, many of which assimilated additional observations during an SOP to produce some of the most observationally informed model output to date for the Antarctic region and permitting closer examination of model performance under various configurations and parameterizations. This intercomparison evaluates six NWP models spanning global and limited domains, coupled and uncoupled, operating in the Antarctic during the austral summer SOP between 16 November 2018 and 15 February 2019. Model performance varies regionally between each model and parameter; however, the majority of models were found to be warm biased over the continent with respect to ERA5 at analysis, some with biases growing to 3.5 K over land after 48 h. Temperature biases over sea ice were found to be strongly correlated between analysis and 48 h in uncoupled models, but that this correlation can be reduced through coupling to a sea ice model. Surface pressure and 500-hPa geopotential height forecasts and biases were found to be strongly correlated over open ocean in all models, and wind speed forecasts were found to be generally more skillful at higher resolutions with the exception of fast modeled winds over sloping terrain in PolarWRF. Surface sensible and latent heat flux forecasts and biases produced diverse correlations, varying by model, parameter, and gridcell classification. Of the models evaluated, those which couple atmosphere, sea ice, and ocean typically exhibited stronger skill.
Significance Statement
We evaluated the performance of six numerical weather prediction models operating over the Antarctic during the Year of Polar Prediction austral summer special observing period (16 November 2018–15 February 2019). Our analysis found that several models were as much as 3.5 K warmer than the reference analysis (ERA5) at 48 h over land and were strongly correlated over sea ice in uncoupled models; however, this correlation is reduced through coupling to a sea ice model. Surface pressure biases are communicated to the midtroposphere over the ocean at larger spatial scales, while higher resolution showed an increase in positive wind biases at longer forecasts. Surface turbulent heat fluxes produced complex correlations with other forecast parameters, which should be quantified in future studies. Coupled models that included an ocean/sea ice component typically performed better; providing evidence that the inclusion of such components leads to improved model performance, even at short time scales such as these.
Abstract
Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SWdown exhibited large errors (mean bias = 54 W m−2, mean absolute error = 82 W m−2, root-mean-square error = 132 W m−2, and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SWdown with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SWdown using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.
Significance Statement
Simulating the amount of sunlight reaching Earth’s surface is difficult because it relies on a good understanding of how much clouds absorb and scatter sunlight. Relative to summertime surface observations, the ERA5 reanalysis still overestimates the amount of sunlight entering the Southern Ocean. We taught some models how to predict the amount of sunlight entering the Southern Ocean using 25 years of surface observations and a small set of meteorological variables from ERA5. By bypassing the ERA5’s internal simulation of the absorption and scattering of sunlight, we can drastically reduce biases in the predicted surface shortwave radiation. Large improvements in cold sectors of cyclones and closer to Antarctica were observed in regions where many numerical models struggle to simulate the amount of incoming sunlight correctly.
Abstract
Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SWdown exhibited large errors (mean bias = 54 W m−2, mean absolute error = 82 W m−2, root-mean-square error = 132 W m−2, and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SWdown with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SWdown using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.
Significance Statement
Simulating the amount of sunlight reaching Earth’s surface is difficult because it relies on a good understanding of how much clouds absorb and scatter sunlight. Relative to summertime surface observations, the ERA5 reanalysis still overestimates the amount of sunlight entering the Southern Ocean. We taught some models how to predict the amount of sunlight entering the Southern Ocean using 25 years of surface observations and a small set of meteorological variables from ERA5. By bypassing the ERA5’s internal simulation of the absorption and scattering of sunlight, we can drastically reduce biases in the predicted surface shortwave radiation. Large improvements in cold sectors of cyclones and closer to Antarctica were observed in regions where many numerical models struggle to simulate the amount of incoming sunlight correctly.
Abstract
Southern Hemisphere extratropical gravity wave activity is examined using simulations from a free-running middle-atmosphere general circulation model called Kanto that contains no gravity wave parameterizations. The total absolute gravity wave momentum flux (MF) and its intermittency, diagnosed by the Gini coefficient, are examined during January and July. The MF and intermittency results calculated from the Kanto model agree well with results from satellite limb and superpressure balloon observations. The analysis of the Kanto model simulations indicates the following results. Nonorographic gravity waves are generated in Kanto in the frontal regions of extratropical depressions and around tropopause-level jets. Regions with lower (higher) intermittency in the July midstratosphere become more (less) intermittent by the mesosphere as a result of lower-level wave removal. The gravity wave intermittency is low and nearly homogeneous throughout the SH middle atmosphere during January. This indicates that nonorographic waves dominate at this time of year, with sources including continental convection as well as oceanic depressions. Most of the zonal-mean MF at 40°–65°S in January and July is due to gravity waves located above the oceans. The zonal-mean MF at lower latitudes in both months has a larger contribution from the land regions but the fraction above the oceans remains larger.
Abstract
Southern Hemisphere extratropical gravity wave activity is examined using simulations from a free-running middle-atmosphere general circulation model called Kanto that contains no gravity wave parameterizations. The total absolute gravity wave momentum flux (MF) and its intermittency, diagnosed by the Gini coefficient, are examined during January and July. The MF and intermittency results calculated from the Kanto model agree well with results from satellite limb and superpressure balloon observations. The analysis of the Kanto model simulations indicates the following results. Nonorographic gravity waves are generated in Kanto in the frontal regions of extratropical depressions and around tropopause-level jets. Regions with lower (higher) intermittency in the July midstratosphere become more (less) intermittent by the mesosphere as a result of lower-level wave removal. The gravity wave intermittency is low and nearly homogeneous throughout the SH middle atmosphere during January. This indicates that nonorographic waves dominate at this time of year, with sources including continental convection as well as oceanic depressions. Most of the zonal-mean MF at 40°–65°S in January and July is due to gravity waves located above the oceans. The zonal-mean MF at lower latitudes in both months has a larger contribution from the land regions but the fraction above the oceans remains larger.
Abstract
The offshore extent of Antarctic katabatic winds exerts a strong control on the production of sea ice and the formation of polynyas. In this study, we make use of a combination of ground-based remotely sensed and meteorological measurements at Dumont d’Urville (DDU) station, satellite images, and simulations with the Weather Research and Forecasting Model to analyze a major katabatic wind event in Adélie Land. Once well developed over the slope of the ice sheet, the katabatic flow experiences an abrupt transition near the coastal edge consisting of a sharp increase in the boundary layer depth, a sudden decrease in wind speed, and a decrease in Froude number from 3.5 to 0.3. This so-called katabatic jump manifests as a turbulent “wall” of blowing snow in which updrafts exceed 5 m s−1. The wall reaches heights of 1000 m and its horizontal extent along the coast is more than 400 km. By destabilizing the boundary layer downstream, the jump favors the trapping of a gravity wave train—with a horizontal wavelength of 10.5 km—that develops in a few hours. The trapped gravity waves exert a drag that considerably slows down the low-level outflow. Moreover, atmospheric rotors form below the first wave crests. The wind speed record measured at DDU in 2017 (58.5 m s−1) is due to the vertical advection of momentum by a rotor. A statistical analysis of observations at DDU reveals that katabatic jumps and low-level trapped gravity waves occur frequently over coastal Adélie Land. It emphasizes the important role of such phenomena in the coastal Antarctic dynamics.
Abstract
The offshore extent of Antarctic katabatic winds exerts a strong control on the production of sea ice and the formation of polynyas. In this study, we make use of a combination of ground-based remotely sensed and meteorological measurements at Dumont d’Urville (DDU) station, satellite images, and simulations with the Weather Research and Forecasting Model to analyze a major katabatic wind event in Adélie Land. Once well developed over the slope of the ice sheet, the katabatic flow experiences an abrupt transition near the coastal edge consisting of a sharp increase in the boundary layer depth, a sudden decrease in wind speed, and a decrease in Froude number from 3.5 to 0.3. This so-called katabatic jump manifests as a turbulent “wall” of blowing snow in which updrafts exceed 5 m s−1. The wall reaches heights of 1000 m and its horizontal extent along the coast is more than 400 km. By destabilizing the boundary layer downstream, the jump favors the trapping of a gravity wave train—with a horizontal wavelength of 10.5 km—that develops in a few hours. The trapped gravity waves exert a drag that considerably slows down the low-level outflow. Moreover, atmospheric rotors form below the first wave crests. The wind speed record measured at DDU in 2017 (58.5 m s−1) is due to the vertical advection of momentum by a rotor. A statistical analysis of observations at DDU reveals that katabatic jumps and low-level trapped gravity waves occur frequently over coastal Adélie Land. It emphasizes the important role of such phenomena in the coastal Antarctic dynamics.
Abstract
Understanding the key dynamical and microphysical mechanisms driving precipitation in the Snowy Mountains region of southeast Australia, including the role of orography, can help improve precipitation forecasts, which is of great value for efficient water management. An intensive observation campaign was carried out during the 2018 austral winter, providing a comprehensive range of ground-based observations across the Snowy Mountains. We used data from three vertically pointing rain radars, cloud radar, a PARSIVEL disdrometer, and a network of 76 pluviometers. The observations reveal that all of the precipitation events were associated with cold front passages. About half accumulated during the frontal passage associated with deep, fully glaciated cloud tops, while the rest occurred in the postfrontal environment and were associated with clouds with supercooled liquid water (SLW) tops. About three-quarters of the accumulated precipitation was observed under blocked conditions, likely associated with blocked stratiform orographic enhancement. Specifically, more than a third of the precipitation resulted from moist cloudless air being lifted over stagnant air, upwind from the barrier, creating SLW-top clouds. These SLW clouds then produced stratiform precipitation mostly over the upwind slopes and mountain tops, with hydrometeors reaching the mountain tops mostly as rimed snow. Two precipitation events were studied in detail, which showed that during unblocked conditions, orographic convection invigoration and unblocked stratiform enhancement were the two main mechanisms driving the precipitation, with the latter being more prevalent after the frontal passage. During these events, ice particle growth was likely dominated by vapor deposition and aggregation during the frontal periods, while riming dominated during the postfrontal periods.
Abstract
Understanding the key dynamical and microphysical mechanisms driving precipitation in the Snowy Mountains region of southeast Australia, including the role of orography, can help improve precipitation forecasts, which is of great value for efficient water management. An intensive observation campaign was carried out during the 2018 austral winter, providing a comprehensive range of ground-based observations across the Snowy Mountains. We used data from three vertically pointing rain radars, cloud radar, a PARSIVEL disdrometer, and a network of 76 pluviometers. The observations reveal that all of the precipitation events were associated with cold front passages. About half accumulated during the frontal passage associated with deep, fully glaciated cloud tops, while the rest occurred in the postfrontal environment and were associated with clouds with supercooled liquid water (SLW) tops. About three-quarters of the accumulated precipitation was observed under blocked conditions, likely associated with blocked stratiform orographic enhancement. Specifically, more than a third of the precipitation resulted from moist cloudless air being lifted over stagnant air, upwind from the barrier, creating SLW-top clouds. These SLW clouds then produced stratiform precipitation mostly over the upwind slopes and mountain tops, with hydrometeors reaching the mountain tops mostly as rimed snow. Two precipitation events were studied in detail, which showed that during unblocked conditions, orographic convection invigoration and unblocked stratiform enhancement were the two main mechanisms driving the precipitation, with the latter being more prevalent after the frontal passage. During these events, ice particle growth was likely dominated by vapor deposition and aggregation during the frontal periods, while riming dominated during the postfrontal periods.
Abstract
Global positioning system (GPS) radio occultation (RO) observations, first made of Earth’s atmosphere in 1995, have contributed in new ways to the understanding of the thermal structure and variability of the tropical upper troposphere–lower stratosphere (UTLS), an important component of the climate system. The UTLS plays an essential role in the global radiative balance, the exchange of water vapor, ozone, and other chemical constituents between the troposphere and stratosphere, and the transfer of energy from the troposphere to the stratosphere. With their high accuracy, precision, vertical resolution, and global coverage, RO observations are uniquely suited for studying the UTLS and a broad range of equatorial waves, including gravity waves, Kelvin waves, Rossby and mixed Rossby–gravity waves, and thermal tides. Because RO measurements are nearly unaffected by clouds, they also resolve the upper-level thermal structure of deep convection and tropical cyclones as well as volcanic clouds. Their low biases and stability from mission to mission make RO observations powerful tools for studying climate variability and trends, including the annual cycle and intraseasonal-to-interannual atmospheric modes of variability such as the quasi-biennial oscillation (QBO), Madden–Julian oscillation (MJO), and El Niño–Southern Oscillation (ENSO). These properties also make them useful for evaluating climate models and detection of small trends in the UTLS temperature, key indicators of climate change. This paper reviews the contributions of RO observations to the understanding of the three-dimensional structure of tropical UTLS phenomena and their variability over time scales ranging from hours to decades and longer.
Abstract
Global positioning system (GPS) radio occultation (RO) observations, first made of Earth’s atmosphere in 1995, have contributed in new ways to the understanding of the thermal structure and variability of the tropical upper troposphere–lower stratosphere (UTLS), an important component of the climate system. The UTLS plays an essential role in the global radiative balance, the exchange of water vapor, ozone, and other chemical constituents between the troposphere and stratosphere, and the transfer of energy from the troposphere to the stratosphere. With their high accuracy, precision, vertical resolution, and global coverage, RO observations are uniquely suited for studying the UTLS and a broad range of equatorial waves, including gravity waves, Kelvin waves, Rossby and mixed Rossby–gravity waves, and thermal tides. Because RO measurements are nearly unaffected by clouds, they also resolve the upper-level thermal structure of deep convection and tropical cyclones as well as volcanic clouds. Their low biases and stability from mission to mission make RO observations powerful tools for studying climate variability and trends, including the annual cycle and intraseasonal-to-interannual atmospheric modes of variability such as the quasi-biennial oscillation (QBO), Madden–Julian oscillation (MJO), and El Niño–Southern Oscillation (ENSO). These properties also make them useful for evaluating climate models and detection of small trends in the UTLS temperature, key indicators of climate change. This paper reviews the contributions of RO observations to the understanding of the three-dimensional structure of tropical UTLS phenomena and their variability over time scales ranging from hours to decades and longer.
Abstract
Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave 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 18 March 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/midlatitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heat wave’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 heat wave, an area of 3.3 million km2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about 100 years, a closer recurrence of such an event is possible under future climate projections. In Part II we describe the various impacts this extreme event had on the East Antarctic cryosphere.
Significance Statement
In March 2022, a heat wave and atmospheric river caused some of the highest temperature anomalies ever observed globally and captured the attention of the Antarctic science community. Using our diverse collective expertise, we explored the causes of the event and have placed it within a historical climate context. One key takeaway is that Antarctic climate extremes are highly sensitive to perturbations in the midlatitudes and subtropics. This heat wave redefined our expectations of the Antarctic climate. Despite the rare chance of occurrence based on past climate, a future temperature extreme event of similar magnitude is possible, especially given anthropogenic climate change.
Abstract
Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave 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 18 March 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/midlatitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heat wave’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 heat wave, an area of 3.3 million km2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about 100 years, a closer recurrence of such an event is possible under future climate projections. In Part II we describe the various impacts this extreme event had on the East Antarctic cryosphere.
Significance Statement
In March 2022, a heat wave and atmospheric river caused some of the highest temperature anomalies ever observed globally and captured the attention of the Antarctic science community. Using our diverse collective expertise, we explored the causes of the event and have placed it within a historical climate context. One key takeaway is that Antarctic climate extremes are highly sensitive to perturbations in the midlatitudes and subtropics. This heat wave redefined our expectations of the Antarctic climate. Despite the rare chance of occurrence based on past climate, a future temperature extreme event of similar magnitude is possible, especially given anthropogenic climate change.
