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A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere-land-ocean-sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the annual means. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states. [ABSTRACT FROM AUTHOR]

We present a comprehensive analysis of Arctic surface energy budget (SEB) components during atmospheric river (AR) events identified by integrated water vapor transport exceeding the monthly 85th percentile climatological threshold in 3-hourly ERA5 reanalysis data from January 1980 to December 2015. Analysis of average anomalies in SEB components, net SEB, and the overall AR contribution to the total seasonal SEB reveals clear seasonality and distinct land – sea – sea ice contrast patterns. Over the sea ice-covered central Arctic Ocean, ARs significantly impact net SEB, inducing substantial surface warming in fall, winter, and spring, primarily driven by large anomalies in surface downward longwave radiation. We find that ARs make a substantial relative contribution to the mean SEB in spring (32 %), exceeding their corresponding occurrence frequency (11 %). However, in other seasons, ARs contribute relatively less to the mean SEB than their frequency, indicating a diminished role compared to their occurrence frequency. Over sub-polar oceans, ARs have the most substantial positive impact on net SEB in cold seasons, mainly attributed to significant positive turbulent heat flux anomalies, with a maximum contribution to the mean SEB in spring averaging 65 %. In summer, ARs induce negative impacts on net SEB, primarily due to reduced shortwave radiation from increased cloud cover during AR events. Over continents, ARs generate smaller absolute impacts on net SEB but contribute significantly to the mean SEB in cold seasons, far surpassing their corresponding frequency, highlighting their crucial role in determining the net SEB over continents during cold seasons. Greenland, especially western Greenland, exhibits significant downward longwave radiation anomalies associated with ARs, which drive large net SEB anomalies and contribute >54 % to mean SEB, and induce amplified surface warming year-round. This holds significance for melt events, particularly during summer. This study quantifies the role of ARs on surface energy budget, contributing to our understanding of the Arctic warming and sea ice decline in ongoing Arctic amplification. [ABSTRACT FROM AUTHOR]

Atmospheric measurements taken over the span of an entire year between October 2019 and September 2020 during the icebreaker-based Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide insight into processes acting in the Arctic atmosphere. Through the merging of disparate yet complementary in situ observations, we can derive information about these thermodynamic and kinematic processes with great detail. This paper describes methods used to create a lower-atmospheric properties dataset containing information on several key features relating to the central Arctic atmospheric boundary layer, including properties of temperature inversions, low-level jets, near-surface meteorological conditions, cloud cover, and the surface radiation budget. The lower-atmospheric properties dataset was developed using observations from radiosondes launched at least four times per day, a 10 m meteorological tower and radiation station deployed on the sea ice near the research vessel Polarstern, and a ceilometer located on the deck of the Polarstern. This lower-atmospheric properties dataset, which can be found at 10.1594/PANGAEA.957760 (Jozef et al., 2023), contains metrics which fall into the overarching categories of temperature, wind, stability, clouds, and radiation at the time of each radiosonde launch. The purpose of the lower-atmospheric properties dataset is to provide a consistent description of general atmospheric boundary layer conditions throughout the MOSAiC year, which can aid in research applications with the overall goal of gaining a greater understanding of the atmospheric processes governing the central Arctic and how they may contribute to future climate change. [ABSTRACT FROM AUTHOR]

Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide a detailed description of the impact of thermodynamic and kinematic forcings on atmospheric boundary layer (ABL) stability in the central Arctic. This study reveals that the Arctic ABL is stable and near-neutral with similar frequencies, and strong stability is the most persistent of all stability regimes. MOSAiC radiosonde observations, in conjunction with observations from additional measurement platforms, including a 10 m meteorological tower, ceilometer, microwave radiometer, and radiation station, provide insight into the relationships between atmospheric stability and various atmospheric thermodynamic and kinematic forcings of ABL turbulence and how these relationships differ by season. We found that stronger stability largely occurs in low-wind (i.e., wind speeds are slow), low-radiation (i.e., surface radiative fluxes are minimal) environments; a very shallow mixed ABL forms in low-wind, high-radiation environments; weak stability occurs in high-wind, moderate-radiation environments; and a near-neutral ABL forms in high-wind, high-radiation environments. Surface pressure (a proxy for synoptic staging) partially explains the observed wind speeds for different stability regimes. Cloud frequency and atmospheric moisture contribute to the observed surface radiation budget. Unique to summer, stronger stability may also form when moist air is advected from over the warmer open ocean to over the colder sea ice surface, which decouples the colder near-surface atmosphere from the advected layer, and is identifiable through observations of fog and atmospheric moisture. [ABSTRACT FROM AUTHOR]

Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide a detailed description of the impact of thermodynamic and kinematic forcings on atmospheric boundary layer (ABL) stability in the central Arctic. This study reveals that the Arctic ABL is stable and near-neutral with similar frequencies, and strong stability is the most persistent of all stability regimes. MOSAiC radiosonde observations, in conjunction with observations from additional measurement platforms including a 10 m meteorological tower, ceilometer, microwave radiometer, and radiation station, provide insight into the relationships between atmospheric stability and various atmospheric thermodynamic and kinematic forcings of ABL turbulence, and how these relationships differ by season. We found that stronger stability largely occurs in low wind (i.e., wind speeds are slow), low radiation (i.e., surface radiative fluxes are minimal) environments, a very shallow mixed ABL forms in low wind, high radiation environments, weak stability occurs in high wind, moderate radiation environments, and a near-neutral ABL forms in high wind, high radiation environments. Surface pressure (a proxy for synoptic staging) partially explains the observed wind speeds for different stability regimes. Cloud frequency and atmospheric moisture contribute to the observed surface radiation budget. Unique to summer, stronger stability may also form when moist air is advected from over the warmer open ocean to over the colder sea ice surface, which decouples the colder near-surface atmosphere from the advected layer, and is identifiable through observations of fog and atmospheric moisture. [ABSTRACT FROM AUTHOR]

During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s -1) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere. [ABSTRACT FROM AUTHOR]

Over a five-month time window between March and July 2020, scientists deployed two small uncrewed aircraft systems (sUAS) to the central Arctic Ocean as part of legs three and four of the MOSAiC expedition. These sUAS were flown to measure the thermodynamic and kinematic state of the lower atmosphere, including collecting information on temperature, pressure, humidity and winds between the surface and 1 km, as well as to document ice properties, including albedo, melt pond fraction, and open water amounts. The atmospheric state flights were primarily conducted by the DataHawk2 sUAS, which was operated primarily in a profiling manner, while the surface property flights were conducted using the HELiX sUAS, which flew grid patterns, profiles, and hover flights. In total, over 120 flights were conducted and over 48 flight hours of data were collected, sampling conditions that included temperatures as low as −35 °C and as warm as 15 °C, spanning the summer melt season. Measurement(s) NetCDF files include full description of all variables Technology Type(s) Uncrewed Aircraft Systems [ABSTRACT FROM AUTHOR]

During the winter of 2019/2020, as the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project started its work, the Arctic Oscillation (AO) experienced some of its largest shifts, ranging from a highly negative index in November 2019 to an extremely positive index during January–February–March (JFM) 2020. The permanent positive AO phase for the 3 months of JFM 2020 was accompanied by a prevailing positive phase of the Arctic Dipole (AD) pattern. Here we analyze the sea ice thickness (SIT) distribution based on CryoSat-2/SMOS satellite-derived data augmented with results from the hindcast simulation by the fully coupled Regional Arctic System Model (RASM) from November 2019 through March 2020. A notable result of the positive AO phase during JFM 2020 was large SIT anomalies of up to 1.3 m that emerged in the Barents Sea (BS), along the northeastern Canadian coast and in parts of the central Arctic Ocean. These anomalies appear to be driven by nonlinear interactions between thermodynamic and dynamic processes. In particular, in the Barents and Kara seas (BKS), they are a result of enhanced ice growth connected with low-temperature anomalies and the consequence of intensified atmospherically driven sea ice transport and deformations (i.e., ice divergence and shear) in this area. The Davies Strait, the east coast of Greenland and the BS regions are characterized by convergence and divergence changes connected with thinner sea ice at the ice borders along with an enhanced impact of atmospheric wind forcing. Low-pressure anomalies that developed over the eastern Arctic during JFM 2020 increased northerly winds from the cold Arctic Ocean to the BS and accelerated the southward drift of the MOSAiC ice floe. The satellite-derived and simulated sea ice velocity anomalies, which compared well during JFM 2020, indicate a strong acceleration of the Transpolar Drift relative to the mean for the past decade, with intensified speeds of up to 6 km d -1. As a consequence, sea ice transport and deformations driven by atmospheric surface wind forcing accounted for the bulk of the SIT anomalies, especially in January 2020 and February 2020. RASM intra-annual ensemble forecast simulations with 30 ensemble members forced with different atmospheric boundary conditions from 1 November 2019 through 30 April 2020 show a pronounced internal variability in the sea ice volume, driven by thermodynamic ice-growth and ice-melt processes and the impact of dynamic surface winds on sea ice formation and deformation. A comparison of the respective SIT distributions and turbulent heat fluxes during the positive AO phase in JFM 2020 and the negative AO phase in JFM 2010 corroborates the conclusion that winter sea ice conditions in the Arctic Ocean can be significantly altered by AO variability. [ABSTRACT FROM AUTHOR]

Between January 2012 and June 2017 a small unmanned aerial system (sUAS), known as the Small Unmanned Meteorological Observer (SUMO), was used to observe the state of the atmospheric boundary layer in the Antarctic. During six Antarctic field campaigns, 116 SUMO flights were completed. These flights took place during all seasons over both permanent ice and ice-free locations on the Antarctic continent and over sea ice in the western Ross Sea. Sampling was completed during spiral ascent and descent flight paths that observed the temperature, humidity, pressure and wind up to 1000 m above ground level and sampled the entire depth of the atmospheric boundary layer, as well as portions of the free atmosphere above the boundary layer. A wide variety of boundary layer states were observed, including very shallow, strongly stable conditions during the Antarctic winter and deep, convective conditions over ice-free locations in the summer. The Antarctic atmospheric boundary layer data collected by the SUMO sUAS, described in this paper, can be retrieved from the United States Antarctic Program Data Center (https://www.usap-dc.org , last access: 8 March 2021). The data for all flights conducted on the continent are available at 10.15784/601054 (Cassano, 2017), and data from the Ross Sea flights are available at 10.15784/601191 (Cassano, 2019). [ABSTRACT FROM AUTHOR]

Between January 2012 and June 2017 a small unmanned aerial system (UAS), known as the Small Unmanned Meteorological Observer (SUMO), was used to observe the state of the atmospheric boundary layer in the Antarctic. During 6 Antarctic field campaigns 116 SUMO flights were completed. These flights took place during all seasons over both permanent ice and ice free locations on the Antarctic continent and over sea ice in the western Ross Sea. Sampling was completed during spiral ascent and descent flight paths that observed the temperature, humidity, pressure and wind up to 1000 m above ground level and sampled the entire depth of the atmospheric boundary layer as well as portions of the free atmosphere above the boundary layer. A wide variety of boundary layer states were observed including very shallow, strongly stable conditions during the Antarctic winter and deep, convective conditions over ice free locations in the summer. The Antarctic atmospheric boundary layer data collected by the SUMO sUAS, described in this paper, can be retrieved from the United States Antarctic Program Data Center (https://www.usap-dc.org). The data for all flights conducted on the continent are available at https://www.usap-dc.org/view/dataset/601054 (Cassano 2017; https://doi.org/10.15784/601054) and data from the Ross Sea flights, are available at https://www.usap-dc.org/view/dataset/601191 (Cassano 2019; https://doi.org/10.15784/601191). [ABSTRACT FROM AUTHOR]

The near-surface climate, including the atmosphere, ocean, sea ice, and land state and fluxes, in the initial version of the Regional Arctic System Model (RASM) are presented. The sensitivity of the RASM near-surface climate to changes in atmosphere, ocean, and sea ice parameters and physics is evaluated in four simulations. The near-surface atmospheric circulation is well simulated in all four RASM simulations but biases in surface temperature are caused by biases in downward surface radiative fluxes. Errors in radiative fluxes are due to biases in simulated clouds with different versions of RASM simulating either too much or too little cloud radiative impact over open ocean regions and all versions simulating too little cloud radiative impact over land areas. Cold surface temperature biases in the central Arctic in winter are likely due to too few or too radiatively thin clouds. The precipitation simulated by RASM is sensitive to changes in evaporation that were linked to sea surface temperature biases. Future work will explore changes in model microphysics aimed at minimizing the cloud and radiation biases identified in this work. [ABSTRACT FROM AUTHOR]

There is growing recognition that reductions in Arctic sea ice extent will influence patterns of atmospheric circulation both within and beyond the Arctic. We explore the impact of 2007 ice conditions (the second lowest Arctic sea ice extent in the satellite era) on atmospheric circulation and surface temperatures and fluxes through a series of model experiments with the NCAR Community Atmospheric Model version 3 ( CAM3). Two 30-year simulations were performed; one using climatological sea ice extent for the end of the 20th century and other using observed sea ice extent from 2007. Circulation differences over the Northern Hemisphere were most prominent during autumn and winter with lower sea level pressure ( SLP) and tropospheric pressure simulated over much of the Arctic for the 2007 sea ice experiment. The atmospheric response to 2007 ice conditions was much weaker during summer, with negative SLP anomalies simulated from Alaska across the Arctic to Greenland. Higher temperatures and larger surface fluxes to the atmosphere in areas of anomalous open water were also simulated. CAM3 experiment results were compared to observed SLP anomalies from the National Center for Environmental Prediction/National Center for Atmospheric Research ( NCEP/ NCAR) Reanalysis data. The observed SLP anomalies during spring are nearly opposite to those simulated. In summer, large differences were shown between the observed and simulated SLP also, suggesting that the sea ice conditions in the months preceding and during the summer of 2007 were not responsible for creating an atmospheric circulation pattern which favoured the large observed sea ice loss. The simulated and observed atmospheric circulation anomalies during autumn and winter were more similar than spring and summer, with the exception of a strong high pressure system in the Beaufort Sea which was not simulated, suggesting that the forced atmospheric response to reduced sea ice was in part responsible for the observed atmospheric circulation anomalies during autumn and winter. [ABSTRACT FROM AUTHOR]

Off the coast of Victoria Land, Antarctica an area of open water—the Terra Nova Bay Polynya (TNBP)—persists throughout the austral winter. The development of this coastal polynya is driven by extreme katabatic winds blowing down the slopes of Transantarctic Mountains. The surface-atmosphere coupling and ABL transformation during the katabatic wind events between 18 and 25 September 2012 in Terra Nova Bay are studied, using observations from Aerosonde unmanned aircraft system (UAS), numerical modeling results and Antarctic Weather Station (AWS) measurements. First, we analyze how the persistence and strength of the katabatic winds relate to sea level pressure (SLP) changes in the region throughout the studied period. Secondly, the polynya extent variations are analysed in relation to wind speed changes. We conclude that the intensity of the flow, surface conditions in the bay and regional SLP fluctuations are all interconnected and contribute to polynya development. We also analyse the Antarctic Mesoscale Prediction System (AMPS) forecast for the studied period and find out that incorrect representation of vertical ABL properties over the TNBP might be caused by overestimated sea ice concentrations (SIC) used as model input. Altogether, this research provides a unique description of TNBP development and its interactions with the atmosphere and katabatic winds. [ABSTRACT FROM AUTHOR]