An official website of the United States government
Abstract Forecasting Antarctic atmospheric, oceanic, and sea ice conditions on subseasonal to seasonal scales remains a major challenge. During both the freezing and melting seasons current operational ensemble forecasting systems show a systematic overestimation of the Antarctic sea-ice edge location. The skill of sea ice cover prediction is closely related to the accuracy of cloud representation in models, as the two are strongly coupled by cloud radiative forcing. In particular, surface downward longwave radiation (DLW) deficits appear to be a common shortcoming in atmospheric models over the Southern Ocean. For example, a recent comparison of ECMWF reanalysis 5th generation (ERA5) global reanalysis with the observations from McMurdo Station revealed a year-round deficit in DLW of approximately 50 Wm−2in marine air masses due to model shortages in supercooled cloud liquid water. A comparison with the surface DLW radiation observations from the Ocean Observatories Initiative mooring in the South Pacific at 54.08° S, 89.67° W, for the time period January 2016–November 2018, confirms approximately 20 Wm−2deficit in DLW in ERA5 well north of the sea-ice edge. Using a regional ocean model, we show that when DLW is artificially increased by 50 Wm−2in the simulation driven by ERA5 atmospheric forcing, the predicted sea ice growth agrees much better with the observations. A wide variety of sensitivity tests show that the anomalously large, predicted sea-ice extent is not due to limitations in the ocean model and that by implication the cause resides with the atmospheric forcing.
more »
« less
This content will become publicly available on August 18, 2026
Comparison of Cloud and Radiation Measurements to Models Over the Southern Ocean at Escudero Station, King George Island
Abstract Clouds and radiation play an important role in warming events over the Southern Ocean (SO). Here we evaluate European Center for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) and Polar Weather Research Forecast (PWRF) output through comparison to surface‐based measurements of clouds, radiation, and the atmospheric state over the SO during 2017–2023 at Escudero Station (62.2°S, 58.97°W) on King George Island. ERA5 mean monthly downward shortwave (DSW) radiative fluxes are found to be 38–50 W m−2higher than observations in summer, whereas ERA5 mean monthly downward longwave (DLW) is biased by −18 to −22 W m−2in summer and −16 W m−2on average over the year. Comparisons of temperature, humidity, and lowest‐cloud base heights between ERA5 and observations rule these factors out as large contributors to the DLW flux biases. The similarity between observed DLW cloud forcing distributions for atmospheric columns containing low‐level liquid and ice‐only clouds suggests limited influence of cloud phase errors on DLW biases. Thus the most likely explanation for DLW flux biases in ERA5 is underestimated cloud optical depth, which is also consistent with DSW flux biases. Similar biases in ERA5 are found during atmospheric river (AR) events. By contrast, PWRF flux bias magnitudes are much smaller during AR events (−12 W m−2for DSW and −2 W m−2for DLW). After bias correction, ERA5 monthly average net cloud forcing over 2017–2023 is found to be a minimum of −107 W m−2in January and a maximum of 65 W m−2in June.
more »
« less
- Award ID(s):
- 2229392
- PAR ID:
- 10628923
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 130
- Issue:
- 16
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract. In coastal polynyas, where sea-ice formation and melting occur, it is crucial to have accurate estimates of heat fluxes in order to predict future sea-ice dynamics. The Amundsen Sea Polynya is a coastal polynya in Antarctica that remains poorly observed by in situ observations because of its remoteness. Consequently, we rely on models and reanalysis that are un-validated against observations to study the effect of atmospheric forcing on polynya dynamics. We use austral summer 2022 shipboard data to understand the turbulent heat flux dynamics in the Amundsen Sea Polynya and evaluate our ability to represent these dynamics in ERA5. We show that cold- and dry-air outbreaks from Antarctica enhance air–sea temperature and humidity gradients, triggering episodic heat loss events. The ocean heat loss is larger along the ice-shelf front, and it is also where the ERA5 turbulent heat flux exhibits the largest biases, underestimating the flux by up to 141 W m−2 due to its coarse resolution. By reconstructing a turbulent heat flux product from ERA5 variables using a nearest-neighbor approach to obtain sea surface temperature, we decrease the bias to 107 W m−2. Using a 1D model, we show that the mean co-located ERA5 heat loss underestimation of 28 W m−2 led to an overestimation of the summer evolution of sea surface temperature (heat content) by +0.76 °C (+8.2×107 J) over 35 d. By obtaining the reconstructed flux, the reduced heat loss bias (12 W m−2) reduced the seasonal bias in sea surface temperature (heat content) to −0.17 °C (−3.30 × 107 J) over the 35 d. This study shows that caution should be applied when retrieving ERA5 turbulent flux along the ice shelves and that a reconstructed flux using ERA5 variables shows better accuracy.more » « less
-
Abstract Snow is the most reflective natural surface on Earth. Since fresh snow on bare sea ice increases the surface albedo, the impact of summer snow accumulation can have a negative radiative forcing effect, which would inhibit sea ice surface melt and potentially slow sea‐ice loss. However, it is not well known how often, where, and when summer snowfall events occur on Arctic sea ice. In this study, we used in situ and model snow depth data paired with surface albedo and atmospheric conditions from satellite retrievals to characterize summer snow accumulation on Arctic sea ice from 2003 to 2017. We found that, across the Arctic, ∼2 snow accumulation events occurred on initially snow‐free conditions each year. The average snow depth and albedo increases were ∼2 cm and 0.08, respectively. 16.5% of the snow accumulation events were optically thick (>3 cm deep) and lasted 2.9 days longer than the average snow accumulation event (3.4 days). Based on a simple, multiple scattering radiative transfer model, we estimated a −0.086 ± 0.020 W m−2change in the annual average top‐of‐the‐atmosphere radiative forcing for summer snowfall events in 2003–2017. The following work provides new information on the frequency, distribution, and duration of observed snow accumulation events over Arctic sea ice in summer. Such results may be particularly useful in understanding the impacts of ephemeral summer weather on surface albedo and their propagating effects on the radiative forcing over Arctic sea ice, as well as assessing climate model simulations of summer atmosphere‐ice processes.more » « less
-
Abstract. An extreme warming event near the North Pole, with 2 m temperature rising above 0 °C, was observed in late December 2015. This specific event has been attributed to cyclones and their associated moisture intrusions. However, little is known about the characteristics and drivers of similar events in the historical record. Here, using data from European Centre for Medium-Range Weather Forecasts Reanalysis, version 5 (ERA5), we study these winter extreme warming events with 2 m temperature over a grid point above 0 °C over the high Arctic (poleward of 80° N) that occurred during 1980–2021. In ERA5, such wintertime extreme warming events can only be found over the Atlantic sector. They occur rarely over many grid points, with a total absence during some winters. Furthermore, even when occurring, they tend to be short-lived, with the majority of the events lasting for less than a day. By examining their surface energy budget, we found that these events transition with increasing latitude from a regime dominated by turbulent heat flux into the one dominated by downward longwave radiation. Positive sea level pressure anomalies which resemble blocking over northern Eurasia are identified as a key ingredient in driving these events, as they can effectively deflect the eastward propagating cyclones poleward, leading to intense moisture and heat intrusions into the high Arctic. Using an atmospheric river (AR) detection algorithm, the roles of ARs in contributing to the occurrence of these extreme warming events defined at the grid-point scale are explicitly quantified. The importance of ARs in inducing these events increases with latitude. Poleward of about 83° N, 100 % of these events occurred under AR conditions, corroborating that ARs were essential in contributing to the occurrence of these events. Over the past 4 decades, both the frequency, duration, and magnitude of these events have been increasing significantly. As the Arctic continues to warm, these events are likely to increase in both frequency, duration, and magnitude, with great implications for the local sea ice, hydrological cycle, and ecosystem.more » « less
-
Abstract The shortwave direct radiative effect of dust, the difference between net shortwave radiative flux in a cloud free and cloud and aerosol free atmosphere, is typically estimated using forward calculations made with a radiative transfer model. However, estimates of the direct radiative effect made via this initial method can be highly uncertain due to difficultly in accurately describing the relevant optical and physical properties of dust used in these calculations. An alternative approach to estimate this effect is to determine the forcing efficiency, or the direct radiative effect normalized by aerosol optical depth. While this approach avoids the uncertainties associated with the initial method for calculating the direct effect, random errors and biases associated with this approach have not been thoroughly examined in literature. Here we explore biases in this observation‐based approach that are related to atmospheric water vapor. We use observations to show that over the Sahara Desert dust optical depth and column‐integrated atmospheric water vapor are positively correlated. We use three idealized radiative models of varying complexity to demonstrate that a positive correlation between dust and water vapor produces a positive bias in the dust forcing efficiency estimated via the observation‐based method. We describe a simple modification to the observation‐based method that correctly accounts for the correlation between dust and water vapor when estimating the forcing efficiency and use this method to estimate the instantaneous forcing efficiency of dust over the Sahara Desert using satellite data, obtaining −12.3 ± 6.68 to 20.9 ± 11.9 W m−2per unit optical depth.more » « less
