Penny Marie Rowe

East Antarctica (EA) experienced an unprecedented atmospheric river (AR)-driven heatwave in March 2022. Using high-resolution model simulations, this study investigates how atmospheric moisture (Q) and sea surface temperature (SST) influence AR development and associated surface impacts through latent heat exchange and circulation evolutions. A 20% increase in Q and an ~1.3°C increase in SST over the target region enhanced area-averaged precipitation over EA by up to 10.25% and 17.23%, respectively, while amplifying Dome C warming by up to 5.38°C and 3.95°C. However, the responses are nonlinear, with AR strength and precipitation responding more strongly to reduced Q and enhanced SST. Increased Q accelerates blocking development and AR intensification, shifting the AR eastward and enhancing oceanic precipitation. In contrast, SST warming enhances evaporation and moisture retention, producing a delayed but stronger precipitation response. Temperature changes show strong spatial variability among sensitivity experiments, likely due to uncertainties in cloud radiative effects.

Climate models struggle to accurately represent polar regions, largely due to the difficulty in modeling clouds. The uncertainty budget of polar radiation is dominated by cloud and cloud-aerosol interactions, but challenges in maintaining robust field observations mean that even basic knowledge such as cloud occurrence is not well known. Measurements of the thermal emission of Earth’s atmosphere can help close this knowledge gap due to the sensitivity of this spectral region to radiative properties of clouds. Measurements of the downwelling atmospheric emission (400 to 3000 cm⁻¹) have been collected at two polar field sites using Atmospheric Emitted Radiance Interferometer (AERI) instruments, two at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Canada (80° N), for which we use data from 2006 to 2022, and another at McMurdo Station (77° S) in Antarctica as part of the Atmospheric Radiation Measurement (ARM) West Antarctica Radiation Experiment (AWARE) project in 2016. We analyze these spectra, with supplementary data from other instruments and models, to compare optical and microphysical properties of moderately thick clouds at Eureka and McMurdo Station, including optical depth, thermodynamic phase, liquid droplet and ice crystal effective scattering radii, and cloud boundaries. We find that the clouds sampled at McMurdo generally feature lower temperatures, smaller liquid droplets, a more concentrated distribution of ice effective radii, less seasonal variability in optical depth, and lower optical thickness because they consist of a higher proportion of ice than those at Eureka. Additionally, both locations have high occurrence rates of supercooled liquid and mixed-phase clouds and exhibit differences between single-phase and mixed-phase microphysics.

Climate models struggle to accurately represent polar regions, largely due to the difficulty in modeling clouds. The uncertainty budget of polar radiation is dominated by cloud and cloud-aerosol interactions, but challenges in maintaining robust field observations mean that even basic knowledge such as cloud occurrence is not well known. Measurements of the thermal emission of Earth’s atmosphere can help close this knowledge gap due to the sensitivity of this spectral region to radiative properties of clouds. Measurements of the downwelling atmospheric emission (400 to 3000 cm⁻¹) have been collected at two polar field sites using Atmospheric Emitted Radiance Interferometer (AERI) instruments, two at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Canada (80° N), for which we use data from 2006 to 2022, and another at McMurdo Station (77° S) in Antarctica as part of the Atmospheric Radiation Measurement (ARM) West Antarctica Radiation Experiment (AWARE) project in 2016. We analyze these spectra, with supplementary data from other instruments and models, to compare optical and microphysical properties of moderately thick clouds at Eureka and McMurdo Station, including optical depth, thermodynamic phase, liquid droplet and ice crystal effective scattering radii, and cloud boundaries. We find that the clouds sampled at McMurdo generally feature lower temperatures, smaller liquid droplets, a more concentrated distribution of ice effective radii, less seasonal variability in optical depth, and lower optical thickness because they consist of a higher proportion of ice than those at Eureka. Additionally, both locations have high occurrence rates of supercooled liquid and mixed-phase clouds and exhibit differences between single-phase and mixed-phase microphysics.

Climate models struggle to accurately represent polar regions, largely due to the difficulty in modeling clouds. The uncertainty budget of polar radiation is dominated by cloud and cloud-aerosol interactions, but challenges in maintaining robust field observations mean that even basic knowledge such as cloud occurrence is not well known. Measurements of the thermal emission of Earth’s atmosphere can help close this knowledge gap due to the sensitivity of this spectral region to radiative properties of clouds. Measurements of the downwelling atmospheric emission (400 to 3000 cm⁻¹) have been collected at two polar field sites using Atmospheric Emitted Radiance Interferometer (AERI) instruments, two at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Canada (80° N), for which we use data from 2006 to 2022, and another at McMurdo Station (77° S) in Antarctica as part of the Atmospheric Radiation Measurement (ARM) West Antarctica Radiation Experiment (AWARE) project in 2016. We analyze these spectra, with supplementary data from other instruments and models, to compare optical and microphysical properties of moderately thick clouds at Eureka and McMurdo Station, including optical depth, thermodynamic phase, liquid droplet and ice crystal effective scattering radii, and cloud boundaries. We find that the clouds sampled at McMurdo generally feature lower temperatures, smaller liquid droplets, a more concentrated distribution of ice effective radii, less seasonal variability in optical depth, and lower optical thickness because they consist of a higher proportion of ice than those at Eureka. Additionally, both locations have high occurrence rates of supercooled liquid and mixed-phase clouds and exhibit differences between single-phase and mixed-phase microphysics.

Atmospheric rivers are episodic events that can advect relatively large quantities of moisture to Antarctica, contributing to both disproportionate precipitation and melting events. The Year of Polar Prediction, an international effort to improve weather prediction over the southern polar region, presents an opportunity to study the clouds and precipitation associated with winter atmospheric river events. This study uses enhanced surface, profile, and remote‐sensing observations from the Antarctic Peninsula (AP) during a Targeted Observing Period around 16 May 2022, when an event occurred with local warming similar to a warm front. We compare regional atmospheric simulations with the polar‐optimized version of the Weather Research and Forecasting Model to various in situ and remote‐sensing observations. The study emphasizes data from three stations: Escudero, Vernadsky, and Rothera. Mixed‐phase clouds were simulated at the three stations, with the precipitation being primarily rain at Escudero and primarily snow at Vernadsky and Rothera. The model produced reasonable simulations of the clouds and precipitation. Furthermore, modeled longwave cloud forcing at Escudero had small errors compared to observed values. A sensitivity test enhancing secondary ice production indicates mixed‐phase cloud sensitivity to the Hallett‐Mossop process, especially at Rothera.

Clouds exert strong influences on surface energy budgets and climate projections. Yet, cloud physics are complex and often incompletely represented in models. For example, supercooled liquid cloud optics parameterizations are rarely incorporated into the radiative transfer models used for climate projections. Prior work has shown that incorporating these optics in longwave radiation calculations increases Arctic downwelling longwave fluxes by as much as 1.7 W m⁻². Here we examine whether implementing supercooled liquid water optics in climate models for longwave radiation impacts global radiative fluxes and climate. We use a novel methodology that uses a hierarchy of dynamical constraints on the sequence of atmospheric states. In the model experiments with stronger dynamical constraints, we find that the supercooled liquid water optics increase Arctic downwelling longwave by 2.17–3.24 W m⁻². In contrast, these optics increased Arctic downwelling longwave radiation by 0.36–0.68 W m⁻² with dynamically unconstrained model experiments. While the optics impact was greater within the dynamically constrained models than in dynamically unconstrained models, the dynamically constrained models are also more idealized than the unconstrained models. In summary, we found a signal from supercooled liquid water optics; the influence of these optics for longwave radiation is small compared to the modeled longwave radiation variability. More broadly, this work demonstrates a novel framework for assessing the climate importance of a physics change.

Clouds play an important role in the Southern Ocean and Antarctic surface energy balance via their radiative effects and in surface mass balance via precipitation formation. Here, we use measurements at Escudero Station (62.2°S, 58.97°W) on King George Island, north of the Antarctic Peninsula, to characterize clouds and their effects on the surface incoming radiation between 2017 and 2023. These measurements are unique providing 7 years of simultaneous cloud and radiation measurements, including year‐round observations. Cloud measurements using a mini micropulse lidar showed that clouds are present 96% of the time with persistent low‐level supercooled liquid‐containing clouds: 86% of the lowest cloud bases are within the first 1 km. Liquid was present about 80% of the time, and most liquid was supercooled: cloud‐base temperatures were below 0°C for 82% of atmospheric columns classified as liquid‐containing. Combining pyranometer and pyrgeometer measurements with clear‐sky radiative transfer modeling, we find that the downward cloud radiative forcing is negative during October–March and positive during April–September. For clouds with base temperatures below 260 K, downward longwave cloud forcing is found to be lower for ice‐only clouds than for liquid‐containing clouds; however, at warmer temperatures, both ice‐only and liquid‐containing clouds exhibited similar radiative forcing. During strong atmospheric river (AR) events, when long corridors of moisture bring heat and precipitation, surface temperatures are found to be positively correlated with downward shortwave (DSW) cloud forcing in summer, indicating that weaker DSW cloud forcing is linked to higher summertime surface temperatures.

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⁻² higher than observations in summer, whereas ERA5 mean monthly downward longwave (DLW) is biased by −18 to −22 W m⁻² in summer and −16 W m⁻² on 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⁻² for DSW and −2 W m⁻² for DLW). After bias correction, ERA5 monthly average net cloud forcing over 2017–2023 is found to be a minimum of −107 W m⁻² in January and a maximum of 65 W m⁻² in June.

Clouds exert strong influences on surface energy budgets and climate projections. Yet, cloud physics is complex and often incompletely represented in models. For example, temperature-dependent cloud optics parameterizations are rarely incorporated into the radiative transfer models used for future climate projections. Prior work has shown that incorporating these optics in downwelling longwave radiation calculations results in increases of as much as 1.7 W m⁻² for Arctic atmospheres. Here we examine whether implementing these optics in climate models leads to significant climate impacts. We use a novel methodology based on a hierarchy of models. In two-stream radiation and single-column models, incorporating temperature-dependent optical properties had a small impact (< 1 W m⁻²). Similarly, impacts were statistically insignificant on infrared radiation within freely evolving atmospheric model simulations. In contrast, there was a much larger effect (1–3 W m⁻²) from optics changes when the winds within our atmospheric model experiments were nudged towards reanalysis winds. This new application of wind-nudging experiments helped to isolate the effect from temperature-dependent cloud optics changes by reducing the internally generated atmospheric variability. In summary, we found a signal from temperature-dependent optics, but this effect is small compared to climate variability and didn't impact long term Arctic temperature trends. More broadly, this work demonstrates a new framework for assessing the climate importance of a physics change.

Clouds exert strong influences on surface energy budgets and climate projections. Yet, cloud physics is complex and often incompletely represented in models. For example, temperature-dependent cloud optics parameterizations are rarely incorporated into the radiative transfer models used for future climate projections. Prior work has shown that incorporating these optics in downwelling longwave radiation calculations results in increases of as much as 1.7 W m⁻² for Arctic atmospheres. Here we examine whether implementing these optics in climate models leads to significant climate impacts. We use a novel methodology based on a hierarchy of models. In two-stream radiation and single-column models, incorporating temperature-dependent optical properties had a small impact (< 1 W m⁻²). Similarly, impacts were statistically insignificant on infrared radiation within freely evolving atmospheric model simulations. In contrast, there was a much larger effect (1–3 W m⁻²) from optics changes when the winds within our atmospheric model experiments were nudged towards reanalysis winds. This new application of wind-nudging experiments helped to isolate the effect from temperature-dependent cloud optics changes by reducing the internally generated atmospheric variability. In summary, we found a signal from temperature-dependent optics, but this effect is small compared to climate variability and didn't impact long term Arctic temperature trends. More broadly, this work demonstrates a new framework for assessing the climate importance of a physics change.