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Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid-latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter-model spread of PHT into the Arctic reflects the tug-of-war between sea-ice and surface-warming effects.

The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response. [ABSTRACT FROM AUTHOR]

Current global reanalyses show marked discrepancies in snow mass and snow cover extent for the Northern Hemisphere. Here, benchmark snow datasets are produced by driving a simple offline snow model, the Brown Temperature Index Model (B-TIM), with temperature and precipitation from each of three reanalyses. B-TIM offline snow performs comparably to or better than online (coupled land-atmosphere) reanalysis snow when evaluated against in situ snow measurements. Sources of discrepancy in snow climatologies, which are difficult to isolate when comparing online reanalysis snow products amongst themselves, are partially elucidated by separately bias-adjusting temperature and precipitation in B-TIM. Interannual variability in snow mass and snow spatial patterns is far more self-consistent amongst offline B-TIM snow products than amongst online reanalysis snow products, and specific artifacts related to temporal inhomogeneity in snow data assimilation are revealed in the analysis. B-TIM, released here as an open-source, self-contained Python package, provides a simple benchmarking tool for future updates to more sophisticated online and offline snow datasets. [ABSTRACT FROM AUTHOR]

The European Space Agency's Aeolus mission, launched in August 2018, provides the first global horizontal line‐of‐sight wind profile measurements. Previous studies have shown that Aeolus winds in global forecast systems improve the overall forecast skill, especially in the upper tropospheric tropics and in other data‐sparse regions. In this study, we use a series of observing system experiments with the latest version of the reprocessed Aeolus wind product (2B11) to better characterize the locations and drivers of improved skill from Aeolus with Environment and Climate Change Canada's Global Deterministic Prediction System. Observing system experiments that test the impact of Aeolus winds and the impact of all operational wind observations are carried out, covering the period summer 2019 and winter 2019–2020. Assimilation of operational winds improves the tropospheric wind forecast over the Tropics by a reduction of 8% in the forecast error, and adding the Aeolus winds to the assimilations results in an extra 0.7–0.9%. Aeolus wind impacts are improvements are 0.7–0.9% for the Arctic, and 0.4–0.6% over the Northern and Southern Hemisphere extratropics. The scale dependence of these impacts is investigated using spatial spectra (spherical harmonic decomposition). The improvement is quantified using the difference of the 250 hPa kinetic energy forecast error spectra between experiments. The operational winds largely improve the forecast of planetary scale to intermediate scale for spherical wave numbers between 1 and 20 in the short‐range forecasts. The operational wind impact decreases as the forecast lead time increases. On the other hand, the impact of Aeolus is mostly seen in the intermediate to large scale range with a peak around spherical wave number 8. The Aeolus‐related improvement around this wave number increases with forecast lead time. This analysis suggests that Aeolus winds provide estimates of the wind state that are valuable and complementary to that provided from current operational winds. [ABSTRACT FROM AUTHOR]

Extreme near-surface wind speeds in cities can have major societal impacts but are not well represented in climate models. Despite this, large-scale dynamics in the free troposphere, which models resolve better, could provide reliable constraints on local extreme winds. This study identifies synoptic circulations associated with midlatitude extreme wind events and assesses how resolution affects their representation in analysis products and a climate model framework. Composites of reanalysis (ERA5) sea level pressure and upper-tropospheric winds during observed extreme wind events reveal distinct circulation structures for each quadrant of the surface-wind rose. Enhanced resolution of the analysis product (ERA5 versus the higher-resolution ECMWF Operational Analysis) reduced wind speed biases but has little impact on capturing occurrences of wind extremes seen in station observations. Composite circulations for surface wind extremes in a climate model (CESM) skillfully reproduce circulations found in reanalysis. Regional refinement of CESM over a region centered on southern Ontario, Canada, using variable resolution (VR-CESM) improves representation of surface ageostrophic circulations and the strength of vertical coupling between upper-level and near-surface winds. We thus can distinguish situations for which regional refinement (dynamical downscaling) is necessary for realistic representation of the large-scale atmospheric circulations associated with extreme winds, from situations where the coarse resolution of standard GCMs is sufficient. [ABSTRACT FROM AUTHOR]

In August 2018, the European Space Agency (ESA) launched the Aeolus satellite, whose Atmospheric LAser Doppler INstrument (ALADIN) is the first space-borne Doppler wind lidar to regularly measure vertical profiles of horizontal line-of-sight (HLOS) winds with global sampling. This mission is intended to assess improvement to numerical weather prediction provided by wind observations in regions poorly constrained by atmospheric mass, such as the tropics, but also, potentially, in polar regions such as the Arctic where direct wind observations are especially sparse. There remain gaps in the evaluation of the Aeolus products over the Arctic region, which is the focus of this contribution. Here, an assessment of the Aeolus Level-2B (L2B) wind product is carried out, progressing from specific locations in the Canadian North to the pan-Arctic. In particular, Aeolus data are compared to a limited sample of coincident ground-based Ka-band radar measurements at Iqaluit, Nunavut, to a larger set of coincident radiosonde measurements over the Canadian North, to Environment and Climate Change Canada (ECCC)'s short-range forecast, and to the reanalysis product, ERA5, from the European Centre for Medium-Range Weather Forecasts (ECMWF). Periods covered include the early phase of the first laser flight model (flight model A – FM-A; September to October 2018), the early phase of the second laser flight model (flight model B – FM-B; August to September 2019), and the middle phase of FM-B (December 2019 to January 2020). The adjusted r -squared between Aeolus and other local datasets is around 0.9 except for lower values for the comparison to the Ka-band radar, reflecting limited sampling opportunities with the radar data. This consistency is degraded by about 10 % for the Rayleigh winds in the summer due to solar background noise and other possible errors. Over the pan-Arctic, consistency, with correlation greater than 0.8, is found in the Mie channel from the planetary boundary layer to the lower stratosphere (near surface to 16 km a.g.l.) and in the Rayleigh channel from the troposphere to the stratosphere (2 to 25 km a.g.l.). In all three periods, Aeolus standard deviations are found to be 5 % to 40 % greater than those from ECCC-B and ERA5. We found that the L2B estimated error product for Aeolus is coherent with the differences between Aeolus and the other datasets and can be used as a guide for expected consistency. Our work shows that the high quality of the Aeolus dataset that has been demonstrated globally applies to the sparsely sampled Arctic region. It also demonstrates the lack of available independent wind measurements in the Canadian North, lending urgency to the need to augment the observing capacity in this region to ensure suitable calibration and validation of future space-borne Doppler wind lidar (DWL) missions. [ABSTRACT FROM AUTHOR]