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Abstract Several far‐infrared (FIR) satellite missions are planned for the next decade, with a special interest for the Arctic region. A theoretical study is performed to help with the design of an FIR radiometer, whose configuration in terms of channels number and frequencies is optimized based on information content analysis. The problem is cast in a context of vertical column experiments (1D) to determine the optimal configuration of a FIR radiometer to study the Arctic polar night. If only observations of the FIR radiometer were assimilated, the results show that for humidity, 90% of the total information content is obtained with four bands, whereas for temperature, 10 bands are needed. When the FIR measurements are assimilated on top of those from the advanced infrared sounder (AIRS), the former bring in additional information between the surface and 850 hPa and from 550 to 250 hPa for humidity. Moreover, between 400 and 200 hPa, the FIR radiometer is better than AIRS at reducing the analysis error variance for humidity. This indicates the potential of FIR observations for improving water vapor analysis in the Arctic. , Key Points FIR channels add information for UTLS water vapor compared to standard MIR channels IC is used to optimize the channels frequencies and widths of a FIR radiometer A high DFS is reached with only a few channels of an optimized FIR radiometer

Abstract Quantile mapping (QM) is a technique often used for statistical post‐processing (SPP) of climate model simulations, in order to adjust their biases relative to a selected reference product and/or to downscale their resolution. However, when QM is applied in univariate mode, there is a risk of generating other problems, like intervariable physical inconsistency (PI). Here, such a risk is investigated with daily temperature minimum ( T min ) and maximum ( T max ), for which the relationship T min > T max would be inconsistent with the definition of the variables. QM is applied to an ensemble of 78 daily CMIP5 simulations over Hudson Bay for the application period 1979–2100, with Climate Forecast System Reanalysis (CFSR) selected as the reference product during the calibration period 1979–2010. This study's specific objectives are as follows: to investigate the conditions under which PI situations are generated; to test whether PI may be prevented simply by tuning some of the QM technique's numerical choices; and to compare the suitability of alternative approaches that hinder PI by design. Primary results suggest that PI situations appear preferentially for small values of the initial (simulated) diurnal temperature range (DTR), but the differential between the respective biases of T min and T max also plays an important role; one cannot completely prevent the generation of PI simply by adjusting QM parameters and options, but forcing preservation of the simulated long‐term trends generates fewer PI situations; for avoiding PI between T min and T max , the present study supports a previous recommendation to directly post‐process T max and DTR before deducing T min .

The paper describes the development of predictive equations of windthrow for five tree species based on remote sensing of wind-affected stands in southwestern New Brunswick (NB). The data characterises forest conditions before, during and after the passing of extratropical cyclone Arthur, July 4–5, 2014. The five-variable logistic function developed for balsam fir (bF) was validated against remote-sensing-acquired windthrow data for bF-stands affected by the Christmas Mountains windthrow event of November 7, 1994. In general, the prediction of windthrow in the area agreed fairly well with the windthrow sites identified by photogrammetry. The occurrence of windthrow in the Christmas Mountains was prominent in areas with shallow soils and prone to localised accelerations in mean and turbulent airflow. The windthrow function for bF was subsequently used to examine the future impact of windthrow under two climate scenarios (RCP’s 4.5 and 8.5) and species response to local changes anticipated with global climate change, particularly with respect to growing degree-days and soil moisture. Under climate change, future windthrow in bF stands (2006–2100) is projected to be modified as the species withdraws from the high-elevation areas and NB as a whole, as the climate progressively warms and precipitation increases, causing the growing environment of bF to deteriorate.

Abstract Several regions of the world, including the east coast of Australia, are characterized by the occurrence of low‐pressure systems with a range of different dynamical structures, including tropical, extratropical, and hybrid cyclones. Future changes in the occurrence of cyclones are better understood if storms are classified according to their dynamical structure. Therefore, we apply a classification of cyclones according to their cold‐core or warm‐core structure to an ensemble of regional climate model simulations. First, we show that historical simulations reproduce well the reanalysis results in terms of cyclone classification. We then show that once cyclone classification is applied, projections of future cyclone activity become more robust, including a decrease in the occurrence of both cold‐core and warm‐core cyclones. Finally, we show that in a warmer climate warm‐core hybrid cyclone activity could increase close to the coast, while the associated rainfall and wind are projected to increase. , Plain Language Summary Cyclones in the tropics derive their energy from the temperature difference between warm ocean waters and the atmosphere and their interior is warmer than the environment (warm core), while cyclones in the midlatitudes derive their energy from differences in the atmospheric temperature and density at different locations and their interior is colder than the environment (cold core). In subtropical regions both types of cyclone can form. Also in those regions cyclones known as hybrid cyclones form, with mixed tropical‐extratropical features, such as a partial lower tropospheric warm core and a partial upper tropospheric cold core. This study is focused on cyclones along the eastern coast of Australia. Here we show that dividing cyclones in different classes according to their thermal structure provides a better framework to interpret changes in cyclone activity at subtropical latitudes. This study has two main results. First, classifying cyclones adds value to climate projection robustness. A large number of models agree on the decrease in the occurrence of both cold‐core and warm‐core cyclones. The study also indicates increased occurrence of hybrid cyclones close to the Australian coast. Second, the study shows evidence of future changes in cyclone‐related impacts, such as an increase in the associated rainfall. , Key Points A physically based classification of hybrid cyclones is applied to an ensemble of regional climate model simulations The cyclone classification method adds value to the projections of future cyclone activity, making them more robust Results indicate future changes (2060–2079) toward more intense impacts associated with hybrid cyclones

Abstract Like many western boundary currents, the East Australian Current (EAC) extension is projected to get stronger and warmer in the future. The CMIP5 multimodel mean (MMM) projection suggests up to 5°C of warming under an RCP85 scenario by 2100. Previous studies employed Sverdrup balance to associate a trend in basin wide zonally integrated wind stress curl (resulting from the multidecadal poleward intensification in the westerly winds over the Southern Ocean) with enhanced transport in the EAC extension. Possible regional drivers are yet to be considered. Here we introduce the NEMO‐OASIS‐WRF coupled regional climate model as a framework to improve our understanding of CMIP5 projections. We analyze a hierarchy of simulations in which the regional atmosphere and ocean circulations are allowed to freely evolve subject to boundary conditions that represent present‐day and CMIP5 RCP8.5 climate change anomalies. Evaluation of the historical simulation shows an EAC extension that is stronger than similar ocean‐only models and observations. This bias is not explained by a linear response to differences in wind stress. The climate change simulations show that regional atmospheric CMIP5 MMM anomalies drive 73% of the projected 12 Sv increase in EAC extension transport whereas the remote ocean boundary conditions and regional radiative forcing (greenhouse gases within the domain) play a smaller role. The importance of regional changes in wind stress curl in driving the enhanced EAC extension is consistent with linear theory where the NEMO‐OASIS‐WRF response is closer to linear transport estimates compared to the CMIP5 MMM. , Plain Language Summary In recent decades, enhanced warming, severe marine heatwaves, and increased transport by the East Australian Current have led to the invasion of nonnative species and the destruction of kelp forests east of Tasmania. The East Australian Current extension is projected to get stronger and warmer in the future. We seek to better understand coupled climate model projections for the Tasman Sea. This is difficult because there is large model diversity and considerable uncertainty as to how and where future changes will occur. In addition, little is known about the possible importance of regional versus large‐scale changes in surface time‐mean winds in driving future circulation changes. Here we use a single limited‐domain ocean‐atmosphere coupled model that takes the average model projections as its inputs and finds that changes in the regional wind stress are most important for the enhanced projected East Australian Current extension. We also find that these projected changes are consistent with simple linear theory and the simulated regional changes in wind stress. , Key Points NEMO‐OASIS‐WRF coupled regional climate model is evaluated and introduced as a new tool for analyzing Tasman Sea climate projections NEMO‐OASIS‐WRF projections suggest that local atmospheric changes drive 73% of the projected 12 Sv increase in EAC extension transport The importance of regional changes in wind stress curl driving the enhanced EAC extension is consistent with linear theory

Two Types of Ice Clouds (TICs) have been characterized in the Arctic during the polar night and early spring. TIC-1 are composed by non-precipitating small ice crystals of less than 30 µm in diameter. The second type, TIC-2, are characterized by a low concentration of large precipitating ice crystals (>30 µm). Here, we evaluate the Weather Research and Forecasting (WRF) model performance both in space and time after implementing a parameterization based on a stochastic approach dedicated to the simulation of ice clouds in the Arctic. Well documented reference cases provided us in situ data from the spring of 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) campaign over Alaska. Simulations of the microphysical properties of the TIC-2 clouds on 15 and 25 April 2008 (polluted or acidic cases) and TIC-1 clouds on non-polluted cases are compared to DARDAR (raDAR/liDAR) satellite products. Our results show that the stochastic approach based on the classical nucleation theory, with the appropriate contact angle, is better than the original scheme in WRF model to represent TIC-1 and TIC-2 properties (ice crystal concentration and size) in response to the IN acidification.

Abstract. Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75 nM) and the overlying atmosphere (up to 1 ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6 nM and a potential contribution to atmospheric DMS of 20 % in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41 % of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20 % to 80 % of the 30–50 nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03 cm s−1).

Abstract We develop a portfolio credit risk model that includes firm‐specific Markov‐switching regimes as well as individual stochastic and endogenous recovery rates. Using weekly credit default swap premiums for 35 financial firms, we analyze the credit risk of each of these companies and their statistical linkages, putting emphasis on the 2005–2012 period. Moreover, we study the systemic risk affecting both the banking and insurance subsectors.