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In a previous study, we investigated whether reanalysis moist static energy (MSE) transport trends over the 1980 through 2018 period are consistent (a) with each other and (b) with the finding that these transport trends are downgradient, as found in climate models. Regarding point (a), our conclusion was that MSE transport trends were dependent on the reanalysis data set. However, Cox et al. (2023) correctly point out that the reanalysis dependence is reduced dramatically if a barotropic mass flux correction is applied at a monthly mean timescale prior to computing the MSE transport trends. In our reply below, we revisit point (b) after applying this correction. We find that even after the correction, reanalysis MSE transport trends are not downgradient nor poleward in the Northern Hemisphere extratropics. However, reanalysis does show a compensation between dry static and latent energy transport trends, which has been shown in climate models historically.

Applying composite analysis to ERA-Interim data, the surface air temperature (SAT) anomaly pattern of the Pacific–North American (PNA) teleconnection is shown to include both symmetric and asymmetric SAT anomalies with respect to the PNA phase. The symmetric SAT anomalies, overlying the Russian Far East and western and eastern North America, grow through advection of the climatological temperature by the anomalous meridional wind and vertical mixing. The asymmetric SAT anomalies, overlying Siberia during the positive PNA and the subtropical North Pacific during the negative PNA, grow through vertical mixing only. For all SAT anomalies, vertical mixing relocates the temperature anomalies of the PNA teleconnection pattern from higher in the boundary layer downward to the level of the SAT. Above the level of the SAT, temperature anomaly growth is caused by horizontal temperature advection in all locations except for the subtropical North Pacific, where adiabatic cooling dominates. SAT anomaly decay is caused by longwave radiative heating/cooling, except over Siberia, where SAT anomaly decay is caused by vertical mixing. Additionally, temperature anomaly decay higher in the boundary layer due to nonlocal mixing contributes indirectly to SAT anomaly decay by weakening downgradient diffusion. These results highlight a diverse array of mechanisms by whichmore »individual anomalies within the PNA pattern grow and decay. Furthermore, with the exception of Siberia, throughout the growth and decay stages, horizontal temperature advection and/or vertical mixing is nearly balanced by longwave radiative heating/cooling, with the former being slightly stronger during the growth stage and the latter during the decay stage.

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Trends in moist static energy (MSE) transport are investigated for the years 1980 through 2018 using four different reanalysis data sets. The reanalysis data sets show agreement in the eddy MSE transport trends and the latitudinal structure of the MSE trends, but vary widely in the trend of the flux of the climatological zonal mean MSE by the anomalous zonal mean meridional wind. The latter dominates the total MSE transport trends in all four data sets. Therefore, none of the four total MSE flux trends is downgradient of the corresponding MSE trend. Further analysis of the MSE trends reveals that dry static energy increases strongly dominate MSE trends at all latitudes, including in the tropics where climate models and theory predict latent energy increases to dominate. As changes in MSE transport are routinely assumed to be downgradient when interpreting changes in climate, including Arctic amplification, further investigation of reanalysis MSE transport is warranted.

Abstract The wintertime (December–February) 1990–2016 Arctic surface air temperature (SAT) trend is examined using self-organizing maps (SOMs). The high-dimensional SAT dataset is reduced into nine representative SOM patterns, with each pattern exhibiting a decorrelation time scale of about 10 days and having about 85% of its variance coming from intraseasonal time scales. The trend in the frequency of occurrence of each SOM pattern is used to estimate the interdecadal Arctic winter warming trend associated with the SOM patterns. It is found that trends in the SOM patterns explain about one-half of the SAT trend in the Barents and Kara Seas, one-third of the SAT trend around Baffin Bay, and two-thirds of the SAT trend in the Chukchi Sea. A composite calculation of each term in the thermodynamic energy equation for each SOM pattern shows that the SAT anomalies grow primarily through the advection of the climatological temperature by the anomalous wind. This implies that a substantial fraction of Arctic amplification is due to horizontal temperature advection that is driven by changes in the atmospheric circulation. An analysis of the surface energy budget indicates that the skin temperature anomalies as well as the trend, although very similar to that of themore »SAT, are produced primarily by downward longwave radiation.« less

Abstract The relationship between latent heating over the Greenland, Barents, and Kara Seas (GBKS hereafter) and Rossby wave propagation between the Arctic and midlatitudes is investigated using global reanalysis data. Latent heating is the focus because it is the most likely source of Rossby wave activity over the Arctic Ocean. Given that the Rossby wave time scale is on the order of several days, the analysis is carried out using a daily latent heating index that resembles the interdecadal latent heating trend during the winter season. The results from regression calculations find a trans-Arctic Rossby wave train that propagates from the subtropics, through the midlatitudes, into the Arctic, and then back into midlatitudes over a period of about 10 days. Upon entering the GBKS, this wave train transports moisture into the region, resulting in anomalous latent heat release. At high latitudes, the overlapping of a negative latent heating anomaly with an anomalous high is consistent with anomalous latent heat release fueling the Rossby wave train before it propagates back into the midlatitudes. This implies that the Rossby wave propagation from the Arctic into the midlatitudes arises from trans-Arctic wave propagation rather than from in situ generation. The method used indicatesmore »the variance of the trans-Arctic wave train, but not in situ generation, and implies that the variance of the former is greater than that of latter. Furthermore, GBKS sea ice concentration regression against the latent heating index shows the largest negative value six days afterward, indicating that sea ice loss contributes little to the latent heating.« less

Abstract Radiative transfer calculations are conducted to determine the contribution of temperature and water vapor anomalies toward the surface clear-sky downward longwave radiation (DLR) anomalies of the NAO. These calculations are motivated by the finding that the NAO’s skin temperature anomalies are driven primarily by changes in surface DLR. The clear-sky radiative transfer calculations follow the result that the clear-sky surface DLR anomalies can account for most of the all-sky surface DLR anomalies of the NAO. The results of the radiative transfer calculations prompt an analysis of the thermodynamic energy and total column water (TCW) budget equations, as water vapor and temperature anomalies are found to be equally important drivers of the surface DLR anomalies of the NAO. Composite analysis of the thermodynamic energy equation reveals that the temperature anomalies of the NAO are wind driven: the advection of climatological temperature by the anomalous wind drives the NAO’s temperature anomalies at all levels except for those in the upper troposphere–lower stratosphere where the advection of anomalous temperature by the climatological wind becomes dominant. A similar analysis of the TCW budget reveals that changes in TCW are driven by water flux convergence. In addition to determining the drivers of the temperaturemore »and TCW anomalies, the thermodynamic energy and water budget analyses reveal that the decay of the temperature anomalies occurs primarily through vertical mixing, and that of the water anomalies mostly by evaporation minus precipitation.« less

Abstract Composite analysis is used to examine the physical processes that drive the growth and decay of the surface air temperature anomaly pattern associated with the North Atlantic Oscillation (NAO). Using the thermodynamic energy equation that the European Centre for Medium-Range Weather Forecasts implements in their reanalysis model, we show that advection of the climatological temperature field by the anomalous wind drives the surface air temperature anomaly pattern for both NAO phases. Diabatic processes exist in strong opposition to this temperature advection and eventually cause the surface air temperature anomalies to return to their climatological values. Specifically, over Greenland, Europe, and the United States, longwave heating/cooling opposes horizontal temperature advection while over northern Africa vertical mixing opposes horizontal temperature advection. Despite the pronounced spatial correspondence between the skin temperature and surface air temperature anomaly patterns, the physical processes that drive these two temperature anomalies associated with the NAO are found to be distinct. The skin temperature anomaly pattern is driven by downward longwave radiation whereas stated above, the surface air temperature anomaly pattern is driven by horizontal temperature advection. This implies that the surface energy budget, although a useful diagnostic tool for understanding skin temperature changes, should not be usedmore »to understand surface air temperature changes.« less

he Arctic has been warming faster than elsewhere, especially during the cold season. According to the leading theory, ice‐albedo feedback warms the Arctic Ocean during the summer, and the heat gained by the ocean is released during the winter, causing the cold‐season warming. Screen and Simmonds (2010; SS10) concluded that the theory is correct by comparing trend patterns in surface air temperature (SAT), surface turbulence heat flux (HF), and net surface infrared radiation (IR). However, in this comparison, downward IR is more appropriate to use. By analyzing the same data used in SS10 using the surface energy budget, it is shown here that over most of the Arctic the skin temperature trend, which closely resembles the SAT trend, is largely accounted for by the downward IR, not the HF, trend.