Surface Air Temperature Trends Research Articles

Contributions to surface air temperature trends estimated from climate time series: Medium-term causalities.

Contributions of various natural and anthropogenic factors to trends of surface air temperatures at different latitudes of the Northern and Southern hemispheres on various temporal horizons are estimated from climate data since the 19th century in empirical autoregressive models. Along with anthropogenic forcing, we assess the impact of several natural climate modes including Atlantic Multidecadal Oscillation, El-Nino/Southern Oscillation, Interdecadal Pacific Oscillation, Pacific Decadal Oscillation, and Antarctic Oscillation. On relatively short intervals of the length of two or three decades, contributions of climate variability modes are considerable and comparable to the contributions of greenhouse gases and even exceed the latter. On longer intervals of about half a century and greater, the contributions of greenhouse gases dominate at all latitudinal belts including polar, middle, and tropical ones.

Impact of Internal Climate Variability on Wintertime Surface Air Temperature Trends Over Eurasia in the CESM1 Large Ensemble

AbstractThis study investigates the role of internal climate variability on the wintertime surface air temperature (SAT) trend over Eurasia during 1970–2004 based on outputs from the Community Earth System Model Large Ensemble Project. The SAT trends vary significantly in both spatial pattern and magnitude among ensemble members, indicating the essential role of internal climate variability on SAT trends. The leading modes of the spread of SAT trends are extracted via inter‐member empirical orthogonal function (EOF) analysis of the SAT trend patterns among 40 ensemble members. The first EOF mode shows widespread warming over northern Eurasia and slight cooling southward of 40°N during its positive phase. The second EOF mode displays a zonal dipole, with one center located in Europe and the other of the opposite sign over Siberia. The Arctic Oscillation and Scandinavian patterns are key dynamical factors associated with the two dominant modes, respectively. A dynamical adjustment method is further employed to decompose the internal climate variability into those related to large‐scale atmospheric circulation and residuals. The spread of SAT trends among ensemble members is primarily associated with the various large‐scale atmospheric circulation and second by the residual component that is closely tied to diverse snow cover trends over Eurasia, especially over northern Eurasia. These results may help understand the relationship between internal climate variability and winter SAT trends over Eurasia via dynamical and thermodynamical processes.

Evaluation of AMIP models from CMIP6 in simulating winter surface air temperature trends over Eurasia during 1998–2012 based on dynamical adjustment

Evaluation of AMIP models from CMIP6 in simulating winter surface air temperature trends over Eurasia during 1998–2012 based on dynamical adjustment

Future evolution of global land surface air temperature trend based on Coupled Model Intercomparison Project Phase 6 models

AbstractIn recent decades, global warming has been an indisputable fact. The increase in extreme events accompanied by the rise in temperature has huge influences on many aspects of the society and economy globally. As a result, forecasting how global temperatures will change and evolve in the future is crucial, but it is restricted by the accuracy and uncertainty of model simulations. Based on ensemble empirical mode decomposition (EEMD) method, this study first evaluates the performance of the CMIP6 models in simulating different timescale components including high‐frequency components (HFC), low‐frequency components (LFC), and secular trend (ST) of surface air temperature (SAT). The results show that the performance of the CMIP6 models in simulating the ST is better. Following the observation constraint method's correction of CMIP6 model simulations, we investigate the evolution characteristics of future temperature secular trends under different Shared Socioeconomic Pathway (SSP) scenarios. The results show that under SSP245 scenario, the rise of SAT first appeared in northwest and east North America and eastern Europe. The spatial distribution of evolution characteristic under the SSP585 scenario is similar to that of the SSP245 scenario but with a larger magnitude. However, more pronounced differences appear in warming rate, which shows a downward trend over time under the SSP245 scenario and an upward trend with time under the SSP585 scenario.

Empirical Estimates of the Contribution of Greenhouse Gases and Natural Climatic Variability to Surface Air Temperature Trends for Various Latitudes

Empirical Estimates of the Contribution of Greenhouse Gases and Natural Climatic Variability to Surface Air Temperature Trends for Various Latitudes

Developing an Optimized Policy Tree-Based Reservoir Operation Model for High Aswan Dam Reservoir, Nile River

The impacts of climate change on the Nile River and Grand Ethiopian Renaissance Dam (GERD) along with the increased water demand downstream suggest an urgent need for more efficient management of the reservoir system that is well-informed by accurate modeling and optimization of the reservoir operation. This study provides an updated water balance model for Aswan High Dam Reservoir, which was validated using combined heterogeneous sources of information, including in situ gauge data, bias-corrected reanalyzed data, and remote sensing information. To investigate the future challenges, the spatial distribution of the annual/seasonal Aswan High Dam Reservoir surface air temperature trends over the period from 1979 to 2018 was studied. An increase of around 0.48 °C per decade in average annual temperature was detected, a trend that is expected to continue until 2100. Moreover, a set of machine learning models were developed and utilized to bias-correct the reanalyzed inflow and outflow data available for Aswan High Dam Reservoir. Finally, a policy tree optimization model was developed to inform the decision-making process and operation of the reservoir system. Results from the historical test simulations show that including reliable inflow data, accurate estimation of evaporation losses, and including new regulations and added projects, such as the Toshka Project, greatly affect the simulation results and guide managers through how the reservoir system should be operated in the future.

An NAO-dominated mode of atmospheric circulation drives large decadal changes in wintertime surface climate and snow mass over Eurasia

The leading mode of wintertime atmospheric variability over the North Atlantic-North Eurasia sector is dominated by the North Atlantic Oscillation (NAO) and accounts for more than one third of the total variability. This study explores the influences of the leading mode on decadal climate variability of Northern Eurasia. We focus on the little-explored decadal covariations of surface air temperature (SAT), snowfall, snow water equivalent (SWE) and snow cover over the region, using extensive model output from the Coupled Model Intercomparison Project sixth phase. Recent decadal trends (−0.92σ per decade) in the leading mode identified, are found to be largely a manifestation of internal climate variability (at least two thirds from the most conservative estimate). These internally-generated decadal trends strongly contributed to recent trends in SAT, snowfall, SWE and snow cover over Eurasia. External forcings should have played a minor role over Eurasia as they usually suggest opposite decadal trends to those observed. An exception is found for snowfall and SWE in east Eurasia, for which external forcings may have driven a large part of the recent upward trends, equally as important as the NAO-dominated mode. This points to a complex interplay between internally-generated and externally-forced climate variability over Northern Eurasia. Model discrepancies are identified in reproducing the linkages between the leading mode and the Eurasian surface climate variability. The internally-generated variability of this leading mode thus represents a large source of uncertainty in future decadal climate projections over Eurasia and, due to the memory effects of snow, also in modelling springtime climate variability.

Trend Analysis of Annual Surface Air Temperature for Some Stations over Iraq

Surface Air Temperature (SAT) is an important weather element affecting the climate and its nature, as it greatly affects the nature of the atmosphere prevailing in the city of Baghdad, as well as the main influence on the pressure systems affecting Iraq and thus the city of Baghdad. In this study, the annual SAT for three aspects of temperatures (mean, maximum, and minimum) for Baghdad city of approved 11 years had studied, analyzed and discussed. The sources of data came from two sources. First, Iraqi Meteorological Organization and Seismology (IMOS), which represented the arithmetic average annually of the SAT, maximum and minimum temperature for the period (2009 – 2019). Second source of data was from Mustansiriyah University, atmospheric sciences department of Atmospheric Sciences - college of Science, the data are supported as monthly average for SAT for Baghdad. Results shown Basrah was high annual of SAT than four selective cities in Iraq. The variation of annual SAT was in the end study period where reach to 7 oC in mean of SAT for Basrah city. The trend of SAT for Baghdad city was positive for Mean and maximum, while negative for minimum case. Mustansiriyah station was high than IMOS station by 2 oC for mean of SAT, and 5 oC for maximum SAT.

Trends in surface equivalent potential temperature: A more comprehensive metric for global warming and weather extremes

Trends in surface air temperature (SAT) are a common metric for global warming. Using observations and observationally driven models, we show that a more comprehensive metric for global warming and weather extremes is the trend in surface equivalent potential temperature (Thetae_sfc) since it also accounts for the increase in atmospheric humidity and latent energy. From 1980 to 2019, while SAT increased by 0.79[Formula: see text], Thetae_sfc increased by 1.48[Formula: see text] globally and as much as 4[Formula: see text] in the tropics. The increase in water vapor is responsible for the factor of 2 difference between SAT and Thetae_sfc trends. Thetae_sfc increased more uniformly (than SAT) between the midlatitudes of the southern hemisphere and the northern hemisphere, revealing the global nature of the heating added by greenhouse gases (GHGs). Trends in heat extremes and extreme precipitation are correlated strongly with the global/tropical trends in Thetae_sfc. The tropical amplification of Thetae_sfc is as large as the arctic amplification of SAT, accounting for the observed global positive trends in deep convection and a 20% increase in heat extremes. With unchecked GHG emissions, while SAT warming can reach 4.8[Formula: see text] by 2100, the global mean Thetae_sfc can increase by as much as 12[Formula: see text], with corresponding increases of 12[Formula: see text] (median) to 24[Formula: see text] (5% of grid points) in land surface temperature extremes, a 14- to 30-fold increase in frequency of heat extremes, a 40% increase in the energy available for tropical deep convection, and an up to 60% increase in extreme precipitation.

Observed Changes in Meteorological Drought Events during 1981–2020 over Rwanda, East Africa

Drought is one of the most complex natural phenomena affecting the life and livelihood of people, especially in the current time of human-induced climate change. This research employs ground-based observations to assess the recent spatiotemporal characteristics of meteorological drought events over Rwanda. The drought is examined based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI) at seasonal and annual time scales from 1981 to 2020. The Man–Kendal test was used to evaluate the trends in rainfall, temperature, and SPEI values at the annual scale and during the March to May (MAM) and October to December (OND) seasons. The analysis revealed nonsignificant trends in annual (8.4 mm/decade), MAM (−3.4 mm/decade), and OND (4.5 mm/decade) rainfall, while an apparent significant increasing trend in surface air temperature was obtained during the MAM (0.19 °C/decade), OND (0.2 °C/decade), and annual (0.23 °C/decade) time slices. Overall, the SPEI characteristics indicated that the country is more prone to moderate drought events than severe and extreme drought events during MAM and OND seasons. However, the intensity, duration, and frequency differ spatially among seasons. The findings of this study inform policy and decision-makers on the past experienced drought behavior, which can serve as a baseline for future drought mitigation and adaptation plans.

The analysis of annual and seasonal surface air temperature trends of southern and southeastern Bosnia and Herzegovina from 1961 to 2017

In some areas of the world, regional climate change is in good agreement with global climate change. This study brings new information about what defines climate change in the contact area of Adriatic Sea and Southeastern Europe, and conclusions are based on trend analysis of annual and seasonal temperatures in the southern and southeastern parts of Bosnia and Herzegovina. Trend analysis was applied on mean annual surface air temperatures, mean maximum temperatures, and mean minimum temperatures of all four seasons. This study used 4 meteorological stations: Livno, Bileća, Mostar, and Ivan Sedlo for 56 years. The main statistical method is the Mann-Kendall test. The total number of analysis is 48. A statistically significant positive trend was determined in 36 analysis, while in the rest of the tests this was not the case. The highest amount of temperature increase is present in the mean maximum summer air temperatures in Livno and Ivan Sedlo. Mean minimum autumn air temperatures had the smallest increase. Negative trend is present in the mean autumn surface air temperatures and mean maximum autumn temperatures. Using a geographical information system resulted in visualizing regional differences in the spatial distribution of isotherms. The study area has combined the influence of orography and maritime effects of the Adriatic Sea. Having in mind these results, the growing temperature has been recognized as a problem which needs more attention in Bosnia and Herzegovina. Unfortunately, official documents which propose economic adaptation on climate change in this country are not at a satisfactory level.

Impact of internal variability on recent opposite trends in wintertime temperature over the Barents–Kara Seas and central Eurasia

The large ensembles of the IPSL-CM6A-LR model output for the historical forcing experiment were employed to investigate the role of internal variability in the formation of the recent “warm Arctic–cold Eurasia” trend pattern in winter surface air temperature (SAT). The ensemble-mean SAT shows a positive trend over Arctic during 1990–2014, indicating a positive contribution of anthropogenic forcing to the warming Arctic. Over the region of central Eurasia, the ensemble-mean SAT trend is opposite to the observed trend. The winter SAT trends display remarkable inter-member diversity over the Barents–Kara Seas (BKS) region and central Eurasia, suggesting an important role played by internal variability. In addition to anthropogenic forcing, the results suggest that the barotropic anticyclone over northern Eurasia arising from internal variability can also contribute positively to the warming anomalies over the BKS region. On the other hand, through a fingerprint pattern matching method, it is found that the observed cooling trend over central Eurasia tends to be predominantly due to the internal variability. Finally, the results estimate that the internal variability can contribute to about 50–60% of the observed warming trend over the BKS region.

Spatial patterns of multi–centennial surface air temperature trends in Antarctica over 1–1000 CE: Insights from ice core records and modeling

The spatial pattern of Antarctic surface air temperature variability on multi–decadal to multi–centennial time scales is poorly known because of the short instrumental records, the relatively small number of high–resolution paleoclimate observations, and biases in climate models. Here, changes in surface air temperature over Antarctica are reconstructed over the past two millennia using data assimilation constrained by different ice core water isotope records in order to identify robust signals. The comparison between previous statistically based temperature reconstructions and simulations covering the full Common Era driven by natural and anthropogenic forcings shows major discrepancies occurring in the period 1–1000 CE over East Antarctica, with the reconstructions displaying a warming over 1–500 CE that is not reproduced by the simulations. This suggests that the trends in the first millennium deduced from the statistically based reconstructions are unlikely to be entirely forced by external forcings. Our reconstructions show the high sensitivity of the 500-year temperature trend in Antarctica and its spatial distribution to selection of the records for the reconstructions, especially during 1–500 CE. A robust cooling over Antarctica during 501–1000 CE has been obtained in three data assimilation–based reconstructions with a larger magnitude in the WAIS than elsewhere over Antarctica, in agreement with previous estimates with the larger changes than simulated in climate models. The reconstructions for atmospheric circulation indicate that the pattern of temperature changes over 501–1000 CE is related to the positive trend of Southern Annular Mode and a deepening of Amundsen Sea Low. This confirms the role of internal variability in the temperature trends on multi–centennial scales.

Inter-model spread in the wintertime Arctic amplification in the CMIP6 models and the important role of internal climate variability

We study the characteristics of wintertime Arctic amplification (AA) and the inter-model spread in model output from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the Community Earth System Model Large Ensemble Project (CESM-LE). The CMIP6 models exhibit a large spread in AA intensity (as measured by an AA index, ranging from about −0.2 to about 1.1 °C/decade in the Historical simulations) and in its spatial/vertical structure (no AA to AA extending to upper-troposphere). A large model spread in Arctic sea-ice trends (from about −3.1 to about 0.3 %/decade) is also found. Intra-model spread in the ensemble simulations of six selected CMIP6 models, which we interpret as a measure of internal climate variability, is similarly large. We further find that CMIP6 model integrations where AA extends to the upper-troposphere, show weaker warming in the midlatitudes. The observed recent midlatitude cooling trends are generally not seen in the one-realization CMIP6 models but are seen in some ensemble members in the CMIP6 ensemble simulations; They are likely not a response to Arctic sea ice decline according to our analysis and are more likely caused by internal climate variability. By comparing the CMIP6 inter-model spread to the intra-model spread in the six selected CMIP6 ensembles and CESM-LE simulations, we argue that a large part of the CMIP6 inter-model spread in AA index, surface air temperature (SAT) trends and Arctic sea ice trends can be attributed to internal climate variability: about 67% for AA index, 58% for Arctic SAT and 22% for Arctic sea-ice. However, the inferred internal climate variability has been relatively stable in the recent several decades, while the inter-model spread in Arctic temperature trends and particularly Arctic sea-ice trends has been increasing in the CMIP6 models. This highlights the importance of constraining CMIP6 model discrepancies in simulating recent climate variations, which will potentially benefit the future multimodel climate projections. • There is a large spread in CMIP6 models in simulating the recent wintertime Arctic amplification. • Internal climate variability can account for a large part of the CMIP6 model spread. • The influences of Arctic sea ice loss on Eurasian temperature as hypothesized in existing studies are not found based on CMIP6 models/ensembles. • Full-AA is associated with weaker warming trends in midlatitudes compared to surface-only AA.

Observed and simulated winter temperature over Gurudongmar area, North Sikkim, India

The global warming and its impact on the cryosphere is a matter of serious concern. The Sikkim and the Eastern Himalaya are a canvas of vivid landscapes and of different climate zones. The study of cryosphere needs more attention on long term climatic trends of surface air temperature. The Gurudongmar area is very much important because this area is surrounded by glaciers and as well as cold desert and TsoLhamo Lake nearby. The Gurudongmar lake (located at an altitude of 17,800 ft) has been studied by several researchers in the context of Glacial Lake Outburst Floods (GLOFs) and reported a high risk lake which is being largely affected by global warming and climate change. The present study is aimed to investigate the trend of temperature in recent past and in future time periods over the study area of Sikkim. The observed and model’s simulated gridded temperature data is considered to inkling of rising trend in winter months of December-January-February (DJF) over the study area. An increase in temperature is found for the future time period. This can be linked to the increasing hazard risk and change in local cryosphere environment.

The effect of urbanization on temperature indices in the Philippines

AbstractThis paper presents a comprehensive analysis of the effect of urbanization on the surface air temperature (SAT) from 1951 to 2018 in the Philippines. The daily minimum temperature (Tmin) and daily maximum temperature (Tmax) records from 34 meteorological stations were used to derive extreme temperature indices. These stations were then classified as urban or rural based on satellite night‐lights. The results showed a significant difference in the SAT trends between urban and rural stations, indicative of the effect of urbanization in the country. Larger and more significant warming trends were observed in indices related to Tmin than those related to Tmax. In particular, the effects of urbanization were significant in the annual index series of Tmin, diurnal temperature range, minimum Tmin, percentage of days when Tmin was less than the 10th percentile (TN10p), percentage of days when Tmin was greater than 90th percentile (TN90p), and the number of coldest nights. The effects of urbanization were not as clear on the index series of maximum Tmax (TXx), minimum Tmax (TXn), percentage of days when Tmax was less than 10th percentile (TX10p), and the number of hottest days. The effects of urbanization on the annual series of extreme temperature indices were statistically significant at the 95% confidence level, with the exception of Tmax, TXn, TXx, TX10p, and the number of hottest days. Further analysis revealed that the effect of urbanization was the greatest during the DJF (December–January–February) season. These findings serve as a baseline study that focuses on the countrywide effect of urbanization on SAT trends in the Philippines.

A GA-Based BP Artificial Neural Network for Estimating Monthly Surface Air Temperature of the Antarctic during 1960–2019

The spatial sparsity and temporal discontinuity of station-based SAT data do not allow to fully understand Antarctic surface air temperature (SAT) variations over the last decades. Generating spatiotemporally continuous SAT fields using spatial interpolation represents an approach to address this problem. This study proposed a backpropagation artificial neural network (BPANN) optimized by a genetic algorithm (GA) to estimate the monthly SAT fields of the Antarctic continent for the period 1960–2019. Cross-validations demonstrate that the interpolation accuracy of GA-BPANN is higher than that of two benchmark methods, i.e., BPANN and multiple linear regression (MLR). The errors of the three interpolation methods feature month-dependent variations and tend to be lower (larger) in warm (cold) months. Moreover, the annual SAT had a significant cooling trend during 1960–1989 (trend = −0.07°C/year; p = 0.04 ) and a significant warming trend during 1990–2019 (trend = 0.06°C/year; p = 0.05 ). The monthly SAT did not show consistent cooling or warming trends in all months, e.g., SAT did not show a significant cooling trend in January and December during 1960–1989 and a significant warming trend in January, June, July, and December during 1990–2019. Furthermore, the Antarctic SAT decreases with latitude and the distance away from the coastline, but the eastern Antarctic is overall colder than the western Antarctic. Spatiotemporal inconsistencies on SAT trends are apparent over the Antarctic continent, e.g., most of the Antarctic continent showed a cooling trend during 1960–1989 (trend = −0.20∼0°C/year; p = 0.01 ∼ 0.27 ) with a peak over the central part of the eastern Antarctic continent, while the entire Antarctic continent showed a warming trend during 1990–2019 (trend = 0∼0.10°C/year; p = 0.04 ∼ 0.42 ) with a peak over the higher latitudes.

BCC-CSM2-HR: a high-resolution version of the Beijing Climate Center Climate System Model

Abstract. BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model (T266 in the atmosphere and 1/4∘ latitude × 1/4∘ longitude in the ocean). Its development is on the basis of the medium-resolution version BCC-CSM2-MR (T106 in the atmosphere and 1∘ latitude × 1∘ longitude in the ocean) which is the baseline for BCC participation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamical core and physical processes. BCC-CSM2-HR is evaluated for historical climate simulations from 1950 to 2014, performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. Observed global warming trends of surface air temperature from 1950 to 2014 are well captured by both BCC-CSM2-MR and BCC-CSM2-HR. Present-day basic atmospheric mean states during the period from 1995 to 2014 are then evaluated at global scale, followed by an assessment on climate variabilities in the tropics including the tropical cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden–Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR represents the global energy balance well and can realistically reproduce the main patterns of atmospheric temperature and wind, precipitation, land surface air temperature, and sea surface temperature (SST). It also improves the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of the double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, almost disappears in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, and the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observations than their counterparts in BCC-CSM2-MR. Some imperfections are, however, noted in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold SST biases and the insufficient number of tropical cyclones in the North Atlantic.

Seasonally changing contribution of sea ice and snow cover to uncertainty in multi-decadal Eurasian surface air temperature trends based on CESM simulations

This study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

The Role of Horizontal Temperature Advection in Arctic Amplification

AbstractThe 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 the SAT, are produced primarily by downward longwave radiation.