Surface Air Temperature Anomalies Research Articles

Biases of the wintertime Arctic Oscillation in CMIP5 models

Distinct biases are found in the pattern and teleconnections of the Arctic Oscillation (AO) in 32 climate models that participate the Coupled Model Intercomparison Project Phase 5 (CMIP5). Compared with observations, the Pacific (Atlantic) center of AO is excessively strong (weak) in most of the 32 CMIP5 models, and the AO-related surface air temperature anomalies are generally weak over the Eurasian continent and North America. These biases are closely tied to the excessively strong linkage, which is marginal in observations, between AO and the North Pacific mode (NPM)—the leading variability of the North Pacific sea level pressure. It implies that the AO in CMIP5 models may be compounded with some regional mode over the North Pacific. Accordingly, a bias-correction method was proposed via correcting the AO index (AOI) to improve the diagnostic estimates of the AO teleconnections. The results suggest that the biases in the pattern and teleconnections of AO can be significantly reduced when the NPM variability is linearly removed from the AOI.

The influence of winter and summer atmospheric circulation on the variability of temperature and sea ice around Greenland

Most peripheral seas of the Arctic Ocean have seen a pronounced rise in sea surface temperatures in the past century, and this signature of Arctic amplification in proximity to the land suggests that the observed marine and terrestrial changes might be connected to each other. Using in situ observations of temperature from nine coastal meteorological stations around Greenland (GrSTs) and remotely sensed fields of sea ice extent (SIE), we examine the interannual variations of surface air temperature (T2m) and sea level pressure (SLP) anomalies associated with the GrSTs and SIEs surrounding Greenland, specifically within Baffin Bay, the Greenland Sea and Kara-Barents Seas. During winter, the interannual variation in T2m and SLP of the west and south coasts of GrSTs and the Baffin Bay SIE are different from that of the east coast of GrSTs and the SIEs in the Greenland Sea and Kara-Barents Seas. The GrSTs on the west and south coasts of Greenland and the Baffin Bay SIE are associated with the T2m anomalies over Baffin Bay and Davis Strait. The winter SLP patterns associated with these GrSTs and SIEs show positive anomalies over the Arctic and negative anomalies over the North Atlantic with a large-scale atmospheric circulation such as the winter NAO. On the contrary, the east coast of GrSTs and the SIEs in the Greenland Sea and Kara-Barents Seas are correlated with the T2m anomalies over the Greenland Sea and Barents Sea. The surface wind pattern associated with the SIEs in the Greenland Sea and Kara-Barents Seas has a cyclonic circulation in the Greenland Sea and Barents Sea. At the local scale the cyclonic circulation could induce negative SIE anomalies and contribute to increasing open water in the Greenland Sea and Barents Sea. The effect of the loss of sea ice and the heat from the open ocean warming to the atmosphere may influence the GrSTs in the east coast of Greenland. As a result, the T2m pattern associated with the GrSTs in the east coast of Greenland is similar to the pattern of the SIEs in the Greenland Sea and Kara-Barents Seas. During summer, the T2m anomalies associated with all GrSTs and SIEs have positive anomalies over mid-latitudes. The two times series of all GrSTs and SIEs fluctuate quickly and display large trends towards warming temperatures and decreasing SIE. The summer SLP associated with all GrSTs and SIEs are characterised by a seesaw pattern between positive anomalies over the Arctic and negative anomalies over mid-latitudes. The summer SLP anomalies are similar to the summer AO pattern, and it is noteworthy that the summer anticyclonic circulation over the Arctic and Greenland has contributed to the variability and trends in both summer GrSTs and SIEs.

Effect of tropical Indian Ocean thermal condition during preceding winter on summer high temperature anomalies over the southern Yangtze River valley

ABSTRACTThe present study investigates signals of summer high temperature anomalies over the southern Yangtze River valley (SYRV) region. The results show that summer high temperature anomalies over the SYRV region are associated with preceding winter sea surface temperature (SST) and surface air temperature (SAT) anomalies over the tropical Indian Ocean (TIO), particularly the tropical northwestern (5°–15°N, 55°–75°E) and southwestern (15°S–0°N, 40°–55°E) Indian Ocean regions. Coupled with SST, positive SAT anomalies over the TIO region may persist from preceding winter to summer, leading to more summer precipitation over the northwestern India and Arabian Sea (IAS) region. More summer precipitation (increased condensational heating) over the IAS region can regulate the strength and location of the western Pacific subtropical high and the South Asian high and result in their vertical superposition over the SYRV region. As such, a deep and stable high‐pressure anomaly forms over the SYRV region and results in high temperature anomalies. In this process, anomalous precipitation over the IAS region may to some degree act as a ‘bridge’ in providing a delayed impact of the preceding winter TIO SAT on summer SAT over the SYRV region. The effect of the preceding winter TIO SAT on summer SYRV SAT becomes weaker after removing the variability of IAS precipitation.

How strong is the impact of the Indo-ocean dipole on the surface air temperature/sea level pressure anomalies in the Mediterranean region?

The aim of this paper is to study the interannual climate variability over the Mediterranean region related to the Indo-ocean dipole (IOD) using the data of re-analyses, archival data and specialized numerical experiments. It is shown that the IOD does not impact essentially the anomalies of surface air temperature (SAT) and sea level pressure (SLP) in the Mediterranean region. On average, the IOD-induced share of the SAT/SLP variance in the total variance of these fields in the Mediterranean region is smaller than 10% even in summer when it is at a maximum. However, the statistically significant IOD-induced SAT/SLP anomalies in the Mediterranean region are detectable. For definite IOD events the associated Mediterranean SAT anomalies can reach about 1°C.

Connection between Anomalous Zonal Activities of the South Asian High and Eurasian Summer Climate Anomalies

Abstract Using the daily mean anomalies of atmospheric variables from the NCEP Reanalysis-1 (NCEP R1), this study reveals the connection between anomalous zonal activities of the South Asian high (SAH) and Eurasian climate anomalies in boreal summer. An analysis of variance identifies two major domains with larger geopotential height variability located in the eastern and western flanks of the SAH at around 100 and 150 hPa, respectively. For both eastern and western domains, extreme events are selected during 1981–2014 when normalized height anomalies are greater than 1.0 (less than −1.0) standard deviation for at least 10 consecutive days. Based on these events, four SAH modes that include strong and weak Tibetan modes (STM and WTM, respectively) and strong and weak Iranian modes (SIM and WIM, respectively) are defined to depict the zonal SAH features. The positive composite in the eastern (western) domain indicates the STM (SIM) manifests a robust wavelike pattern with an anomalous low at 150 hPa, and surface cold and wet anomalies over Mongolia and northern China (Kazakhstan and western Siberia) are surrounded by three anomalous highs at 150 hPa and surface warm and dry anomalies over Eurasia. Opposite distributions are also evident in the negative composites of the two domains (WTM and WIM). The surface air temperature anomalies are the downward extension of an anomalous air column aloft while the precipitation anomalies are directly associated with the height anomalies above the air column.

The warmest year 2015 in the instrumental record and its comparison with year 1998

AbstractThe global annual averaged Surface Air Temperature Anomaly (SATA) in 2015 and its rank in the historical instrumental records are analyzed using the CRU, NASA, and NOAA datasets. All datasets indicate that 2015 is the warmest year, which is 0.74 °C warmer than normal years from 1961 to 1990 in the HadCRUT4 data-set. The most evident warm anomaly occurs over land, especially at high latitudes. The averaged SATA over land is 1.13 °C, which is 0.54 °C warmer than that over oceans (0.59 °C). Because an El Nino event occurred in 2015 and 1998 and 1998 is also the warmest year in the twentieth century, these two years are compared to explain the formation of the warmest climate. A statistical approach that is known as the Ensemble Empirical Mode Decomposition (EEMD) is employed to isolate the components with different timescales, which range from interannual to centennial and a long-term trend. In 2015 the developing El Nino may have contributed an anomaly of 0.10 °C, while this value is 0.18 °C for 199...

SeFo: A Package for Generating Probabilistic Forecasts from NMME Predictive Ensembles

Long-range weather forecasts based on output from ensembles of computer simulations are attracting increasing interest. A variety of methods have been proposed to convert the ensemble outputs to calibrated probabilistic forecasts. The package presented here (SeFo, for Seasonal Forecasting) implements a number of methods for producing forecasts of monthly surface air temperature anomalies up to 9 months in advance using output from the North American Multi-Model Ensemble (NMME). The package contains modules for downloading and reading past observations and ensemble output; producing forecast probability distributions; and verifying and calibrating a user-determined subset of methods using arbitrary past periods. By changing individual modules, the package could be extended to use other model ensembles, forecast other weather variables, or apply other forecast methods. SeFo is written in the numerical computing language Octave and is available on Bitbucket under the GNU General Public License (Version 3 or later).

The signatures of large‐scale patterns of atmospheric variability in Antarctic surface temperatures

AbstractWe investigate the impact that the four principal large‐scale patterns of Southern Hemisphere (SH) atmospheric circulation variability have on Antarctic surface air temperature (SAT): (1) the southern baroclinic annular mode (BAM), which is associated with variations in extratropical storm amplitude; (2) the Southern Annular Mode (SAM), associated with latitudinal shifts in the midlatitude jet; and (3) the two Pacific‐South American patterns (PSA1 and PSA2), which are characterized by wave trains originating in the tropical Pacific that extend across the SH extratropics. A key aspect is the use of 35 years of daily observations and reanalysis data, which affords a sufficiently large sample size to assess the signatures of the circulation patterns in both the mean and variability of daily mean SAT anomalies. The BAM exerts the weakest influence on Antarctic SAT, albeit it is still important over select regions. Consistent with previous studies, the SAM is shown to influence SAT across most of the continent throughout the year. The PSA1 also affects SAT across almost all of Antarctica. Regionally, both PSA patterns can exert a greater impact on SAT than the SAM but also have a significantly weaker influence during summer, reflecting the seasonality of the SH response to El Niño–Southern Oscillation. The SAM and PSA patterns have distinct signatures in daily SAT variance that are physically consistent with their signatures in extratropical dynamic variability. The broad‐scale climate linkages identified here provide benchmarks for interpreting the Antarctic climate response to future changes in tropical sea surface temperatures, ozone recovery, and greenhouse gas increases.

Physical characteristics of Eurasian winter temperature variability

Despite the on-going global warming, recent winters in Eurasian mid-latitudes were much colder than average. In an attempt to better understand the physical characteristics for cold Eurasian winters, major sources of variability in surface air temperature (SAT) are investigated based on cyclostationary EOF analysis. The two leading modes of SAT variability represent the effect of Arctic amplification (AA) and the Arctic oscillation (AO), respectively. These two modes are distinct in terms of the physical characteristics, including surface energy fluxes and tropospheric circulations, and result in significantly different winter SAT patterns over the Eurasian continent. The AA-related SAT anomalies are dipolar with warm Arctic, centered at the Barents–Kara Seas, and cold East Asia. In contrast, the negative AO-related SAT anomalies are characterized by widespread cold anomalies in Northern Eurasia. Relative importance of the AA and the negative AO contributions to cold Eurasian winters is sensitive to the region of interest.

Climatic anomalous patterns associated with the Arctic and Polar cell strength variations

The Arctic cell as a reversed and closed loop next to the Polar cell has been recently revealed in the Northern Hemisphere (NH). In this paper, we study the interannual variability of the Arctic and Polar cell strengths during 1979–2012, and their influence on surface air temperature (SAT), precipitation, and sea-ice concentration (SIC) at mid- and high-latitudes of the NH. We show that there is a significant negative correlation between the Arctic and Polar cell strengths. Both the Arctic and Polar cell strengths can well indicate the recurring climatic anomalies of SAT, precipitation, and SIC in their extreme winters. The surface large-scale cold–warm and dry–wet anomalous patterns in these extreme winters are directly linked with the vertical structure of height and temperature anomalies in the troposphere. Results suggest that the past climatic anomalies are better indicated by the strength anomalies of the Polar and Arctic cells than the traditional indices of mid-high latitude pattern such as the Arctic Oscillation and North Atlantic Oscillation. This study illustrates a three-dimensional picture of atmospheric variable anomalies in the troposphere that result in surface climatic anomalies.

Forced and Internal Components of Winter Air Temperature Trends over North America during the past 50 Years: Mechanisms and Implications*

Abstract This study elucidates the physical mechanisms underlying internal and forced components of winter surface air temperature (SAT) trends over North America during the past 50 years (1963–2012) using a combined observational and modeling framework. The modeling framework consists of 30 simulations with the Community Earth System Model (CESM) at 1° latitude–longitude resolution, each of which is subject to an identical scenario of historical radiative forcing but starts from a slightly different atmospheric state. Hence, any spread within the ensemble results from unpredictable internal variability superimposed upon the forced climate change signal. Constructed atmospheric circulation analogs are used to estimate the dynamical contribution to forced and internal components of SAT trends: thermodynamic contributions are obtained as a residual. Internal circulation trends are estimated to account for approximately one-third of the observed wintertime warming trend over North America and more than half locally over parts of Canada and the United States. Removing the effects of internal atmospheric circulation variability narrows the spread of SAT trends within the CESM ensemble and brings the observed trends closer to the model’s radiatively forced response. In addition, removing internal dynamics approximately doubles the signal-to-noise ratio of the simulated SAT trends and substantially advances the “time of emergence” of the forced component of SAT anomalies. The methodological framework proposed here provides a general template for improving physical understanding and interpretation of observed and simulated climate trends worldwide and may help to reconcile the diversity of SAT trends across the models from phase 5 of the Coupled Model Intercomparison Project (CMIP5).

Dominant Modes of Interannual Variability in Eurasian Surface Air Temperature during Boreal Spring

Abstract This study investigates interannual variations of surface air temperature (SAT) over mid- and high latitudes of Eurasia during boreal spring and their association with snow, atmospheric circulation, and sea surface temperature (SST) changes. The leading mode of spring SAT variations is featured by same-sign anomalies over most regions. The second mode features a tripole anomaly pattern with anomalies over the central part opposite to those over the eastern and western parts of Eurasia. A diagnosis of surface heat flux anomalies suggests that snow change contributes partly to SAT anomalies in several regions mainly by modulating surface shortwave radiation but cannot explain SAT changes in other regions. Atmospheric circulation anomalies play an important role in spring SAT variability via wind-induced heat advection and cloud-induced surface radiation changes. Positive SAT anomalies are associated with anomalous westerly winds from the North Atlantic Ocean or with anomalous anticyclone and southerly winds. Negative SAT anomalies occur in regions of anomalous cyclone and northerly winds. Atmospheric circulation anomalies associated with the first mode have a close relationship to spring Arctic Oscillation (AO), indicating the impact of the AO on continental-scale spring SAT variations over the mid- and high latitudes of Eurasia. The atmospheric circulation anomalies associated with the second mode feature a wave pattern over the North Atlantic and Eurasia. Such a wave pattern is related to a tripole SST anomaly pattern in the North Atlantic Ocean, signifying the contribution of the North Atlantic Ocean state to the formation of a tripole SAT anomaly pattern over the mid- and high latitudes of Eurasia.

Unforced Surface Air Temperature Variability and Its Contrasting Relationship with the Anomalous TOA Energy Flux at Local and Global Spatial Scales*

Abstract Unforced global mean surface air temperature () is stable in the long term primarily because warm anomalies are associated with enhanced outgoing longwave radiation () to space and thus a negative net radiative energy flux (, positive downward) at the top of the atmosphere (TOA). However, it is shown here that, with the exception of high latitudinal and specific continental regions, warm unforced surface air temperature anomalies at the local spatial scale [T(θ, ϕ), where (θ, ϕ) = (latitude, longitude)] tend to be associated with anomalously positive N(θ, ϕ). It is revealed that this occurs mainly because warm T(θ, ϕ) anomalies are accompanied by anomalously low surface albedo near sea ice margins and over high altitudes, low cloud albedo over much of the middle and low latitudes, and a large water vapor greenhouse effect over the deep Indo-Pacific. It is shown here that the negative versus relationship arises because warm anomalies are associated with large divergence of atmospheric energy transport over the tropical Pacific [where the N(θ, ϕ) versus T(θ, ϕ) relationship tends to be positive] and convergence of atmospheric energy transport at high latitudes [where the N(θ, ϕ) versus T(θ, ϕ) relationship tends to be negative]. Additionally, the characteristic surface temperature pattern contains anomalously cool regions where a positive local N(θ, ϕ) versus T(θ, ϕ) relationship helps induce negative . Finally, large-scale atmospheric circulation changes play a critical role in the production of the negative versus relationship as they drive cloud reduction and atmospheric drying over large portions of the tropics and subtropics, which allows for greatly enhanced .

Time scales of the European surface air temperature variability: The role of the 7–8 year cycle

AbstractAir temperature variability on different time scales exhibits recurring patterns and quasi‐oscillatory phenomena. Climate oscillations with the period about 7–8 years have been observed in many instrumental records in Europe. Although these oscillations are weak if considering their amplitude, they might have nonnegligible influence on temperature variability on shorter time scales due to cross‐scale interactions recently observed by Paluš (2014). In order to quantify the cross‐scale influence, we propose a simple conditional mean approach which estimates the effect of the cycle with the period close to 8 years on the amplitude of the annual cycle in surface air temperature (SAT) in the range 0.7–1.4°C and the effect on the overall variability of the SAT anomalies (SATA) leads to the changes 1.5–1.7°C in the annual SATA means. The strongest effect in the winter SATA means reaches 4–5°C in central European station and reanalysis data.

Modulation of summer monsoon sub-seasonal surface air temperature over India by soil moisture-temperature coupling

The influence of soil moisture on the sub-seasonal warmer surface air temperature anomalies during drier soil conditions associated with break spells in the Indian summer monsoon precipitation is explored using observations. The multi-model analysis of land surface states and fluxes available from the Second Global Soil Wetness Project (GSWP-2) are found useful in understanding the mechanism for this soil moisture-temperature coupling on sub-seasonal timescales. The analysis uses a soil moisture-temperature coupling diagnostic computed based on linear correlations of daily fields. It is shown that the summer surface air temperature variations are linked to intraseasonal variations of the Indian monsoon precipitation, which control the land-climate coupling by modulating the soil moisture variations. Strong coupling mainly occurs during dry soil states within the summer monsoon season over the transition zones between wet and dry climates of central to north-west India. In contrast, the coupling is weak for constantly wet and energy-limited evaporative regimes over eastern India during the entire summer monsoon season. This observational based analysis provided a better understanding of the linkages between the sub-seasonal dry soil states and warm conditions during the Indian summer monsoon season. A proper representation of these aspects of land-atmosphere interactions in weather and climate models used for sub-seasonal and seasonal monsoon forecasting could be critical for several applications, in particular agriculture. The soil moisture-temperature coupling diagnostic used in this study will be a useful metric for evaluating the performance of weather and climate models.

The Effects of Gridding Algorithms on the Statistical Moments and Their Trends of Daily Surface Air Temperature*

Abstract This paper explores the effects from averaging weather station data onto a grid on the first four statistical moments of daily minimum and maximum surface air temperature (SAT) anomalies over the entire globe. The Global Historical Climatology Network–Daily (GHCND) and the Met Office Hadley Centre GHCND (HadGHCND) datasets from 1950 to 2010 are examined. The GHCND station data exhibit large spatial patterns for each moment and statistically significant moment trends from 1950 to 2010, indicating that SAT probability density functions are non-Gaussian and have undergone characteristic changes in shape due to decadal variability and/or climate change. Comparisons with station data show that gridded averages always underestimate observed variability, particularly in the extremes, and have altered moment trends that are in some cases opposite in sign over large geographic areas. A statistical closure approach based on the quasi-normal approximation is taken to explore SAT’s higher-order moments and point correlation structure. This study focuses specifically on relating variability calculated from station data to that from gridded data through the moment equations for weighted sums of random variables. The higher-order and nonlinear spatial correlations up to the fourth order demonstrate that higher-order moments at grid scale can be determined approximately by functions of station pair correlations that tend to follow the usual Kolmogorov scaling relation. These results can aid in the development of constraints to reduce uncertainties in climate models and have implications for studies of atmospheric variability, extremes, and climate change using gridded observations.

The Early 1990s Change in ENSO–PSA–SAM Relationships and Its Impact on Southern Hemisphere Climate

Abstract This study uncovers an early 1990s change in the relationships between El Niño–Southern Oscillation (ENSO) and two leading modes of the Southern Hemisphere (SH) atmospheric variability: the southern annular mode (SAM) and the Pacific–South American (PSA) pattern. During austral spring, while the PSA maintained a strong correlation with ENSO throughout the period 1948–2014, the SAM–ENSO correlation changed from being weak before the early 1990s to being strong afterward. Through the ENSO connection, PSA and SAM became more in-phase correlated after the early 1990s. The early 1990s is also the time when ENSO changed from being dominated by the eastern Pacific (EP) type to being dominated by the central Pacific (CP) type. Analyses show that, while the EP ENSO can excite only the PSA, the CP ENSO can excite both the SAM and PSA through tropospheric and stratospheric pathway mechanisms. The more in-phase relationship between SAM and PSA impacted the post-1990s Antarctic climate in at least two aspects: 1) a stronger Antarctic sea ice dipole structure around the Amundsen–Bellingshausen Seas due to intensified geopotential height anomalies over the region and 2) a shift in the phase relationships of surface air temperature anomalies among East Antarctica, West Antarctica, and the Antarctic Peninsula. These findings imply that ENSO–Antarctic climate relations depend on the dominant ENSO type and that ENSO forcing has become more important to the Antarctic sea ice and surface air temperature variability in the past two decades and will in the coming decades if the dominance of CP ENSO persists.

Boreal Winter MJO Teleconnection in the Community Atmosphere Model Version 5 with the Unified Convection Parameterization

Abstract The Madden–Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, influences weather and climate in the extratropics through atmospheric teleconnection. In this study, two simulations using the Community Atmosphere Model version 5 (CAM5)—one with the default shallow and deep convection schemes and the other with the unified convection scheme (UNICON)—are employed to examine the impacts of cumulus parameterizations on the simulation of the boreal wintertime MJO teleconnection in the Northern Hemisphere. It is demonstrated that the UNICON substantially improves the MJO teleconnection. When the UNICON is employed, the simulated circulation anomalies associated with the MJO better resemble the observed counterpart, compared to the simulation with the default convection schemes. Quantitatively, the pattern correlation for the 300-hPa geopotential height anomalies between the simulations and observation increases from 0.07 for the default schemes to 0.54 for the UNICON. These circulation anomalies associated with the MJO further help to enhance the surface air temperature and precipitation anomalies over North America, although room for improvement is still evident. Initial value calculations suggest that the realistic MJO teleconnection with the UNICON is not due to the changes in the background wind, but rather primarily to the improved tropical convective heating associated with the MJO.

The Influence of the MJO on the Intraseasonal Variability of Northern Hemisphere Spring Snow Depth

Abstract Intraseasonal variability in springtime Northern Hemisphere daily snow depth change (ΔSD) by phase of the MJO was explored in this study. Principal findings of the relationship between ΔSD and the MJO included the following: 1) Statistically significant regions of lagged ΔSD anomalies for multiple phases of the MJO were found in March, April, and May in both North America and Eurasia. 2) In each month, lagged ΔSD anomalies were physically supported by corresponding lagged anomalies of 500-hPa height (Z500) and surface air temperature (SAT). Spearman rank correlation coefficients indicated a moderate to strong relationship between both Z500 and ΔSD and SAT and ΔSD in both Eurasia and North America for phases 5 and 7 in March. In April, a moderately strong relationship between Z500 and ΔSD was found over Eurasia for phase 5, but the relationship between SAT and ΔSD was weak. In May, correlations between ΔSD and both Z500 and SAT over a hemisphere-wide latitude band from 60° to 75°N were close to −0.5 and −0.4, respectively. Given the strength of these statistical relationships, the following physical pathway is proposed for intraseasonal variability of spring snow depth changes: poleward-propagating Rossby waves in response to tropical MJO convection interact with Northern Hemisphere background flow, leading to anomalous troughing and ridging. These anomalous circulation centers then impact daily snow depth change via precipitation processes and anomalies in surface air temperature.

Causes for different spatial distributions of minimum Arctic sea-ice extent in 2007 and 2012

Satellite records show the minimum Arctic sea ice extents (SIEs) were observed in the Septembers of 2007 and 2012, but the spatial distributions of sea ice concentration reduction in these two years were quite different. Atmospheric circulation pattern and the upper-ocean state in summer were investigated to explain the difference. By employing the ice-temperature and ice-specific humidity (SH) positive feedbacks in the Arctic Ocean, this paper shows that in 2007 and 2012 the higher surface air temperature (SAT) and sea level pressure (SLP) accompanied by more surface SH and higher sea surface temperature (SST), as a consequence, the strengthened poleward wind was favorable for melting summer Arctic sea ice in different regions in these two years. SAT was the dominant factor influencing the distribution of Arctic sea ice melting. The correlation coefficient is–0.84 between SAT anomalies in summer and the Arctic SIE anomalies in autumn. The increase SAT in different regions in the summers of 2007 and 2012 corresponded to a quicker melting of sea ice in the Arctic. The SLP and related wind were promoting factors connected with SAT. Strengthening poleward winds brought warm moist air to the Arctic and accelerated the melting of sea ice in different regions in the summers of 2007 and 2012. Associated with the rising air temperature, the higher surface SH and SST also played a positive role in reducing summer Arctic sea ice in different regions in these two years, which form two positive feedbacks mechanism.