Projected Changes in Extreme Event Indices for Alaska

As climate has warmed in recent decades, Alaska has experienced a variety of high-impact extreme events that include heat waves, wildfires, coastal storms and freezing rain. Because the warming is projected to continue, it is essential to consider future changes when planning adaptation actions and building resilience. In this study, we synthesize information on future changes in extreme events in Alaska from an ensemble of regional climate model simulations performed as part of Arctic-CORDEX (Coordinated Regional Climate Downscaling Experiment). A set of 13 extreme event indices, based on those developed by the World Climate Research Programme’s Expert Team on Climate Change Detection and Indices (ETCCDI), are evaluated from the Arctic-CORDEX output for Alaska. Of the 13 indices, six pertain to temperature, five to total precipitation, one to wind and one to snow. The results for locations in seven different climate zones of Alaska include large increases (5˚C - 10˚C) in the temperature thresholds for the five hottest and coldest days of the year, and large increases in warm spell duration and decreases in cold spell duration. Changes in the cold day temperature threshold are generally larger than the changes in the hot day temperature threshold, consistent with the projections of a stronger warming in winter than in summer in Alaska yearly maximum 1-day and 5-day precipitation amounts as well as the yearly number of consecutive wet days are projected to increase at all locations. The indices for heavy snow days and high-wind days show mixed changes, although the results indicate increases in heavy snow days at the more northern locations and increases in windy days at coastal locations. The changes in the extreme event indices continue through 2100 under the higher-emission (RCP 8.5) emission scenario, while the changes generally stabilize under the lower-emission (RCP 4.5) scenario. .

A Two-way Stratosphere–Troposphere Coupling of Submonthly Zonal-Mean Circulations in the Arctic

This paper examines the dominant submonthly variability of zonally symmetrical atmospheric circula- tion in the Northern Hemisphere （NH） winter within the context of the Northern Annular Mode （NAM）, with particular emphasis on interactive stratosphere-troposphere processes. The submonthly variability is identified and measured using a daily NAM index, which concentrates primarily on zonally symmetrical circulation. A schematic lifecycle of submonthly variability is developed that reveals a two-way coupling pro- cess between the stratosphere and troposphere in the NH polar region. Specifically, anomalous tropospheric zonal winds in the Atlantic and Pacific sectors of the Arctic propagate upwards to the low stratosphere, disturbing the polar vortex, and resulting in an anomalous stratospheric geopotential height （HGT） that subsequently propagates down into the troposphere and changes the sign of the surface circulations. From the standpoint of planetary-scale wave activities, a feedback loop is also evident when the anoma- lous planetary-scale waves （with wavenumbers 2 and 3） propagate upwards, which disturbs the anomalous zonally symmetrical flow in the low stratosphere, and induces the anomalous HGT to move poleward in the low stratosphere, and then propagates down into the troposphere. This increases the energy of waves at wavenumbers 2 and 3 in the low troposphere in middle latitudes by enhancing the land-sea contrast of the anomalous HGT field. Thus, this study supports the viewpoint that the downward propagation of stratospheric NAM signals may not originate in the stratosphere.

Dominant patterns of winter Arctic surface wind variability

Dominant statistical patterns of winter Arctic surface wind （WASW） variability and their impacts on Arctic sea ice motion are investigated using the complex vector empirical orthogonal function （CVEOF） method. The results indicate that the leading CVEOF of Arctic surface wind variability, which accounts for 33% of the covariance, is characterized by two different and alternating spatial patterns （WASWP1 and WASWP2）. Both WASWP1 and WASWP2 show strong interannual and decadal variations, superposed on their declining trends over past decades. Atmospheric circulation anomalies associated with WASWPI and WASWP2 exhibit, respectively, equivalent barotropic and some baroclinic characteristics, differing from the Arctic dipole anomaly and the seesaw structure anomaly between the Barents Sea and the Beaufort Sea. On decadal time scales, the decline trend of WASWP2 can be attributed to persistent warming of sea surface temperature in the Greenland--Barents--Kara seas from autunm to winter, reflecting the effect of the Arctic warming. The second CVEOF, which accounts for 18% of the covariance, also contains two different spatial patterns （WASWP3 and WASWP4）. Their time evolutions are significantly correlated with the North Atlantic Oscillation （NAO） index and the central Arctic Pattern, respectively, measured by the leading EOF of winter sea level pressure （SLP） north of 70~N. Thus, winter anomalous surface wind pattern associated with the NAO is not the most important surface wind pattern. WASWP3 and WASWP4 primarily reflect natural variability of winter surface wind and neither exhibits an apparent trend that differs from WASWP1 or WASWP2. These dominant surface wind patterns strongly influence Arctic sea ice motion and sea ice exchange between the western and eastern Arctic. Furthermore, the Fram Strait sea ice volume flux is only significantly correlated with WASWP3. The results demonstrate that surface and geostrophic winds are not interchangeable in terms of describing wind field variability over the Arctic Ocean. The results have important implications for understanding and investigating Arctic sea ice variations： Dominant patterns of Arctic surface wind variability, rather than simply whether there are the Arctic dipole anomaly and the Arctic Oscillation （or NAO）, effectively affect the spatial distribution of Arctic sea ice anomalies.

Decadal Variability Shown by the Arctic Ocean Hydrochemical Data and Reproduced by an Ice-Ocean Model

The Arctic is experiencing a significant warming trend as well as a decadal oscillation. The atmospheric circulation represented by the Polar Vortex and the sea ice cover show decadal variabilities, while it has been difficult to reveal the decadal oscillation from the ocean interior. The recent distribution of Russian hydrochemical data collected from the Arctic Basin provides useful information on ocean interior variabilities. Silicate is used to provide the most valuable data for showing the boundary between the silicate-rich Pacific Water and the opposite Atlantic Water. Here, it is assumed that the silicate distribution receives minor influence from seasonal biological productivity and Siberian Rivers outflow. It shows a clear maximum around 100m depth in the Canada Basin, along with a vertical gradient below 100 m, which provides information on the vertical motion of the upper boundary of the Atlantic Water at a decadal time scale. The boundary shifts upward (downward), as realized by the silicate reduction (increase) at a fixed depth, responding to a more intense (weaker) Polar Vortex or a positive (negative) phase of the Arctic Oscillation. A coupled ice-ocean model is employed to reconstruct this decadal oscillation.

Preface to the Special Issue:Towards Improving Understanding and Prediction of Arctic Change and its Linkage with Eurasian Mid-latitude Weather and Climate

The dramatic changes in the Arctic climate system during recent decades are one of the most prominent features of global climate change.Two most striking and fundamental characteristics are the amplified near-surface warming at a rate twice the global average since the mid 20th century(e.g.,Blunden and Arndt,2012;Huang et al.,2017),and the rapid

Modeling Arctic Ocean heat transport and warming episodes in the 20th century caused by the intruding Atlantic Water

This study investigates the Arctic Ocean warming episodes in the 20th century using both a high-resolution coupled global climate model and historical observations. The model, with no flux adjustment, reproduces well the Atlantic Water core temperature （AWCT） in the Arctic Ocean and shows that four largest decadalscale warming episodes occurred in the 1930s, 70s, 80s, and 90s, in agreement with the hydrographic observational data. The difference is that there was no pre-warming prior to the 1930s episode, while there were two pre-warming episodes in the 1970s and 80s prior to the 1990s, leading the 1990s into the largest and prolonged warming in the 20th century. Over the last century, the simulated heat transport via Fram Strait and the Barents Sea was estimated to be, on average, 31.32 TW and 14.82 TW, respectively, while the Bering Strait also provides 15.94 TW heat into the west- ern Arctic Ocean. Heat transport into the Arctic Ocean by the Atlantic Water via Fram Strait and the Barents Sea correlates significantly with AWCT （ C = 0.75 ） at 0- lag. The modeled North Atlantic Oscillation （NAO） index has a significant correlation with the heat transport （ C = 0.37 ）. The observed AWCT has a significant correlation with both the modeled AWCT （ C =0.49） and the heat transport （ C =0.41 ）. However, the modeled NAO index does not significantly correlate with either the observed AWCT （ C = 0.03 ） or modeled AWCT （ C = 0.16 ） at a zero-lag, indicating that the Arctic climate system is far more complex than expected.

Atmospheric feedbacks on Arctic summer sea-ice anomalies in ensemble simulations of a coupled regional climate model

Ensemble simulations with the Arctic coupled regional climate model HIRHAM-NAOSIM have been analyzed to investigate atmospheric feedbacks to September sea-ice anomalies in the Arctic in autumn and the following winter. Different ＂low- minus high ice＂ composites have been calculated using selected model runs and different periods. This approach allows us to investigate the robustness of the simulated regional atmospheric feedbacks to detected sea-ice anomalies. Since the position and strength of the September sea-ice anomaly varies between the different ＂low- minus high ice＂ composites, the related simulated atmospheric patterns in autumn differ depending on the specific surface heat flux forcing through the oceaaa-atmosphere interface. However, irrespective of those autumn differences, the regional atmospheric feedback in the following winter is rather insensitive to the applied compositing. Neither the selection of simulations nor the considered period impacts the results. The simulated consistent large-scale atmospheric circulation pattern show-s a wave-like pattern with positive pressure anomaly over the region of the Barents/Kara Seas and Scandinavia/western Russia （＂Scandinavian-Ural blocking＂） and negative pressure anomaly over the East Siberian/Laptev Seas.

加拿大海盆的营养盐极大

根据 1 999年和 2 0 0 3年中国北极科学考察航次 ,从Canada海盆收集温、盐、深和营养盐浓度数据 ,用文献报道的低浓度1 2 9I和高浓度金属钡 (Ba)来指示太平洋源水、用相应的高浓度1 2 9I和低浓度Ba来指示大西洋源水 ,划分了该海盆物理化学特征的 4个水团。表层水 ( <40m)的盐度从 2 5至 31 .6;硝酸盐处于耗尽水平 ,而磷酸盐和硅酸盐处于最低水平。营养盐再生水大致位于 40— 2 0 0m ;盐度特征为 31 .6— 33.1 ;营养盐浓度一致增至最高 ;极大峰的盐度在 33.1附近 ,其位温则处于最低水平 (约 - 1 .5°C)。混合水 (深约 2 0 0— 385m)盐度从 33.1至 34.8;位温从局域最低升至整个水柱最高的 0 .5 0— 0 .65 7°C ;营养盐则逐渐降低。深层水深度变化较大 ( 385m至 1 90 0m以下海底 ) ;但其盐度变化较小 ( 34.8— 34.9) ;位温则从最高降低到 - 0 .4至 - 0 5 4°C ;营养盐均轻微增加。结合文献中对于营养盐极大的年际观测 ,1 2 9I、Ba与氯氟烃CFC 1 1的浓度及3H 3He示踪年龄的结果分析表明 ,营养盐再生水是无季节性变化的、高年龄 (约 8— 1 5年 )的太平洋源水 ;深层为大西洋源水 ;而混合水团即为上述 2大源水的混合层。硅酸盐和磷酸盐的强极大指示优势种硅藻及其再生主导太平洋源水。

全球气候变暖背景下的大气环流基本模态

利用 NCEP/NCAR REANALYSIS 1948年1月～2001年2月1000～100 hPa的高度场资料研究全球纬圈平均大气环流的变化。EOF1显示全球纬圈平均大气高度场在高纬度和低纬度地区呈明显的反向变化,这一变化特点解释了总方差的一半左右。从时间系数上看,近53年低纬度高度上升,高纬度高度下降。这表明20世纪60年代以后,特别是20世纪80年代中期以后,对流层中纬度西风有明显的加强趋势。与全球平均地面气温变化比较证明这种大气环流的变化与全球平均地面气温的变化有显著的相关。用观测海温强迫运行大气环流模式积分两个50年(1900～1950年和1950～1999年),EOF1与再分析资料所得的EOF1特征十分相似,解释的方差大小也基本一致。伴随着近20年的全球气温的剧烈上升,低纬度高度场升高,高纬度高度场降低,两个半球中纬度西风显著加强成为全球大气环流变化的最主要特征。

白令海夏季水文结构年际变化特征研究

基于2008、2010、2012和2014年我国北极科学考察期间在白令海获取的水文观测数据,结合历史共享资料,通过对白令海水团、上层海洋热含量、净热通量变化、风场及海平面气压分布情况等的分析,探讨了白令海水文结构的年际变化特征及其原因。研究发现,白令海夏季的水团包括白令海上层水团(BUW)、中层水团(BIW)、深层水团(BDW)和白令海陆架水团(BSW)。白令海温盐分布差异最大、年际变化最剧烈的情况主要集中在上层水团。对比4年水团分布情况,最明显的变化是2012年7月调查区上层海水温度偏低,2014年7月上层海水温度偏高。这种异常变化在热含量方面表现为:2012年7月调查区各个测站上的热含量异常低,而2014年7月测站上的热含量都高于平均水平。着重研究了2014年7月海温偏高的原因,认为是由于陆架和海盆区分别有两种不同的形成机制造成:陆架区累积净热通量偏高,海水吸收热量升温;海盆区在异常强大而持久的海面气压(SLP)高压系统下,海面负的风应力旋度得到加强,从而引起持续的暖平流输送及强烈的Ekman抽吸作用,最终导致了上层海水偏暖。

南极普里兹湾海域夏季表层水与绕极深层水年际变化

利用中国第27、28、29和31次南极科学考察期间在普里兹湾海域获取的水文观测数据,分析了该海域的水团分布、夏季表层水年际变化及其原因和绕极深层水涌升的年际变化特征。研究发现:第27和31航次观测到的夏季表层水的温盐范围较大;第27航次观测到的夏季表层水温度相对较高,可达1.22℃;第29航次观测期间海冰较少,夏季表层水的厚度约为50 m(73.00°E、75.50°E和67.25°S断面),第31航次观测到的夏季表层水最深达到100 m;第28和29航次观测到较为明显的绕极深层水涌升,在73.00°E断面尤为突出;观测到的绕极深层水在第28航次向上涌升到90 m,在第29航次向南延伸较远,达到67.67°S;湾内气旋性环流对绕极深层水的涌升有明显的输运作用。

Regime Shifts in the North Pacific Simulated by a COADS-driven Isopycnal Model

The Miami Isopycnal Coordinate Ocean Model (MICOM) is adopted to simulate the intevdecadal variability in the Pacific Ocean with most emphasis on regime shifts in the North Pacific. The computational domain covers 60°N to 40°S with an enclosed boundary condition for momentum flux, whereas there are thermohalirie fluxes across the southern end as a restoring term. In addition, sea surface salinity of the model relaxes to the climatological season cycle, which results in climatological fresh water fluxes. Surface forcing functions from January 1945 through December 1998 are derived from the Comprehensive Ocean and Atmospheric Data Set (COADS). Such a numerical experiment reproduces the observed evolution of the interdecadal variability in the heat content over the upper 400-m layer by a two-year lag. Subduction that occurs at the ventilated thermocline in the central North Pacific is also been simulated and the subducted signals propagate from 35°N to 25°N, taking about 8 to 10 years, in agreement with the expendable Bathy Thermograph observation over recent decades. Interdecadal signals take a southwest-ward and downward path rather than westward propagation, meaning they are less associated with the baroclinic planetary waves. During travel, the signals appear to conserve potential vorticity. Therefore, the ventilated thermocline and related subduction are probably the fundamental physics for interdecadal variability in the mid-latitude subtropics of the North Pacific.

Nutrient maximums related to low oxygen concentrations in the southern Canada Basin

The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brines from the Chukchi Sea shelf (【 50 m) in winter providedthe nutrient maximums. However, we found that there are five problems in the direct injectionprocess. Formerly Jin et al. considered that the formation of nutrient maximums can be a process oflocally long-term regeneration. Here we propose a regeneration-mixture process. Data of temperature,salinity, oxygen and nutrients were collected at three stations in the southern Canada Basin duringthe summer 1999 cruise. We identified the cores of the surface, near-surface, potential temperaturemaximum waters and Arctic Bottom Water by the diagrams and vertical profiles of salinity, potentialtemperature, oxygen and nutrients. The historical ^(129)I data indicated that the surface andnear-surface waters were Pacific-origin, but the waters below the potential temperature maximum coredepth was Atlantic-origin. Along with the correlation of nutrient maximums and very low oxygencontents in the near-surface water, we hypothesize that, the putative organic matter was decomposedto inorganic nutrients; and the Pacific water was mixed with the Atlantic water in the transitionzone. The idea of the regeneration-mixture process agrees with the historical observations of noapparent seasonal changes, the smooth nutrient profiles, the lowest saturation of CaCO_3 above 400m, low rate of CFC-11 ventilation and ~3H-~3He ages of 8～18 a around the nutrient maximum depths.

Ocean Mixing with Lead-Dependent Subgrid Scale Brine Rejection Parameterization in a Climate Model

Sea ice thickness is highly spatially variable and can cause uneven ocean heat and salt flux on subgrid scales in climate models.Previous studies have demonstrated improvements in ocean mixing simulation using parameterization schemes that distribute brine rejection directly in the upper ocean mixed layer.In this study,idealized ocean model experiments were conducted to examine modeled ocean mixing errors as a function of the lead fraction in a climate model grid.When the lead is resolved by the grid,the added salt at the sea surface will sink to the base of the mixed layer and then spread horizontally.When averaged at a climate-model grid size,this vertical distribution of added salt is lead-fraction dependent.When the lead is unresolved,the model errors were systematic leading to greater surface salinity and deeper mixed-layer depth(MLD).An empirical function was developed to revise the added-salt-related parameter n from being fixed to lead-fraction dependent.Application of this new scheme in a climate model showed significant improvement in modeled wintertime salinity and MLD as compared to series of CTD data sets in 1997/1998 and 2006/2007.The results showed the most evident improvement in modeled MLD in the Arctic Basin,similar to that using a fixed n=5,as recommended by the previous Arctic regional model study,in which the parameter n obtained is close to 5 due to the small lead fraction in the Arctic Basin in winter.

The Intra-Annual Variability of Discharge, Sediment Load and Chemical Flux from the Monitoring: The Yukon River, Alaska

The covered-ice breakup in subarctic to arctic rivers in the early snowmelt season often gives any damage to instruments monitoring physical and chemical factors of water. The serious condition has brought few time series data during the snowmelt runoff except the river stage or discharge. In this study, the contribution of snowmelt runoff to the discharge and sediment load is quantified by monitoring water turbidity and temperature at the lowest gauging station of U. S. Geological Survey in the Yukon River, Alaska, for more than 3 years (June 2006 to September 2009). The turbidity was recorded by a self-recording turbidimeter with a sensor of infrared-ray back-scattering type, of which the window is cleaned by a wiper just before a measurement. The turbidity time series, coupled with frequent river water sampling at mid-channel, produce time series of suspended sediment (SS) concentration, particulate organic carbon (POC) concentration and particulate organic nitrogen (PON) concentration (mg?L–1) by using the high correlation (R2 = 0.747 to 0.790;P 11 to 2.01 × 1011 m3), 8.7% - 22.5% of the annual sediment load (3.94 × 107 to 5.08 × 107 ton), 11.6% - 23.7% of the annual POC flux (4.05 × 105 to 4.77 × 105 ton), and 10.3% - 24.5% of the annual PON flux (2.80 × 104 to 3.44 × 104 ton). In the snowmelt season, the peak suspended sediment concentration preceded the peak discharge by a few days. This probably results from the fluvial sediment erosion in the river channels.

Observations and modeling of the ice-ocean conditions in the coastal Chukchi and Beaufort Seas

The Chukchi and Beaufort Seas include several important hydrological features： inflow of the Pacific water, Alaska coast current （ ACC ）, the seasonal to perennial sea ice cover, and landfast ice ＇along the Alaskan coast. The dynamics of this coupled ice-ocean system is important for both regional scale oceanography and large-scale global climate change research. A mumber of moorings were deployed in the area by JAMSTEC since 1992, and the data revealed highly variable characteristics of the hydrological environment. A regional high-resolution coupled ice-ocean model of the Chukchi and Beaufort Seas was established to simulate the ice-ocean environment and unique seasonal landfast ice in the coastal Beaufort Sea. The model results reproduced the Beaufort gyre and the ACC. The depthaveraged annual mean ocean currents along the Beaufort Sea coast and shelf hreak compared well with data from four moored ADCPs, but the simulated velocity had smaller standard deviations, which indicate small-scale eddies were frequent in the region. The model resuits captured the sea,real variations of sea ice area as compared with remote sensing data, and the simulated sea ice velocity showed an ahnost stationary area along the Beaufort Sea coast that was similar to the observed landfast ice extent. It is the combined effects of the weak oceanic current near the coast, a prevailing wind with an onshore component, the opposite direction of the ocean current, and the blocking hy the coastline that make the Beaufort Sea coastal areas prone to the formation of landfast ice.

A coupled ice-ocean ecosystem model for 1-D and 3-D applications in the Bering and Chukchi Seas

Primary production in the Bering and Chukchi Seas is strongly influenced by the annual cycle of sea ice. Here pelagic and sea ice algal ecosystems coexist and interact with each other. Ecosystem modeling of sea ice associated phytoplankton blooms has been understudied compared to open water ecosystem model applications. This study introduces a general coupled ice-ocean ecosystem model with equations and parameters for 1-D and 3-D applications that is based on 1-D coupled ice-ocean ecosystem model development in the landfast ice in the Chukchi Sea and marginal ice zone of Bering Sea. The biological model includes both pelagic and sea ice algal habitats with 10 compartments： three phytoplankton （pelagic diatom, flagellates and ice algae： D, F, and Ai） , three zooplankton （copepods, large zooplankton, and microzooplankton ： ZS, ZL, ZP） , three nutrients （ nitrate ＋ nitrite, ammonium, silicon ： NO3 , NH4, Si） and detritus （Det）. The coupling of the biological models with physical ocean models is straightforward with just the addition of the advection and diffusion terms to the ecosystem model. The coupling with a multi-category sea ice model requires the same calculation of the sea ice ecosystem model in each ice thickness category and the redistribution between categories caused by both dynamic and thermodynamic forcing as in the physical model. Phytoplankton and ice algal self-shading effect is the sole feedback from the ecosystem model to the physical model.

Ocean stratification and sea-ice cover in Barents and Kara seas modulate sea-air methane flux:satellite data

The diverse range of mechanisms driving the Arctic amplification and global climate are not completely understood and,in particular,the role of the greenhouse gas methane(CH4)in the Arctic warming remains unclear.Strong sources of methane at the ocean seabed in the Barents Sea and other polar regions are well documented.Nevertheless,some of those publications suggest that negligible amounts of methane fluxed from the seabed enter the atmosphere,with roughly 90%of the methane consumed by bacteria.Most in situ observations are taken during summer,which is favorable for collecting data but also characterized by a stratified water column.We present perennial observations of three Thermal IR space-borne spectrometers in the Arctic between 2002 and 2020.According to estimates derived from the data synthesis ECCO(Estimating the Circulation and Climate of the Ocean),in the ice-free Barents Sea the stratification in winter weakens after the summer strong stability.The convection,storms,and turbulent diffusion mix the full-depth water column.CH4 excess over a control area in North Atlantic,measured by three sounders,and the oceanic Mixed Layer Depth(MLD)both maximize in winter.A significant seasonal increase of sea-air exchange in ice-free seas is assumed.The amplitude of the seasonal methane cycle for the Kara Sea significantly increased since the beginning of the century.This may be explained by a decline of ice concentration there.The annual CH4 emission from the Arctic seas is estimated as 2/3 of land emission.The Barents/Kara seas contribute between 1/3 and 1/2 into the Arctic seas annual emission.

Estimating sea ice albedo feedback in a regional climate modeling sensitivity experiment

Surface albedo feedback （SAF）, or sea ice albedo feedback over the Arctic Ocean, has an important effect on the Arctic climate, even though it is not the leading contributor to polar amplification. Previous model-based studies on SAF have primarily used global climate models to exploit their global coverage and favorable configurations. This study verified the capability of using regional climate models （RCMs） to investigate SAF by designing a sensitivity experinaent in terms of sea ice coverage. This study modeled two control cases of the years 1980 and 2012, as well as two sensitivity cases performed by switching the sea ice coverages in the control cases. The results proved the Weather Research and Forecast model capable of separating and quantifying the respective contributions of the atmosphere and the surface albedo to the surface radiation budget. Supported by the ALL/CLR model, the balanced surface shortwave radiation absorption was used to calculate SAF. The experiments overestimated SAF, largely because of the canceled cloud effect during model initialization. This study highlights a new possibility of designing experiments for studying climatic sensitivity and feedback using RCMs.

The effect of the feedback cycle between the soil organic carbon and the soil hydrologic and thermal dynamics

Biogeochemical feedback processes between soil organic carbon (SOC) in high-latitude organic soils and climate change is of great concern for projecting future climate. More accurate models of the SOC stock and its dynamics in organic soil are of increasing importance. As a first step toward creating a soil model that accurately represents SOC dynamics, we have created the Physical and Biogeochemical Soil Dynamics Model (PB-SDM) that couples a land surface model with a SOC dynamics model to simulate the feedback cycle of SOC accumulation and thermal hydrological dynamics of high-latitude soils. The model successfully simulated soil temperatures for observed data from a boreal forest near Fairbanks, and 2000 year simulations indicated that the effect of the feedback cycle of SOC accumulation on soil thickness would result in a significant differences in the amount of SOC.