GC23A-0972
Impact of Surface Air Temperature and Snow Cover Depth on the Upper Soil Temperature Variations in Russia
A study of the impact of climate changes during for the last four decades on soil temperatures at depths up to 3.2 meters has been conducted for the territory of Russia. For the 1965-2004 period, we compiled and analyzed data from all Russian meteorological stations with long-term soil temperature observations at depths 80, 160 and 320 cm. Traditionally, these stations also observe a complete set of standard meteorological variables (that include surface air temperature and extensive monitoring of snow cover characteristics). This allowed us to investigate the impact of surface air temperatures and snow depth variations on soil temperatures in the upper soil layer, to quantify it using statistical analyses of multi-dimensional 40-year-long time series at 164 locations throughout the country, and assess the representativeness of the obtained results. Three-dimensional spatial distributions of regression and correlation coefficients were mapped for warm and cold seasons separately as well as for the entire year, and thereafter analyzed. In the permafrost zone we found special features in these fields that distinctively separate the permafrost zone from the remaining territory. In this zone, soil temperatures are practically uncorrelated with surface air temperatures and variations of the snow depth controls soil temperature variations (with R2 up to 0.5) Quantitative estimates of the contribution of mid-annual air temperature and snow cover depth in the long-term changes of mid-annual soil temperatures across the Russia territory were received. We found that the prevailing influence on soil temperature variations in the European part was surface air temperatures and in the Asian part of Russia was snow cover depth. Furthermore, increase of the winter snow depth in the permafrost zone (by preserving the heat accumulated in the warm season) promotes annual soil temperature increase and therefore may foster the further permafrost degradation associated with ongoing regional warming.
GC23A-0973
Changes in Snow Cover Characteristics Over the Russian Territory in Recent Decades
The state of snow cover is one of the most important characteristics of the Northern Eurasia climate. The present work sheds light on the snow variations by using empirical and statistical analysis of time series of daily snow depth over Russia. For 400 Russian stations, time series of the daily snow depth and of the extent to which the near-station territory is covered by snow have been prepared in RIHMI-WDC for the period 1951-2006. Our analyses revealed the following regional features in the change of snow cover characteristics. Increases in winter precipitation and surface air temperature affected the variability of snow characteristics. In particular, tendencies towards the increase in the average snow depth over the Russian territory are prevailing, while only a few Russian regions show a decrease in winter snow depth. The largest variations in the average snow depth occur in the late winter - early spring period. In the recent three decades a substantial part of the Russian territory exhibits a shorter snow-cover period. The regionally-averaged snow cover characteristics were analyzed across the seven quasi-homogeneous climatic regions of Russia as well as for the entire nation. In the European part of Russia and in the Russian Far East, the increase in the average snow depth is controlled by winter and autumn precipitation growth. Time series of the number of days with different snow depths have been derived from daily snow depth observations. In the past decades, the number of days with the snow depth above 1 cm tends to decrease in the west of European Russia, in the Urals, Siberia and the Chukotka Peninsula (i.e., over most of Russia), while the number of days with significant snow depth (above 20 cm) tends to increase slightly. Taking into account that the Russian territory dominates the snow-covered areas of Eurasia, we conclude that across most of Northern Eurasia the snowy season became shorter but more âintenseâ.
GC23A-0974
Prolonged Dry Episodes Over Northern Eurasia and North America: New Tendencies Emerging During the Last 40 Years
A disproportionate increase in precipitation coming from intense rain events, in the situation of general warming (thus, an extension of the vegetation period with intensive transpiration) and an insignificant change in total precipitation could lead to an increase in the frequency of potentially serious type of extreme events: prolonged periods without precipitation (even when the mean seasonal rainfall totals increase). We investigated whether this development is already occurring during the past several decades over North America and Northern Eurasia, for the same period when changes in frequency of intense precipitation events are being observed. Lengthy strings of "dry" days without sizeable (>1.0mm) precipitation were assessed only during the warm season (defined as a period when mean daily temperature is above the 5°C threshold) when water is intensively used for transpiration and prolonged periods without sizable rainfall represent a hazard for terrestrial ecosystem's health and agriculture. For these strings we estimate the distribution of their frequency and duration and study their trends (if any) for dry regions within North America and the former USSR. During the past four decades, the mean duration of prolonged dry episodes (20-days or longer in southeastern Canada, 1-month or longer in the southern Siberia and Russian Far East, eastern United States, and along the Gulf Coast of Mexico and 2-months or longer in the Southwestern United States and Northern Mexico) has significantly increased. Over the Asian part of Russia we also observed an increase in duration of "fire" weather conditions. Research of the latest tendencies of prolonged dry episodes across the newly independent Central Asia States is hampered by data access problems.
GC23A-0975
River Runoff within Large River Basins of Russia during Epochs of Global Warming in Past and Future
Results of an estimation of deviations of river runoff from their modern values within the largest rivers of Russian plain (Volga, Don, Dnieper) and Siberia (Lena) observed during the period of the Late Atlantic Optimum of the Holocene (5-6 thousand years ago) and probable at global climate warming in the XXI century caused by growth of atmospheric content of greenhouse gases of an anthropogenic origin are presented. A scenarios of climatic changes are based on results of experiments on global models of the general circulation of atmosphere and ocean, included in the international programs of comparison of results of paleoclimate modeling (Paleoclimate Modeling Intercomparison Project PIMP) and future climate (Intergovernmental Group of Experts on Climate Change IPCC) have been used. For estimation of hydrological changes macroscale model of monthly water balance developed in Institute of Geography of the Russian Academy of Science (Georgiadi, Milyukova, 2000; 2002; 2006) especially for study of hydrological consequences of global climatic changes in large river basins is used. Research was executed at support of Russian Fund on Basic Research 07-05-12085-ofi and 05-05-64499a.
GC23A-0976
Dynamics of soil moisture and actual evaporation over the East-European Plain during the second part of the 20th century
During the second part of the 20th century more important elements of the soil water balance exhibited significant changes over the Great Russian Plain. Soil moisture increasing was observed practically in all natural zones. In the past 10-15 years soil moisture values exceeded the level of the field capacity at some stations. Moreover, maximal soil moisture increasing was fixed during the summer-autumn period. Winter water content increased as well, especially in the forest zone. Only in the dry steppe zone soil moisture growth was observed in the winter-spring season. It should be also noted that the most intensive changes in the soil water content were fixed within the transition zones and especially in the steppe zone. These changes in the soil water regime inevitably affect the regime of evaporation from the soil surface. Actual evaporation increased in all natural zones except the dry steppe zone. In this zone actual evaporation decrease was fixed. Similar soil moisture, the most intensive actual evaporation changes were observed within the transition zones and especially in the dry steppe zone. Despite evaporation increasing, soil overmoistening affects the agrophysical soil properties. Processes of chernozems' leaching, bogging and desertification of soil settled into critical phase. During the past 45-50 years soil's salinification and gleying are well defined. Soil degradation is sometimes of irreversible character.
GC23A-0977
Land Surface Water and Energy Budgets Assessment Across NEESPI
Northern Eurasia represents a large region of the Earth's land surface, and observational evidence has shown a stronger climate change signal there than other regions of the globe. Despite its importance and climate sensitivity, the land surface's water and energy budgets in this region are poorly known. While land surface states are poorly described by observations due to the sparse monitoring network, the understanding of Northern Eurasia's land surface climate can be enhanced by offline land surface modeling. We use a retrospective, meteorological forcing dataset that extends back to 1930 to drive the Variable Infiltration Capacity (VIC) model, a macro-scale hydrologic model that has been shown to perform well in northern regions. Model validation with in situ observations provides an understanding of the mean and variability of hydrologic states across the NEESPI region. Given the length of the dataset, we examine the model's ability to capture the long-term discharge trends reported in the literature and examine if trends are also present in other hydrologic states. The combined study of trends in discharge and hydrological states may then further our understanding of what is causing the observed discharge trends in the large Arctic basins.
GC23A-0978
Analyses of Ground-based and Satellite Observations for Developing a Dust Climatology in Central and East Asia
In support of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), we have been working on the development of the Asian Dust Databank by integrating the diverse satellite and ground-based data on mineral dust, land-cover and land-use change (LCLUC), and climatic variables in Central and East Asia. The ultimate goal of this effort is to gain a better understanding of interactions between LCLUC, atmospheric dust, and their linkages to climate changes which have been observed in Northern Eurasia over the past 50 years. This study will present an in-depth analysis of 50-year ground-based observations of visibility and WMO present weather from selected meteorological stations in Central and East Asia. We examine the duration, intensity, frequency and area coverage of dust events on a case-by-case basis, addressing the regional importance of natural and human-disturbed dust sources. We also present a new methodology for developing a reliable dust climatology by merging visibility and WMO dust present weather records. Visibility data can potentially provide quantitative information on dust events. However, the visibility reduction is caused not only by dust but also by other factors (e.g., haze, smoke, fog, mist, rain, snow). The advantage of WMO dust present weather is that it serves as a direct indicator of atmospheric dust, although in the qualitative way. Our analysis reveals various inconsistencies between visibility and dust present weather records that question the accuracy of dust frequency reported by previous studies based on visibility records only. In addition, we will present examples of integrated analyses of ground-based data and satellite observations (e.g., TOMS AI, MODIS aerosol products and true color images) with the goal of developing a new observation-based climatology of dust events.
GC23A-0979
The Analysis Of Climatic Tendencies In Eurasia
Numerous researches indicate to the probability of the future climate warming, caused by the antropogeneously produced increase of the greenhouse gases. But there is a certain vagueness as to the regional specifics and, particularly, concerning the frequency of the irregular regimes' occurrence and degree of its extremality (e.g. the winter of 2006-07 in Europe and Russia). There is no an adequate physical explanation to such variation of the global and, particularly, regional temperature's secular course. At least, by modeling the Arctic climate, the acknowledged models do not reproduce the trice-changed sign of the temperature tendencies (for instance, the Hamburg model, see Wang et al., 2007). As to the other main thermodynamic parameters of the climate system there is no global archival data of proper quality and sufficient range. Though, the main distrust to results obtained by the forecasting is related to the fact that the modern climate models present only linear or logarithmical dependence between the air temperature changes and change of the greenhouse gases concentration in the atmosphere. We have developed the first version for description of the climate system dynamical and radiation reactions to the periodical irregularity of the Earth rotation (rotational mechanism). New approach based on composition of the "greenhouse" and "rotational" effects allows to make an explanation for not only growth of temperature caused by emission of the greenhouse gases but also for variations of the regional and global climate (in particular, cooling observed during 1940-1970). Using composition of the "greenhouse" and "rotational" effects there are given estimations of probable changes of climate in XXI century, including the nearest 5-10 - years.
GC23A-0980
Hydrological changes across Northern Eurasia: contemporary status and future projections
Evidence pointing to significant change in the hydrological regime over the North Eurasian region were analyzed. Understanding alterations due to both global climate change and local anthropogenic influences are important to explore potential signals of global climate change and to assess their feedbacks to hydrological systems and the global climate, and to their impacts upon humans. We analyzed changes in annual, monthly and daily extreme discharge for river basins with minimal human impact along with total river inflow to the Arctic Ocean from the largest watersheds and sea basins. The effect of human impacts was estimated through water use data collected at the State Hydrological Institute (SHI), Russia. The role of reservoir regulation in discharge variability was analyzed with a newly developed Hydrograph Transformation Model (HTM). The model is based on the unit hydrograph approach and transforms daily hydrographs sequentially from upstream to downstream to reduce the effects of reservoir regulation. To explore potential future patterns of change in the hydrology of Northern Eurasia we used projections of climate changes simulated by two coupled atmosphere-ocean general circulation models (AOGCMs) to drive our hydrological models. Future simulations from the UNH Water Balance and Water Transport Models (WBM/WTM) which incorporate irrigation and reservoir effects were analyzed along with results from the SHI and UNH permafrost water balance models with improved frozen ground schemes. All models demonstrated a general tendency toward increases in river runoff although the changes across Northern Eurasia were not spatially uniform.
GC23A-0981
Coupling Satellite and Ground-Based Snow Data With Snow Cover Model for Estimating the Area-Averaged Snow Water Equivalent Over Large River Basins
Improvement of long-range forecasts of snowmelt flood volume is one of key hydrological problems in Northern Russia. Accurate quantitative characterization of snow cover properties required in snowmelt runoff models is challenging in this region since the existing network of hydrometeorological stations is sparse. Application of satellite data for snow monitoring is hampered by large areas of coniferous forests masking the snow pack and by persistent cloudiness in the fall and winter season. In order to enhance quantitative characterization of snowpack properties we have developed a new technique where satellite data are coupled with a snow cover model. The physically-based snowpack model uses interpolated data from ground-based meteorological stations and incorporates a number of products derived from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites. The input satellite data include albedo, land surface temperature, leaf area index and the canopy coverage. The outputs of the model are the snow depth, snow density, ice and liquid water content of snow and the snow grain size. The model was tested over a region with a size of ~240 000 km2 (56°N to 60°N, and 48°E to 54°E) located within the NEESPI area. This region includes the Vyatka River basin with the catchment area of about 120 000 km2. Snow pack simulations were conducted for 1 x 1 km grid cells for the spring season of 2002 and 2003. Spatial correlation between the modeled snow extent and the MODIS-derived snow cover distribution over the study area ranged from 0.9-1.0 in the beginning and in the end of the melt season to 0.5-0.6 during the period of intensive snow melt. The analysis of MODIS snow retrievals over the study area demonstrated their good agreement with surface observations. Satellite information on snow cover was not used in the current version of the model, however high accuracy of satellite snow retrievals makes their incorporation in the next version of the model very attractive. In the presentation we will discuss ways to incorporate satellite snow retrievals in the snowpack model and advantages of the use of improved estimates of SWE in runoff hydrograph calculations.
GC23A-0982
Lake and wetland variability in regions of seasonal and permanent soil frost
Northern Eurasian plays an important role in global climate partially due to the potential for positive carbon-cycle feedbacks associated with the interaction between frozen soil, temperature, and moisture. In particular, this region is characterized by numerous wetlands and lakes in areas of both seasonal and permanent soil frost. Soil ice content has a large influence on the temporal and spatial variation of soil moisture in these wetlands, which have the potential to produce large amounts of methane under saturated conditions. As soil temperatures increase, ice melt may result in more drainage and less soil saturation in areas of seasonal frost and discontinuous permafrost. In permafrost areas, the ice layer may provide a barrier to restrict drainage and subsequently increase surface inundation. Simulation of such changes in wetland extent is limited by understanding of the spatial heterogeneity of surface saturation. The Variable Infiltration Capacity (VIC) macroscale hydrologic model was modified to represent sub-grid variability in wetland distribution by integrating a modified topographic wetness index approach. In addition, simulation of changes in the extent of lake and wetland systems is improved by allowing the exchange of moisture content between lakes and adjacent wetlands. The modified VIC model is evaluated with respect to observations of water table depth and runoff obtained over a period of three decades from the Valdai research station located south of St. Petersburg, Russia. The variability in simulated wetland extent is then evaluated between 1930 and 2000 in the Upper Volga and Zapadnaya Dvina watersheds (seasonal soil frost) and the Yeloguy and Syum watersheds (discontinuous permafrost). The average wetland area determined from simulated hydrology is compared to landcover classifications derived from L-band satellite synthetic aperture radar imagery. This work was carried out at Purdue University, at the University of Washington, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.
GC23A-0983
The Whole Tien Shan Glacier Area Changes Between 1973 and 2003 Estimated From Corona and ASTER Satellite Imagery
Changes in glacier covered area of the Tien Shan Mountains (western, central and eastern) was estimated between 1973-2003 using Corona KH-9 (9 m) and ASTER (15 m) imagery. Large spatial coverage of a single Corona KH-9 photograph (almost eight ASTER images) and accurate geometric qualities of the KH-9 frame- mapping camera provide a unique opportunity for reconstruction of the glacier covered area during the last 30 years with comparable spatial resolution. The images were orthorectified using SRTM DEM with void areas filled with ASTER DEM and ground control points collected from 1:25,000 and 1:50,000 topographic maps. The Corona and ASTER orthorectification RMS residuals were in the same order of 7-15 m. Glacier boundaries were derived using segmentation of ASTER 3N/4 band ratio and manual digitizing with error-checking in stereo viewing. Since the middle of 1970s, Tien Shan was experiencing abrupt increase in air temperature, that accelerated glacier recession particularly in the mountain ranges lower than 5,000 m a.s.l. From 1973 to 2003 all Tien Shan glaciers have significant recession trend. The most notable recession has been observed in the western and southern Tien Shan: from 20% to 17.1% of the total glacier area. The eastern and northern Tien Shan glaciers have lost 12.6% - 11% of their total area while the largest and highest (up to 7,000 m) central Tien Shan remained nearly the same glacierized area: only 1% of the total glacier area reduction. The large dendritic glaciers in the central Tien Shan are heavily covered by moraine debris, which protect glaciers from intensive ablation. The Tien Shan mountain ranges longitudinally spans more than 2,000 km and glaciers exist in different geo-morphological and climatic conditions determining the difference in glacier recession. However, the Tien Shan glacier surface has decreased in all regions and has to be measured by GPS and satellite altimetry to estimate real changes in glacier ice water resources.
GC23A-0984
Changes in Seasonal Snow Cover in Tien Shan During the MODIS Period of Record
Snow melt in the Tien Shan region accounts for a large portion of the seasonal water supply for millions of inhabitants of central Asia. Studies based on in situ records suggest that maximum snow depth and snow duration in the Tien Shan has decreased, as has annual river flow at lower elevations, over the past 50 years [Aizen et al., 1997]. While the need to monitor trends in winter snow accumulation increase as this resource is threatened by climate change, the number of in situ measurements of snow depth has declined, forcing reliance on remote sensing methods. This talk will describe trends in seasonal snow cover for 8 individual hydrological basins in Central Asia, as well as for the Tien Shan as a whole, using operational products derived from the MODIS Terra instrument. The ultimate goal is to provide input data for snow runoff models. Data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) data, available since early 2000, have proven useful for a large variety of land, ocean and atmospheric applications. The MODIS standard snow-cover products, archived at the National Snow and Ice Data Center, are available in swath-based, daily, 8-day and monthly aggregations at a variety of spatial resolutions and grids. Similar products are also available from the MODIS Aqua instrument launched in 2002. For this study daily and 8-day products at 500m resolution were used. Seven winter seasons were analyzed. For a given season the date of maximum snow coverage varies widely between basins but for the Tien Shan as a whole the period of peak coverage and the rate at which the total snow covered area declines is rather consistent for the 7 winters. Some basins have a large degree of the interannual variability in maximum snow cover while for others this variability is small. Interannual variability in total snow cover for the Tien Shan as a whole is approximately 10 % RMS throughout the peak and decay periods, with 2003 having the most snow cover and 2000 having the least.
GC23A-0985
Modeling the Effect of Organic Layer and Water Content on Permafrost Dynamics in the Northern Hemisphere
Climate projections for the 21st century indicate that there could be a pronounced warming and degradation of permafrost with a corresponding shift in landscape processes. Therefore, we expect a further degradation of permafrost in the Arctic and sub-Arctic regions. In order to simulate the distribution and temperatures of permafrost and active layer thickness for the entire Northern Hemisphere permafrost domain, the equilibrium model GIPL1.1 has been developed. GIPL1.1 is a spatially distributed model of permafrost based on an approximate analytical solution of soil freezing and thawing, which includes an estimation of thermal offset due to the difference of frozen and thawed soil thermal properties. GIPL1.1 model also accounts effectively for the effects of snow cover, vegetation, soil moisture, and soil thermal properties. Comparison between calculated distribution of permafrost temperatures using GIPL1.1 model and the International Permafrost Association (IPA) permafrost map shows a very good agreement. For this study we used three different GIPL1.1 runs, each driven by the same boundary conditions but with different soil properties. The control run takes into account the organic matter layer and the thawing/freezing of soil water. For the second simulation, the presence of water was also taken into account, but the organic soil properties were replaced by the mineral soil properties throughout the entire calculated domain. The third simulation was performed only for the mineral soil that contains no water. All three simulations were implemented for two time intervals. For the present-day climatic conditions, the CRU2 data set with 0.5° by 0.5° latitude/longitude resolution was used. The future climate scenario was derived from the MIT-2D climate model output for the 21st century. Results of permafrost modeling show significant differences between the all three runs in both spatial distribution of permafrost and in permafrost temperatures. These results show that incorrect treatment of soil properties (the lack of organic matter) has much greater influence on ground temperatures and permafrost distribution than the incorrectly prescribed soil water content. The difference in mean value of the mean annual ground temperature (MAGT) for the total 40,423 grid points for the entire Northern Hemisphere for the present time reached 2.6°C that corresponds to the permafrost area reduction by 6.8 million km2. In case of incorrectly prescribed soil water content, much greater discrepancies were found in the active layer thickness evaluation. These discrepancies grew dramatically when MAGT values were approaching 0°C.
GC23A-0986
Remote Sensing and GIS Based Quantification of Thermokarst in North Siberian Yedoma Deposits and Implications for Holocene Landscape and Carbon Dynamics
Ice Complex deposits, also known as yedoma, are widely distributed in the North Siberian coastal lowlands. These Late Pleistocene terrestrial accumulations of up to several tens of meters in thickness are characterised by fine to medium grained clastic sediments, a very high ground ice content up to 90 vol-%, and mean total organic carbon (TOC) contents of 2-4%. Ground ice content includes large ice wedges and segregated ground ice in the form of small ice lenses and ice bands. Degradation of the Ice Complex in the form of thermokarst and thermo-erosion during the course of the Holocene produced massive landscape changes degenerating the existing accumulation plains to a complex system of thermokarst basins, lakes, and thermo-erosive valleys. Thermokarst triggered several feedback mechanisms that involve hydrology, vegetation and energy and matter fluxes. Thermokarst was a major agent in the partial transformation of the stored TOC into greenhouse gases. To evaluate the past and possible future impacts of thermokarst and related environmental feedbacks, the assessment of the current distribution and characteristics of Ice Complex deposits and thermokarst features is an important task. Field data, remote sensing, and terrain modelling within a geographical information system (GIS) are used to characterize Ice Complex deposits and thermokarst for a variety of sites in the Laptev Sea region, North Siberia. Field data consists of Ice Complex distribution, thickness, ice content, and TOC. Remote sensing was applied for the mapping of Ice Complex extent and distribution of thermokarst surface features in this area. Terrain modelling was used to quantify the volume of Ice Complex deposits based on digital elevation models, stratigraphical information, and satellite image mapping. Subsequently, terrain modelling was also applied to characterize thermokarst in this area. An assessment of the original, eroded, and remaining volume for the Ice Complex in the study area is provided.
GC23A-0987
Study of permafrost dynamics within the Northern Eurasia Region by a coupling between permafrost and water balance models
Thawing and freezing of Arctic soils is affected by many factors, with air temperature, vegetation, snow accumulation, and soil moisture among the most significant. Here we describe the coupling of a Permafrost Model and the pan-Arctic Water Balance Model (PWBM), developed at the University of Alaska Fairbanks and the University of New Hampshire, respectively. Additionally, we present resultant simulated soil temperature and moisture dynamics, depth of seasonal freezing and thawing, river run-off and water storage across the Northern Eurasia Region. The coupled models simulate the snow/ground temperature with a 5-layer snow and 23-layer soil model. In the soil model the layers thicken with depth and span a 60 meter thick column. The PWBM has two soil storage zones; a root zone that gains water from infiltration and loses water via evapotranspiration and horizontal and vertical drainage, and a deep zone that gains water via root zone vertical drainage and loses water via horizontal drainage. Forcing data (i.e. air temperature, precipitation) are taken from ERA40. We validate our model simulations by comparing soil moisture and thermal profiles with observational data collected within the Northern Eurasia Region. The coupling captures thresholds and non-linear feedback processes induced by changes in hydrology and sub- surface temperature dynamics, and hence helps us to study the spatial and temporal variability of permafrost dynamics as well as potential future alterations to permafrost and the terrestrial arctic water cycle. Through explicit coupling of the Permafrost Model with the PWBM we are able to simulate the temporal and spatial variability in soil water/ice content, active layer thickness, and associated large-scale hydrology that are driven by contemporary and future climate variability and change.
GC23A-0988
Feedback of the changing Russian permafrost to the global climate system through methane emission.
Large amounts of soil carbon deposited in permafrost may be released due to deeper seasonal thawing under the projected for the future climatic conditions. Increase in the volume of the available organic material together with the higher ground temperatures may lead to enhanced emission of greenhouse gasses. Particular concerns are associated with methane, which has much stronger greenhouse effect than the equal amount of CO2. Production of methane is favored in the wetlands, which occupy up to 0.7 mln km2 in Russian permafrost regions and have accumulated about 50 Gt C. We used the permafrost model and several climatic scenarios to construct the projections of the soil temperature and depth of seasonal thawing. Results for the mid-21st century climate indicated up to 50 % increase in the depth of seasonal thawing in the northernmost locations along the Arctic coast and in the East Siberia, where wetlands are sparse, and relatively small increase by 10-15 % in the West Siberia where wetlands occupy 50-80 % of land. These results together with the projected for the future soil temperatures have been used in the carbon model to estimate the changes in the methane fluxes. According to our results, by mid-21st century the annual net flux of methane from Russian permafrost regions may increase by 6-8 Mt, depending on climatic scenario. If other sinks and sources of methane remain unchanged, this may increase the overall content of methane in the atmosphere by approximately 100 Mt, or 0.04 ppm and lead to approximately 0.01 C global temperature rise.
GC23A-0989
A 100 yr Ice Core Record of Anthropogenic Activity, Volcanic Eruptions, and Biomass Burning From the Siberian Altai
The 50m upper part from 170m of total deep ice core was retrieved from the Belukha snow-ice plateau (49°48âN, 86°32âE, 4110m.a.s.l.) in the summer of 2003 representing the time series since the beginning of the 20th Century. Data on high-resolution physical stratigraphy and density, as well as geochemical data including major ions, stable (δ18O) and radiogenic (δ3H) isotopes were developed for ice-core dating, climatic and environmental analysis. A clear tritium isotope ratio peak associated with the global maximum nuclear testing of the early 1960âs, and a soluble major ion peak coincident with the eruption of Mt. Katmai in 1912 reveals a linear depth-age scale for the upper 50m and indicates an average accumulation rate of 376m.w.e. Major soluble ions sulfate and nitrate showed the greatest increase subsequent to the 1950âs, and provides evidence for direct effects associated with increased atmospheric aerosol loading from industrialized activity in central Asia. Extremely low sulfate and nitrate concentrations (<3.0μEq/L average) before the 1950âs approximate atmospheric background levels. Sulfate concentrations decrease rapidly during the time period associated with the early 1990âs, providing an example of the effects of short-run deindustrialization subsequent to the dissolution of the Soviet Union. Ammonium concentrations reveal an association with documented periods of extended boreal forest fires during the 1960âs and 1970âs. Elevated calcium concentrations during the 1950âs and 1960âs correspond to the reported period of maximum dust activity in China since 1950.
GC23A-0990
A modelling study of the effects of species composition changes on radiation, H2O and CO2 fluxes in a boreal forest ecosystem
Climatic changes may have significant impacts on forest ecosystems. They can result in changes of tree species composition, forest productivity and soil carbon sequestration. A global warming which is expected to be particularly large at higher latitudes will affect boreal forests probably more strongly than forests in other latitudinal zones (e.g. IPCC 2007). It can be expected that the greatest changes may occur at the southern boundary of the boreal forest zone, where the boreal coniferous forest is likely to give way to broadleaf species. How such vegetation changes will affect water and CO2 budgets of land surface at this area is not known yet. Within the framework of this study effects of species composition (coniferous and broadleaf species) on evapotranspiration and Net Ecosystem Exchange (NEE) of CO2 in a boreal forest ecosystem were determined using an one- and three-dimensional SVAT (Soil Vegetation Atmosphere Transfer) models (Mixfor-SVAT, Mixfor-3D). Both models were developed to describe the energy, water and CO2 exchange within and above vertically structured mixed or mono-specific forest stands. They allow simulating realistically the H2O and CO2 exchange between forest ecosystems and the atmosphere taking into account transpiration, water uptake, photosynthesis and respiration of different tree species in the forest overstorey and understorey, as well as evaporation and respiration of the soil and dead biomass respirations. Modelling experiments were carried out for five different scenarios of changes of tree species composition. Each scenario assumes different admixture of spruce and broadleaf species in a forest stand. As input meteorological parameters in our modelling experiments the measured meteorological air temperature, humidity, wind speed, precipitation rate and global solar radiation data for one year test period were used. Results of modelling experiments showed a relatively high dependence of forest radiation regime, evapotranspiration, photosynthesis and respiration on species composition. This effect is strongly depended on environmental and soil moisture conditions and it has a clear seasonal trend.
GC23A-0991
Carbon Dioxide Fluxes in European Russia
Measurements of carbon balance of boreal ecosystems in the southern taiga of European Russia have been conducted using eddy covariance technique starting from 1998 to the present. The method allows to continuously collect net ecosystem exchange (NEE) fluxes of water and heat between forest and atmosphere with high time resolution. Simultaneous measurements of atmospheric meteorological parameters are carried out. The studies have been conducted in the Tver Region, Russia (Central Forest Biosphere Nature Reserve, 56N, 33E) using a 29 m high tower in low-productive wet spruce forest (P. Sphagnum forest, WSF), a 44 m high tower in high- productive complex spruce forest (CSF) and under the surface of ombrotrophic bog. Eddy flux measurements during limited time intervals are supplemented by measurements of soil, leaves and trunks respiration. Observations of decomposition speed of organic material and the rating NPP are conducted as well. In general, the measurements period has captured a wide range of changes of climatic conditions. Years with extreme dry and damp vegetative seasons and years with close to average climatic conditions for this region fall into the period of observations. The results of our measurements show that unmanaged uneven-aged spruce forests can be both source and sink of carbon to the atmosphere depending on the type of forest and weather conditions. Soil respiration as a result of decomposition of the abundant dead surface- and underground biomass determines the sign and absolute mean of the carbon balance. The overall annual balance of carbon of the studied forest ecosystems differs from zero. The cumulative total of the NEE fluxes for the period of April to October depends first of all on spring temperature and precipitation with temperature being within the range of 5-10C and on the duration of this period. For the period of active vegetation, when air temperature is higher than 10C - the NEE flux depends on humidity. We found significant seasonal and interannual variability of carbon dioxide fluxes for the ombrotrophic bog. The sign and the mean of carbon dioxide fluxes between the surface of the bog and the atmosphere depend on humidity conditions during the green season. When the water balance is negative the ombotrophic bog becomes a source of carbon for the atmosphere.
GC23A-0992
Wildfire, Ecosystems and Climate in Siberia: Developing Weather and Climate Data Sets for Use in Fire Weather and Bioclimatic Models
A primary driving force of land cover change in boreal regions is fire, and extreme fire seasons are influenced by local weather and ultimately climate. It is predicted that fire frequency, area burned, fire severity, fire season length, and severe fire seasons will increase under current climate change scenarios. Already, there is evidence of an increased number of extreme fire seasons in Siberia that correlate with current warming. Our overall goal is to explore the degree to which current and future climate variability has and will affect wildfire-induced land cover change and to highlight the significance of the interaction between the biosphere and the climate system. Developing reliable weather and climate data provides the backbone of this research, which is to examine the relationships between weather, extreme fire events, and fire-induced land cover change in the changing climate of Siberia. The primary focus in this presentation is the description of the assembled weather and climate data sets and the verification efforts, followed by an example where the data set is used in a fire prediction application. Ground- based weather observations from the National Climatic Data Center (NCDC) for the years 1983-2006, have been used to verify various modeled meteorological parameters from the NASA Goddard Earth Observing System version 4 (GEOS-4) data. Specifically, we have extracted "Summary of the Day" and "Integrated Surface Hourly (ISH)" weather data from the NCDC. The ISH data has been processed to obtain hourly observation times for all stations in Siberia, including Mongolia and parts of northern China. A subset of these stations have been selected for validation purposes if they meet a criteria of having at least 75% of the possible reporting observations per day and 75% of the possible days in each month. GEOS-4 data interpolated to a 1x1 degree grid have compared well with the NCDC station data, covering the burning season from April through September and for the entire 1983-2006 period. In cases where large differences exist between the NCDC station and the GEOS-4 grid elevations, lapse rate corrections have been applied to the temperature parameters. With the declining number of Siberian surface observation stations through the 1983-2006 period, using GEOS-4 data ensures data coverage over the entire Siberian region and through the entire data set period. One advantage of the GEOS-4 data is that it is consistent and spatially explicit, which makes it easily portable to multiple data applications or models. One such application being used in this study is the Canadian Forest Fire Weather Index (FWI) System developed by the Canadian Forestry Service. Using local noon values of air temperature, relative humidity, wind speed, and daily rainfall as input, the FWI assesses the conditions of forest fire burning potential for the day. Typically, local weather observation stations supply these meteorological parameters. In Siberia, the density of stations is limited; hence results may not be representative of the spatial reality. GEOS-4 data, on the other hand, provides complete temporal and spatial coverage. Using the GEOS-4 meteorological data as input into the FWI, the generated indices compare well with large and small fires in the 1983 to 2006 timeframe.
GC23A-0993
Changes in Land Use Intensity Within the Don and Dnieper River Basins Following the Collapse of the Soviet Union as Revealed by Spatio-temporal Trend Analysis
We analyzed changes in trends of land surface phenology (LSP) within two major river basins in Western Eurasia. The basins of Don and Dnieper Rivers extend over 862,000 ha and include 17% of the impounded water surface area in the former Soviet Union. Major changes in agricultural practices occurring after 1991 led to some time drastic reductions in the cultivated area receiving fertilizers and the amount of water consumed for irrigation in addition to other macro-indicators of agricultural sector land use intensity. Image time series analysis can localize the extent, direction, and intensity of changes during the 1990s. Using vegetation index data from the AVHRR PAL and GIMMS datasets from 1982-1988 (Soviet period) and 1995-2000 (post-Soviet period) coupled with contemporary land cover maps from MODIS, we identified the spatial extent of temporal trends and assess their significance using seasonal Mann-Kendall tests adjusted for first-order autocorrelation. Roughly 90% of croplands and forested land in Dnieper Basin exhibited no significant trends during the Soviet period. The Don Basin had more significant positive trends during the Soviet period than the Dnieper Basin. There was a substantial disagreement between datasets on the extent of significant positive trends in Don croplands (35% for GIMMS vs. 8% for PAL) and in Don forests during Soviet period (38% for GIMMS vs. 27% for PAL). Although very little area in either basins showed significant negative trends during the Soviet period, substantial areas fell under significant negative trends during the post-Soviet period. We also found major disagreement on extent of significant negative trends in Don forests during post-Soviet period (6% for GIMMS vs. 24% for PAL). Even though, there are some significant disagreements between the datasets, there is no evidence of a consistent bias in the change analysis. Changes in irrigation water use may account for some of the changes in trend direction.
GC23A-0994
Impact of Wildland Fire and Climate Change on the Amur Tiger and its Habitat
The Sikhote-Alin ecoregion of the Russian Far East (RFE) is an area of high biological importance designated by the UNESCO as a World Heritage Site. It presents a combination of boreal and temperate forest rich in rare endemic species including the critically endangered Amur tiger. The Amur tiger has the lowest population densities and reproductive potential of all tiger subspecies and thus requires extensive hunting areas. The availability of large hunting tracts for tigers is limited by economic activity and wildland fire. Increases in frequency of fire occurrence and amounts of burned area over the last 30 years resulted in extensive and irreversible modifications of the Amur tiger habitat. Changes in the natural fire cycle in the Amur tiger habitat require adopting a proactive approach to resource protection from wildland fire impacts. The fuzzy logic driven Fire Threat Model (FTM) has been developed to enable the resource managers to monitor tiger habitat quality, availability, and connectivity under changing climate. The model operates on publicly available remotely sensed data products and auxiliary information. It is parameterized to account for the regional drivers of fire occurrence and is focused on the specific habitat requirements of the Amur tiger. The analysis of fire threat to the Amur tiger under the present climate shows that fire occurrence has an immediate negative impact on the tiger habitat due to habitat fragmentation at the home-range scale, a significant decrease in food availability for the main prey species, and a subsequent drop in prey densities. However, post-fire emergence of a superior food base for browsers in combination with a sufficient protection offered by shrubland vegetation create a potential for an improvement of tiger habitat quality long-term. The potential is stronger in the northern portion of the tiger distribution area where dark coniferous and larch forests are replaced by shrublands and broadleaved deciduous forests, habitat types supporting higher prey densities. The projected increase in temperatures with a minimal increase in precipitation is shown by the ECHAM5 climate change scenarios over the RFE during the 21st century. The FTM runs during 2046-2050 and 2096-2100 time periods show an increase in fire threat to the Amur tiger. More frequent fire occurrence amplifies the negative short term impacts, minimizes the positive long-term impacts, and impedes forest regeneration leading to degradation of the tiger habitat under the current land management approach.
GC23A-0995
Potential Climate-Induced Vegetation Change in Siberia During the 21st Century
Climate change regional studies in Siberia have already registered climate warming by the end of the 20th century. Our goal is to model hot spots of possible vegetation change across Siberia caused by climatic anomalies for every 30-year period starting in 1960. January and July temperature and annual precipitation anomalies for 1960-1990 are calculated from the observed data across central Siberia. Anomalies for 2020, 2050, and 2080 are derived from two A1 and B2 SRES climate change scenarios from the Hadley Center (HADCM3), which differ from each other by their effects on Siberian vegetation changes. Our Siberian bioclimatic model operates through three climatic indices: degree- days above 5oC and below 0oC; annual moisture index; and active layer depth (ALD) related to permafrost. Coupled with climatic indices and ALD for 1960, 1990, 2020, 2050 and 2080, the bioclimatic model predicts vegetation changes for every 30-year period. This analyses demonstrate the far-reaching effects of a changing climate on vegetation cover during the 21st century. Because of a dryer climate, forest-steppe and steppe, rather than forests, are predicted to dominate the Siberian landscapes. Within forests, light-needled larch taiga is predicted to remain dominant across Siberia because permafrost is not predicted to thaw deep enough to support dark-needled taiga. Additionally, it is predicted that increases in fire weather danger and large forest phytomass losses would favor large fire events in southern Siberia, which would accelerate landscapes towards equilibrium with the climate.
GC23A-0996
Regional Differences in Carbon Storage Based on Distribution of Forest Age across Russia Using the FAREAST Gap Model and Detailed Forest Inventory Data
The FAREAST model, an individual-based forest-dynamics model, was developed to simulate forests of Changbai Mountain in northern China. It was then applied to forests at selected sites in Siberia and the Russian Far East. More recently, the model was used to generate results for expected biomass and species composition of mature forest landscapes for 223 sites across all of Russia. After these results were published, we became aware of actual forest survey data (developed by one of the authors, Krankina) arranged in 10-year intervals based on the age of the forest. Age in this case refers the age of the dominant tree cohort in a stand. These data were in percent coverage of total forest area surveyed for 36 forest sites aggregated in three regions denoted the northwest, south, and far eastern regions of Russia. This presented the opportunity to predict an expected biomass for the three regions corrected for age structure. The original simulation data was sorted to match the field data for regional forest age-cohort structure of the three regions. Thirty-four simulation sites from the original paper were distributed in the three regions used in the field study. This simulation data was re-compiled as biomass (tCha-1) for simulation plots summed at each 10 year interval from year zero to mature forests (250 years) and multiplied times the relative percent coverage in each age category. Using the expected biomass for the three regions derived from the inventory data, we obtain a picture of the current carbon storage across Russia. The potential change in carbon storage for these regions was found by calculating the difference between the expected biomass of a mature forest (250 years), the current forest state (derived from inventory data), and a managed forest condition characterized by an even distribution of age cohorts for each 10-year interval. The simulation biomass data was validated using novel cohort data arranged according to species biomass (tCha-1) from the inventory data for 43 forests across Russia (developed by Krankina) and 46 simulation sites sorted to match the field data. Transition of the regions from the current forest state to 100% mature forest (250 years) resulted in an accumulation of 9.075 tCha-1 in the east region of Russia, a loss of 0.206 tCha-1 in the southern region, and an accumulation of 36.266 tCha-1 in the northwest region. Alternately, a transition of the forest from the current state to an even distribution of age cohorts resulted in an accumulation of only 0.223 tCha-1 in the east region of Russia, 2.744 tCha-1 in the southern region, and a loss of 6.903 tCha-1 in the northwest region.
GC23A-0997
Continental Mapping of Northern Eurasia Forest Disturbance Using MODIS Products
The capabilities of the MODerate resolution Imaging Spectroradiometer (MODIS) present some exciting possibilities for improved and timely monitoring of forest disturbance at different scales. At a continental scale, several quantitative indices are used in this research to map forest disturbance including fire, clearcuts, and possibly insect damages for Northern Eurasia (between 50N and 70N). The tasseled cap greenness and normalized difference water index are derived from Nadir BRDF-Adjusted Reflectance (NBAR) to map burned- area. The NBAR-based indices have several advantages for this application: (1) standardized reflectance with a unique nadir view and can minimize potential inaccuracy related to variable geometry, and (2) reduced data redundancy and improved vegetation signal. After the QA filtering and temporal smoothing, growing-season vegetation anomalies are calculated to quantify the percentage of the climatological annual grid-point growth either gained or lost during a given year. With the knowledge that major disturbances tend to result in lower vegetation greenness, a threshold-based algorithm can identify burned area for each year. Our preliminary estimates indicate three percent of the 7-million km2 forests were burned from 2000 to 2006, with 70% of this activity occurring in 2003. High-resolution ETM data are used to validate the algorithm using a pixel-based comparison at Sakha. About 80-90% of the ETM burned pixels can be detected by this algorithm. At regional scale, 250-m MODIS NDVI is used to map recent clearcuts based on the difference between growing-season accumulated NDVI for different years. Although MODIS product can identify recent clearcuts at some locations, MODIS does not appear to be good source to map fine-scale clearcuts for all of Northern Eurasia, especially for heterogeneous regions when natural forests are interspersed with human activities. Finally, by determining the post-burned vegetation growth as a function of time, a quantitative index can provide useful information on re- growth rate for different burned regions. Overall, the MODIS product suite is a useful tool in widespread forest disturbance mapping at continental scales. Our work, part of the NELDA (Northern Eurasia Landcover Dynamics Analysis) project, is preparing a continental map of forest disturbance for Northern Eurasia a preliminary version of this map will be presented here. Such maps will provide a fundamental understanding of the changing patterns of forest disturbance as well as the impacts of climate dynamics and land use changes on forest ecosystems
GC23A-0998
The NASA NEESPI Tools Use in Studies of Environmental Changes in Northern Eurasia
The NASA NEESPI portal is a multi-sensor, online, easy access data archive and distribution system to provide advanced data management capabilities in support of the Northern Eurasia Earth Science Partnership Initiative (NEESPI) scientific objectives. Its tools include data analysis and visualization, and other techniques for better science data usage in assessment of the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with the Earth's Climate system. Several cases are investigated using the NEESPI online visualization and analysis system Giovanni that demonstrate ability to multi-sensor data exploration. The analysis of fire occurrence in western Kazakhstan during 2001-2002 has indicated a potential relationship between precipitation, NDVI, and fire occurrence. Inter-annual change in precipitation occurrence is shown to drive the vegetation response observed through NDVI. A greater amount of precipitation during May of 2002 prompted an increase in plant productivity and the corresponding NDVI signal. The enhanced plant productivity potentially leads to a greater accumulation of fuels during the senescence period between June and September. Fuel accumulation results in increased fire occurrence (observed through Fire Counts) and higher fire intensity (observed through the Fire Radiative Power). Other sample studies will be presented in this paper are ice frequency changes over Sea of Okhotsk and other northern seas, and potential drought risk assessment in Mongolia and Central Asia republics using remotely sensed soil moisture and rainfall rate.
GC23A-0999
Determining Regional Carbon Emissions Under Variable Fire Regimes in Central Siberia
The Russian boreal zone is a region of global significance in terms of climate change impacts and carbon storage. Wildfires are the dominant disturbance regime here, currently burning 10 to 15 million ha annually depending upon burning conditions. Fires are projected to increase in both frequency and severity across Siberia under climate change. Changes in boreal fire regimes can be expected to lead to large changes in patterns of burn severity, with attendant effects on emissions per unit burned area and on postfire vegetation recovery. Developing accurate regional to continental estimates of carbon emissions from wildfires in Siberia requires data and models that will enable us to accurately quantify not only the areas that are burned annually, but the emissions per unit of burned area for fires of widely varying characteristics. Fire emissions are a function of the site specific fuel loading and structure, the burning conditions, and the amount of fuel consumed in a fire, all of which combine to determine the way a fire behaves and the amount of fuel that is burned. It is important in the accurate modeling of fire severity to be able to account for the heterogeneous nature of fire behavior. This is due to the constant changes in daily burning conditions, topography, and wildland fuel types. We have carried out a series of 20 experimental burns in Scots pine and larch forests of central Siberia under a variety of conditions to develop data and models that will allow us to integrate remote sensing data on active fire and burned areas with information on fuel condition and fire weather to estimate the impact of wildfires over large areas. Our research has shown that emissions from surface fires, which during normal fire years comprise roughly 80% of all fires, may range up to 3-fold as a function of the fuel type and the weather conditions preceding and during a fire. Emissions from crown fires may add another 7-15%, depending on the intensity of the fire and on crown structure. By correlating field data on fire behavior (e.g., rates of spread, energy release) and fuel consumption on these fires, we have developed models that relate these characteristics to elements of the Canadian Fire Behavior Prediction System or the Russian Moisture Index. We are now beginning to use these relationships to estimate the emissions from fires in pine and larch stands over large geographic areas of Siberia. They also have the potential to enable us to predict carbon emissions from active fires and from increased fires that might occur in the future under changing climate. Using emission factors derived from experimental fires, we can also project the emissions of various greenhouse gases and aerosols. Projecting future fire regimes and impacts of fire on carbon storage and atmospheric chemistry under a changing climate requires a baseline of recent fire activity that can be coupled with weather data and emission data to quantify past effects. This information can then be linked to outputs of climate models and projections of potential future vegetation change to predict future burned areas, fire severity and impacts on carbon storage and atmospheric chemistry.
GC23A-1000
Alpine forest-tundra ecotone response to temperature change, Sayan Mountains, Siberia
Models of climate change predict shifts of vegetation zones. Tree response to climate trends is most likely observable in the forest-tundra ecotone, where temperature mainly limits tree growth. There is evidence of vegetation change on the northern treeline However, observations on alpine tree line response are controversial. In this NEESPI related study we show that during the past three decades in the forest-tundra ecotone of the Sayan Mountains, Siberia, there was an increase in forest stand crown closure, regeneration propagation into the alpine tundra, and transformation of prostrate Siberian pine and fir into arboreal forms. We found that these changes occurred since the mid 1980s, and strongly correlates with positive temperature (and to a lesser extent, precipitation) trends. Improving climate for forest growth( i.e., warmer temperatures and increased precipitation) provides competitive advantages to Siberian pine in the alpine forest-tundra ecotone, as well as in areas typically dominated by larch, where it has been found to be forming a secondary canopy layer. Substitution of deciduous conifer, larch, for evergreen conifers, decreases albedo and provides positive feedback for temperature increase.
GC23A-1001
Quantifying the Effects of Land Cover Change on Carbon Budgets in Romania
Remote sensing observations provide a cost-effective means of monitoring changes on Earth's surface over large areas. We used multitemporal observations derived from the Landsat global orthorectified datasets to map land cover changes in a wall-to-wall fashion in Romania over the period circa-1990 and circa-2000. A combination of the multispectral transforms of brightness, greenness, wetness and change in brightness greenness and wetness derived from atmospherically corrected data served as input in a supervised neural network classifier to map land cover changes. The resulting estimates of rates of forest clearing were then used in conjunction with data on forest biomass, and the fates of harvested forest biomass, in a terrestrial carbon bookkeeping model to estimate the emissions of carbon dioxide from land cover change and its effect on the terrestrial carbon cycle of the region. Results show a slow rate of forest harvest of 2.6% over the circa-10 year period. A preliminary independent validation of the remote sensing results shows an overall accuracy of 88.7 %. The terrestrial carbon model estimates the past, the present and the future terrestrial carbon budget of the country. Over the last 200 years Romania has been a large carbon sink. However, if forest harvest rates continue at current rates, about the year 2100 the country will change from a carbon sink to a carbon source. The change is mainly a result of the accumulation and decomposition over time of carbon stored in the long-term carbon pools like timber products.