GC41A-0673
The NASA NEESPI Data Portal: Products, Information and Services
Studies have indicated that land cover and use changes in Northern Eurasia influence global climate system. However, the procedures are not fully understood and it is challenging to understand the interactions between the land changes in this region and the global climate. Having integrated data collections from multiple disciplines are important for studies of climate and environmental changes. Remote sensed and model data are particularly important due to sparse in situ measurements in many Eurasia regions especially in Siberia. The NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) NEESPI data portal provides satellite remote sensing and numerical model data for atmospheric, land surface, and cryosphere through an online, easily-accessible data archive and distribution system. Data searching, subsetting, and downloading functions are available. One useful tool is the Web-based online data analyses and visualizations system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure), that allows scientists to assess easily the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with global climate system. Recently, we have developed a metadata database prototype to expend the NASA NEESPI data portal for providing a venue for NEESPI scientists to find the desired data easily and leveraging data sharing within NEESPI projects. The database provides product level information, which are grouped into three topics: atmosphere, land surface, and cryosphere. The desired data can be found through navigation and free text search and narrowed down by filtering with a number of constraints. The standard metadata includes product name, product description, temporal and spatial coverage, data source, person of contact, etc. This presentation introduces the infrastructure of NEESPI data portal: products, tools, and information. Sample studies will be presented that demonstrates the usefulness of the Giovanni NEESPI system in multi-sensor data exploration. Detailed information can be found at NEESPI portal: http://neespi.gsfc.nasa.gov
GC41A-0674
Impact of Surface Air Temperature and Snow Cover Depth on the Upper Soil Temperature Variations in Russia
For the 1965-2004 period, data from all Russian meteorological stations with long-term soil temperature observations at depths 80, 160 and 320 cm were compiled and analyzed. It was found that the prevailing influence on soil temperature variations in the European part of Russia was surface air temperature and in the Asian part of Russia - snow cover depth. By preserving the heat accumulated in the warm season, an observed increase of the winter snow depth in the permafrost zone (cf., Bulygina et al. 2007) promotes annual soil temperature increase and therefore may foster the further permafrost degradation associated with ongoing regional warming. The impact of long-term changes in surface air temperatures on soil temperatures in the central regions of the permafrost zone is weak throughout the year. However, in the regions with intermittent permafrost, this impact is substantial. The impact of snow depth on soil temperatures is observed throughout the entire permafrost zone of Russia. Reference cited: Bulygina O.N., N.N. Korshunova, and V.N. Razuvaev, 2007: Variations in snow characteristics over the Russian territory in the recent decades. Transactions of RIHMI-WDC, 173, 41-46.
GC41A-0675
Recent Climatic Changes over Kazakhstan
We used a comprehensive archive of daily in situ meteorological information for Republic of Kazakhstan created by joint efforts of the Kazakh Scientific Research Institute of Ecology and Climate of the Ministry of Environment Protection of the Republic of Kazakhstan, All-Russian Research Institute for Hydrometeorological Information-World Data Center of the Federal Service for Hydrometeorology and Environmental Monitoring, Obninsk, Russian Federation, and the NOAA National Climatic Data Center, Asheville, North Carolina. Archive includes the data of 351 synoptic stations and spans the period of instrumental observations with the best data coverage during the 1936-2006 period. This period was used to assess climatology and the latest (since 1990) climatic changes in surface air temperature, precipitation, relative humidity, and the near surface wind speed and atmospheric pressure over Kazakhstan. We found that during the last two decades (1990-2006) compared to the previous three decades, surface air temperature, T, in Kazakhstan increased by 1 to 2 K in winter, spring, and autumn (with the maximum warming in the autumn) but not in summers where a cooling was observed in the central parts of the nation. Changes in relative humidity were symmetric and negatively correlated with T: reporting drier surface air conditions in winter, spring, and autumn and an increase in the mean summer relative humidity values. Countrywide, annual precipitation did not change substantially (it somewhat increased in winter and summer, but mostly decreased in the intermediate seasons). The largest change signal found is a substantial nationwide decrease of the wind speed at 10 m above the ground in all seasons.
GC41A-0676
Weather Conditions over the Russian Federation in 2007
By and large, the year 2007 was abnormally warm in Russia. The mean annual air temperature anomaly averaged over the region was 2.0°C. Last winter and summer were also extremely warm over the Russian territory, with mean seasonal air temperature anomalies being 3.2°C and 1.8°C, respectively. For the whole of Russia, in spring and fall, the air temperature anomaly attained 2.2°C and 1.8°C, respectively. January in 2007 proved to be abnormally warm over most of Russia. The vast territory of Russia, from its western boundaries to the Lena River, has not experienced such high temperatures for the past 117 years, i.e. for the entire period of regular meteorological observations. As a result, the January of 2007 in Russia has proved to be the warmest since 1891. Spring temperatures over the Russian territory were higher than the long-term average. The seasonal air temperature anomaly, averaged over the Russian territory, ranked second for the period of record. On the Arctic coast of European Russia and in Western Siberia, a positive anomaly of the mean seasonal air temperature averaged over the region attained a record-breaking value. Mean summer air temperatures were above normal in all quasi- homogeneous regions. For the Russian territory as a whole, August proved to be the warmest for the period in question. The fall in 2007 was also abnormally warm, particularly on the Arctic coast of Asian Russia. The snow cover over the Russian territory in the 2006-2007 winter was studied from regular snow observations at 600 Russian meteorological stations. To estimate the snow cover duration, the number of days when more than 50% of the territory around a meteorological station was covered with snow was used. Positive values (no more than 20 days) of snow cover duration anomalies are prevailing in the territory of Russia in the 2006/2007 winter.
GC41A-0677
New Version of the Data Set "Daily Temperature and Precipitation Data for 223 USSR Stations"
The first version of the data set "Daily Temperature and Precipitation Data for 223 USSR Stations" contains mean daily, minimum and maximum air temperatures and daily precipitation totals for 223 stations of the former USSR for the period 1881 - 1989. The data set was created by RIHMI-WDC and was jointly prepared for publication by RIHMI-WDC and Carbon Dioxide Information Analysis Center (CDIAC; ORNL, Oak Ridge, USA). The data set was described by V.N. Razuvaev, E.G. Apasova, R.A. Martuganov (RIHMI-WDC) and Russel Vose (CDIAC) and was published by CDIAC in 1993 as ORNL/CDIAC 56 (NDP-40) (Razuvaev et al. 1993). The data set is distributed free of charge by request. The data set has recently been widely used by the international scientific community to study climate changes over the Russian territory and their relation to global climate changes. The authors have received a lot of responses and comments concerning data quality, errors and uncertainties, and proposals to improve the data set. Particular attention was given to the need for complementing the data set with current data. Currently, a new version of the data set has been prepared, including the data up to 2006. Wherever possible, errors in data are corrected and gaps are filled. The new version has a data retrieval system and is complemented with a metadata set. Unfortunately, some stations over the Russian territory were closed and a number of stations in the former USSR republics (beyond Russia) do not make their information available for the international data exchange. The new version has already been used in analyzing the climate changes and the frequency of extreme events over the Russian territory (Bulygina et al. 2007). The new version of the data set is available from the RIHMI-WDC Web site http://www.meteo.ru and is disseminated free of charge. The English copy of the data set will also be available from the CDIAC Web site.
GC41A-0678
Current activity in the exchange of environmental data between the United States and the Russian Federation
In November, 2008 data exchange coordinators from NOAA, Roshydromet, Oak Ridge National Laboratory (ORNL), the National Center for Atmospheric Research (NCAR), and the National Snow and Ice Data Center (NSIDC) met at the All Russian Institute for Hydrometeorological Information (RIHMI) in Obninsk, Russia to renew data exchange and research protocols, and to update existing data exchanges between the United States and Russia, many of which have been occurring since the 1970s. The coordinators also discussed the development of new data sets, the exchange of International Polar Year (IPY) data, the rescue of historical data from deteriorating media, and the conduct of joint research activities in support of data collection, compilation, and analyses. In addition to detailing new bilateral data exchanges and joint U.S.- Russian research activities, this paper provides an overview of the status of a number of environmental data sets presently available to researchers that are either directly exchanged between the United States and the Russian Federation or to which both the U.S. and Russia provide data.
GC41A-0679
Forest Fire Frequency in Scots Pine Stands of Tuva
Forests fires resulting from long periods of drought cause the heaviest forest ecosystem destruction and have often unpredictable impacts on the regional environment. Past fire frequency is reconstructed for Tuvan Scots pine stands using dendrochronological methods and statistical information. While Scots pine stands occupying big sites in central Tuva are subject to fire annually, high-intensity fires responsible for the biggest damage occur here much rarer. However, these severe fires have shaped multi-story Scots pine communities at a local level. Fire type and frequency are directly related to climatic change, i.e. with alternation of dry and wet periods, and are also dependent on anthropogenic influences. Dry periods promoting fire ignition and spread occur in Tuva mainly in April and May. These spring fires are typically surface fires of low severity. In some years, precipitation deficit combined with high air temperatures induce long droughts. Surface fires occurring during such periods often go up to tree crowns and result in high forest damage. Although the mean fire interval is found to be 17.5 years for these stands, it is much longer for high-severity fires. The mean fire interval is twice to three times as long in mountain larch stands. Global climate change is determined to result in increasing fire intensity rather than fire frequency in Tuva.
GC41A-0680
Surface Fire Influence on Carbon Balance Components in Scots Pine Forest of Siberia, Russia
Wildfire is one of the most important disturbances in boreal forests, and it can have a profound effect on forest-atmosphere carbon exchange. Pinus sylvestris (Scots pine) stands of Siberia are strongly impacted by fires of low to high severity. Biomass distribution in mature lichen/feathermoss Scots pine stands indicates that they are carbon sinks before fire. Fires contribute significantly to the carbon budget resulting in a considerable carbon efflux, initially through direct consumption of forest fuels and later as a result of tree mortality and decomposition of dead material accumulated on the forest floor. In initial postfire years these processes dominate over photosynthetic carbon assimilation, and the ecosystems become a carbon source. Over several postfire years, above-ground carbon in dead biomass tends to increase, with the increase depending significantly on fire severity. High-severity fire enhances dead biomass carbon, while moderate- and low-severity fires have minimal effect on above-ground carbon distribution in Scots pine ecosystems. Dead stand biomass carbon increases, primarily during the first two years following fires, due to tree mortality. This increase can account for up to 12.4% of the total stand biomass after low- and moderate- intensity fires. We found tree dieback following a high-intensity fire is an order of magnitude higher, and thus the dead biomass increases up to 88.1% of total above-ground biomass. Photosynthetic CO2 uptake decreases with increasing tree mortality, and needle foliage and bark are incorporated into the upper layer of the forest floor in the course of years. Ground vegetation and duff carbon were >90, 71-83, and 82% of prefire levels after fires of low, moderate, and high severity, respectively for the first 4 to 5 years after fire. Fires of low and moderate severity caused down woody fuel carbon to increase by 2.1 and 3.6 t ha-1 respectively by four years after burning as compared to the pre-fire values. Climate change and increasing drought length observed in recent decades have increased the probability of high-intensity fire occurrence. Areas burned have increased in extent and severity across Siberia, resulting in increased carbon emissions to the atmosphere from fuel combustion and post fire decomposition.
GC41A-0681
Estimating Fire-Caused Boreal Forest Disturbances Using Remote Sensing Data
Russia accounts for about half of the world's forests, most of which are in Siberia. Numerous forest fires, mostly human-caused, and extensive forest harvesting, including illegal logging, have resulted in considerable ecological damage and economic loss. At present, forest inventory agencies assess the effects of fire based on the known forest area burned. Due to potential cost and difficulty of access types and severity of fire effects are normally not assessed. The lack of reliable estimates of ecological and economic impacts of forest fires prevents development of effective approaches for forest management and forest fire protection. Remote sensing and GIS-based technologies provide for the development of fundamental new methods to assess and monitor forest condition and wildfire behavior and effects. Wildfire and insect and disease outbreaks are the main natural factors responsible for partial or complete mortality of forest stands in Siberia. Negative human influences include forest harvesting, mining, industrial pollution, and human-caused fires. Estimating the scale, rate, and severity of disturbance is of key importance for appraising the resulting ecological and economical damage. In this study, we developed a GIS- and satellite-based methodology to appraise forest damage by taking advantage of unique spectral signature of the underlying forest types. Our focus was on an area of intensive forest harvest in the Angara river basin, which includes the southern and central taiga zones. We have assessed the type, extent, and severity of disturbances in vegetation cover and mapped the current condition of disturbed forest sites.
GC41A-0682
Modeling and Assessing Insect Disturbance on Boreal Forests in the Krasnoyarsk region of Russia by Employing the FAREAST Gap Model and Local Forest Inventory and Disturbance Data.
FAREAST: an individual-based forest dynamics model was initially developed to simulate the forested region around Changbai Mountain in northern China. In recent years the model has been expanded across Siberia. The model output for biomass (tCha-1) has been verified against forest inventory data for a number of sites across Russia. With this success, an additional module for the model was written by Anton Kovalev to predict the impact of insect disturbance on the Boreal forests. This model predicts the probability of an insect outbreak occurring, and then, by assessing each individual tree in a modeled stand, predicts whether a tree will be killed as a result of insect predation. From this, a disturbance index is calculated that includes lost biomass as a result of insect disturbance and subsequent species composition. This disturbance "fingerprint" is being compared to forest inventory and insect disturbance data from the Usolsky forests in the Krasnoyarsk region of central Siberia. Silkworm disturbance is expressed in this geo- database as a percentage of trees damaged or killed in a stand. The forest inventory data allows us to calculate a biomass estimate that will be compared to the biomass outputs generated by the model post insect disturbance. The validation of simulated biomass with independent inventory data confirms that FAREAST is a robust model of Russian forest dynamics. Effective validation of the insect disturbance model will allow us to generate a more complete picture of the changing ecology of the Siberian Boreal landscape. The economic cost of lumber lost as a result of Silkworm damage has been enormous, if verified, FAREAST will afford us the opportunity to estimate the extent of that loss and predict the changing ecological dynamics of the Boreal forest system under the worlds evolving climate.
GC41A-0683
Simulating the Effects of Fire on Forests in the Russian Far East: Integrating a Fire Danger Model and the FAREAST Forest Growth Model Across a Complex Landscape
The remaining natural habitat of the critically endangered Amur tiger (Panthera tigris altaica) and Amur leopard (Panthera pardus orientalis) is a vast, biologically and topographically diverse area in the Russian Far East (RFE). Although wildland fire is a natural component of ecosystem functioning in the RFE, severe or repeated fires frequently re-set the process of forest succession, which may take centuries to return the affected forests to the pre-fire state and thus significantly alters habitat quality and long-term availability. The frequency of severe fire events has increased over the last 25 years, leading to irreversible modifications of some parts of the species' habitats. Moreover, fire regimes are expected to continue to change toward more frequent and severe events under the influence of climate change. Here we present an approach to developing capabilities for a comprehensive assessment of potential Amur tiger and leopard habitat availability throughout the 21st century by integrating regionally parameterized fire danger and forest growth models. The FAREAST model is an individual, gap-based model that simulates forest growth in a single location and demonstrates temporally explicit forest succession leading to mature forests. Including spatially explicit information on probabilities of fire occurrence at 1 km resolution developed from the regionally specific remotely –sensed data-driven fire danger model improves our ability to provide realistic long-term projections of potential forest composition in the RFE. This work presents the first attempt to merge the FAREAST model with a fire disturbance model, to validate its outputs across a large region, and to compare it to remotely-sensed data products as well as in situ assessments of forest structure. We ran the FAREAST model at 1,000 randomly selected points within forested areas in the RFE. At each point, the model was calibrated for temperature, precipitation, slope, elevation, and fire probability. The output of the model includes biomass estimates for 44 tree species that occur in the RFE, grouped by genus. We compared the model outputs with land cover classifications derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data and LIDAR-based estimates of biomass across the entire region, and Russian forest inventory records at selected sites. Overall, we find that the FAREAST estimates of forest biomass and general composition are consistent with the observed distribution of forest types.
GC41A-0684
Using Large-scale Spatially and Temporally Consistent Reanalysis Data to Assess Fire Weather and Fire Regimes in Siberia in Preparation for Future Fire Weather Prediction
A primary driving force of land cover change in boreal regions is fire, where 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. The use of local ground based weather data can be used to gauge the local fire potential on a daily, monthly, or seasonal basis. However, the number and distribution of surface observing stations in Siberia have been declining since the early 1990's. A compounding problem is existing observing stations have missing data on various time scales. The density of stations is limited; hence results may not be representative of the spatial reality. One solution is the temporally and spatially consistent NASA Goddard Earth Observing System version 4 (GEOS-4) satellite-derived weather data interpolated to a 1x1 degree grid. In previous work, we showed the Canadian Forest Fire Weather Index (FWI) derived using GEOS-4 weather and Global Precipitation Climatology Project (GPCP) precipitation data compared well to ground based weather data from Jakutsk (Sakha) and Kyzyl (Tuva), Russia. Our primary focus is to expand on this work by spatially comparing the FWI derived from GEOS-4 / GPCP data and ground-based weather observations from the National Climatic Data Center (NCDC). Extreme fires burned in Sakha and Tuva in 2002 and 2004, respectively, while in contrast, normal fire seasons occurred in Sakha and Tuva in 1999 and 2002, respectively. For this reason, we focus on the 1999, 2002, and 2004 fire seasons (April - September). In this investigation, we demonstrate how fire weather models perform on a large scale and investigate the performance of these models relative to input uncertainties. We intend to use this information to build regional-scale fire predictions systems that can be used for future interactive fire-weather-climate assessments.
GC41A-0685
River Runoff Sensitivity in Eastern Siberia to Global Climate Warming
During several last decades significant climate warming is observed in permafrost regions of Eastern Siberia. These changes include rise of air temperature as well as precipitation. Changes in regional climate are accompanied with river runoff changes. The analysis of the data shows that in the past 25 years, the largest contribution to the annual river runoff increase in the lower reaches of the Lena (Kyusyur) is made (in descending order) by the Lena river watershed (above Tabaga), the Aldan river (Okhotsky Perevoz), and the Vilyui river (Khatyryk-Khomo). The similar relation is also retained in the case of flood, with the seasonal river runoff of the Vilyui river being slightly decreased. Completely different relations are noted in winter, when a substantial river runoff increase is recorded in the lower reaches of the Lena river. In this case the major contribution to the winter river runoff increase in the Lena outlet is made by the winter river runoff increase on the Vilyui river. Unlike the above cases, the summer-fall river runoff in the lower reaches of the Lena river tends to decrease, which is similar to the trend exhibited by the Vilyui river. At the same time, the river runoff of the Lena (Tabaga) and Aldan (Verkhoyansky Perevoz) rivers increase. According to the results of hydrological modeling the expected anthropogenic climate warming in XXI century can bring more significant river runoff increase in the Lena river basin as compared with the recent one. Hydrological responses to climate warming have been evaluated for the plain part of the Lena river basin basing on a macroscale hydrological model featuring simplified description of processes developed in Institute of Geography of the Russian Academy of Sciences. Two atmosphere-ocean global circulation models included in the IPCC (ECHAM4/OPY3 and GFDL-R30) were used as scenarios of future global climate. According to the results of hydrological modeling the expected anthropogenic climate warming in 21st century can bring much more significant river runoff changes in plain part of Lena river basin compared with the 20th. The both scenarios suggest quite a significant change in the character of the annual stream-flow distribution in middle of XXI. The scenarios give, in essence, the similar pattern of changes in the wave of spring-summer high water. The onset of the flood can be shifted one month backward, as compared with the current situation. The main contribution to the river runoff change in the mid-21st century can be made by the increase in atmospheric precipitation and air temperature, while the scenario changes in the active layer depth are not to make a perceptible impact. This study was supported by NASA grant NNG06GH41G and the Russian Fund on Basic Research grant 07- 05-12085-ofi.
GC41A-0686
Spatial-temporal structures of intraseasonal precipitation oscillations over northern Eurasia during summer
This study examines intraseasonal oscillations in summer precipitation over northern Eurasia using a multi- channel singular spectrum analysis (MSSA). For the analysis, a gauge-based daily gridded precipitation data set for the northern Eurasian domain is used. The analysis period extends June-August of 1979-2002 (23years). Empirical orthogonal function analysis is first performed on 8-day low-pass filtered precipitation records at 2.5 degree grid resolution in the northern Eurasian domain (50-70N, 40-140E). Then, the MSSA was carried out on the ten leading principal components (PCs). As a result, three quasi-periodic oscillations with timescales of 45 days, 14 days, and 10 days are identified, respectively. Spatial-temporal structures of the precipitation oscillatory modes are defined by composite analysis based on reconstructed time series of spatial-temporal PCs obtained from the MSSA. A composite life cycle of each mode is classified into eight phase categories. The 45-day oscillation is characterized by a broad east-west contrastive pattern over the entire northern Eurasian domain which appears to be associated with quasi- stationary rainfall events persisting for about one to two weeks. On the other hand, the 14-day oscillation has an east-west dipole pattern between western and eastern Siberia. This mode dominates submonthly dry (below normal rainfall) and wet (above normal rainfall) seesaw extreme events in major Siberian river basins. The 10-day oscillation has a comparatively smaller spatial-scale and amplitude, and is localized in the southern part (approximately 50-60N) of northern Eurasia. Connections between the precipitation oscillatory modes and mid- and high-latitude atmospheric circulation patterns are also explored. The similar composite method is applied to 500-hPa geopotential height anomalies over the Northern Hemisphere. A broad large-scale trough-ridge pattern (wave numbers 2-3) prevails over the high-latitude North Atlantic and northern Eurasia associated with the 45-day oscillation. This wave appears to have both standing and slow eastward-propagating components. A circulation pattern responsible for the 14-day oscillation exhibits wave train structure extending from the North Atlantic into the North Pacific. The eastward propagation of this wave (wave numbers 4-5) reflects the zonal displacements of Siberian rainfall anomalies. A comparatively smaller-scale (wave number 6) wave train arcing through northern Eurasia develops at high-amplitude phases of the 10-day oscillation.
GC41A-0687
Climate Change in the NEESPI Region in the 21st Century
Probable climate change is considered over the Northern Eurasia in the 21st century based on simulation of global climate with an ensemble of the comprehensive coupled atmosphere-ocean GCM CMIP3. Analysis results are presented of future changes of thermal and hydrological regimes over the investigated territories. The future changes of surface air temperature, precipitation, snow cover, soil moisture and annual runoff were estimated for the different regions at the beginning, middle and end of the 21st century under greenhouse gases and aerosols SRES A2 scenario. Besides the mean changes of different climatic variables, the standard deviation and level of statistical significance were also evaluated using the ensemble of simulations. NEESPI = Northern Eurasia Earth Science Partnership Initiative.
GC41A-0688
Regional Modeling of Permafrost Evolution in Russia
The analysis of current seasonal thawing/freezing ground characteristics and their changes under warmer climate conditions using VMGO Regional Climate Model (RCM) scenario for European part of Russia, West and East Siberia has been conducted. The late 20th century permafrost simulation using the RCM output has been validated against observations in the region of East Siberian transect. The results are compared with the calculations based on the GCM climate data. The differences between GCM and RCM simulations are discussed. It has been shown that the use of higher spatial resolution of vegetation distribution and topography in the RCM gives a realistic representation of regional ground temperatures. The most significant permafrost degradation is projected at the southern boundary of the permafrost area. The correlation between seasonal freezing/thawing depths and meteorological characteristics of warm and cold seasons has been studied. The ground temperature at different levels has been calculated for the mid and late 21st century.
GC41A-0689
Impact of the freezing level surface height to cryospheric changes in China
The height of the freezing level surface (FLS) – the elevation above sea level at which the air temperature is close to 0°C – is an important parameter for cryospheric changes, because it denotes the approximate position of permanent ice and snow on the surface, and thus constitutes an important indicator of climate variability and change. In the former works, the height of FLS was general extended from surface stationary observation by a constant laps rate due to lack of higher altitude station. Recently, several researches has introduced radiosonde data to cryosphere investigation (Seidle and Free, 2003; Gaffen et al.,2000; Diaz and Graham 1996), they deduce the height of FLS from radiosonde data and demonstrated it robust forcing factor for cryospheric changes. There are about 150 stations in Chinese radiosonde network, and near 100 stations have efficient air temperature time series. In this work, we deduce changes in freezing level heights from those time series and examine its potential impacts on changing snow cover, permafrost and glacier mass balances. The results reveal that FLS could be significant forcing element to changing cryosphere.
GC41A-0690
GRACE Hydrologic Mass Balance Secular Trends and Variations on Arctic Permafrost Watersheds
Permafrost is largest component of the Arctic cryosphere by area extent. Over the last century, substantial changes in storage and cycling of fresh water have been observed. Observations of the globally distributed hydrologic mass balance (water equivalent thickness change relative to the geoid) from the Gravity Recovery and Climate Experiment mission offer to provide a greater understanding of the processes controlling redistribution of water mass (groundwater storage, discharge, snow water equivalent storage, vegetation water storage, and ice sheet mass balance) under ongoing effects of climate warming. Using newly processed monthly GRACE grids, Level-3 Release 4, de-striped, adjusted for post-glacial rebound I investigate the hydrologic mass balance of the Arctic watershed regions. Regionally-averaged monthly time series show strong seasonal periodicity, with maxima occurring in April/May and minima in September/October. Eurasian watersheds have significant positive secular trends. The Ob-Irtysh watershed shows a water equivalent gain of 22.7 ± 13.5 km3/yr, and the Lena watershed shows a water equivalent gain of 44.7 ± 0.8 km3/yr from August 2002 through March 2008. The Mackenzie watershed shows a water equivalent volume change of -5.6 ± 7.2 km3/yr in the same time period. The permafrost area extent in the watersheds investigated shows the Ob-Irtysh draining the least continuous permafrost extent and the Lena draining the most. The Mackenzie watershed drains a mixture of continuous and discontinuous permafrost area extents. Regionally-average snow water equivalent time series show seasonal periodicity whose maxima and minima occur one month ahead of the GRACE time series. Secular trends of snow water equivalent show neither significant gain nor loss over the time period. This removes snow water equivalent (a component of surface water storage) as being the source of the GRACE secular trends. A subsurface source of water mass exchange of the GRACE secular trends on the Arctic watersheds is suggested.
GC41A-0691
Estimating Soil Moisture, Inundation, and Methane Emissions from Siberian Wetlands Using Models and Remote Sensing
Estimation of methane emissions from high-latitude wetlands and changes that may occur in a warming climate has important implications for projections of global warming, due to the strength of methane as a greenhouse gas and the substantial fraction of global methane emissions that come from high latitudes. Efforts to monitor high-latitude methane emissions are hampered by the sparseness of in situ data at high latitudes, and in Northern Eurasia in particular. While biogeochemical modeling can provide estimates of methane emissions in areas where in situ measurements are scarce, the lack of in situ measurements also makes it difficult to calibrate and/or constrain these models. However, remote sensing products based on synthetic aperture radar that can be used to calibrate or constrain biogeochemical models in these regions at high resolution over multiple seasons have recently become available. We compare multi-temporal remotely-sensed estimates of saturated soil extent and inundation from the ALOS/PALSAR L-band sensor to simulations from our modeling framework (consisting of the Variable Infiltration Capacity macroscale hydrological model (VIC), extended to include carbon cycling and coupled to a methane emissions model) of these same quantities at multiple points in time over two growing seasons (2006 and 2007) for various locations in the West Siberian Lowlands. We explore the effects of model parameter uncertainty on the errors between simulations and remote sensing estimates, and on the magnitudes and distributions of simulated methane emissions.
GC41A-0692
An Integrated Biogeophysically Based Model Of Land Surface Water And Energy Fluxes And Its Application To Different Climate Conditions
A land surface model was developed to evaluate the dynamics of water, energy, and CO2 fluxes in the soil- vegetation-atmosphere system of the Arctic regions. The model includes three submodels: vegetation, snow cover, and soil. The energy budgets are solved for the radiative and energy fluxes both at the canopy layer and the soil surface. The snow submodel calculates snow temperature, depth, density, and water content. In the soil submodel, the soil moisture transport scheme was retained, and the thermal and moisture fluxes are solved separately. At each time step, thermal fluxes through the soil layers are solved prior to the prediction of soil layer ice content. Subsequently, moisture fluxes are computed using the estimated ice contents. The model provides a consistent treatment of carbon exchange by plants, by linking photosynthesis with stomatal conductance. The model also represents spatial heterogeneity in land cover by dividing each grid cell into three land cover types: lake, wetland, and vegetation. The vegetated portion of the grid cell is further divided into several patches of plant functional types. Multiple plant functional types can co-occur in a grid cell so that, for example, a mixed broadleaf deciduous and needleleaf evergreen forest may consist of patches of broadleaf deciduous trees, needleleaf evergreen trees, and other vegetation. The land surface model was applied to the three Arctic sites (Tiksi, Yaktsuk, and Fairbanks) of the different climatic and land surface conditions. The model performance was validated to the temporal dynamics of water, energy, and carbon budget. Spin-up required about 1000 model years, achieved by cycling the 25-a time series (1980-2004) of atmospheric forcing. At Yakutsk, four plant functional types were initially established by the model. Arctic grasses initially dominate and decline as trees grow. This similar pattern of plant dynamics was found in Fairbanks. However, Tiksi was mainly dominated by arctic grasses, different from the two forested regions. It shows that the simulated energy fluxes at the three sites were generally consistent well with the measurements. The model overestimated sometimes latent heat flux, which is due to the overestimation of rainfall interception by the canopy. The simulation for the dynamics of snow depth was very good at the three sites. However, the model represented the earlier snow melt than the observations. This is related to the overestimate of solar radiation over the snow surface by the model. The model also simulated well the seasonal variations of soil water and temperature, as well as their differences between regions. It was found that the seasonality of active layer depth was especially well expressed at the three sites, when compared the measurements. This is attributed to the consideration of the effect of organic matter on the soil water and temperature into the model. Comparison in carbon fluxes showed good agreement between the simulation and observation in Yakutsk and Fairbanks, although there was sometimes large scattering. The good model simulations for biogeophysical processes under the different climatic conditions suggest that the model can be used to evaluate biogeophysical feedbacks in the Arctic climate system related to vegetation dynamics under the climate change.
GC41A-0693
Carbon fluxes of high-latitude steppes as analogues of Pleistocene tundrasteppes of Beringia.
The problem of existence of the largest Pleistocene biome - "mammoth" ecosystem is exploring within the bounds of tundrasteppe conception, that have been highly developed since the second half of XX century. Modern high-latitude steppes and tundrasteppes of North-East Eurasia and North America serve as an unique information source about Beringia landscapes for the resemblance of many components of these ecosystems. It allows considering contemporary steppen ecosystems as more or less analogous to Pleistocene steppes. Carbon fluxes cycle studies were carried out upon two types of steppen areas (petrophytic and thermophytic) of Kolyma Lowland, North-East Siberia. Xerophyte and cryophyte phytocoenosis of steppes have similar composition of plant species, that is generally typical for vegetation of relict steppes, but they differ in their abundance of species and phytomass storages, different influence of small grazers upon their vegetation. Steppe soils are characterizing with an extreme value of soil temperature and aridity (active-layer thickness is one of the most intense in its region - over 1.5 m), neutral or low alkaline pH, the high dynamics of seasonal heat exchanges and cryoaridic type of soil genesis. Modern high- latitude steppe soils have the highest fertilization (C org. humic acids, N, P, K, Ca) in the soil cover of region. Upper horizons of steppe soils are generally humic. The distribution of C org. is relatively equal in mineral part of soil profiles and increased in layers with high roots density and rarely above permafrost boundary. Growing season has two maximum of photosyntesis activity - spring-summer and less intensive autumnal (second wave of vegetation). Decomposition of organic material is limited with moisture but high though short-time CO2 emission is typical for early spring and fall periods. Processes that forming C budget in high- latitude steppes are similar to those in zonal steppe landscapes of North Eurasia, but have some differences, connected with polar day effect and influence of permafrost.
GC41A-0694
Proxy-Model Comparison of Temperatures in Lake Baikal Region for the Last Climatic Cycle
The response of the climate system to future anthropogenic and natural forcings remains associated with significant uncertainty. A better understanding is limited by the lack of direct observational data on the behaviour of the climate system under different boundary conditions. Comparison of paleo-proxy data with results from coupled atmosphere-ocean general circulation models can reveal to what degree the output of the most comprehensive tools for predicting future climate changes is consistent with the evidence from the past. However, a robust model-data comparison requires reliable global-scale past climate quantitative reconstructions. These data are widely available for the ocean surface on sea surface temperature, but reliable quantitative and accurate continental temperature proxies have proven difficult to obtain, particularly from Eurasia. Here we present the first quantitative climatic reconstruction of central Siberia during the last climatic cycle, and use it to assess the results from several GCM in the Paleoclimate Modelling Intercomparison Project (PMIP) over Siberia. Lake Baikal has proved to be a highly climatically sensitive system with a well preserved sedimentary record. Several paleoclimatic studies have been conducted based e.g. on diatom abundance and pollen, but there is still a lack of quantitative outputs in climatic reconstructions of that region. We have used novel proxies based on archaeal and bacterial lipid biomarkers (indices TEX86, MBT and CBT) to obtain a record of lake temperature and air temperature for the last climatic cycle, from two sediment cores located in the north and the south basins of Lake Baikal. The reconstructed lake waters and air temperatures evolve in a similar pattern from cold temperatures between 24-22 kyr BP to warmer temperatures ca. 18 kyr BP, which remain quite constant until recent times, thus suggesting that our proxies are recording the last deglaciation in the Lake Baikal area. Another prominent feature of the quantitative temperature records derived from TEX86 is a succession of cooling episodes which are synchronous with a lowering of diatom production in the lake. These events occur at ca. 16, 24, 29, 34 and 50 ka, and this timing suggests a correlation with the Bond cycles known for the North Atlantic region (core ODP-609). We have compared the obtained temperature values to the output of coupled ocean-atmosphere-vegetation models included in the PMIP2. Differences between the model output and the proxy reconstructions range from around 2°C in the Holocene optimum to ca. 10°C in the Last Glacial Maximum, results which are discussed in terms of seasonality of the proxy signal, influence of the lake water mass and precision of the models used.
GC41A-0695
Evaluation of Thermal State of Siberian Permafrost From Accumulated Surface Heat Flow Balance.
Permafrost exists as a response to the climatic condition and has significant longer response time than that of climate change itself. It is oftern reported the warming of permafrost in relation with recent warming. It is essential to look into the past trends of variation, since its response of to the climate change is partly determined by past condition. In this study, we use the "accumulated surface heat flow balance" as an index to discuss the year-to-year change of the thermal condition of the permafrost. This method aim to analyze the trend of the ground temperature change quantitatively, using relatively shallow-depth ground temperature data, up to several meters deep. It would be useful because deep boreholes are not always available at the field observation, while the shallow depth measurements is far easier to install. As an application of this method, we present a case of Siberian permafrost, using dataset "Russian Historical Soil Temperature Data" compiled by Zhang et al. (2001) and archived by NCAR/EOL. Some sites in this data are showing the sign of temperature rise, which should correspond to the permafrost degradation. Central Siberia is one of the key regions where a remarkable rise of ground temperature was observed recently. Our analysis provides historical information of thermal state in the region.
GC41A-0696
A semi-analytical model for remote estimation of chlorophyll-a in turbid productive waters: Calibration and Validation
Accurate assessment of phytoplankton chlorophyll-a (chla) concentrations in turbid waters by means of remote sensing is challenging due to the optical complexity of case 2 waters. We have applied a recently developed three band model for the estimation of chla concentrations in turbid productive waters of Dnieper and Don River basins. The objectives of this paper are (a) to validate the three-band model and its special case, the two-band model, using datasets collected over a considerable range of optical properties, trophic status, and geographical locations in turbid lakes, reservoirs, estuaries, and coastal waters, and (b) to evaluate the extent to which the three-band model could be applied to the MERIS data and two-band model could be applied to the MODIS data to estimate chla in turbid waters. The three-band model was calibrated and validated using three MERIS spectral bands (660-670 nm, 703.75-713.75 nm, and 750-757.5 nm), and the 2-band model was tested using two MODIS spectral bands (662-672 nm and 743-753 nm). We assessed the accuracy of chla prediction in four independent datasets without re-parameterization (adjustment of the coefficients) after initial calibration elsewhere. Although the validation data set contained widely variable chla, Secchi disk depth, and turbidity, chla predicted by the 3-band and 2-band algorithms was strongly correlated with observed chla: determination coefficients were 0.96 and 0.92, respectively. These findings imply that, provided that an atmospheric correction scheme for the red and NIR bands is available, the extensive database of MERIS and MODIS imagery could be used for quantitative monitoring of chla in turbid waters. Uncertainties of Chla retrieval from MODIS and MERIS data are discussed.
GC41A-0697
Satellite Monitoring of Chlorophyll-a Concentration in the Water Bodies of the Dnieper and Don River Basins
We present and discuss here the results of our work using satellite data to estimate chlorophyll-a concentration in reservoirs of the Dnieper River and the Sea of Azov, which are typical Case II waters, i.e., turbid and productive. Our objective was two-folded – (i) to test the potential of remote sensing as a tool for near-real-time monitoring of these water bodies, and (ii) to feed the results of our work into a larger project that involved the use of satellite technology to investigate and understand the effects on the bio-optical characteristics of these water bodies due to changes in the land use and land cover in the surrounding regions. MODIS and MERIS images were used. We tested the performance of a three-band model and a two- band model that use the reflectance at the red and NIR spectral bands for the retrieval of chlorophyll-a concentration. The higher spatial resolution and the availability of a spectral band at around 708 nm with the MERIS data offered great promise for the three-band model. We tested the applicability of two standard MODIS and MERIS algorithms for Case II waters. We compared results from several different atmospheric correction procedures available for MODIS and MERIS data. No one particular procedure was consistently and systematically better than the rest. Nevertheless, even in the absence of a perfect atmospheric correction procedure, both the three-band and the two-band models showed promising results when compared to in-situ chlorophyll-a measurements. The challenges and limitations involved in satellite remote monitoring of turbid productive waters are discussed.
GC41A-0698
Eurasia terrestrial water storage changes and boreal drought from multi-sensor satellite observations, in-situ data
High latitude biomes are changing in response to recent and persistent climatic warming. Dramatic changes have been observed in the Arctic terrestrial hydrologic cycle over the last century with the rate of change increasing during recent decades. Surface air temperatures have increased more over northern land areas than elsewhere in the world with most general circulation models projecting amplified Arctic warming through the 21st century [IPCC, 2001]. Northern terrestrial ecosystems are critical to global climate because they are a major sink for atmospheric CO2 and contain up to 40% of the global reservoir of potentially reactive organic carbon soil. This work has the goal of improving understanding of how Northern terrestrial ecosystems are responding to recent climate warming. Our study domain is the Eurasian land mass encompassing the major river basins in the region (Lena, Ob and Yenisey). We study correlations of terrestrial water storage estimates from the GRACE satellite with precipitation and river discharge measurements, length of thaw/freeze season from satellite microwave remote sensing, MODIS derived net primary production (NPP) and permafrost extent. Results of these comparisons and interpretation will be presented.
GC41A-0699
Effects and Feedbacks of Windthrow/breaks in Boreal Forest Ecosystems
The increased frequency of severe storms (Leckebusch et al., 2007) as a result of ongoing climate change, results in a wide area damage events within boreal forest ecosystems. The damage occurs at exposed forest edges as well as inside forest stands creating the gaps. Once a windthrow/break gap occurs, it results in changes of surface albedo and microclimatological conditions and in increasing wind stress on remaining trees around the gap which in turn increase the risk of further wind damage. The self-induced growth of windthrow gap provides other positive as well as negative feedbacks to climate forcing at different spatial and temporal scales as shown in Vygodskaya et al., 2007, e.g. an increase of CO2 efflux (climate warming) and an increase of surface albedo (climate cooling). The present study characterizes the spatial variation of wind load and the changes in radiative regime (surface albedo) within the damaged forest stand. For description of wind field and load on trees the atmospheric boundary-layer two-equation closure model SCADIS based on transport equations for turbulent kinetic energy (E) and specific dissipation (omega) (E–omega model), which accounts for the flow dynamics within a plant canopy (Panferov and Sogachev, 2008; Sogachev and Panferov, 2006) was used. The radiative regime within the damaged forest is described by means of a three-dimensional radiation transfer model SPM3D (Panferov et al., 2005). A series of numerical experiments with circular and rectangular forest gaps with sizes from 3 to 75 tree heights, h, have been carried out for a modelled boreal forest. To evaluate the changes produced by gaps relatively to undisturbed forest all characteristics were normalized by their values for the latter. The results of the study show that the magnitude of wind load on trees surrounding the newly created forest gaps increases with gap size and is app. 7 times higher than the load on trees in an undisturbed forest. The gust component of wind load reaches its maximum at app. 20 tree heights, h, and remains almost constant for larger gaps, while the static load and radiation characteristics continue to change significantly with gap size. The study has also demonstrated that the spatial distribution of wind load and of short-wave radiation depends strongly on the gap size and on mutual distribution of gaps within the modelled domain. 1) Leckebusch, G. C., U. Ulbrich, L. Fröhlich, and J. G. Pinto (2007), Property loss potentials for European midlatitude storms in a changing climate, Geophys. Res. Lett., 34, L05703, doi:10.1029/2006GL027663; 2) Sogachev, A., and O. Panferov, 2006, Modification of two-equation models to account for plant drag, Boundary-Layer Meteorology 121:229–266; 3)Vygodskaya N.N., Groisman P.Ya., Tchebakova N.M., Kurbatova J.A., Panfyorov O., Parfenova E.I., Sogachev A.F., 2007, Ecosystems and climate interactions in the boreal zone of Northern Eurasia, Environ. Res. Lett. 2, 045033 (7pp) doi:10.1088/1748-9326/2/4/045033
GC41A-0700
The Future of Eurasian Boreal Forests: Ecological Modeling Projections in the Russian Federation
Ecological modeling is one of the primary methodologies for making predictions on future changes in forested ecosystems such as those occurring in Northern Eurasia and Siberia. In particular, combining ecological modeling with global circulation model simulation outputs is a method in which scientists can forecast the impact of climate change on biodiversity (Thuiller, 2007) as well as the forested landscape. Dynamic global vegetation models (DGVMs) have been designed for specifically this purpose, however, these vegetation models run at large spatial scales and as a result make predictions that are highly uncertain (Purves and Pacala, 2008). In previous papers, we discussed the FAREAST forest gap model and its ability to accurately predict boreal forest dynamics at smaller scales and higher resolution than DGVMs. This presentation investigates the use of the FAREAST gap model, modified for spatial expansion to cover the entire country of Russia, to predict future land cover trends under different warming scenarios. The poster provides the initial framework for the project, as well as some initial results. The collection of input variables needed by FAREAST to model the Russian continent will involve collaboration with the Russian Academy of Sciences (CEPF). Together we have developed a framework in which to amalgamate both original (temperature, precipitation, soil values) parameters as well as new parameters (fire probability, logging probability) into a GIS database that can be integrated with the FAREAST model. This framework will be capable of providing visual and graphical output for interpretation of large model runs. In order to ensure accuracy in FAREAST's ability to simulate the current environment, a run of the model under current-day conditions will be compared to recent remote sensing land cover maps. The GLC2000 land cover classification project (EU JRC) will be the primary validation method with additional validation through other biophysical variables extracted by remote sensing such as biomass and LAI. These steps will ensure that the model's predictions of forests under future climate will be acceptable. The updated and expanded version of FAREAST will be run for several future climate scenarios using projections from the PCMDI. Comparison between future and present FAREAST runs of the Russian federation will provide information regarding potential changes of the region's forests and land cover. Implications for biodiversity and climate interactions from these results will be analyzed, as well as socio-economic impacts for regional and local economies.
GC41A-0701
Towards a new High Resolution Orthophoto Mosaic Circa 1976 for the Northern Eurasia: Assessing the Potential of Declassified Hexagon KH-9 Images (Tien Shan Region, Central Asia Case Study)
Repeated satellite-based inventories of land-cover and land-use, such as Global Landsat Orthorectified data collection (28.5-57 m resolution), are crucial for understanding dynamics of terrestrial ecosystems. However, accurate estimation of dynamics of certain natural and man-made phenomena (mountain glaciers, lakes, urban and agricultural areas) often requires higher resolution remote sensed datasets (with resolution below 10-20 m). In the Northern Eurasia, such datasets are often too expensive or unavailable for a regional study (for example SPOT, TK-350, aerial photography) or span only the last decade (for example Landsat ETM, ASTER, IRS, ALOS/PRISM). This study estimates accuracy and potential of historical Hexagon KH-9 images for generation of a high resolution orthorectified product circa 1976 on a regional scale. The Hexagon KH-9 images were declassified by the U.S. Government in 2002. Although the KH-9 dataset coverage is global, it is particularly rich over the Northern Eurasia where multiple repeat images were acquired for the U.S. Defense Mapping Agency. Using a set of KH-9 images we generated a high quality orthorectified mosaic for the area of Tien Shan mountain system (about 550,000 km2) with resolution of 6-9 m and horizontal accuracy about 9 m. The panchromatic orthophoto mosaic is a unique dataset that for the first time portrays the remote region with such detail and, at the same time, extends the retrospective for more than three decades. The mosaic enabled creation of a glacier inventory for the Tien Shan mountains circa 1976. The Tien Shan case study demonstrated that Hexagon KH-9 images can be used for generation of a land-cover/land-use inventory circa 1976 on regional scales and with high spatial resolution.
GC41A-0702
Asian Ice Core Array (AICA): Climate and Environmental Reconstruction of Asia
The large landmass and relief of the Asian continent has a substantial influence on global atmospheric circulation and the regional climate that supports ~2.5 billion people. Recent changes in climate and environmental conditions may lead to desertification and affect water resources, possibly resulting in serious consequences on humans and ecosystems. To put recent changes into context, it is first necessary to have an understanding of past climate and environmental variability. However, instrumental records of climate and environmental variability over the region are sparse and temporally limited. Fortunately, ice cores from high elevation mountain glaciers in Asia can be used to reconstruct atmospheric chemistry and past climate variability spanning seasonal to millennial time scales. The goal of the Asian Ice Core Array (AICA) is to enhance the spatial and temporal understanding of physical and chemical climate variability, establish a baseline for assessing modern climate variability in the context of human activity, and contribute to the prediction of climate variability in Asia. Highly resolved ice core reconstructions of past climate (e.g. atmospheric circulation, temperature, precipitation, and atmospheric chemistry) will utilize continuous, co-registered, and multi-parameter measurements of major ions, trace elements, and stable isotopes (along with selected sections for radionuclide analysis). AICA sites include cores from the Himalayas, Pamir, Tien Shan, Altai, and the Tibetan Plateau. An overview of the AICA project will be presented, in addition to some early results of AICA including reconstructions of the behavior of the summer South Asian monsoon over the Himalayas and the identification of a potential teleconnection between the central Tibetan Plateau and the Pacific Decadal Oscillation (PDO).