Improving Earth System Models: What Can Be Learned from the Arctic-Boreal Region? As Part of the Arctic-Boreal Vulnerability Experiment
No abstract provided
Braghiere, Renato↗
SEARCH · Search NASA
Results for “BOREAL REGIONS”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
[Sources of Methane in the Boreal Region]
In determining the global methane budget the sources of methane must be balanced with the sinks and atmospheric inventory. The approximate contribution of the different methane sources to the budget has been establish showing the major terrestrial inputs as rice, wetlands, bogs, fens, and tundra. Measurements and modeling of production in these sources suggest that temperature, water table height and saturation along with substratum composition are important in controlling methane production and emission. The isotopic budget of 13 C and D/H in methane can be used as a tool to clarify the global budget. This approach has achieved success at constraining the inputs. Studies using the isotopic approach place constraints on global methane production from different sources. Also, the relation between the two biogenic production pathways, acetate fermentation and CO2 reduction, and the effect of substratum composition can be made using isotope measurements shows the relation between the different biogenic, thermogenic and anthropogenic sources of methane as a function of the carbon and hydrogen isotope values for each source and the atmosphere, tropospheric composition. Methane emissions from ponds and fens are a significant source in the methane budget of the boreal region. An initial study in 1993 and 1994 on the isotopic composition of this methane source and the isotopic composition in relation to oxidation of methane at the sediment surface of the ponds or fen was conducted as part of our BOREAS project. The isotopic composition of methane emitted by saturated anoxic sediment is dependent on the sediment composition and geochemistry, but will be influenced by in situ oxidation, in part, a function of rooted plant activity. The influence of oxidation mediated by rooted plant activities on the isotopic composition of methane is not well known and will depend on the plant type, sediment temperature, and numerous other variables. Information on this isotopic composition is important in both understanding the bio-geochemistry of the system and also in determining the regional and global inputs for the methane isotope budget. In determining the destruction of methane for balancing the atmospheric methane budget soil oxidation must be considered.
Source record↗
Classification of Radar Imagery over Boreal Regions for Methane Exchange Studies
NASA/JPL AIRSAR data were acquired over Minto Flats, Alaska on 18 July 1993. These data.
Boreal Regions↗
Air temperature and precipitation constraining the modelled wetland methane emissions in a boreal region in northern Europe
Wetland methane responses to temperature and precipitation are studied in a boreal wetland-rich region in northern Europe using ecosystem process models. Six ecosystem models (JSBACH-HIMMELI, LPX-Bern, LPJ-GUESS, JULES, CLM4.5, and CLM5) are compared to multi-model means of ecosystem models and atmospheric inversions from the Global Carbon Project and upscaled eddy covariance flux results for their temperature and precipitation responses and seasonal cycles of the regional fluxes. Two models with contrasting response patterns, LPX-Bern and JSBACH-HIMMELI, are used as priors in atmospheric inversions with Carbon Tracker Europe–CH4 (CTE-CH4) in order to find out how the assimilation of atmospheric concentration data changes the flux estimates and how this alters the interpretation of the flux responses to temperature and precipitation. Inversion moves wetland emissions of both models towards co-limitation by temperature and precipitation. Between 2000 and 2018, periods of high temperature and/or high precipitation often resulted in increased emissions. However, the dry summer of 2018 did not result in increased emissions despite the high temperatures. The process models show strong temperature and strong precipitation responses for the region (51 %–91 % of the variance explained by both). The month with the highest emissions varies from May to September among the models. However, multi-model means, inversions, and upscaled eddy covariance flux observations agree on the month of maximum emissions and are co-limited by temperature and precipitation. The setup of different emission components (peatland emissions, mineral land fluxes) has an important role in building up the response patterns. Considering the significant differences among the models, it is essential to pay more attention to the regional representation of wet and dry mineral soils and periodic flooding which contribute to the seasonality and magnitude of methane fluxes. The realistic representation of temperature dependence of the peat soil fluxes is also important. Furthermore, it is important to use process-based descriptions for both mineral and peat soil fluxes to simulate the flux responses to climate drivers.
54 ENVIRONMENTAL SCIENCES↗
Using Support Vector Machines to Automatically Extract Open Water Signatures from POLDER Multi-Angle Data Over Boreal Regions
This study used Support Vector Machines to classify multiangle POLDER data. Boreal wetland ecosystems cover an estimated 90 x 10(exp 6) ha, about 36% of global wetlands, and are a major source of trace gases emissions to the atmosphere. Four to 20 percent of the global emission of methane to the atmosphere comes from wetlands north of 4 degrees N latitude. Large uncertainties in emissions exist because of large spatial and temporal variation in the production and consumption of methane. Accurate knowledge of the areal extent of open water and inundated vegetation is critical to estimating magnitudes of trace gas emissions. Improvements in land cover mapping have been sought using physical-modeling approaches, neural networks, and active microwave, examples that demonstrate the difficulties of separating open water, inundated vegetation and dry upland vegetation. Here we examine the feasibility of using a support vector machine to classify POLDER data representing open water, inundated vegetation and dry upland vegetation.
Pierce, J.↗
Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region
Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.
land data assimilation↗
Optical Properties of Boreal Region Biomass Burning Aerosols in Central Alaska and Seasonal Variation of Aerosol Optical Depth at an Arctic Coastal Site
Long-term monitoring of aerosol optical properties at a boreal forest AERONET site in interior Alaska was performed from 1994 through 2008 (excluding winter). Large interannual variability was observed, with some years showing near background aerosol optical depth (AOD) levels (<0.1 at 500 nm) while 2004 and 2005 had August monthly means similar in magnitude to peak months at major tropical biomass burning regions. Single scattering albedo (omega (sub 0); 440 nm) at the boreal forest site ranged from approximately 0.91 to 0.99 with an average of approximately 0.96 for observations in 2004 and 2005. This suggests a significant amount of smoldering combustion of woody fuels and peat/soil layers that would result in relatively low black carbon mass fractions for smoke particles. The fine mode particle volume median radius during the heavy burning years was quite large, averaging approximately 0.17 micron at AOD(440 nm) = 0.1 and increasing to approximately 0.25 micron at AOD(440 nm) = 3.0. This large particle size for biomass burning aerosols results in a greater relative scattering component of extinction and, therefore, also contributes to higher omega (sub 0). Additionally, monitoring at an Arctic Ocean coastal site (Barrow, Alaska) suggested transport of smoke to the Arctic in summer resulting in individual events with much higher AOD than that occurring during typical spring Arctic haze. However, the springtime mean AOD(500 nm) is higher during late March through late May (approximately 0.150) than during summer months (approximately 0.085) at Barrow partly due to very few days with low background AOD levels in spring compared with many days with clean background conditions in summer.
Eck, T. F.↗
Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region
Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic-boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8-day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. Here, to further reduce the remaining bias in GPP after LAI bias correction, we re-parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.
58 GEOSCIENCES↗
Uncertain Spatial Pattern of Future Land Use and Land Cover Change and Its Impacts on Terrestrial Carbon Cycle Over the Arctic–Boreal Region of North America
Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on terrestrial ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regional LULCC projections by integrated assessment models, such as the Global Change Analysis Model (GCAM). The uncertainty associated with the different spatial downscaling methods and its impacts on the subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on their impacts on the carbon cycle over the Arctic-Boreal Vulnerability Experiment (ABoVE) domain, where extensive LULCC is expected. Specifically, we used the Future Land Use Simulation model (FLUS) and the Demeter model to generate 0.25° gridded LULCC data (i.e., LULCC FLUS and LULCC Demeter , respectively) with the same input of regional LULCC projections from GCAM, under both the low (i.e., SSP126) and high (i.e., SSP585) greenhouse gas emission scenarios. The two sets of downscaled LULCC were used to drive the Community Land Model version 5 and prognostically simulate the terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between LULCC FLUS and LULCC Demeter , and the spatial distributions of the needleleaf evergreen boreal tree, broadleaf deciduous boreal tree, broadleaf deciduous boreal shrub, and C3 arctic grass are particularly different under both SSP126 and SSP585. Additionally, the spatiotemporal differences are larger under SSP126 than SSP585, due to more intensive LULCC under SSP126 than SSP585 from GCAM projection. The differences in LULCC further lead to large discrepancies in the spatial patterns of projected gross primary productivity, ecosystem respiration, and net ecosystem exchange, which represent more than 79% of the contributions of future LULCC in 2100. Additionally, the difference in carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by the spatial downscaling process in future LULCC projections and carbon cycle simulations.
54 ENVIRONMENTAL SCIENCES↗
Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region
During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.
Poe, Jeralyn [Northern Arizona University, Flagsta↗
The Interplay between Canopy Structure and Topography and Its Impacts on Seasonal Variations in Surface Reflectance Patterns in the Boreal Region of Alaska—Implications for Surface Radiation Budget
Explore the source record for details and available documents.
Bibhash Nath↗
Underestimation of the impact of land cover change on the biophysical environment of the Arctic and boreal region of North America
Explore the source record for details and available documents.
Hamid Dashti↗
Simulating future climate change impacts on snow- and ice-related driving hazards in Arctic-boreal regions
Explore the source record for details and available documents.
Heather E Greaves↗
Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) Science Implementation Plan
Boreal regions have experienced warming faster than the rest of the Earth, and the arctic ice cover has declined at a rate faster than predicted by most climate models. Uncertainties in climate projections for this region are large, in part due to the lack of observational guidance to constrain the treatment of aerosol-cloud-precipitation linkages in climate models. To remedy this shortfall, field campaigns have been conducted to collect integrated, comprehensive measurements under specific atmospheric regimes. While considerable efforts have been devoted to subtropical marine boundary-layer clouds, as well as to clouds in the stable arctic environment, very few targeted observations exist of convective boundary-layer clouds that form over open water when cold airmasses are advected off ice-covered regions or boreal continents. There is an urgent need to shed light on the dynamics and microphysical properties of clouds and precipitation in the high-latitude marine boundary layer during cold-air outbreaks. Despite the common occurrence of linear and cellular cloud patterns that typify cold-air outbreaks, little is known about the properties of these clouds; how they vary with surface, environmental, and aerosol conditions; the role of cold-air outbreaks in the global atmospheric and ocean circulation; and the accuracy of the treatment of this atmospheric regime in climate models. Thus, we proposed to conduct the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE), to focus on marine boundary-layer clouds during cold-air outbreaks. COMBLE will deploy the first ARM Mobile Facility (AMF1) and an AMF “satellite” station in the far North Atlantic in January–May 2020. COMBLE will take advantage of the synergy with several coincident campaigns, notably MOSAIC, which will characterize the source airmasses of cold-air outbreaks over the arctic ice, and (AC) 3 , which will operate several aircraft between northern Scandinavia and the MOSAIC deployment to document evolution of these airmasses. COMBLE and its sister campaigns will compose a four-member array of supersites between northern Scandinavia and the Arctic, each with profiling and in situ cloud, precipitation, radiation, and aerosol measurements. COMBLE will be guided by six science themes. The first five deal with boundary-layer convection in cold-air outbreaks: (1) the fetch-dependent mesoscale organization of clouds and precipitation, including linear and cellular convection; (2) surface heat and momentum fluxes and vertical profiles of temperature, humidity, wind, and turbulence; (3) vertical structure of clouds and precipitation; (4) the sources and sinks of aerosol, including ice-nucleating particles, and the role of cloud-active aerosol on cloud processes and radiative fluxes; and (5) the influence of these four themes on polar cyclogenesis and polar low vertical structure. The overarching sixth theme is that COMBLE will provide integrated data sets of dynamical, thermodynamic, and cloud microphysical characteristics of marine boundary-layer convection in cold-air outbreaks, including cloud and aerosol properties, that will enable constraining high-resolution numerical simulations, developing process-level understanding, and, subsequently, evaluating and improving representations of shallow convection in weather and climate models.
54 ENVIRONMENTAL SCIENCES↗
Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
Abstract The regional variability in tundra and boreal carbon dioxide (CO 2 ) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO 2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO 2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO 2 fluxes and test the accuracy and uncertainty of different statistical models. CO 2 fluxes were upscaled at relatively high spatial resolution (1 km 2 ) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO 2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr −1 , respectively) compared to tundra (average annual NEE +10 and −2 g C m −2 yr −1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO 2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO 2 sink during 1990–2015, although uncertainty remains high.
Virkkala, Anna‐Maria↗
Forest and land inventory using ERTS imagery and aerial photography in the boreal forest region of Alberta, Canada
Satellite imagery and small-scale (1:120,000) infrared ektachrome aerial photography for the development of improved forest and land inventory techniques in the boreal forest region are presented to demonstrate spectral signatures and their application. The forest is predominately mixed, stands of white spruce and poplar, with some pure stands of black spruce, pine and large areas of poorly drained land with peat and sedge type muskegs. This work is part of coordinated program to evaluate ERTS imagery by the Canadian Forestry Service.
Kirby, C. L.↗
Vegetation Heights for Landsat Land Cover Classes in the Interior Boreal Forest Region of Alaska
Accurate determination and mapping of vegetation height is a prerequisite for regional estimations of above ground biomass, carbon pool dynamics, and improved modeling of future climate-vegetation-soil interactions. This study combined land cover class maps (at 30-m pixel resolution) derived from Landsat image bands with canopy vegetation heights detected at 1-m resolution from NASA G-LiHT Lidar flights, both from the year 2014 for the Middle Tanana Valley near Fairbanks, Alaska. The statistical distributions and structural attributes from Lidar plant heights were derived and refined for all Landsat vegetation classes. Results showed that the tallest cover classes in this region were deciduous forests (dominated by birch and aspen), followed by evergreen spruce and wooded wetlands. Open shrubland and herbaceous cover areas were determined to be 2 - 5 m shorter, on average, than these boreal forest stands. Tall shrubland cover areas were slightly shorter than most spruce-dominated evergreen forest areas. Nearly 60% of all low shrubland and herbaceous wetland pixels were detected with at least one tree crown greater than 10 m tall. This was in contrast to evergreen and deciduous forest classes that showed 88% of stands with at least one tree crown greater than 10 m tall.
Vegetation↗
Intensive aerosol properties of boreal and regional biomass burning aerosol at Mt. Bachelor Observatory: larger and black carbon (BC)-dominant particles transported from Siberian wildfires
We characterize the aerosol physical and optical properties of 13 transported biomass burning (BB) events. BB events included long-range influence from fires in Alaskan and Siberian boreal forests transported to Mt. Bachelor Observatory (MBO) in the free troposphere (FT) over 8–14+ d and regional wildfires in northern California and southwestern Oregon transported to MBO in the boundary layer (BL) over 10 h to 3 d. Intensive aerosol optical properties and normalized enhancement ratios for BB events were derived from measured aerosol light scattering coefficients (σ scat ), aerosol light-absorbing coefficients (σ abs ), fine particulate matter (PM 1 ), and carbon monoxide (CO) measurements made from July to September 2019, with particle size distribution collected from August to September. The observations showed that the Siberian BB events had a lower scattering Ångström exponent (SAE), a higher mass scattering efficiency (MSE; Δσ scat /ΔPM 1 ), and a bimodal aerosol size distribution with a higher geometric mean diameter (D g ). We hypothesize that the larger particles and associated scattering properties were due to the transport of fine dust alongside smoke in addition to contributions from condensation of secondary aerosol, coagulation of smaller particles, and aqueous-phase processing during transport. Alaskan and Siberian boreal forest BB plumes were transported long distances in the FT and characterized by lower absorption Ångström exponent (AAE) values indicative of black carbon (BC) dominance in the radiative budget. Significantly elevated AAE values were only observed for BB events with <1 d transport, which suggests strong production of brown carbon (BrC) in these plumes but limited radiative forcing impacts outside of the immediate region.
54 ENVIRONMENTAL SCIENCES↗