Biosphere Atmosphere Research Articles

A test of an optimal stomatal conductance scheme within the CABLE land surface model

Abstract. Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We constrained the key model parameter "g1", which represents plant water use strategy, by PFT, based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960–1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal model, in conjunction with PFT parameterisations, resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance against upscaled data products was not degraded, but did not noticeably reduce existing model–data biases. We identified assumptions relating to the coupling of the vegetation to the atmosphere and the parameterisation of the minimum stomatal conductance as areas requiring further investigation in both CABLE and potentially other LSMs. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.

Influence of air mass origin on aerosol properties at a remote Michigan forest site

The northern Great Lakes region of North America is a large, relatively pristine area. To date, there has only been limited study of the atmospheric aerosol in this region. During summer 2009, a detailed characterization of the atmospheric aerosol was conducted at the University of Michigan Biological Station (UMBS) as part of the Community Atmosphere–Biosphere Interactions Experiment (CABINEX). Measurements included particle size distribution, water-soluble composition, and CCN activity. Aerosol properties were strongly dependent on the origin of the air masses reaching the site. For ∼60% of the study period, air was transported from sparsely populated regions to the northwest. During these times aerosol loadings were low, with mean number and volume concentrations of 1630 cm−3 and 1.91 μm3 cm−3, respectively. The aerosol during clean periods was dominated by organics, and exhibited low hygroscopicities (mean κ = 0.18 at s = 0.3%). When air was from more populated regions to the east and south (∼29% of the time), aerosol properties reflected a stronger anthropogenic influence, with 85% greater particle number concentrations, 2.5 times greater aerosol volume, six times more sulfate mass, and increased hygroscopicity (mean к = 0.24 at s = 0.3%). These trends are have the potential to influence forest–atmosphere interactions and should be targeted for future study.

Potential combined hydrologic impacts of climate change and El Niño Southern Oscillation to South Saskatchewan River Basin

A physically based land surface scheme, the Modified Interaction Soil Biosphere Atmosphere (MISBA) of Kerkhoven and Gan (2006) was used to assess the future streamflow of the South Saskatchewan River Basin (SSRB) of Alberta under the combined impacts of climate change and El Niño Southern Oscillation (ENSO). Potential impacts of climate change on the streamflows of 15 sub-basins of the SSRB for the 2010–2039 (2020s), 2040–2069 (2050s) and 2070–2099 (2080s) were simulated by MISBA based on 30 years (1961–1990) of re-analysis data of the European Centre for Mid-range Weather Forecasts (ERA-40) adjusted with climate scenarios projected by four General Circulation Models (GCMs) for three Special Report on Emissions Scenarios (SRES) emissions (A1FI, A21, B21) of Intergovernmental Panel on Climate Change (IPCC). Next, the combined impacts of climate change and ENSO are simulated by driving MISBA with the ERA-40 dataset re-sampled for active El Niño and La Niña episodes adjusted for climate projections of 2050s. Under SRES climate projections alone, MISBA simulated an overall decrease in streamflow for sub-basins of SSRB in 2020s, 2050s, and 2080s. While under a combined impact of climate change and ENSO, a further decrease (increase) in the streamflow of SSRB by 2050s was simulated if the climate anomaly considered was El Niño (La Niña).

Contribution of surface roughness to simulations of historical deforestation

Surface roughness which partitions surface net radiation into energy fluxes is a key parameter for estimation of biosphere–atmosphere interactions and climate variability. An earth system model of intermediate complexity (EMIC), MPM-2, is used to derive the impact of surface roughness on climate from simulations of historical land cover change effects. The direct change in surface roughness leads to a global surface warming of 0.08°C through altering the turbulence in the boundary layer. The regional temperature response to surface roughness associated deforestation is very strong at northern mid-latitudes with a most prominent warming of 0.72°C around 50°N in the Eurasia continent during summer. They can be explained mainly as direct and indirect consequences of decreases in surface albedo and increases in precipitation in response to deforestation, although there are a few significant changes in precipitation. There is also a prominent warming of 0.25°C around 40°N in the North American continent. This study indicates that land surface roughness plays a significant role which is comparable with the whole land conversion effect in climate change. Therefore, further investigation of roughness–climate relationship is needed to incorporate these aspects.

Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

Abstract. While a majority of global climate models project drier and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC (Interaction Soil–Biosphere–Atmosphere Carbon Cycle) land surface model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent throughfall exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different water stress functions (WSFs) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentrations, the increased water-use efficiency (WUE) mitigates the sensitivity of ISBACC to drought. While one of the proposed WSF formulations improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

Biogeochemistry: agriculture and the global carbon cycle.

Evolving agricultural practices dramatically increased crop production in the twentieth century. Two studies now find that this has altered the seasonal flux of atmospheric carbon dioxide. See Letters p.394 & p.398 The atmospheric CO2 record displays a seasonal cycle reflecting seasonal variations in CO2 uptake by terrestrial vegetation. An increase in the amplitude of this seasonal cycle over the past five decades cannot be fully explained at present. Two groups now report that the intensification of agriculture may have been a key contributor to the increase in atmospheric CO2 seasonal amplitude. Ning Zeng et al. used the VEGAS terrestrial biosphere model to show that enhanced mid-latitude agricultural productivity contributed 45% of the increasing amplitude of global net surface carbon fluxes for the period 1961 to 2010, compared to 29% from climate change and 26% from CO2 fertilization. Josh Gray et al. used crop production statistics from the UN Food and Agriculture Organization and a carbon accounting model to demonstrate that as much as a quarter of the observed change in atmospheric CO2 seasonality can be explained by elevated crop productivity, with maize, wheat, rice and soybean major contributors. These studies will contribute to a better understanding of the global carbon cycle, and highlight the extent to which human actions are changing large-scale biosphere–atmosphere interactions.

Water-saving ground cover rice production system reduces net greenhouse gas fluxes in an annual rice-based cropping system

Abstract. To safeguard food security and preserve precious water resources, the technology of water-saving ground cover rice production system (GCRPS) is being increasingly adopted for rice cultivation. However, changes in soil water status and temperature under GCRPS may affect soil biogeochemical processes that control the biosphere–atmosphere exchanges of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2). The overall goal of this study is to better understand how net ecosystem greenhouse gas exchanges (NEGE) and grain yields are affected by GCRPS in an annual rice-based cropping system. Our evaluation was based on measurements of the CH4 and N2O fluxes and soil heterotrophic respiration (CO2 emissions) over a complete year, and the estimated soil carbon sequestration intensity for six different fertilizer treatments for conventional paddy and GCRPS. The fertilizer treatments included urea application and no N fertilization for both conventional paddy (CUN and CNN) and GCRPS (GUN and GNN), and solely chicken manure (GCM) and combined urea and chicken manure applications (GUM) for GCRPS. Averaging across all the fertilizer treatments, GCRPS increased annual N2O emission and grain yield by 40 and 9%, respectively, and decreased annual CH4 emission by 69%, while GCRPS did not affect soil CO2 emissions relative to the conventional paddy. The annual direct emission factors of N2O were 4.01, 0.09 and 0.50% for GUN, GCM and GUM, respectively, and 1.52% for the conventional paddy (CUN). The annual soil carbon sequestration intensity under GCRPS was estimated to be an average of −1.33 Mg C ha−1 yr−1, which is approximately 44% higher than the conventional paddy. The annual NEGE were 10.80–11.02 Mg CO2-eq ha−1 yr−1 for the conventional paddy and 3.05–9.37 Mg CO2-eq ha−1 yr−1 for the GCRPS, suggesting the potential feasibility of GCRPS in reducing net greenhouse effects from rice cultivation. Using organic fertilizers for GCRPS considerably reduced annual emissions of CH4 and N2O and increased soil carbon sequestration, resulting in the lowest NEGE (3.05–5.00 Mg CO2-eq ha−1 yr−1). Accordingly, water-saving GCRPS with organic fertilizer amendments was considered the most promising management regime for simultaneously achieving relatively high grain yield and reduced net greenhouse gas emission.

Impact of interactive vegetation phenology on the Canadian RCM simulated climate over North America

Biosphere–atmosphere interactions play a very important role in modulating regional climate. To capture these bi-directional interactions, a dynamic vegetation model, the Canadian Terrestrial Ecosystem Model (CTEM), has been implemented in the fifth generation of the Canadian Regional Climate Model (CRCM5). CTEM can grow vegetation from bare ground and includes processes of photosynthesis, autotrophic and heterotrophic respiration, phenology, turnover, mortality and allocation. This study focuses on assessing the impact of interactive vegetation phenology, i.e. CTEM, on the CRCM5 simulated climate over North America. This is achieved by comparing two CRCM5 simulations—one with interactive phenology and the other with prescribed vegetation, driven by ECMWF reanalysis data (ERA40 and ERA-Interim) at the lateral boundaries, for the 1971–2010 period. Comparison of simulated vegetation attributes, temperature and precipitation in both simulations to those observed indicates that introduction of interactive phenology improves the performance of CRCM5 in some regions, although it introduces new biases in other regions, which are related to the underestimation of leaf area index (LAI). Interactive phenology enhances biosphere–atmosphere interactions, which are reflected in the higher values of correlation between atmosphere and biosphere variables. Interactive phenology also introduces long-term memory in CRCM5, estimated via lagged correlations between precipitation/temperature and LAI. Improved biosphere–atmosphere interactions and long-term memory in the CRCM5 simulation with interactive phenology leads to better interannual variability, particularly noticeable in the biosphere and atmosphere states during anomalously wet and dry years. This study thus provides useful insights related to the added value of interactive phenology in CRCM5 as well as the nature and variability of biosphere–atmosphere interactions over North America.

Online appendix 2:Soil water retention curves for the major soil types of the Kruger National Park

Soil water potential is crucial to plant transpiration and thus to carbon cycling and biosphere–atmosphere interactions, yet it is difficult to measure in the field. Volumetric and gravimetric water contents are easy and cheap to measure in the field, but can be a poor proxy of plant-available water. Soil water content can be transformed to water potential using soil moisture retention curves. We provide empirically derived soil moisture retention curves for seven soil types in the Kruger National Park, South Africa. Site-specific curves produced excellent estimates of soil water potential from soil water content values. Curves from soils derived from the same geological substrate were similar, potentially allowing for the use of one curve for basalt soils and another for granite soils. It is anticipated that this dataset will help hydrologists and ecophysiologists understand water dynamics, carbon cycling and biosphere–atmosphere interactions under current and changing climatic conditions in the region.

Online appendix 1: Soil water retention curves for the major soil types of the Kruger National Park

Soil water potential is crucial to plant transpiration and thus to carbon cycling and biosphere–atmosphere interactions, yet it is difficult to measure in the field. Volumetric and gravimetric water contents are easy and cheap to measure in the field, but can be a poor proxy of plant-available water. Soil water content can be transformed to water potential using soil moisture retention curves. We provide empirically derived soil moisture retention curves for seven soil types in the Kruger National Park, South Africa. Site-specific curves produced excellent estimates of soil water potential from soil water content values. Curves from soils derived from the same geological substrate were similar, potentially allowing for the use of one curve for basalt soils and another for granite soils. It is anticipated that this dataset will help hydrologists and ecophysiologists understand water dynamics, carbon cycling and biosphere–atmosphere interactions under current and changing climatic conditions in the region.

Soil water retention curves for the major soil types of the Kruger National Park

Soil water potential is crucial to plant transpiration and thus to carbon cycling and biosphere–atmosphere interactions, yet it is difficult to measure in the field. Volumetric and gravimetric water contents are easy and cheap to measure in the field, but can be a poor proxy of plant-available water. Soil water content can be transformed to water potential using soil moisture retention curves. We provide empirically derived soil moisture retention curves for seven soil types in the Kruger National Park, South Africa. Site-specific curves produced excellent estimates of soil water potential from soil water content values. Curves from soils derived from the same geological substrate were similar, potentially allowing for the use of one curve for basalt soils and another for granite soils. It is anticipated that this dataset will help hydrologists and ecophysiologists understand water dynamics, carbon cycling and biosphere–atmosphere interactions under current and changing climatic conditions in the region.

Global carbon assimilation system using a local ensemble Kalman filter with multiple ecosystem models

AbstractIn this paper, a global carbon assimilation system (GCAS) is developed for optimizing the global land surface carbon flux at 1° resolution using multiple ecosystem models. In GCAS, three ecosystem models, Boreal Ecosystem Productivity Simulator, Carnegie‐Ames‐Stanford Approach, and Community Atmosphere Biosphere Land Exchange, produce the prior fluxes, and an atmospheric transport model, Model for OZone And Related chemical Tracers, is used to calculate atmospheric CO2 concentrations resulting from these prior fluxes. A local ensemble Kalman filter is developed to assimilate atmospheric CO2 data observed at 92 stations to optimize the carbon flux for six land regions, and the Bayesian model averaging method is implemented in GCAS to calculate the weighted average of the optimized fluxes based on individual ecosystem models. The weights for the models are found according to the closeness of their forecasted CO2 concentration to observation. Results of this study show that the model weights vary in time and space, allowing for an optimum utilization of different strengths of different ecosystem models. It is also demonstrated that spatial localization is an effective technique to avoid spurious optimization results for regions that are not well constrained by the atmospheric data. Based on the multimodel optimized flux from GCAS, we found that the average global terrestrial carbon sink over the 2002–2008 period is 2.97 ± 1.1 PgC yr−1, and the sinks are 0.88 ± 0.52, 0.27 ± 0.33, 0.67 ± 0.39, 0.90 ± 0.68, 0.21 ± 0.31, and 0.04 ± 0.08 PgC yr−1 for the North America, South America, Africa, Eurasia, Tropical Asia, and Australia, respectively. This multimodel GCAS can be used to improve global carbon cycle estimation.

Introduction of groundwater capillary rises using subgrid spatial variability of topography into the ISBA land surface model

AbstractThis paper presents a simple method for representing upward capillary fluxes from shallow groundwater into the unsaturated soil column of the large‐scale hydrological models generally used at low resolution in global climate models. The groundwater scheme implemented in the Total Runoff Integrating Pathways river‐routing model in a previous study is coupled with the Interaction between Soil Biosphere Atmosphere (ISBA) land surface model. In this coupling, the simulated water table depth acts as the lower boundary condition for the soil moisture diffusive equation. An original parameterization accounting for the subgrid topography inside each grid cell is proposed in order to compute this fully coupled soil lower boundary condition. The impact of this coupling on the simulated water budget is evaluated over France for the 1989–2009 period. Simulations are performed at high (1/12°) and low (0.5°) resolutions. Upward capillary fluxes induce a decrease in the simulated recharge from ISBA to the aquifers and contributes to an enhancement of the soil moisture memory. The simulated water table depths are then lowered, which induces a slight decrease in the simulated mean annual river discharges. These differences do not affect the comparison with observations. As a consequence, the simulated river discharges and water table heads compare still well with observations for the two soil bottom condition (free drain or fully coupled). It confirms the suitability of the coupling parameterization using subgrid spatial variability of topography. Compared to a free drain experiment, upward capillary fluxes at the bottom of the soil increase the mean annual evapotranspiration simulated over the aquifer domain by 3.12% and 1.54% at high and low resolutions, respectively. This increase can locally reach 50% and 30%, respectively.

Intercomparison of the JULES and CABLE land surface models through assimilation of remotely sensed soil moisture in southeast Australia

Numerous land surface models exist for predicting water and energy fluxes in the terrestrial environment. These land surface models have different conceptualizations (i.e., process or physics based), together with structural differences in representing spatial variability, alternate empirical methods, mathematical formulations and computational approach. These inherent differences in modeling approach, and associated variations in outputs make it difficult to compare and contrast land surface models in a straight-forward manner. While model intercomparison studies have been undertaken in the past, leading to significant progress on the improvement of land surface models, additional framework towards identification of model weakness is needed. Given that land surface models are increasingly being integrated with satellite based estimates to improve their prediction skill, it is practical to undertake model intercomparison on the basis of soil moisture data assimilation. Consequently, this study compares two land surface models: the Joint UK Land Environment Simulator (JULES) and the Community Atmosphere Biosphere Land Exchange (CABLE) for soil moisture estimation and associated assessment of model uncertainty. A retrieved soil moisture data set from the Soil Moisture and Ocean Salinity (SMOS) mission was assimilated into both models, with their updated estimates validated against in-situ soil moisture in the Yanco area, Australia. The findings show that the updated estimates from both models generally provided a more accurate estimate of soil moisture than the open loop estimate based on calibration alone. Moreover, the JULES output was found to provide a slightly better estimate of soil moisture than the CABLE output at both near-surface and deeper soil layers. An assessment of the updated membership in decision space also showed that the JULES model had a relatively stable, less sensitive, and more highly convergent internal dynamics than the CABLE model.

Impact of mountain pine beetle induced mortality on forest carbon and water fluxes

Quantifying impacts of ecological disturbance on ecosystem carbon and water fluxes will improve predictive understanding of biosphere—atmosphere feedbacks. Tree mortality caused by mountain pine bark beetles (Dendroctonus ponderosae) is hypothesized to decrease photosynthesis and water flux to the atmosphere while increasing respiration at a rate proportional to mortality. This work uses data from an eddy-covariance flux tower in a bark beetle infested lodgepole pine (Pinus contorta) forest to test ecosystem responses during the outbreak. Analyses were conducted on components of carbon (C) and water fluxes in response to disturbance and environmental factors (solar radiation, soil water content and vapor pressure deficit). Maximum CO2 uptake did not change as tree basal area mortality increased from 30 to 78% over three years of beetle disturbance. Growing season evapotranspiration varied among years while ecosystem water use efficiency (the ratio of net CO2 uptake to water vapor loss) did not change. Between 2009 and 2011, canopy water conductance increased from 98.6 to 151.7 mmol H2O m−2 s−1. Ecosystem light use efficiency of photosynthesis increased, with quantum yield increasing by 16% during the outbreak as light increased below the mature tree canopy and illuminated remaining vegetation more. Overall net ecosystem productivity was correlated with water flux and hence water availability. Average weekly ecosystem respiration, derived from light response curves and standard Ameriflux protocols for CO2 flux partitioning into respiration and gross ecosystem productivity, did not change as mortality increased. Separate effects of increased respiration and photosynthesis efficiency largely canceled one another out, presumably due to increased diffuse light in the canopy and soil organic matter decomposition resulting in no change in net CO2 exchange. These results agree with an emerging consensus in the literature demonstrating CO2 and H2O dynamics following large scale disturbance events are dependent not only on tree mortality but also on the remaining and new vegetation responses because mortality and recovery occur at the same time.

Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

Abstract. Land surface albedo, the fraction of incoming solar radiation reflected by the land surface, is a key component of the Earth system. This study evaluates snow-free surface albedo simulations by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour L'Observation de la Terre (SPOT) albedo. We compare results from offline simulations over the Australian continent. The control simulation has prescribed background snow-free and vegetation-free soil albedo derived from MODIS whilst the experiments use a simple parameterisation based on soil moisture and colour, originally from the Biosphere Atmosphere Transfer Scheme (BATS), and adopted in the Common Land Model (CLM). The control simulation, with prescribed soil albedo, shows that CABLE simulates overall albedo over Australia reasonably well, with differences compared to MODIS and SPOT albedos within ±0.1. Application of the original BATS scheme, which uses an eight-class soil classification, resulted in large differences of up to −0.25 for the near-infrared (NIR) albedo over large parts of the desert regions of central Australia. The use of a recalibrated 20-class soil colour classification from the CLM, which includes a higher range for saturated and VIS (visible) and NIR soil albedos, reduced the underestimation of the NIR albedo. However, this soil colour mapping is tuned to CLM soil moisture, a quantity which is not necessarily transferrable between land surface models. We therefore recalibrated the soil color map using CABLE's climatological soil moisture, which further reduced the underestimation of the NIR albedo to within ±0.15 over most of the continent as compared to MODIS and SPOT albedos. Small areas of larger differences of up to −0.25 remained within the central arid parts of the continent during summer; however, the spatial extent of these large differences is substantially reduced as compared to the simulation using the default eight-class uncalibrated soil colour map. It is now possible to use CABLE coupled to atmospheric models to investigate soil-moisture–albedo feedbacks, an important enhancement of the model.

Concentrations and fluxes of isoprene and oxygenated VOCs at a French Mediterranean oak forest

Abstract. The CANOPEE project aims to better understand the biosphere–atmosphere exchanges of biogenic volatile organic compounds (BVOCs) in the case of Mediterranean ecosystems and the impact of in-canopy processes on the atmospheric chemical composition above the canopy. Based on an intensive field campaign, the objective of our work was to determine the chemical composition of the air inside a canopy as well as the net fluxes of reactive species between the canopy and the boundary layer. Measurements were carried out during spring 2012 at the field site of the Oak Observatory of the Observatoire de Haute Provence (O3HP) located in the southeast of France. The site is a forest ecosystem dominated by downy oak, Quercus pubescens Willd., a typical Mediterranean species which features large isoprene emission rates. Mixing ratios of isoprene, its degradation products methylvinylketone (MVK) and methacrolein (MACR) and several other oxygenated VOC (OxVOC) were measured above the canopy using an online proton transfer reaction mass spectrometer (PTR-MS), and fluxes were calculated by the disjunct eddy covariance approach. The O3HP site was found to be a very significant source of isoprene emissions, with daily maximum ambient concentrations ranging between 2–16 ppbv inside and 2–5 ppbv just above the top of the forest canopy. Significant isoprene fluxes were observed only during daytime, following diurnal cycles with midday net emission fluxes from the canopy ranging between 2.0 and 9.7 mg m−2 h1. Net isoprene normalized flux (at 30 °C, 1000 μmol quanta m−2 s−1) was estimated at 7.4 mg m−2 h−1. Evidence of direct emission of methanol was also found exhibiting maximum daytime fluxes ranging between 0.2 and 0.6 mg m−2 h−1, whereas flux values for monoterpenes and others OxVOC such as acetone and acetaldehyde were below the detection limit. The MVK+MACR-to-isoprene ratio provided useful information on the oxidation of isoprene, and is in agreement with recent findings proposing weak production yields of MVK and MACR, in remote forest regions where the NOx concentrations are low. In-canopy chemical oxidation of isoprene was found to be weak and did not seem to have a significant impact on isoprene concentrations and fluxes above the canopy.

Assessment of land surface model uncertainty: A crucial step towards the identification of model weaknesses

Summary Assessment of uncertainty in land surface models is complex, mainly because of the numerous sources of error from model parameters, initial states, input forcing data, and the model structure. These sources of uncertainty interact together to impact the simulated output generated from the land surface model. To account for these uncertainties, the goal in diagnostic model evaluation has been to determine the erroneous/inadequate components of the model structure that need improvement. However, the specification of inaccurate model components is not straightforward, requiring crucial steps to determine the uncertainty contributions from individual error sources. Also, the interaction between the uncertainty sources makes it difficult to assess the impact of the individual error sources on the simulated output. The approach undertaken in this study was to quantify the specific uncertainties linked with model parameters, states, input forcing variables, and spatial variations in landscape properties, such that the remaining model uncertainty is equivalent to the inadequacy/inaccuracy associated with the model structure. This study employed the Evolutionary Data Assimilation, together with multi-dimensional clustering, to quantify these individual uncertainties for the Community Atmosphere Biosphere Land Exchange (CABLE) model, in terms of soil moisture estimation for the Yanco area in south-east Australia. The findings showed that the updated soil moisture was more accurate than both the open loop and calibrated estimates. The minimum uncertainty for model components was found to reduce the original and updated bounds by 68% and 62% respectively. The estimated model pathway has accurately reproduced the updated estimates with less than 0.02 m 3 / m 3 error, and was found to be more accurate than both the calibrated and the updated estimates when evaluated against in-situ soil moisture.

Biogeographic variation in evergreen conifer needle longevity and impacts on boreal forest carbon cycle projections.

Leaf life span is an important plant trait associated with interspecific variation in leaf, organismal, and ecosystem processes. We hypothesized that intraspecific variation in gymnosperm needle traits with latitude reflects both selection and acclimation for traits adaptive to the associated temperature and moisture gradient. This hypothesis was supported, because across 127 sites along a 2,160-km gradient in North America individuals of Picea glauca, Picea mariana, Pinus banksiana, and Abies balsamea had longer needle life span and lower tissue nitrogen concentration with decreasing mean annual temperature. Similar patterns were noted for Pinus sylvestris across a north-south gradient in Europe. These differences highlight needle longevity as an adaptive feature important to ecological success of boreal conifers across broad climatic ranges. Additionally, differences in leaf life span directly affect annual foliage turnover rate, which along with needle physiology partially regulates carbon cycling through effects on gross primary production and net canopy carbon export. However, most, if not all, global land surface models parameterize needle longevity of boreal evergreen forests as if it were a constant. We incorporated temperature-dependent needle longevity and %nitrogen, and biomass allocation, into a land surface model, Community Atmosphere Biosphere Land Exchange, to assess their impacts on carbon cycling processes. Incorporating realistic parameterization of these variables improved predictions of canopy leaf area index and gross primary production compared with observations from flux sites. Finally, increasingly low foliage turnover and biomass fraction toward the cold far north indicate that a surprisingly small fraction of new biomass is allocated to foliage under such conditions.

Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case

Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.