ORCID Profile
0000-0002-7346-0927
Current Organisation
CSIRO
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Atmospheric Sciences | Atmospheric Dynamics | Physical Oceanography | Climate Change Processes | Environmental Chemistry (Incl. Atmospheric Chemistry) | Fire Management | Climatology (Incl. Palaeoclimatology) | Meteorology | Cloud Physics
Climate Variability (excl. Social Impacts) | Climate Change Models | Atmospheric composition | Climate change | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Atmospheric Processes and Dynamics |
Publisher: Bureau of Meteorology, Australia
Date: 03-2013
DOI: 10.22499/2.6301.005
Publisher: Springer Science and Business Media LLC
Date: 05-2018
DOI: 10.1038/S41586-018-0130-2
Abstract: Various forms of immunotherapy, such as checkpoint blockade immunotherapy, are proving to be effective at restoring T cell-mediated immune responses that can lead to marked and sustained clinical responses, but only in some patients and cancer types
Publisher: American Geophysical Union (AGU)
Date: 26-05-2007
DOI: 10.1029/2006JD007659
Publisher: Copernicus GmbH
Date: 24-08-2016
Abstract: Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show ergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are sub ided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).
Publisher: Copernicus GmbH
Date: 04-04-2014
Abstract: Abstract. Climate extremes, such as heat waves and heavy precipitation events, have large impacts on ecosystems and societies. Climate models provide useful tools for studying underlying processes and lifying effects associated with extremes. The Australian Community Climate and Earth System Simulator (ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land Exchange (CABLE) model. We examine how this model represents climate extremes derived by the Expert Team on Climate Change Detection and Indices (ETCCDI) and compare them to observational data sets using the AMIP framework. We find that the patterns of extreme indices are generally well represented. Indices based on percentiles are particularly well represented and capture the trends over the last 60 years shown by the observations remarkably well. The diurnal temperature range is underestimated, minimum temperatures (TMIN) during nights are generally too warm and daily maximum temperatures (TMAX) too low in the model. The number of consecutive wet days is overestimated, while consecutive dry days are underestimated. The maximum consecutive 1-day precipitation amount is underestimated on the global scale. Biases in TMIN correlate well with biases in incoming longwave radiation, suggesting a relationship with biases in cloud cover. Biases in TMAX depend on biases in net shortwave radiation as well as evapotranspiration. The regions and season where the bias in evapotranspiration plays a role for the TMAX bias correspond to regions and seasons where soil moisture availability is limited. Our analysis provides the foundation for future experiments that will examine how land-surface processes contribute to these systematic biases in the ACCESS modelling system.
Publisher: Copernicus GmbH
Date: 30-07-2018
DOI: 10.5194/GMD-2018-153
Abstract: Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes against local and global observations in a wide variety of settings, including snow schemes that are included in Earth System Models. The project aims at identifying crucial processes and snow characteristics that need to be improved in snow models in the context of local- and global-scale modeling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. ESM-SnowMIP is tightly linked to the Land Surface, Snow and Soil Moisture Model Intercomparison Project, which in turn is part of the 6th phase of the Coupled Model Intercomparison Project (CMIP6).
Publisher: Copernicus GmbH
Date: 10-05-2016
DOI: 10.5194/GMD-2016-14
Abstract: Abstract. Over the last decade many climate models have evolved into earth system models (ESMs), which are able to simulate both physical and biogeochemical processes through the inclusion of additional components such as the carbon cycle. The Australian Community Climate and Earth System Simulator (ACCESS) has been recently extended to include land and ocean carbon cycle components in its ACCESS-ESM1 version. A detailed description of ACCESS-ESM1 components including results from pre-industrial simulations is provided in Part 1. Here, we focus on the evaluation of ACCESS-ESM1 over the historical period (1850–2005) in terms of its capability to reproduce climate and carbon related variables. Comparisons are performed with observations, if available, but also with other ESMs to highlight common weaknesses. We find that climate variables controlling the exchange of carbon are well reproduced, however ACCESS-ESM1 is somewhat over-sensitive to anthropogenic aerosols which leads to an overly strong cooling response in the land from about 1960 onwards. The land carbon cycle is evaluated for two scenarios: running with a prescribed leaf area index (LAI) and running with a prognostic LAI. We overestimate the seasonal litude of the prognostic LAI at the global scale, which is common amongst CMIP5 ESMs. However, the prognostic LAI is our preferred choice, because it allows for the vegetation feedback through the coupling between LAI and the leaf carbon pool. Globally integrated land-atmosphere and ocean-atmosphere fluxes and flux patterns are well reproduced and show good agreement with most recent observations. The seasonal cycle of simulated atmospheric CO2 is close to the observed seasonal cycle, but shows a larger litude in the high northern latitudes. Overall, ACCESS-ESM1 performs well over the historical period, making it a useful tool to explore the change in land and oceanic carbon uptake in the future.
Publisher: American Geophysical Union (AGU)
Date: 12-1999
DOI: 10.1029/1999GB900073
Publisher: American Geophysical Union (AGU)
Date: 24-01-2004
DOI: 10.1029/2003GB002111
Publisher: Aspendale, CSIRO Atmospheric Research
Date: 2001
Publisher: [Aspendale], CSIRO
Date: 1995
Publisher: Wiley
Date: 04-1995
Publisher: Stockholm University Press
Date: 2006
Publisher: Wiley
Date: 12-12-2020
DOI: 10.1111/GCB.14917
Abstract: Robust estimates of CO
Publisher: CSIRO Publishing
Date: 08-10-2020
DOI: 10.1071/ES19040
Abstract: A new version of the Australian Community Climate and Earth System Simulator coupled model, ACCESS-CM2, has been developed for a wide range of climate modelling research and applications. In particular, ACCESS-CM2 is one of Australia’s contributions to the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the ACCESS1.3 model used for our CMIP5 submission, all model components have been upgraded as well as the coupling framework (OASIS3-MCT) and experiment control system (Rose/Cylc). The component models are: UM10.6 GA7.1 for the atmosphere, CABLE2.5 for the land surface, MOM5 for the ocean, and CICE5.1.2 for the sea ice. This paper describes the model configuration of ACCESS-CM2, documents the experimental set up, and assesses the model performance for the preindustrial spin-up simulation in comparison against (reconstructed) observations and ACCESS1.3 results. While the performance of the two generations of the ACCESS coupled model is largely comparable, ACCESS-CM2 shows better global hydrological balance, more realistic ocean water properties (in terms of spatial distribution) and meridional overturning circulation in the Southern Ocean but a poorer simulation of the Antarctic sea ice and a larger energy imbalance at the top of atmosphere. This energy imbalance reflects a noticeable warming trend of the global ocean over the spin-up period.
Publisher: Copernicus GmbH
Date: 06-07-2017
Abstract: Abstract. Earth system models (ESMs) that incorporate carbon–climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1, which comprises atmosphere (UM7.3), land (CABLE), ocean (MOM4p1), and sea-ice (CICE4.1) components with OASIS-MCT coupling, to which ocean and land carbon modules have been added. The land carbon model (as part of CABLE) can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model (WOMBAT, added to MOM) simulates the evolution of phosphate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. We perform multi-centennial pre-industrial simulations with a fixed atmospheric CO2 concentration and different land carbon model configurations (prescribed or prognostic leaf area index). We evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. Simulating leaf area index results in a slight warming of the atmosphere relative to the prescribed leaf area index case. Seasonal and interannual variations in land carbon exchange are sensitive to whether leaf area index is simulated, with interannual variations driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations. While our model overestimates surface phosphate values, the global primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model and consequent limits on the applicability of this model version. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.
Publisher: American Geophysical Union (AGU)
Date: 08-2008
DOI: 10.1029/2007GB003050
Publisher: Copernicus GmbH
Date: 21-02-2019
Abstract: Abstract. The Southern Ocean (south of 30∘ S) is a key global-scale sink of carbon dioxide (CO2). However, the isolated and inhospitable nature of this environment has restricted the number of oceanic and atmospheric CO2 measurements in this region. This has limited the scientific community's ability to investigate trends and seasonal variability of the sink. Compared to regions further north, the near-absence of terrestrial CO2 exchange and strong large-scale zonal mixing demands unusual inter-site measurement precision to help distinguish the presence of midlatitude to high latitude ocean exchange from large CO2 fluxes transported southwards in the atmosphere. Here we describe a continuous, in situ, ultra-high-precision Southern Ocean region CO2 record, which ran at Macquarie Island (54∘37′ S, 158∘52′ E) from 2005 to 2016 using a LoFlo2 instrument, along with its calibration strategy, uncertainty analysis and baseline filtering procedures. Uncertainty estimates calculated for minute and hourly frequency data range from 0.01 to 0.05 µmol mol−1 depending on the averaging period and application. Higher precisions are applicable when comparing Macquarie Island LoFlo measurements to those of similar instruments on the same internal laboratory calibration scale and more uncertain values are applicable when comparing to other networks. Baseline selection is designed to remove measurements that are influenced by local Macquarie Island CO2 sources, with effective removal achieved using a within-minute CO2 standard deviation metric. Additionally, measurements that are influenced by CO2 fluxes from Australia or other Southern Hemisphere land masses are effectively removed using model-simulated radon concentration. A comparison with flask records of atmospheric CO2 at Macquarie Island highlights the limitation of the flask record (due to corrections for storage time and limited temporal coverage) when compared to the new high-precision, continuous record: the new record shows much less noisy seasonal variations than the flask record. As such, this new record is ideal for improving our understanding of the spatial and temporal variability of the Southern Ocean CO2 flux, particularly when combined with data from similar instruments at other Southern Hemispheric locations.
Publisher: Stockholm University Press
Date: 04-1999
Publisher: Copernicus GmbH
Date: 07-02-2013
Abstract: Abstract. This paper reports a study of the full carbon (C-CO2) budget of the Australian continent, focussing on 1990–2011 in the context of estimates over two centuries. The work is a contribution to the RECCAP (REgional Carbon Cycle Assessment and Processes) project, as one of numerous regional studies. In constructing the budget, we estimate the following component carbon fluxes: net primary production (NPP) net ecosystem production (NEP) fire land use change (LUC) riverine export dust export harvest (wood, crop and livestock) and fossil fuel emissions (both territorial and non-territorial). Major biospheric fluxes were derived using BIOS2 (Haverd et al., 2012), a fine-spatial-resolution (0.05°) offline modelling environment in which predictions of CABLE (Wang et al., 2011), a sophisticated land surface model with carbon cycle, are constrained by multiple observation types. The mean NEP reveals that climate variability and rising CO2 contributed 12 & m 24 (1σ error on mean) and 68 & m 15 TgC yr−1, respectively. However these gains were partially offset by fire and LUC (along with other minor fluxes), which caused net losses of 26 & m 4 TgC yr−1 and 18 & m 7 TgC yr−1, respectively. The resultant net biome production (NBP) is 36 & m 29 TgC yr−1, in which the largest contributions to uncertainty are NEP, fire and LUC. This NBP offset fossil fuel emissions (95 & m 6 TgC yr−1) by 38 & m 30%. The interannual variability (IAV) in the Australian carbon budget exceeds Australia's total carbon emissions by fossil fuel combustion and is dominated by IAV in NEP. Territorial fossil fuel emissions are significantly smaller than the rapidly growing fossil fuel exports: in 2009–2010, Australia exported 2.5 times more carbon in fossil fuels than it emitted by burning fossil fuels.
Publisher: Copernicus GmbH
Date: 04-06-2019
Abstract: Abstract. Climate change mitigation efforts require information on the current greenhouse gas atmospheric concentrations and their sources and sinks. Carbon dioxide (CO2) is the most abundant anthropogenic greenhouse gas. Its variability in the atmosphere is modulated by the synergy between weather and CO2 surface fluxes, often referred to as CO2 weather. It is interpreted with the help of global or regional numerical transport models, with horizontal resolutions ranging from a few hundreds of kilometres to a few kilometres. Changes in the model horizontal resolution affect not only atmospheric transport but also the representation of topography and surface CO2 fluxes. This paper assesses the impact of horizontal resolution on the simulated atmospheric CO2 variability with a numerical weather prediction model. The simulations are performed using the Copernicus Atmosphere Monitoring Service (CAMS) CO2 forecasting system at different resolutions from 9 to 80 km and are evaluated using in situ atmospheric surface measurements and atmospheric column-mean observations of CO2, as well as radiosonde and SYNOP observations of the winds. The results indicate that both diurnal and day-to-day variability of atmospheric CO2 are generally better represented at high resolution, as shown by a reduction in the errors in simulated wind and CO2. Mountain stations display the largest improvements at high resolution as they directly benefit from the more realistic orography. In addition, the CO2 spatial gradients are generally improved with increasing resolution for both stations near the surface and those observing the total column, as the overall inter-station error is also reduced in magnitude. However, close to emission hotspots, the high resolution can also lead to a deterioration of the simulation skill, highlighting uncertainties in the high-resolution fluxes that are more diffuse at lower resolutions. We conclude that increasing horizontal resolution matters for modelling CO2 weather because it has the potential to bring together improvements in the surface representation of both winds and CO2 fluxes, as well as an expected reduction in numerical errors of transport. Modelling applications like atmospheric inversion systems to estimate surface fluxes will only be able to benefit fully from upgrades in horizontal resolution if the topography, winds and prior flux distribution are also upgraded accordingly. It is clear from the results that an additional increase in resolution might reduce errors even further. However, the horizontal resolution sensitivity tests indicate that the change in the CO2 and wind modelling error with resolution is not linear, making it difficult to quantify the improvement beyond the tested resolutions. Finally, we show that the high-resolution simulations are useful for the assessment of the small-scale variability of CO2 which cannot be represented in coarser-resolution models. These representativeness errors need to be considered when assimilating in situ data and high-resolution satellite data such as Greenhouse gases Observing Satellite (GOSAT), Orbiting Carbon Observatory-2 (OCO-2), the Chinese Carbon Dioxide Observation Satellite Mission (TanSat) and future missions such as the Geostationary Carbon Observatory (GeoCarb) and the Sentinel satellite constellation for CO2. For these reasons, the high-resolution CO2 simulations provided by the CAMS in real time can be useful to estimate such small-scale variability in real time, as well as providing boundary conditions for regional modelling studies and supporting field experiments.
Publisher: Springer Science and Business Media LLC
Date: 10-02-2013
DOI: 10.1038/NCLIMATE1817
Publisher: CSIRO Publishing
Date: 24-08-2020
DOI: 10.1071/ES19035
Abstract: The Australian Community Climate and Earth System Simulator (ACCESS) has been extended to include land and ocean carbon cycle components to form an Earth System Model (ESM). The current version, ACCESS-ESM1.5, has been mainly developed to enable Australia to participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6) with an ESM version. Here we describe the model components and changes to the previous version, ACCESS-ESM1. We use the 500-year pre-industrial control run to highlight the stability of the physical climate and the carbon cycle. The long spin-up, negligible drift in temperature and small pre-industrial net carbon fluxes (0.02 and 0.08 PgC year−1 for land and ocean respectively) highlight the suitability of ACCESS-ESM1.5 to explore modes of variability in the climate system and coupling to the carbon cycle. The physical climate and carbon cycle for the present day have been evaluated using the CMIP6 historical simulation by comparing against observations and ACCESS-ESM1. Although there is generally little change in the climate simulation from the earlier model, many aspects of the carbon simulation are improved. An assessment of the climate response to CO2 forcing indicates that ACCESS-ESM1.5 has an equilibrium climate sensitivity of 3.87°C.
Publisher: American Geophysical Union (AGU)
Date: 12-1996
DOI: 10.1029/96GB01892
Publisher: Copernicus GmbH
Date: 23-08-2016
Abstract: Abstract. The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions are more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Overall we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.
Publisher: Copernicus GmbH
Date: 03-12-2013
Abstract: Abstract. Climate extremes, such as heat waves and heavy precipitation events, have large impacts on ecosystems and societies. Climate models provide useful tools to study underlying processes and lifying effects associated with extremes. The Australian Community Climate and Earth System Simulator (ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land Exchange model. We examine how this model represents climate extremes derived by the Expert Team on Climate Change Detection and Indices and compare them to observational datasets using the AMIP framework. We find that the patterns of extreme indices are generally well represented. Indices based on percentiles are particularly well represented and capture the trends over the last 60 yr shown by the observations remarkably well. The diurnal temperature range is underestimated, minimum temperatures (TMIN) during nights are generally too warm and daily maximum temperatures (TMAX) too low in the model. The number of consecutive wet days is overestimated while consecutive dry days are underestimated. The maximum consecutive 1 day precipitation amount is underestimated on the global scale. Biases in TMIN correlate well with biases in incoming longwave radiation, suggesting a relationship with biases in cloud cover. Biases in TMAX depend on biases in net shortwave radiation as well as evapotranspiration. The regions and season where the bias in evapotranspiration plays a role for the TMAX bias correspond to regions and seasons where soil moisture availability is limited. Our analysis provides the foundation for future experiments that will examine how land surface processes contribute to these systematic biases in the ACCESS modelling system.
Publisher: Aspendale, Vic., CSIRO Marine and Atmospheric Research
Date: 2006
Publisher: Springer Science and Business Media LLC
Date: 25-02-2016
DOI: 10.1038/NCOMMS10724
Abstract: Increasing atmospheric carbon dioxide (CO 2 ) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world’s 10 largest national emitters of CO 2 . Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO 2 concentration. The Asian land biosphere was a net sink of −0.46 (−0.70–0.24) PgC per year (median and range) for 1996–2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO 2 sink increased between 1996–2001 and 2008–2012 by 0.56 (0.30–0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change.
Publisher: Copernicus GmbH
Date: 27-02-2019
DOI: 10.5194/ACP-2019-177
Abstract: Abstract. Climate change mitigation efforts require information on the current greenhouse gas atmospheric concentrations and their sources and sinks. Carbon dioxide (CO2) is the most abundant anthropogenic greenhouse gas. Its variability in the atmosphere is modulated by the synergy between weather and CO2 surface fluxes, often referred to as CO2 weather. It is interpreted with the help of global or regional numerical transport models, with horizontal resolutions ranging from a few hundreds of km to a few km. Changes in the model horizontal resolution affect not only atmospheric transport, but also the representation of topography and surface CO2 fluxes. This paper assesses the impact of horizontal resolution on the simulated atmospheric CO2 variability with a numerical weather prediction model. The simulations are performed using the Copernicus Atmosphere Monitoring Service (CAMS) CO2 forecasting system at different resolutions from 9 km to 80 km and are evaluated using in situ atmospheric surface measurements and atmospheric column-mean observations of CO2, as well as radiosonde and SYNOP observations of the winds. The results indicate that both diurnal and day-to-day variability of atmospheric CO2 are generally better represented at high resolution, as shown by a reduction in the errors in simulated wind and CO2. Mountain stations display the largest improvements at high resolution as they directly benefit from the more realistic orography. In addition, the CO2 spatial gradients are generally improved with increasing resolution for both stations near the surface and those observing the total column, as the overall inter-station error is also reduced in magnitude. However, close to emission hotspots, the high resolution can also lead to a deterioration of the simulation skill, highlighting uncertainties in the high resolution fluxes that are more diffuse at lower resolutions. We conclude that increasing horizontal resolution matters for modelling CO2 weather because it has the potential to bring together improvements in the surface representation of both winds and CO2 fluxes, as well as an expected reduction in numerical errors of transport. Modelling applications like atmospheric inversion systems to estimate surface fluxes will only be able to benefit fully from upgrades in horizontal resolution if the topography, winds and prior flux distribution are also upgraded accordingly. It is clear from the results that an additional increase in resolution might reduce errors even further. However, the horizontal resolution sensitivity tests indicate that the change in the CO2 and wind modelling error with resolution is not linear, making it difficult to extrapolate the results beyond the tested resolutions. Finally, we show that the high resolution simulations are useful for the assessment of the small-scale variability of CO2 which cannot be represented in coarser resolution models. These representativeness errors need to be considered when assimilating in situ data and high resolution satellite data such as Greenhouse gases Observing Satellite (GOSAT), Orbiting Carbon Observatory-2 (OCO-2), the Chinese Carbon Dioxide Observation Satellite Mission (TanSat) and future missions such as the Geostationary Carbon Observatory (GeoCarb) and the Sentinel satellite constellation for CO2. For these reasons, the high resolution CO2 simulations provided by the CAMS in real-time can be useful to estimate such small-scale variability in real time, as well as providing boundary conditions for regional modelling studies and supporting field experiments.
Publisher: Copernicus GmbH
Date: 09-12-2019
Publisher: Copernicus GmbH
Date: 07-2011
Abstract: Abstract. The scientific understanding of the Earth's climate system, including the central question of how the climate system is likely to respond to human-induced perturbations, is comprehensively captured in GCMs and Earth System Models (ESM). Diagnosing the simulated climate response, and comparing responses across different models, is crucially dependent on transparent assumptions of how the GCM/ESM has been driven – especially because the implementation can involve subjective decisions and may differ between modelling groups performing the same experiment. This paper outlines the climate forcings and setup of the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document the prescribed greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the HadGEM2-ES historical and future experiments following the Representative Concentration Pathways. In addition, we provide details of how HadGEM2-ES ensemble members were initialised from the control run and how the palaeoclimate and AMIP experiments, as well as the "emission-driven" RCP experiments were performed.
Publisher: Copernicus GmbH
Date: 13-01-2015
Abstract: Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air s les that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November), rather than winter, maximum for wetland emissions.
Publisher: American Geophysical Union (AGU)
Date: 24-07-2008
DOI: 10.1029/2007GB003068
Publisher: Copernicus GmbH
Date: 18-09-2015
Abstract: Abstract. Earth System Models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1 that combines existing ocean and land carbon models into the physical climate model to simulate exchanges of carbon between the land, atmosphere and ocean. The land carbon model can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model simulates the evolution of nitrate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. From two multi-centennial simulations of the pre-industrial period with different land carbon model configurations, we evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. For the land carbon cycle, leaf area index is simulated reasonably, and seasonal carbon exchange is well represented. Interannual variations of land carbon exchange are relatively large, driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations and very good agreement with existing Coupled Model Intercomparison Project (CMIP5) models. While our model over estimates surface nitrate values, the primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.
Publisher: Copernicus GmbH
Date: 11-02-2015
Abstract: Abstract. We analyse global and regional changes in CO2 fluxes using two simple models, an airborne fraction of anthropogenic emissions and a linear relationship with CO2 concentrations. We show that both models are able to fit the non-anthropogenic (hereafter natural) flux over the length of the atmospheric concentration record. Analysis of the linear model (including its uncertainties) suggests no significant decrease in the response of the natural carbon cycle. Recent data points rather to an increase. We apply the same linear diagnostic to fluxes from atmospheric inversions. Flux responses show clear regional and seasonal patterns driven by terrestrial uptake in the northern summer. Ocean fluxes show little or no linear response. Terrestrial models show clear responses, agreeing globally with the inversion responses, however the spatial structure is quite different, with dominant responses in the tropics rather than the northern extratropics.
Publisher: American Geophysical Union (AGU)
Date: 09-2000
DOI: 10.1029/1999GB001166
Publisher: Stockholm University Press
Date: 09-1992
Publisher: Copernicus GmbH
Date: 02-07-2013
DOI: 10.5194/BGD-10-10759-2013
Abstract: Abstract. The Indian Ocean (44° S–30° N) plays an important role in the global carbon cycle, yet remains one of the most poorly s led ocean regions. Several approaches have been used to estimate net sea–air CO2 fluxes in this region: interpolated observations, ocean biogeochemical models, atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Indian Ocean sea–air CO2 fluxes between 1990 and 2009. Using all of the models and inversions, the median annual mean sea–air CO2 uptake of −0.37 ± 0.06 Pg C yr–1, is consistent with the −0.24 ± 0.12 Pg C yr–1 calculated from observations. The fluxes from the Southern Indian Ocean (18° S–44° S −0.43 ± 0.07 Pg C yr–1) are similar in magnitude to the annual uptake for the entire Indian Ocean. All models capture the observed pattern of fluxes in the Indian Ocean with the following exceptions: underestimation of upwelling fluxes in the northwestern region (off Oman and Somalia), over estimation in the northeastern region (Bay of Bengal) and underestimation of the CO2 sink in the subtropical convergence zone. These differences were mainly driven by a lack of atmospheric CO2 data in atmospheric inversions, and poor simulation of monsoonal currents and freshwater discharge in ocean biogeochemical models. Overall, the models and inversions do capture the phase of the observed seasonality for the entire Indian Ocean but over estimate the magnitude. The predicted sea–air CO2 fluxes by Ocean BioGeochemical Models (OBGM) respond to seasonal variability with strong phase lags with reference to climatological CO2 flux, whereas the atmospheric inversions predict an order of magnitude higher seasonal flux than OBGMs. The simulated interannual variability by the OBGMs is weaker than atmospheric inversions. Prediction of such weak interannual variability in CO2 fluxes by atmospheric inversions was mainly caused by lack of atmospheric data in the Indian Ocean. The OBGM models suggest a small strengthening of the sink over the period 1990–2009 of −0.01 Pg C decade–1. This is inconsistent with the observations in the southwest Indian Ocean that shows the growth rate of oceanic pCO2 was faster than the observed atmospheric CO2 growth, a finding attributed to the trend of the Southern Annual Mode (SAM) during the 1990s.
Publisher: Copernicus GmbH
Date: 27-02-2019
Publisher: Copernicus GmbH
Date: 06-11-2013
Abstract: Abstract. The Indian Ocean (44° S–30° N) plays an important role in the global carbon cycle, yet it remains one of the most poorly s led ocean regions. Several approaches have been used to estimate net sea–air CO2 fluxes in this region: interpolated observations, ocean biogeochemical models, atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Indian Ocean sea–air CO2 fluxes between 1990 and 2009. Using all of the models and inversions, the median annual mean sea–air CO2 uptake of −0.37 ± 0.06 PgC yr−1 is consistent with the −0.24 ± 0.12 PgC yr−1 calculated from observations. The fluxes from the southern Indian Ocean (18–44° S −0.43 ± 0.07 PgC yr−1 are similar in magnitude to the annual uptake for the entire Indian Ocean. All models capture the observed pattern of fluxes in the Indian Ocean with the following exceptions: underestimation of upwelling fluxes in the northwestern region (off Oman and Somalia), overestimation in the northeastern region (Bay of Bengal) and underestimation of the CO2 sink in the subtropical convergence zone. These differences were mainly driven by lack of atmospheric CO2 data in atmospheric inversions, and poor simulation of monsoonal currents and freshwater discharge in ocean biogeochemical models. Overall, the models and inversions do capture the phase of the observed seasonality for the entire Indian Ocean but overestimate the magnitude. The predicted sea–air CO2 fluxes by ocean biogeochemical models (OBGMs) respond to seasonal variability with strong phase lags with reference to climatological CO2 flux, whereas the atmospheric inversions predicted an order of magnitude higher seasonal flux than OBGMs. The simulated interannual variability by the OBGMs is weaker than that found by atmospheric inversions. Prediction of such weak interannual variability in CO2 fluxes by atmospheric inversions was mainly caused by a lack of atmospheric data in the Indian Ocean. The OBGM models suggest a small strengthening of the sink over the period 1990–2009 of −0.01 PgC decade−1. This is inconsistent with the observations in the southwestern Indian Ocean that shows the growth rate of oceanic pCO2 was faster than the observed atmospheric CO2 growth, a finding attributed to the trend of the Southern Annular Mode (SAM) during the 1990s.
Publisher: Copernicus GmbH
Date: 24-10-2013
Abstract: Abstract. Atmospheric CO2 inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO2 measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2010. Mean fluxes for 2001–2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale sub isions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (−3.4 Pg C yr−1 (±0.5 Pg C yr−1 standard deviation), with slightly more uptake over land than over ocean), a significant although more variable source over the tropics (1.6 ± 0.9 Pg C yr−1) and a compensatory sink of similar magnitude in the south (−1.4 ± 0.5 Pg C yr−1) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.06 versus 0.33 Pg C yr−1 for the 1996–2007 period), with much higher consistency among the inversions for the land. While the tropical land explains most of the IAV (standard deviation ~ 0.65 Pg C yr−1), the northern and southern land also contribute (standard deviation ~ 0.39 Pg C yr−1). Most inversions tend to indicate an increase of the northern land carbon uptake from late 1990s to 2008 (around 0.1 Pg C yr−1, predominantly in North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data over the northern land (at the continental scale), but still highly dependent on the prior flux seasonality over the ocean. Finally we provide recommendations to interpret the regional fluxes, along with the uncertainty estimates.
Publisher: American Geophysical Union (AGU)
Date: 10-2013
DOI: 10.1002/GBC.20091
Publisher: Springer Science and Business Media LLC
Date: 25-06-2013
DOI: 10.1038/NCLIMATE1925
Publisher: American Geophysical Union (AGU)
Date: 03-2004
DOI: 10.1029/2003GB002136
Publisher: American Geophysical Union (AGU)
Date: 07-01-2006
DOI: 10.1029/2004GB002439
Publisher: American Association for the Advancement of Science (AAAS)
Date: 02-2008
Abstract: Unlike Le Quéré et al . (Reports, 22 June 2007, p. 1735), we do not find a saturating Southern Ocean carbon sink due to recent climate change. In our ocean model, observed wind forcing causes reduced carbon uptake, but heat and freshwater flux forcing cause increased uptake. Our inversions of atmospheric carbon dioxide show that the Southern Ocean sink trend is dependent on network choice.
Publisher: Copernicus GmbH
Date: 19-12-2011
DOI: 10.5194/ACP-11-12813-2011
Abstract: Abstract. A chemistry-transport model (CTM) intercomparison experiment (TransCom-CH4) has been designed to investigate the roles of surface emissions, transport and chemical loss in simulating the global methane distribution. Model simulations were conducted using twelve models and four model variants and results were archived for the period of 1990–2007. All but one model transports were driven by reanalysis products from 3 different meteorological agencies. The transport and removal of CH4 in six different emission scenarios were simulated, with net global emissions of 513 ± 9 and 514 ± 14 Tg CH4 yr−1 for the 1990s and 2000s, respectively. Additionally, sulfur hexafluoride (SF6) was simulated to check the interhemispheric transport, radon (222Rn) to check the subgrid scale transport, and methyl chloroform (CH3CCl3) to check the chemical removal by the tropospheric hydroxyl radical (OH). The results are compared to monthly or annual mean time series of CH4, SF6 and CH3CCl3 measurements from 8 selected background sites, and to satellite observations of CH4 in the upper troposphere and stratosphere. Most models adequately capture the vertical gradients in the stratosphere, the average long-term trends, seasonal cycles, interannual variations (IAVs) and interhemispheric (IH) gradients at the surface sites for SF6, CH3CCl3 and CH4. The vertical gradients of all tracers between the surface and the upper troposphere are consistent within the models, revealing vertical transport differences between models. An average IH exchange time of 1.39 ± 0.18 yr is derived from SF6 time series. Sensitivity simulations suggest that the estimated trends in exchange time, over the period of 1996–2007, are caused by a change of SF6 emissions towards the tropics. Using six sets of emission scenarios, we show that the decadal average CH4 growth rate likely reached equilibrium in the early 2000s due to the flattening of anthropogenic emission growth since the late 1990s. Up to 60% of the IAVs in the observed CH4 concentrations can be explained by accounting for the IAVs in emissions, from biomass burning and wetlands, as well as meteorology in the forward models. The modeled CH4 budget is shown to depend strongly on the troposphere-stratosphere exchange rate and thus on the model's vertical grid structure and circulation in the lower stratosphere. The 15-model median CH4 and CH3CCl3 atmospheric lifetimes are estimated to be 9.99 ± 0.08 and 4.61 ± 0.13 yr, respectively, with little IAV due to transport and temperature.
Publisher: Copernicus GmbH
Date: 10-09-2014
Abstract: 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.
Publisher: Copernicus GmbH
Date: 28-09-2023
DOI: 10.5194/BG-2023-146
Publisher: Copernicus GmbH
Date: 02-01-2017
Abstract: Abstract. It is a widely established fact that standard semi-Lagrangian advection schemes are highly efficient numerical techniques for simulating the transport of atmospheric tracers. However, as they are not formally mass conserving, it is essential to use some method for restoring mass conservation in long time range forecasts. A common approach is to use global mass fixers. This is the case of the semi-Lagrangian advection scheme in the Integrated Forecasting System (IFS) model used by the Copernicus Atmosphere Monitoring Service (CAMS) at the European Centre for Medium-Range Weather Forecasts (ECMWF).Mass fixers are algorithms with substantial differences in complexity and sophistication but in general of low computational cost. This paper shows the positive impact mass fixers have on the inter-hemispheric gradient of total atmospheric column-averaged CO2 and CH4, a crucial feature of their spatial distribution. Two algorithms are compared: the simple "proportional" and the more complex Bermejo–Conde schemes. The former is widely used by several Earth system climate models as well the CAMS global forecasts and analysis of atmospheric composition, while the latter has been recently implemented in IFS. Comparisons against total column observations demonstrate that the proportional mass fixer is shown to be suitable for the low-resolution simulations, but for the high-resolution simulations the Bermejo–Conde scheme clearly gives better results. These results have potential repercussions for climate Earth system models using proportional mass fixers as their resolution increases. It also emphasises the importance of benchmarking the tracer mass fixers with the inter-hemispheric gradient of long-lived greenhouse gases using observations.
Publisher: Copernicus GmbH
Date: 03-2016
DOI: 10.5194/GMD-2016-35
Abstract: Abstract. The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. Cooler NH summer temperatures in canopy covered areas are attributed to two factors. Firstly CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below this placement of canopy above the ground eliminates the need for a separate bare ground tile in canopy covered areas. Secondly, CABLE produces larger evapotranspiration fluxes and slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow covered areas. In particular prognostic snow density increases through the winter and lowers diurnally resolved snow albedo variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses liquid precipitation freezing within the snowpack delays the building of the snow pack in autumn and accelerates snow melting in spring.
Publisher: CSIRO
Date: 2020
DOI: 10.25919/PZAF-P326
Publisher: Copernicus GmbH
Date: 15-03-2013
Abstract: Abstract. Atmospheric CO2 inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO2 measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2009. Mean fluxes for 2001–2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale sub isions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (−3.3 Pg Cy−1 (±0.6 standard deviation)) nearly equally spread between land and ocean, a significant although more variable source over the tropics (1.6 ± 1.0 Pg Cy−1) and a compensatory sink of similar magnitude in the south (−1.4 ± 0.6 Pg Cy−1) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.05 versus 0.34 Pg Cy−1 for the 1996–2007 period), with much higher consistency amoung the inversions for the land. While the tropical land explains most of the IAV (stdev ∼ 0.69 Pg Cy−1), the northern and southern land also contribute (stdev ∼ 0.39 Pg Cy−1). Most inversions tend to indicate an increase of the northern land carbon uptake through the 2000s (around 0.11 Pg Cy−1), shared by North America and North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data over the northern land (at the continental scale), but still highly dependent on the prior flux seasonality over the ocean. Finally we provide recommendations to interpret the regional fluxes, along with the uncertainty estimates.
Publisher: Copernicus GmbH
Date: 19-01-2016
DOI: 10.5194/GI-5-1-2016
Abstract: Abstract. Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both in idually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The in idual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to in idually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.
Publisher: Copernicus GmbH
Date: 18-08-2020
Abstract: Abstract. Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.
Publisher: Springer Science and Business Media LLC
Date: 20-02-2017
Publisher: Stockholm University Press
Date: 09-1996
Publisher: Copernicus GmbH
Date: 11-04-2016
DOI: 10.5194/GMD-2016-72
Abstract: Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show ergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are sub ided in two components, the first addressing systematic land biases in offline mode ("LMIP", building upon the 3rd phase of Global Soil Wetness Project GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework ("LFMIP", building upon the GLACE-CMIP blueprint).
Publisher: Copernicus GmbH
Date: 05-08-2015
Abstract: Abstract. Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimize the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both in idually and in a combined network using multiple objectives. Optimal networks are generated by adding up to 5 new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The in idual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to in idually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.
Publisher: Stockholm University Press
Date: 04-1999
Publisher: Stockholm University Press
Date: 04-1999
Publisher: American Geophysical Union (AGU)
Date: 03-2006
DOI: 10.1029/2005GL025403
Publisher: CSIRO Publishing
Date: 14-07-2022
DOI: 10.1071/ES21031
Abstract: The Australian Community Climate and Earth System Simulator (ACCESS) has contributed to the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 6 (CMIP6) using two fully coupled model versions (ACCESS-CM2 and ACCESS-ESM1.5) and two ocean–sea-ice model versions (1° and 0.25° resolution versions of ACCESS-OM2). The fully coupled models differ primarily in the configuration and version of their atmosphere components (including the aerosol scheme), with smaller differences in their sea-ice and land model versions. Additionally, ACCESS-ESM1.5 includes biogeochemistry in the land and ocean components and can be run with an interactive carbon cycle. CMIP6 comprises core experiments and associated thematic Model Intercomparison Projects (MIPs). This paper provides an overview of the CMIP6 submission, including the methods used for the preparation of input forcing datasets and the post-processing of model output, along with a comprehensive list of experiments performed, detailing their initialisation, duration, ensemble number and computational cost. A small selection of model output is presented, focusing on idealised experiments and their variants at global scale. Differences in the climate simulation of the two coupled models are highlighted. ACCESS-CM2 produces a larger equilibrium climate sensitivity (4.7°C) than ACCESS-ESM1.5 (3.9°C), likely a result of updated atmospheric parameterisation in recent versions of the atmospheric component of ACCESS-CM2. The idealised experiments run with ACCESS-ESM1.5 show that land and ocean carbon fluxes respond to both changing atmospheric CO2 and to changing temperature. ACCESS data submitted to CMIP6 are available from the Earth System Grid Federation (0.22033/ESGF/CMIP6.2281 and 0.22033/ESGF/CMIP6.2288). The information provided in this paper should facilitate easier use of these significant datasets by the broader climate community.
Publisher: Copernicus GmbH
Date: 06-10-2011
DOI: 10.5194/ACP-11-10071-2011
Abstract: Abstract. Fourteen global atmospheric transport models were evaluated by comparing the simulation of 222Rn against measurements at three continental stations in Germany: Heidelberg, Freiburg and Schauinsland. Hourly concentrations simulated by the models using a common 222Rn-flux without temporal variations were investigated for 2002 and 2003. We found that the mean simulated concentrations in Heidelberg are related to the diurnal litude of boundary layer height in each model. Summer mean concentrations simulated by in idual models were negatively correlated with the seasonal mean of diurnal litude of boundary layer height, while in winter the correlation was positive. We also found that the correlations between simulated and measured concentrations at Schauinsland were higher when the simulated concentrations were interpolated to the station altitude in most models. Temporal variations of the mismatch between simulated and measured concentrations suggest that there are significant interannual variations in the 222Rn exhalation rate in this region. We found that the local inversion layer during daytime in summer in Freiburg has a significant effect on 222Rn concentrations. We recommend Freiburg concentrations for validation of models that resolve local stable layers and those at Heidelberg for models without this capability.
Publisher: Springer Science and Business Media LLC
Date: 02-2002
DOI: 10.1038/415626A
Publisher: Stockholm University Press
Date: 11-1996
Publisher: American Geophysical Union (AGU)
Date: 15-02-1999
DOI: 10.1029/1999GL900008
Publisher: American Geophysical Union (AGU)
Date: 13-05-2013
DOI: 10.1002/JGRD.50380
Publisher: Copernicus GmbH
Date: 19-08-2014
DOI: 10.5194/ACPD-14-21189-2014
Abstract: Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air s les that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September-October-November), rather than winter, maximum for wetland emissions.
Publisher: American Geophysical Union (AGU)
Date: 25-06-2011
DOI: 10.1029/2010JD014887
Publisher: Copernicus GmbH
Date: 29-10-2018
Publisher: American Geophysical Union (AGU)
Date: 09-10-2002
DOI: 10.1029/2001GB001593
Publisher: Authorea, Inc.
Date: 25-05-2023
DOI: 10.22541/ESSOAR.168500240.06202349/V1
Abstract: Forestation is a major component of future long-term emissions reduction and CO$_2$ removal strategies, but the viability of carbon stored in vegetation under future climates is highly uncertain. We analyze the results from seven CMIP6 models for a combined scenario with high fossil fuel emissions (from SSP5-8.5) and moderate forest expansion (from SSP1-2.6). This scenario aims to demonstrate the ability of forestation strategies to mitigate climate change under continued increasing CO$_2$ emissions and includes the potential impacts of increased CO$_2$ concentration and a warming climate on vegetation growth. The model intercomparison shows that moderate forestation as a CO$_2$ removal strategy has limited impact on global climate under a high global warming scenario, despite generating a substantial cumulative carbon sink of 10–60 Pg C over the period 2015–2100. Using a single model ensemble, we show that there are local increases in warm extremes in response to forestation associated with decreases in the number of cool days. Furthermore, we find evidence of a shift in the global carbon balance, whereby increased carbon storage on land of $\\sim$25 Pg C by 2100 associated with forestation has a concomitant decrease in the carbon uptake by the ocean due to reduced atmospheric CO$_2$ concentrations.
Publisher: American Geophysical Union (AGU)
Date: 22-07-2006
DOI: 10.1029/2006JD007428
Publisher: Springer Science and Business Media LLC
Date: 14-03-2020
Publisher: Copernicus GmbH
Date: 06-07-2017
Abstract: Abstract. Over the last decade many climate models have evolved into Earth system models (ESMs), which are able to simulate both physical and biogeochemical processes through the inclusion of additional components such as the carbon cycle. The Australian Community Climate and Earth System Simulator (ACCESS) has been recently extended to include land and ocean carbon cycle components in its ACCESS-ESM1 version. A detailed description of ACCESS-ESM1 components including results from pre-industrial simulations is provided in Part 1. Here, we focus on the evaluation of ACCESS-ESM1 over the historical period (1850–2005) in terms of its capability to reproduce climate and carbon-related variables. Comparisons are performed with observations, if available, but also with other ESMs to highlight common weaknesses. We find that climate variables controlling the exchange of carbon are well reproduced. However, the aerosol forcing in ACCESS-ESM1 is somewhat larger than in other models, which leads to an overly strong cooling response in the land from about 1960 onwards. The land carbon cycle is evaluated for two scenarios: running with a prescribed leaf area index (LAI) and running with a prognostic LAI. We overestimate the seasonal mean (1.7 vs. 1.4) and peak litude (2.0 vs. 1.8) of the prognostic LAI at the global scale, which is common amongst CMIP5 ESMs. However, the prognostic LAI is our preferred choice, because it allows for the vegetation feedback through the coupling between LAI and the leaf carbon pool. Our globally integrated land–atmosphere flux over the historical period is 98 PgC for prescribed LAI and 137 PgC for prognostic LAI, which is in line with estimates of land use emissions (ACCESS-ESM1 does not include land use change). The integrated ocean–atmosphere flux is 83 PgC, which is in agreement with a recent estimate of 82 PgC from the Global Carbon Project for the period 1959–2005. The seasonal cycle of simulated atmospheric CO2 is close to the observed seasonal cycle (up to 1 ppm difference for the station at Mace Head and up to 2 ppm for the station at Mauna Loa), but shows a larger litude (up to 6 ppm) in the high northern latitudes. Overall, ACCESS-ESM1 performs well over the historical period, making it a useful tool to explore the change in land and oceanic carbon uptake in the future.
Publisher: Copernicus GmbH
Date: 05-08-2016
Publisher: Copernicus GmbH
Date: 18-09-2015
Publisher: Copernicus GmbH
Date: 02-2013
Abstract: Abstract. A modified cumulus convection parametrisation scheme is presented. This scheme computes the mass of air transported upward in a cumulus cell using conservation of moisture and a detailed distribution of convective precipitation provided by a reanalysis dataset. The representation of vertical transport within the scheme includes entrainment and detrainment processes in convective updrafts and downdrafts. Output from the proposed parametrisation scheme is employed in the National Institute for Environmental Studies (NIES) global chemical transport model driven by JRA-25/JCDAS reanalysis. The simulated convective precipitation rate and mass fluxes are compared with observations and reanalysis data. A simulation of the short-lived tracer 222Rn is used to further evaluate the performance of the cumulus convection scheme. Simulated distributions of 222Rn are evaluated against observations at the surface and in the free troposphere, and compared with output from models that participated in the TransCom-CH4 Transport Model Intercomparison. From this comparison, we demonstrate that the proposed convective scheme in general is consistent with observed and modeled results.
Publisher: Copernicus GmbH
Date: 09-12-2019
DOI: 10.5194/BG-2019-473
Abstract: Abstract. Results from the fully-, biogeochemically-, and radiatively-coupled simulations in which CO2 increases at a rate of 1 % per year (1pctCO2) from its pre-industrial value are analyzed to quantify the magnitude of two feedback parameters which characterize the coupled carbon-climate system. These feedback parameters quantify the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate. The results are based on eight comprehensive Earth system models from the fifth Coupled Model Intercomparison Project (CMIP5) and eleven models from the sixth CMIP (CMIP6). The comparison of model results from two CMIP phases shows that, for both land and ocean, the model mean values of the feedback parameters and their multi-model spread has not changed significantly across the two CMIP phases. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The sensitivity of feedback parameters to the three different ways in which they may be calculated is shown and, consistent with existing studies, the most relevant definition is that calculated using results from the fully- and biogeochemically-coupled configurations. Based on these two simulations simplified expressions for the feedback parameters are obtained when the small temperature change in the biogeochemically-coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters allows identification of the reasons for differing responses among ocean and land carbon cycle models.
Publisher: Copernicus GmbH
Date: 08-01-2013
Abstract: Abstract. The Southern Ocean (44° S–75° S) plays a critical role in the global carbon cycle, yet remains one of the most poorly s led ocean regions. Different approaches have been used to estimate sea-air CO2 fluxes in this region: synthesis of surface ocean observations, ocean biogeochemical models, and atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Southern Ocean sea-air CO2 fluxes between 1990–2009. Using all models and inversions (26), the integrated median annual sea-air CO2 flux of −0.42 ± 0.07 Pg C yr−1 for the 44° S–75° S region is consistent with the −0.27 ± 0.13 Pg C yr−1 calculated using surface observations. The circumpolar region south of 58° S has a small net annual flux (model and inversion median: −0.04 ± 0.07 Pg C yr−1 and observations: +0.04 ± 0.02 Pg C yr−1), with most of the net annual flux located in the 44° S to 58° S circumpolar band (model and inversion median: −0.36 ± 0.09 Pg C yr−1 and observations: −0.35 ± 0.09 Pg C yr−1). Seasonally, in the 44° S–58° S region, the median of 5 ocean biogeochemical models captures the observed sea-air CO2 flux seasonal cycle, while the median of 11 atmospheric inversions shows little seasonal change in the net flux. South of 58° S, neither atmospheric inversions nor ocean biogeochemical models reproduce the phase and litude of the observed seasonal sea-air CO2 flux, particularly in the Austral Winter. Importantly, no in idual atmospheric inversion or ocean biogeochemical model is capable of reproducing both the observed annual mean uptake and the observed seasonal cycle. This raises concerns about projecting future changes in Southern Ocean CO2 fluxes. The median interannual variability from atmospheric inversions and ocean biogeochemical models is substantial in the Southern Ocean up to 25% of the annual mean flux with 25% of this inter-annual variability attributed to the region south of 58° S. Trends in the net CO2 flux from the inversions and models are not statistically different from the expected increase of –0.05 Pg C yr−1 decade−1 due to increasing atmospheric CO2 concentrations. However, resolving long term trends is difficult due to the large interannual variability and short time frame (1990–2009) of this study.
Publisher: Copernicus GmbH
Date: 23-07-2010
Abstract: Abstract. Carbon storage by many terrestrial ecosystems can be limited by nutrients, predominantly nitrogen (N) and phosphorus (P), in addition to other environmental constraints, water, light and temperature. However the spatial distribution and the extent of both N and P limitation at the global scale have not been quantified. Here we have developed a global model of carbon (C), nitrogen (N) and phosphorus (P) cycles for the terrestrial biosphere. Model estimates of steady state C and N pool sizes and major fluxes between plant, litter and soil pools, under present climate conditions, agree well with various independent estimates. The total amount of C in the terrestrial biosphere is 2767 Gt C, and the C fractions in plant, litter and soil organic matter are 19%, 4% and 77%. The total amount of N is 135 Gt N, with about 94% stored in the soil, 5% in the plant live biomass, and 1% in litter. We found that the estimates of total soil P and its partitioning into different pools in soil are quite sensitive to biochemical P mineralization. The total amount of P (plant biomass, litter and soil) excluding occluded P in soil is 17 Gt P in the terrestrial biosphere, 33% of which is stored in the soil organic matter if biochemical P mineralization is modelled, or 31 Gt P with 67% in soil organic matter otherwise. This model was used to derive the global distribution and uncertainty of N or P limitation on the productivity of terrestrial ecosystems at steady state under present conditions. Our model estimates that the net primary productivity of most tropical evergreen broadleaf forests and tropical savannahs is reduced by about 20% on average by P limitation, and most of the remaining biomes are N limited N limitation is strongest in high latitude deciduous needle leaf forests, and reduces its net primary productivity by up to 40% under present conditions.
Publisher: Aspendale, CSIRO Atmospheric Research
Date: 2002
Publisher: Copernicus GmbH
Date: 25-06-2014
Abstract: Abstract. We analyze global and regional changes in CO2 fluxes using two simple models, an airborne fraction of anthropogenic emissions and a linear relationship with CO2 concentrations. We show that both models are able to fit the nonanthropogenic (hereafter natural) flux over the length of the atmospheric concentration record and that departures in the airborne fraction model are largely due to departures from exponential growth of emissions. Analysis of the first-order model (including its uncertainties) suggests no significant change in the response of the natural carbon cycle. We apply the same first-order diagnostic to fluxes from atmospheric inversions. Their responses show clear regional and seasonal patterns driven by terrestrial uptake in the northern summer. Ocean fluxes show little or no first-order response. terrestrial models also show clear responses, agreeing globally with the inversion responses, however the spatial structure is quite different, with dominant responses in the tropics rather than the northern extratropics.
Publisher: Stockholm University Press
Date: 2013
Publisher: Stockholm University Press
Date: 2010
Publisher: Copernicus GmbH
Date: 31-05-2017
Abstract: Abstract. Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800 000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3 ppm, CH4 at 808.2 ppb and N2O at 273.0 ppb. The data are available at earch/input4mips/ and www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).
Publisher: Copernicus GmbH
Date: 05-08-2016
DOI: 10.5194/GMD-2016-169
Abstract: Abstract. Atmospheric greenhouse gas concentrations are at unprecedented, record-high levels compared to pre-industrial reconstructions over the last 800,000 years. Those elevated greenhouse gas concentrations warm the planet and together with net cooling effects by aerosols, they are the reason of observed climate change over the past 150 years. An accurate representation of those concentrations is hence important to understand and model recent and future climate change. So far, community efforts to create composite datasets with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since 1980s. Here, we provide consolidated data sets of historical atmospheric (volume) mixing ratios of 43 greenhouse gases specifically for the purpose of climate model runs. The presented datasets are based on AGAGE and NOAA networks and a large set of literature studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved, and include seasonality over the period between year 0 to 2014. We assimilate data for CO2, methane (CH4) and nitrous oxide (N2O), 5 chlorofluorocarbons (CFCs), 3 hydrochlorofluorocarbons (HCFCs), 16 hydrofluorocarbons (HFCs), 3 halons, methyl bromide (CH3Br), 3 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen triflouride (NF3) and sulfuryl fluoride (SO2F2). We estimate 1850 annual and global mean surface mixing ratios of CO2 at 284.3 ppmv, CH4 at 808.2 ppbv and N2O at 273.0 ppbv and quantify the seasonal and hemispheric gradients of surface mixing ratios. Compared to earlier intercomparisons, the stronger implied radiative forcing in the northern hemisphere winter (due to the latitudinal gradient and seasonality) may help to improve the skill of climate models to reproduce past climate and thereby reduce uncertainty in future projections.
Publisher: American Geophysical Union (AGU)
Date: 26-11-2008
DOI: 10.1029/2007GB003081
Publisher: Copernicus GmbH
Date: 25-10-2018
DOI: 10.5194/AMT-2018-300
Abstract: Abstract. The Southern Ocean (south of 30° S) is a key global scale sink of carbon dioxide (CO2). However, the isolated and inhospitable nature of this environment has restricted the number of oceanic and atmospheric CO2 measurements in this region. This has limited the scientific community’s ability to investigate trends and seasonal variability of the sink. Compared to regions further north, the near-absence of terrestrial CO2 exchange and strong large-scale zonal mixing demands unusual inter-site measurement precision to help distinguish the presence of mid-to-high latitude ocean exchange from large CO2 fluxes transported southwards in the atmosphere. Here we describe a continuous, in-situ, ultra-high-precision, Southern Ocean region CO2 record, which ran at Macquarie Island (54°37’ S, 158°52’ E) from 2005–2016 using a LoFlo2 instrument, along with its calibration strategy, uncertainty analysis and baseline filtering procedures. Uncertainty estimates calculated for minute and hourly frequency data range from 0.01 to 0.05 μmol mol−1 depending on averaging period and application. Higher precisions are applicable when comparing MQA LoFlo measurements to those of similar instruments on the same internal laboratory calibration scale and more uncertain values are applicable when comparing to other networks. Baseline selection is designed to remove measurements that are influenced by local, Macquarie Island, CO2 sources, with effective removal achieved using a within-minute CO2 standard deviation metric. Additionally, measurements that are influenced by CO2 fluxes from Australia or other southern hemisphere land masses are effectively removed using model-simulated radon concentration. A comparison with flask records of atmospheric CO2 at Macquarie Island highlights the limitation of the flask record (due to corrections for storage time and limited temporal coverage) when compared to the new high-precision, continuous record the new record shows much less noisy seasonal variations than the flask record. As such this new record is ideal for improving our understanding of the spatial and temporal variability of the Southern Ocean CO2 flux particularly when combined with data from similar instruments at other Southern Hemispheric locations.
Publisher: Copernicus GmbH
Date: 15-03-2013
Publisher: Copernicus GmbH
Date: 19-03-2014
DOI: 10.5194/ACPD-14-7557-2014
Abstract: 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 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 time scale. Prior uncertainties are derived on a weekly time scale for biosphere fluxes and fossil fuel emissions from high resolution BIOS2 model runs and from 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 optimization 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.
Publisher: American Geophysical Union (AGU)
Date: 07-11-2002
DOI: 10.1029/2001JD000618
Publisher: Copernicus GmbH
Date: 15-02-2016
Publisher: Copernicus GmbH
Date: 10-12-2018
Abstract: Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).
Location: Australia
Start Date: 07-2005
End Date: 12-2008
Amount: $125,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 08-2017
End Date: 12-2024
Amount: $30,050,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2011
End Date: 06-2018
Amount: $21,400,000.00
Funder: Australian Research Council
View Funded Activity