scholarly journals HESFIRE: an explicit fire model for projections in the coupled Human–Earth System

2014 ◽  
Vol 11 (7) ◽  
pp. 10779-10826 ◽  
Author(s):  
Y. Le Page ◽  
D. Morton ◽  
B. Bond-Lamberty ◽  
J. M. C. Pereira ◽  
G. Hurtt
Keyword(s):  
Fire Ecology ◽  
Optimization Procedure ◽  
Global Scale ◽  
Ecosystem Dynamics ◽  
Model Parameters ◽  
Observation Data ◽  
Earth System ◽  
Fire Model ◽  
Annual Variability ◽  
Fire Activity

Abstract. Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Potential changes in fire activity under future climate and land use scenarios thus have important consequences for human and natural systems. Anticipating these consequences relies first on a realistic model of fire activity (e.g. fire incidence and inter-annual variability) and second on a model accounting for fire impacts (e.g. mortality and emissions). Key opportunities remain to develop the capabilities of fire activity models, which include quantifying the influence of poorly understood fire drivers, modeling the occurrence of large, multi-day fires – which have major impacts – and evaluating the fire driving assumptions and parameterization with observation data. Here, we describe a fire model, HESFIRE, which integrates the influence of weather, vegetation characteristics, and human activities in a standalone framework, with a particular emphasis on keeping model assumptions consistent with fire ecology, such as allowing fires to spread over consecutive days. A subset of the model parameters was calibrated through an optimization procedure using observational data to enhance our understanding of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality and inter-annual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies – most notably regarding fires in boreal regions, in xeric ecosystems, and fire size distribution – are investigated to propose model development strategies. We highlight the capabilities of HESFIRE and its optimization procedure to analyze the sensitivity of fire activity, and to provide fire projections in the coupled Human–Earth System at regional and global scale. These capabilities and their detailed evaluation also provide a solid foundation for integration within a vegetation model to represent fire impacts on vegetation dynamics and emissions.

scholarly journals HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

2015 ◽  
Vol 12 (3) ◽  
pp. 887-903 ◽  
Author(s):  
Y. Le Page ◽  
D. Morton ◽  
B. Bond-Lamberty ◽  
J. M. C. Pereira ◽  
G. Hurtt
Keyword(s):  
Interannual Variability ◽  
Anthropogenic Activities ◽  
Optimization Procedure ◽  
Realistic Model ◽  
Ecosystem Dynamics ◽  
Burned Area ◽  
Model Parameters ◽  
Observation Data ◽  
Fire Model ◽  
Fire Activity

Abstract. Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spread over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.

scholarly journals Appraising the capability of a land biosphere model as a tool in modelling land surface interactions: results from its validation at selected European ecosystems

2015 ◽  
Vol 6 (1) ◽  
pp. 217-265 ◽  
Author(s):  
M. R. North ◽  
G. P. Petropoulos ◽  
G. Ireland ◽  
J. P. McCalmont
Keyword(s):  
Land Surface ◽  
Model Performance ◽  
Global Scale ◽  
Surface Interactions ◽  
Climatic Conditions ◽  
Model Parameters ◽  
Observation Data ◽  
Ongoing Research ◽  
In Situ Data

Abstract. In this present study the ability of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) model in estimating key parameters characterising land surface interactions was evaluated. Specifically, SimSphere's performance in predicting Net Radiation (Rnet), Latent Heat (LE), Sensible Heat (H) and Air Temperature (Tair) at 1.3 and 50 m was examined. Model simulations were validated by ground-based measurements of the corresponding parameters for a total of 70 days of the year 2011 from 7 CarboEurope network sites. These included a variety of biomes, environmental and climatic conditions in the models evaluation. Overall, model performance can largely be described as satisfactory for most of the experimental sites and evaluated parameters. For all model parameters compared, predicted H fluxes consistently obtained the highest agreement to the in-situ data in all ecosystems, with an average RMSD of 55.36 W m−2. LE fluxes and Rnet also agreed well with the in-situ data with RSMDs of 62.75 and 64.65 W m−2 respectively. A good agreement between modelled and measured LE and H fluxes was found, especially for smoothed daily flux trends. For both Tair 1.3 m and Tair 50 m a mean RMSD of 4.14 and 3.54 °C was reported respectively. This work presents the first all-inclusive evaluation of SimSphere, particularly so in a European setting. Results of this study contribute decisively towards obtaining a better understanding of the model's structure and its correspondence to the real world system. Findings also further establish the model's capability as a useful teaching and research tool in modelling Earth's land surface interactions. This is of considerable importance in the light of the rapidly expanding use of the model worldwide, including ongoing research by various Space Agencies examining its synergistic use with Earth Observation data towards the development of operational products at a global scale.

scholarly journals The global biological microplastic particle sink

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
K. Kvale ◽  
A. E. F. Prowe ◽  
C.-T. Chien ◽  
A. Landolfi ◽  
A. Oschlies
Keyword(s):  
Global Scale ◽  
System Model ◽  
Global Ocean ◽  
Model Parameters ◽  
Marine Snow ◽  
Earth System ◽  
Removal Mechanism ◽  
Lagrangian Particle ◽  
Faecal Pellets ◽  
Biological Uptake

Abstract Every year, about four percent of the plastic waste generated worldwide ends up in the ocean. What happens to the plastic there is poorly understood, though a growing body of evidence suggests it is rapidly spreading throughout the global ocean. The mechanisms of this spread are straightforward for buoyant larger plastics that can be accurately modelled using Lagrangian particle models. But the fate of the smallest size fractions (the microplastics) are less straightforward, in part because they can aggregate in sinking marine snow and faecal pellets. This biologically-mediated pathway is suspected to be a primary surface microplastic removal mechanism, but exactly how it might work in the real ocean is unknown. We search the parameter space of a new microplastic model embedded in an earth system model to show that biological uptake can significantly shape global microplastic inventory and distributions and even account for the budgetary “missing” fraction of surface microplastic, despite being an inefficient removal mechanism. While a lack of observational data hampers our ability to choose a set of “best” model parameters, our effort represents a first tool for quantitatively assessing hypotheses for microplastic interaction with ocean biology at the global scale.

Global estimation of rainfall-runoff model parameters: an empirical experiment

2021 ◽  
Author(s):  
Léonard Santos ◽  
Jafet C. M. Andersson ◽  
Berit Arheimer
Keyword(s):  
Land Use ◽  
Parameter Estimation ◽  
World Wide ◽  
Global Scale ◽  
Second Step ◽  
Model Parameters ◽  
Earth System ◽  
Climate Classification ◽  
Soil Map ◽  
Parameter Values

<p>When setting up global scale hydrological models, parameter estimation is a crucial step. Some modellers assign pre-defined parameter values to physical characteristics (such as soil, land cover, etc.) while others estimate parameter values based on observed hydrological data. In both cases, the regionalisation of parameters is a major challenge since both literature values and observed data are often lacking and assumptions are needed. This work aims at identifying suitable parameter regions to perform a regional calibration of the global model World-Wide HYPE (Arheimer et al., 2020) through empirical tests.<br>The work is organised in two steps. First we compare different ways of taking soil into account when creating hydrological response units. The soil is either considered uniform, indexed to land use or to a simplified soil map. The best soil representation is selected based on the model performance at a global scale. Based on this best representation, the second step aims at evaluating different ways to regionalise the soil parameters of the hydrological model.  Previous classifications of hydrological uniform regions are tested for regionalisation of model parameters: hydrobelts (Meybeck et al., 2013), Köppen climate regions (Kottek et al., 2006), soil capacity index (Wang-Erlandsson et al., 2016) and hydroclimatic regions (Knoben et al., 2018).<br>For the first step, the results show that the best solution is to represent soil by land use. This counterintuitive result is due to the fact that adding information based on a soil map add another calibration step. To avoid increased equifinality, such an effort increases the need for data, which is often lacking at the global scale.  For the second step, the creation of parameter regions contributed with minor improvement in terms of model performances, probably because the choice of regions was not suitable for the model approach. Also, the improvement has shown to be higher when available discharge data for calibration were better distributed over the different regions. This work shows that, when calibrating a model at very large scale, a balance should be found between available data and parameter regions resolution. </p><p><br><strong>References</strong><br>Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation, Hydrol. Earth Syst. Sci. 24, 535–559, 2020.<br>Knoben, W. J., Woods, R. A., and Freer, J. E.: A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data. Water Resources Research, 54(7), 5088-5109, 2018.<br>Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15, 259-263, 2006.<br>Meybeck, M., Kummu, M., and Dürr, H. H.: Global hydrobelts and hydroregions: improved reporting scale for waterrelated issues? Hydrology and Earth System Sciences, 17(3), 1093-1111, 2013.<br>Wang-Erlandsson, L., Bastiaanssen, W. G. M., Gao, H., Jägermeyr, J., Senay, G. B., van Dijk, A. I. J. M., Guerschman, J. P., Keys, P. W., Gordon, L. J., and Savenije, H. H. G.: Global root zone storage capacity from satellite-based evaporation, Hydrology Earth System Sciences, 20, 1459-1481, 2016.</p>

Preliminary uncertainty analysis – a prerequisite for assessing the predictive uncertainty of hydrologic models

1996 ◽  
Vol 33 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Jian Hua Lei ◽  
Wolfgang Schilling
Keyword(s):  
Uncertainty Analysis ◽  
Model Parameters ◽  
Observation Data ◽  
Calibration Data ◽  
Model Output ◽  
Predictive Uncertainty ◽  
Runoff Volume ◽  
Output Uncertainty ◽  
Sensitive Parameters ◽  
Calculated Model

Physically-based urban rainfall-runoff models are mostly applied without parameter calibration. Given some preliminary estimates of the uncertainty of the model parameters the associated model output uncertainty can be calculated. Monte-Carlo simulation followed by multi-linear regression is used for this analysis. The calculated model output uncertainty can be compared to the uncertainty estimated by comparing model output and observed data. Based on this comparison systematic or spurious errors can be detected in the observation data, the validity of the model structure can be confirmed, and the most sensitive parameters can be identified. If the calculated model output uncertainty is unacceptably large the most sensitive parameters should be calibrated to reduce the uncertainty. Observation data for which systematic and/or spurious errors have been detected should be discarded from the calibration data. This procedure is referred to as preliminary uncertainty analysis; it is illustrated with an example. The HYSTEM program is applied to predict the runoff volume from an experimental catchment with a total area of 68 ha and an impervious area of 20 ha. Based on the preliminary uncertainty analysis, for 7 of 10 events the measured runoff volume is within the calculated uncertainty range, i.e. less than or equal to the calculated model predictive uncertainty. The remaining 3 events include most likely systematic or spurious errors in the observation data (either in the rainfall or the runoff measurements). These events are then discarded from further analysis. After calibrating the model the predictive uncertainty of the model is estimated.

scholarly journals Enhanced Neural Network Model for Worldwide Estimation of Weighted Mean Temperature

2021 ◽  
Vol 13 (12) ◽  
pp. 2405
Author(s):  
Fengyang Long ◽  
Chengfa Gao ◽  
Yuxiang Yan ◽  
Jinling Wang
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Model Performance ◽  
Global Scale ◽  
Radiosonde Data ◽  
Model Parameters ◽  
Measured Temperature ◽  
Weighted Mean ◽  
Weighted Mean Temperature ◽  
Application Scope

Precise modeling of weighted mean temperature (Tm) is critical for realizing real-time conversion from zenith wet delay (ZWD) to precipitation water vapor (PWV) in Global Navigation Satellite System (GNSS) meteorology applications. The empirical Tm models developed by neural network techniques have been proved to have better performances on the global scale; they also have fewer model parameters and are thus easy to operate. This paper aims to further deepen the research of Tm modeling with the neural network, and expand the application scope of Tm models and provide global users with more solutions for the real-time acquisition of Tm. An enhanced neural network Tm model (ENNTm) has been developed with the radiosonde data distributed globally. Compared with other empirical models, the ENNTm has some advanced features in both model design and model performance, Firstly, the data for modeling cover the whole troposphere rather than just near the Earth’s surface; secondly, the ensemble learning was employed to weaken the impact of sample disturbance on model performance and elaborate data preprocessing, including up-sampling and down-sampling, which was adopted to achieve better model performance on the global scale; furthermore, the ENNTm was designed to meet the requirements of three different application conditions by providing three sets of model parameters, i.e., Tm estimating without measured meteorological elements, Tm estimating with only measured temperature and Tm estimating with both measured temperature and water vapor pressure. The validation work is carried out by using the radiosonde data of global distribution, and results show that the ENNTm has better performance compared with other competing models from different perspectives under the same application conditions, the proposed model expanded the application scope of Tm estimation and provided the global users with more choices in the applications of real-time GNSS-PWV retrival.

scholarly journals Forest summer albedo is sensitive to species and thinning: how should we account for this in Earth system models?

2014 ◽  
Vol 11 (8) ◽  
pp. 2411-2427 ◽  
Author(s):  
J. Otto ◽  
D. Berveiller ◽  
F.-M. Bréon ◽  
N. Delpierre ◽  
G. Geppert ◽  
...  
Keyword(s):  
Forest Management ◽  
Tree Species ◽  
Near Infrared ◽  
Model Parameters ◽  
Earth System ◽  
Forest Thinning ◽  
Area Index ◽  
System Models ◽  
Maximum Change ◽  
Earth System Models

Abstract. Although forest management is one of the instruments proposed to mitigate climate change, the relationship between forest management and canopy albedo has been ignored so far by climate models. Here we develop an approach that could be implemented in Earth system models. A stand-level forest gap model is combined with a canopy radiation transfer model and satellite-derived model parameters to quantify the effects of forest thinning on summertime canopy albedo. This approach reveals which parameter has the largest affect on summer canopy albedo: we examined the effects of three forest species (pine, beech, oak) and four thinning strategies with a constant forest floor albedo (light to intense thinning regimes) and five different solar zenith angles at five different sites (40° N 9° E–60° N 9° E). During stand establishment, summertime canopy albedo is driven by tree species. In the later stages of stand development, the effect of tree species on summertime canopy albedo decreases in favour of an increasing influence of forest thinning. These trends continue until the end of the rotation, where thinning explains up to 50% of the variance in near-infrared albedo and up to 70% of the variance in visible canopy albedo. The absolute summertime canopy albedo of all species ranges from 0.03 to 0.06 (visible) and 0.20 to 0.28 (near-infrared); thus the albedo needs to be parameterised at species level. In addition, Earth system models need to account for forest management in such a way that structural changes in the canopy are described by changes in leaf area index and crown volume (maximum change of 0.02 visible and 0.05 near-infrared albedo) and that the expression of albedo depends on the solar zenith angle (maximum change of 0.02 visible and 0.05 near-infrared albedo). Earth system models taking into account these parameters would not only be able to examine the spatial effects of forest management but also the total effects of forest management on climate.

scholarly journals Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy

2004 ◽  
Vol 92 (2) ◽  
pp. 959-976 ◽  
Author(s):  
Renaud Jolivet ◽  
Timothy J. Lewis ◽  
Wulfram Gerstner
Keyword(s):  
Cortical Neurons ◽  
Direct Reduction ◽  
Spike Trains ◽  
Model Parameters ◽  
Detailed Model ◽  
Fire Model ◽  
Integrate And Fire ◽  
Fire Models ◽  
Wide Range ◽  
Simple Models

We demonstrate that single-variable integrate-and-fire models can quantitatively capture the dynamics of a physiologically detailed model for fast-spiking cortical neurons. Through a systematic set of approximations, we reduce the conductance-based model to 2 variants of integrate-and-fire models. In the first variant (nonlinear integrate-and-fire model), parameters depend on the instantaneous membrane potential, whereas in the second variant, they depend on the time elapsed since the last spike [Spike Response Model (SRM)]. The direct reduction links features of the simple models to biophysical features of the full conductance-based model. To quantitatively test the predictive power of the SRM and of the nonlinear integrate-and-fire model, we compare spike trains in the simple models to those in the full conductance-based model when the models are subjected to identical randomly fluctuating input. For random current input, the simple models reproduce 70–80 percent of the spikes in the full model (with temporal precision of ±2 ms) over a wide range of firing frequencies. For random conductance injection, up to 73 percent of spikes are coincident. We also present a technique for numerically optimizing parameters in the SRM and the nonlinear integrate-and-fire model based on spike trains in the full conductance-based model. This technique can be used to tune simple models to reproduce spike trains of real neurons.

scholarly journals Comparison of ocean vertical mixing schemes in the Max Plank Institute Earth System Model (MPI-ESM1.2)

2020 ◽  
Author(s):  
Oliver Gutjahr ◽  
Nils Brüggemann ◽  
Helmuth Haak ◽  
Johann H. Jungclaus ◽  
Dian A. Putrasahan ◽  
...  
Keyword(s):  
Vertical Mixing ◽  
Global Scale ◽  
Earth System Model ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Max Planck ◽  
Vertical Diffusion ◽  
Mixing Schemes ◽  
Mean State

Abstract. We compare the effects of four different ocean vertical mixing schemes on the ocean mean state simulated by the Max Planck Institute Earth System Model (MPI-ESM1.2) in the framework of the Community Vertical Mixing (CVMix) library. Besides the PP and KPP scheme, we implemented the TKE scheme and a recently developed prognostic scheme for internal wave energy and its dissipation (IDEMIX) to replace the often assumed constant background diffusivity in the ocean interior. We analyse in particular the effects of IDEMIX on the ocean mean state, when combined with TKE (TKE+IDEMIX). In general, we find little sensitivity of the ocean surface, but considerable effects for the interior ocean. Overall, we cannot classify any scheme as superior, because they modify biases that vary by region or variable, but produce a similar pattern on the global scale. However, using a more realistic and energetically consistent scheme (TKE+IDEMIX) produces a more heterogeneous pattern of vertical diffusion, with lower diffusivity in deep and flat-bottom basins and elevated turbulence over rough topography. In addition, TKE+IDEMIX improves the circulation in the Nordic Seas and Fram Strait, thus reducing the warm bias of the Atlantic water (AW) layer in the Arctic Ocean to a similar extent as has been demonstrated with eddy-resolving ocean models. We conclude that although shortcomings due to model resolution determine the global-scale bias pattern, the choice of the vertical mixing scheme may play an important role for regional biases.

scholarly journals Recent climatic, cryospheric, and hydrological changes over the interior of western Canada: a synthesis and review

2015 ◽  
Vol 12 (8) ◽  
pp. 8615-8674 ◽  
Author(s):  
C. M. DeBeer ◽  
H. S. Wheater ◽  
S. K. Carey ◽  
K. P. Chun
Keyword(s):  
Temporal Trends ◽  
Global Scale ◽  
Western Canada ◽  
Earth System ◽  
Predictive Capacity ◽  
Late 20Th Century ◽  
Cold Regions ◽  
Mountain Glaciers ◽  
System Components ◽  
Earth’S Climate

Abstract. It is well-established that the Earth's climate system has warmed significantly over the past several decades, and in association there have been widespread changes in various other Earth system components. This has been especially prevalent in the cold regions of the northern mid to high-latitudes. Examples of these changes can be found within the western and northern interior of Canada, a region that exemplifies the scientific and societal issues faced in many other similar parts of the world, and where impacts have global-scale consequences. This region has been the geographic focus of a large amount of previous research on changing climatic, cryospheric, and hydrological Earth system components in recent decades, while current initiatives such as the Changing Cold Regions Network (CCRN) seek to further develop the understanding and diagnosis of this change and hence improve predictive capacity. This paper provides an integrated review of the observed changes in these Earth system components and a concise and up-to-date regional picture of some of the temporal trends over the interior of western Canada since the mid or late-20th century. The focus is on air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, and river discharge. Important long-term observational networks and datasets are described, and qualitative linkages among the changing components are highlighted. Systematic warming and significant changes to precipitation, snow and ice regimes are unambiguous. However, integrated effects on streamflow are complex. It is argued that further diagnosis is required before predictions of future change can be made with confidence.

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