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Автор: Grafiati

Опубліковано: 9 червня 2023

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1

Edwards, Neil R., David Cameron, and Jonathan Rougier. "Precalibrating an intermediate complexity climate model." Climate Dynamics 37, no. 7-8 (October 13, 2010): 1469–82. http://dx.doi.org/10.1007/s00382-010-0921-0.

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2

Gutmann, Ethan, Idar Barstad, Martyn Clark, Jeffrey Arnold, and Roy Rasmussen. "The Intermediate Complexity Atmospheric Research Model (ICAR)." Journal of Hydrometeorology 17, no. 3 (March 1, 2016): 957–73. http://dx.doi.org/10.1175/jhm-d-15-0155.1.

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Abstract With limited computational resources, there is a need for computationally frugal models. This is particularly the case for atmospheric sciences, which have long relied on either simplistic analytical solutions or computationally expensive numerical models. The simpler solutions are inadequate for many problems, while the cost of numerical models makes their use impossible for many problems, most notably high-resolution climate downscaling applications spanning large areas, long time periods, and many global climate projections. Here the Intermediate Complexity Atmospheric Research model (ICAR) is presented to provide a new step along the modeling complexity continuum. ICAR leverages an analytical solution for high-resolution perturbations to wind velocities, in conjunction with numerical physics schemes, that is, advection and cloud microphysics, to simulate the atmosphere. The focus of the initial development of ICAR is for predictions of precipitation, and eventually temperature, humidity, and radiation at the land surface. Comparisons between ICAR and the Weather Research and Forecasting (WRF) Model for simulations over an idealized mountain are presented, as well as among ICAR, WRF, and the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) observation-based product for a year-long simulation over the Colorado Rockies. In the ideal simulations, ICAR matches WRF precipitation predictions across a range of environmental conditions with a coefficient of determination r2 of 0.92. In the Colorado Rockies, ICAR, WRF, and PRISM show very good agreement, with differences between ICAR and WRF comparable to the differences between WRF and PRISM in the cool season. For these simulations, WRF required 140–800 times more computational resources than ICAR.

3

Roy, Manojit, Karin Harding, and Robert D. Holt. "Generalizing Levins metapopulation model in explicit space: Models of intermediate complexity." Journal of Theoretical Biology 255, no. 1 (November 2008): 152–61. http://dx.doi.org/10.1016/j.jtbi.2008.07.022.

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4

Lehmann, B., D. Gyalistras, M. Gwerder, K. Wirth, and S. Carl. "Intermediate complexity model for Model Predictive Control of Integrated Room Automation." Energy and Buildings 58 (March 2013): 250–62. http://dx.doi.org/10.1016/j.enbuild.2012.12.007.

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5

Holden, P. B., N. R. Edwards, K. Fraedrich, E. Kirk, F. Lunkeit, and X. Zhu. "PLASIM-GENIE: a new intermediate complexity AOGCM." Geoscientific Model Development Discussions 8, no. 12 (December 18, 2015): 10677–710. http://dx.doi.org/10.5194/gmdd-8-10677-2015.

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Abstract. We describe the development, tuning and climate of PLASIM-GENIE, a new intermediate complexity Atmosphere–Ocean Global Climate Model (AOGCM), built by coupling the Planet Simulator to the GENIE earth system model. PLASIM-GENIE supersedes "GENIE-2", a coupling of GENIE to the Reading IGCM. It has been developed to join the limited number of models that bridge the gap between EMICS with simplified atmospheric dynamics and state of the art AOGCMs. A 1000 year simulation with PLASIM-GENIE requires approximately two weeks on a single node of a 2.1 GHz AMD 6172 CPU. An important motivation for intermediate complexity models is the evaluation of uncertainty. We here demonstrate the tractability of PLASIM-GENIE ensembles by deriving a "subjective" tuning of the model with a 50 member ensemble of 1000 year simulations.

6

Gushchina, D. Yu, B. Dewitte, and S. A. Korkmazova. "Intraseasonal tropical variability in an intermediate complexity atmospheric model." Russian Meteorology and Hydrology 35, no. 4 (April 2010): 237–52. http://dx.doi.org/10.3103/s1068373910040011.

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7

Holden, Philip B., Neil R. Edwards, Klaus Fraedrich, Edilbert Kirk, Frank Lunkeit, and Xiuhua Zhu. "PLASIM–GENIE v1.0: a new intermediate complexity AOGCM." Geoscientific Model Development 9, no. 9 (September 21, 2016): 3347–61. http://dx.doi.org/10.5194/gmd-9-3347-2016.

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Abstract. We describe the development, tuning and climate of Planet Simulator (PLASIM)–Grid-ENabled Integrated Earth system model (GENIE), a new intermediate complexity Atmosphere–Ocean General Circulation Model (AOGCM), built by coupling the Planet Simulator to the ocean, sea-ice and land-surface components of the GENIE Earth system model. PLASIM–GENIE supersedes GENIE-2, a coupling of GENIE to the Reading Intermediate General Circulation Model (IGCM). The primitive-equation atmosphere includes chaotic, three-dimensional (3-D) motion and interactive radiation and clouds, and dominates the computational load compared to the relatively simpler frictional-geostrophic ocean, which neglects momentum advection. The model is most appropriate for long-timescale or large ensemble studies where numerical efficiency is prioritised, but lack of data necessitates an internally consistent, coupled calculation of both oceanic and atmospheric fields. A 1000-year simulation with PLASIM–GENIE requires approximately 2 weeks on a single node of a 2.1 GHz AMD 6172 CPU. We demonstrate the tractability of PLASIM–GENIE ensembles by deriving a subjective tuning of the model with a 50-member ensemble of 1000-year simulations. The simulated climate is presented considering (i) global fields of seasonal surface air temperature, precipitation, wind, solar and thermal radiation, with comparisons to reanalysis data; (ii) vegetation carbon, soil moisture and aridity index; and (iii) sea surface temperature, salinity and ocean circulation. Considering its resolution, PLASIM–GENIE reproduces the main features of the climate system well and demonstrates usefulness for a wide range of applications.

8

Perry, Joe N. "Host-Parasitoid Models of Intermediate Complexity." American Naturalist 130, no. 6 (December 1987): 955–57. http://dx.doi.org/10.1086/284759.

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9

Moore, J. Keith, Scott C. Doney, Joanie A. Kleypas, David M. Glover, and Inez Y. Fung. "An intermediate complexity marine ecosystem model for the global domain." Deep Sea Research Part II: Topical Studies in Oceanography 49, no. 1-3 (January 2001): 403–62. http://dx.doi.org/10.1016/s0967-0645(01)00108-4.

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10

Ehrendorfer, Martin, and Ronald M. Errico. "An atmospheric model of intermediate complexity for data assimilation studies." Quarterly Journal of the Royal Meteorological Society 134, no. 636 (October 2008): 1717–32. http://dx.doi.org/10.1002/qj.329.

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11

Saffin, Leo, Sam Hatfield, Peter Düben, and Tim Palmer. "Reduced‐precision parametrization: lessons from an intermediate‐complexity atmospheric model." Quarterly Journal of the Royal Meteorological Society 146, no. 729 (February 19, 2020): 1590–607. http://dx.doi.org/10.1002/qj.3754.

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12

Ganopolski, A., V. Petoukhov, S. Rahmstorf, V. Brovkin, M. Claussen, A. Eliseev, and C. Kubatzki. "CLIMBER-2: a climate system model of intermediate complexity. Part II: model sensitivity." Climate Dynamics 17, no. 10 (July 1, 2001): 735–51. http://dx.doi.org/10.1007/s003820000144.

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13

Bellon, Gilles, and Adam Sobel. "Poleward-Propagating Intraseasonal Monsoon Disturbances in an Intermediate-Complexity Axisymmetric Model." Journal of the Atmospheric Sciences 65, no. 2 (February 1, 2008): 470–89. http://dx.doi.org/10.1175/2007jas2339.1.

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Abstract A model of intermediate complexity based on quasi-equilibrium theory—a version of the quasi-equilibrium tropical circulation model with a prognostic atmospheric boundary layer, as well as two free-tropospheric modes in momentum, and one each in moisture and temperature—is used in a zonally symmetric aquaplanet configuration to simulate aspects of the South Asian monsoon and its variability. Key qualitative features of both the mean state and the 30–60-day mode of the intraseasonal variability are simulated satisfactorily. The model has two limit cycles of similar period and structure that can account for this mode. Both feature northward propagation of the tropical convergence zone from 5°S to 25°N with a period of about 50 days. The dynamics of the oscillations are investigated. The system reaches a Hopf bifurcation when the asymmetry of the sea surface temperature (SST) forcing is increased. Beyond the bifurcation, the mean flow is linearly unstable, and the one linearly unstable mode is similar in structure and period to the nonlinear mode. The wind-induced surface heat fluxes are necessary to obtain the instability of the mean monsoon flow, as are the 2 degrees of freedom in the vertical structure of both humidity and wind.

14

Stone, P. H., and M. S. Yao. "The ice-covered Earth instability in a model of intermediate complexity." Climate Dynamics 22, no. 8 (May 19, 2004): 815–22. http://dx.doi.org/10.1007/s00382-004-0408-y.

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15

Goosse, H., V. Brovkin, T. Fichefet, R. Haarsma, P. Huybrechts, J. Jongma, A. Mouchet, et al. "Description of the Earth system model of intermediate complexity LOVECLIM version 1.2." Geoscientific Model Development 3, no. 2 (November 2, 2010): 603–33. http://dx.doi.org/10.5194/gmd-3-603-2010.

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Abstract. The main characteristics of the new version 1.2 of the three-dimensional Earth system model of intermediate complexity LOVECLIM are briefly described. LOVECLIM 1.2 includes representations of the atmosphere, the ocean and sea ice, the land surface (including vegetation), the ice sheets, the icebergs and the carbon cycle. The atmospheric component is ECBilt2, a T21, 3-level quasi-geostrophic model. The ocean component is CLIO3, which consists of an ocean general circulation model coupled to a comprehensive thermodynamic-dynamic sea-ice model. Its horizontal resolution is of 3° by 3°, and there are 20 levels in the ocean. ECBilt-CLIO is coupled to VECODE, a vegetation model that simulates the dynamics of two main terrestrial plant functional types, trees and grasses, as well as desert. VECODE also simulates the evolution of the carbon cycle over land while the ocean carbon cycle is represented by LOCH, a comprehensive model that takes into account both the solubility and biological pumps. The ice sheet component AGISM is made up of a three-dimensional thermomechanical model of the ice sheet flow, a visco-elastic bedrock model and a model of the mass balance at the ice-atmosphere and ice-ocean interfaces. For both the Greenland and Antarctic ice sheets, calculations are made on a 10 km by 10 km resolution grid with 31 sigma levels. LOVECLIM1.2 reproduces well the major characteristics of the observed climate both for present-day conditions and for key past periods such as the last millennium, the mid-Holocene and the Last Glacial Maximum. However, despite some improvements compared to earlier versions, some biases are still present in the model. The most serious ones are mainly located at low latitudes with an overestimation of the temperature there, a too symmetric distribution of precipitation between the two hemispheres, and an overestimation of precipitation and vegetation cover in the subtropics. In addition, the atmospheric circulation is too weak. The model also tends to underestimate the surface temperature changes (mainly at low latitudes) and to overestimate the ocean heat uptake observed over the last decades.

16

Goosse, H., V. Brovkin, T. Fichefet, R. Haarsma, P. Huybrechts, J. Jongma, A. Mouchet, et al. "Description of the Earth system model of intermediate complexity LOVECLIM version 1.2." Geoscientific Model Development Discussions 3, no. 1 (March 30, 2010): 309–90. http://dx.doi.org/10.5194/gmdd-3-309-2010.

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Abstract. The main characteristics of the new version 1.2 of the three-dimensional Earth system model of intermediate complexity LOVECLIM are briefly described. LOVECLIM 1.2 includes representations of the atmosphere, the ocean and sea ice, the land surface (including vegetation), the ice sheets, the icebergs and the carbon cycle. The atmospheric component is ECBilt2, a T21, 3-level quasi-geostrophic model. The oceanic component is CLIO3, which is made up of an ocean general circulation model coupled to a comprehensive thermodynamic-dynamic sea-ice model. Its horizontal resolution is 3° by 3°, and there are 20 levels in the ocean. ECBilt-CLIO is coupled to VECODE, a vegetation model that simulates the dynamics of two main terrestrial plant functional types, trees and grasses, as well as desert. VECODE also simulates the evolution of the carbon cycle over land while the oceanic carbon cycle is represented in LOCH, a comprehensive model that takes into account both the solubility and biological pumps. The ice sheet component AGISM is made up of a three-dimensional thermomechanical model of the ice sheet flow, a visco-elastic bedrock model and a model of the mass balance at the ice-atmosphere and ice ocean interfaces. For both the Greenland and Antarctic ice sheets, calculations are made on a 10 km by 10 km resolution grid with 31 sigma levels. LOVECLIM 1.2 reproduces well the major characteristics of the observed climate both for present-day conditions and for key past periods such as the last millennium, the mid-Holocene and the Last Glacial Maximum. However, despite some improvements compared to earlier versions, some biases are still present in the model. The most serious ones are mainly located at low latitudes with an overestimation of the temperature there, a too symmetric distribution of precipitation between the two hemispheres, an overestimation of precipitation and vegetation cover in the subtropics. In addition, the atmospheric circulation is too weak. The model also tends to underestimate the surface temperature changes (mainly at low latitudes) and to overestimate the ocean heat uptake observed over the last decades.

17

Ullman, David J., and Andreas Schmittner. "A cloud feedback emulator (CFE, version 1.0) for an intermediate complexity model." Geoscientific Model Development 10, no. 2 (February 23, 2017): 945–58. http://dx.doi.org/10.5194/gmd-10-945-2017.

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Abstract. The dominant source of inter-model differences in comprehensive global climate models (GCMs) are cloud radiative effects on Earth's energy budget. Intermediate complexity models, while able to run more efficiently, often lack cloud feedbacks. Here, we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4 × CO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.

18

Weber, S. L., and J. Oerlemans. "Holocene glacier variability: three case studies using an intermediate-complexity climate model." Holocene 13, no. 3 (April 2003): 353–63. http://dx.doi.org/10.1191/0959683603hl628rp.

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19

Babanin, Alexander V., Andrey Ganopolski, and William R. C. Phillips. "Wave-induced upper-ocean mixing in a climate model of intermediate complexity." Ocean Modelling 29, no. 3 (January 2009): 189–97. http://dx.doi.org/10.1016/j.ocemod.2009.04.003.

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20

Bellon, Gilles, and Adam H. Sobel. "Multiple Equilibria of the Hadley Circulation in an Intermediate-Complexity Axisymmetric Model." Journal of Climate 23, no. 7 (April 1, 2010): 1760–78. http://dx.doi.org/10.1175/2009jcli3105.1.

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Abstract A model of intermediate complexity based on quasi-equilibrium theory—a version of the Quasi-Equilibrium Tropical Circulation Model with a prognostic atmospheric boundary layer, as well as two free-tropospheric modes in momentum, and one each in moisture and temperature—is used in a zonally symmetric aquaplanet configuration to study the sensitivity of the Hadley circulation to the sea surface temperature (SST) latitudinal distribution. For equatorially symmetric SST forcing with large SST gradients in the tropics, the model simulates the classical double Hadley cell with one equatorial intertropical convergence zone (ITCZ). For small SST gradients in the tropics, the model exhibits multiple equilibria, with one equatorially symmetric equilibrium and two asymmetric equilibria (mirror images of each other) with an off-equatorial ITCZ. Further investigation of the feedbacks at play in the model shows that the assumed vertical structure of temperature variations is crucial to the existence and stability of the asymmetric equilibria. The free-tropospheric moisture–convection feedback must also be sufficiently strong to sustain asymmetric equilibria. Both results suggest that the specific physics of a given climate model condition determine the existence of multiple equilibria via the resulting sensitivity of the convection to free-tropospheric humidity and the vertical structure of adiabatic heating. The symmetry-breaking mechanism and resulting multiple equilibria have their origin in the local multiple equilibria that can be described by a single-column model using the weak temperature gradient approximation. An additional experiment using an SST latitudinal distribution with a relative minimum at the equator shows that the feedbacks controlling these multiple equilibria might be relevant to the double-ITCZ problem.

21

Eby, M., A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, et al. "Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity." Climate of the Past 9, no. 3 (May 16, 2013): 1111–40. http://dx.doi.org/10.5194/cp-9-1111-2013.

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Abstract. Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

22

Herein, Mátyás, János Márfy, Gábor Drótos, and Tamás Tél. "Probabilistic Concepts in Intermediate-Complexity Climate Models: A Snapshot Attractor Picture." Journal of Climate 29, no. 1 (December 31, 2015): 259–72. http://dx.doi.org/10.1175/jcli-d-15-0353.1.

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Abstract A time series resulting from a single initial condition is shown to be insufficient for quantifying the internal variability in a climate model, and thus one is unable to make meaningful climate projections based on it. The authors argue that the natural distribution, obtained from an ensemble of trajectories differing solely in their initial conditions, of the snapshot attractor corresponding to a particular forcing scenario should be determined in order to quantify internal variability and to characterize any instantaneous state of the system in the future. Furthermore, as a simple measure of internal variability of any particular variable of the model, the authors suggest using its instantaneous ensemble standard deviation. These points are illustrated with the intermediate-complexity climate model Planet Simulator forced by a CO2 scenario, with a 40-member ensemble. In particular, the leveling off of the time dependence of any ensemble average is shown to provide a much clearer indication of reaching a steady state than any property of single time series. Shifts in ensemble averages are indicative of climate changes. The dynamical character of such changes is illustrated by hysteresis-like curves obtained by plotting the ensemble average surface temperature versus the CO2 concentration. The internal variability is found to be the most pronounced on small geographical scales. The traditionally used 30-yr temporal averages are shown to be considerably different from the corresponding ensemble averages. Finally, the North Atlantic Oscillation (NAO) index, related to the teleconnection paradigm, is also investigated. It is found that the NAO time series strongly differs in any individual realization from each other and from the ensemble average, and climatic trends can be extracted only from the latter.

23

Horak, Johannes, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach. "A process-based evaluation of the Intermediate Complexity Atmospheric Research Model (ICAR) 1.0.1." Geoscientific Model Development 14, no. 3 (March 23, 2021): 1657–80. http://dx.doi.org/10.5194/gmd-14-1657-2021.

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Abstract. The evaluation of models in general is a nontrivial task and can, due to epistemological and practical reasons, never be considered complete. Due to this incompleteness, a model may yield correct results for the wrong reasons, i.e., via a different chain of processes than found in observations. While guidelines and strategies exist in the atmospheric sciences to maximize the chances that models are correct for the right reasons, these are mostly applicable to full physics models, such as numerical weather prediction models. The Intermediate Complexity Atmospheric Research (ICAR) model is an atmospheric model employing linear mountain wave theory to represent the wind field. In this wind field, atmospheric quantities such as temperature and moisture are advected and a microphysics scheme is applied to represent the formation of clouds and precipitation. This study conducts an in-depth process-based evaluation of ICAR, employing idealized simulations to increase the understanding of the model and develop recommendations to maximize the probability that its results are correct for the right reasons. To contrast the obtained results from the linear-theory-based ICAR model to a full physics model, idealized simulations with the Weather Research and Forecasting (WRF) model are conducted. The impact of the developed recommendations is then demonstrated with a case study for the South Island of New Zealand. The results of this investigation suggest three modifications to improve different aspects of ICAR simulations. The representation of the wind field within the domain improves when the dry and the moist Brunt–Väisälä frequencies are calculated in accordance with linear mountain wave theory from the unperturbed base state rather than from the time-dependent perturbed atmosphere. Imposing boundary conditions at the upper boundary that are different to the standard zero-gradient boundary condition is shown to reduce errors in the potential temperature and water vapor fields. Furthermore, the results show that there is a lowest possible model top elevation that should not be undercut to avoid influences of the model top on cloud and precipitation processes within the domain. The method to determine the lowest model top elevation is applied to both the idealized simulations and the real terrain case study. Notable differences between the ICAR and WRF simulations are observed across all investigated quantities such as the wind field, water vapor and hydrometeor distributions, and the distribution of precipitation. The case study indicates that the precipitation maximum calculated by the ICAR simulation employing the developed recommendations is spatially shifted upwind in comparison to an unmodified version of ICAR. The cause for the shift is found in influences of the model top on cloud formation and precipitation processes in the ICAR simulations. Furthermore, the results show that when model skill is evaluated from statistical metrics based on comparisons to surface observations only, such an analysis may not reflect the skill of the model in capturing atmospheric processes like gravity waves and cloud formation.

24

Frederiksen, Carsten Segerlund, Jorgen S. Frederiksen, and Ramesh C. Balgovind. "Dynamic variability and seasonal predictability in an intermediate complexity coupled ocean-atmosphere model." ANZIAM Journal 54 (May 12, 2013): 34. http://dx.doi.org/10.21914/anziamj.v54i0.6296.

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25

Huntingford, C., B. B. B. Booth, S. Sitch, N. Gedney, J. A. Lowe, S. K. Liddicoat, L. M. Mercado, et al. "IMOGEN: an intermediate complexity model to evaluate terrestrial impacts of a changing climate." Geoscientific Model Development 3, no. 2 (November 29, 2010): 679–87. http://dx.doi.org/10.5194/gmd-3-679-2010.

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Abstract. We present a computationally efficient modelling system, IMOGEN, designed to undertake global and regional assessment of climate change impacts on the physical and biogeochemical behaviour of the land surface. A pattern-scaling approach to climate change drives a gridded land surface and vegetation model MOSES/TRIFFID. The structure allows extrapolation of General Circulation Model (GCM) simulations to different future pathways of greenhouse gases, including rapid first-order assessments of how the land surface and associated biogeochemical cycles might change. Evaluation of how new terrestrial process understanding influences such predictions can also be made with relative ease.

26

Yool, A., E. E. Popova, and T. R. Anderson. "Medusa-1.0: a new intermediate complexity plankton ecosystem model for the global domain." Geoscientific Model Development 4, no. 2 (May 10, 2011): 381–417. http://dx.doi.org/10.5194/gmd-4-381-2011.

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Abstract. The ongoing, anthropogenically-driven changes to the global ocean are expected to have significant consequences for plankton ecosystems in the future. Because of the role that plankton play in the ocean's "biological pump", changes in abundance, distribution and productivity will likely have additional consequences for the wider carbon cycle. Just as in the terrestrial biosphere, marine ecosystems exhibit marked diversity in species and functional types of organisms. Predicting potential change in plankton ecosystems therefore requires the use of models that are suited to this diversity, but whose parameterisation also permits robust and realistic functional behaviour. In the past decade, advances in model sophistication have attempted to address diversity, but have been criticised for doing so inaccurately or ahead of a requisite understanding of underlying processes. Here we introduce MEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification), a new "intermediate complexity" plankton ecosystem model that expands on traditional nutrient-phytoplankton-zooplankton-detritus (NPZD) models, and remains amenable to global-scale evaluation. MEDUSA-1.0 includes the biogeochemical cycles of nitrogen, silicon and iron, broadly structured into "small" and "large" plankton size classes, of which the "large" phytoplankton class is representative of a key phytoplankton group, the diatoms. A full description of MEDUSA-1.0's state variables, differential equations, functional forms and parameter values is included, with particular attention focused on the submodel describing the export of organic carbon from the surface to the deep ocean. MEDUSA-1.0 is used here in a multi-decadal hindcast simulation, and its biogeochemical performance evaluated at the global scale.

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Willeit, Matteo, and Andrey Ganopolski. "PALADYN v1.0, a comprehensive land surface–vegetation–carbon cycle model of intermediate complexity." Geoscientific Model Development 9, no. 10 (October 28, 2016): 3817–57. http://dx.doi.org/10.5194/gmd-9-3817-2016.

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Abstract. PALADYN is presented; it is a new comprehensive and computationally efficient land surface–vegetation–carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies. The model treats in a consistent manner the interaction between atmosphere, terrestrial vegetation and soil through the fluxes of energy, water and carbon. Energy, water and carbon are conserved. PALADYN explicitly treats permafrost, both in physical processes and as an important carbon pool. It distinguishes nine surface types: five different vegetation types, bare soil, land ice, lake and ocean shelf. Including the ocean shelf allows the treatment of continuous changes in sea level and shelf area associated with glacial cycles. Over each surface type, the model solves the surface energy balance and computes the fluxes of sensible, latent and ground heat and upward shortwave and longwave radiation. The model includes a single snow layer. Vegetation and bare soil share a single soil column. The soil is vertically discretized into five layers where prognostic equations for temperature, water and carbon are consistently solved. Phase changes of water in the soil are explicitly considered. A surface hydrology module computes precipitation interception by vegetation, surface runoff and soil infiltration. The soil water equation is based on Darcy's law. Given soil water content, the wetland fraction is computed based on a topographic index. The temperature profile is also computed in the upper part of ice sheets and in the ocean shelf soil. Photosynthesis is computed using a light use efficiency model. Carbon assimilation by vegetation is coupled to the transpiration of water through stomatal conductance. PALADYN includes a dynamic vegetation module with five plant functional types competing for the grid cell share with their respective net primary productivity. PALADYN distinguishes between mineral soil carbon, peat carbon, buried carbon and shelf carbon. Each soil carbon type has its own soil carbon pools generally represented by a litter, a fast and a slow carbon pool in each soil layer. Carbon can be redistributed between the layers by vertical diffusion and advection. For the vegetated macro surface type, decomposition is a function of soil temperature and soil moisture. Carbon in permanently frozen layers is assigned a long turnover time which effectively locks carbon in permafrost. Carbon buried below ice sheets and on flooded ocean shelves is treated differently. The model also includes a dynamic peat module. PALADYN includes carbon isotopes 13C and 14C, which are tracked through all carbon pools. Isotopic discrimination is modelled only during photosynthesis. A simple methane module is implemented to represent methane emissions from anaerobic carbon decomposition in wetlands (including peatlands) and flooded ocean shelf. The model description is accompanied by a thorough model evaluation in offline mode for the present day and the historical period.

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Farneti, R., and G. K. Vallis. "An Intermediate Complexity Climate Model (ICCM) based on the GFDL Flexible Modelling System." Geoscientific Model Development Discussions 2, no. 1 (April 22, 2009): 341–83. http://dx.doi.org/10.5194/gmdd-2-341-2009.

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Abstract. An intermediate complexity coupled ocean-atmosphere-land-ice model, based on the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modelling System (FMS), has been developed to study mechanisms of ocean-atmosphere interactions and natural climate variability at interannual to interdecadal and longer time scales. The model uses the three-dimensional primitive equations for both ocean and atmosphere, but is simplified from a "state of the art" coupled model in two respects: it uses simplified physics and parameterisation schemes, especially in the atmosphere, and idealised geometry and geography. These simplifications provide considerable savings in computational expense and, perhaps more importantly, allow mechanisms to be investigated more cleanly and thoroughly than with a more elaborate model. For example, the model allows integrations of several millennia as well as broad parameter studies. For the ocean, the model uses the free surface primitive equations Modular Ocean Model (MOM) and the GFDL/FMS sea-ice model (SIS) is coupled to the oceanic grid. The atmospheric component consists of the FMS B-grid moist primitive equations atmospheric dynamical core with highly simplified physical parameterisations. A simple bucket model is implemented for our idealised land following the GFDL/FMS Land model. Here we describe the model components and present a climatology of coupled simulations achieved with two different geometrical configurations. Throughout the paper, we give a flavour of the potential for this model to be a powerful tool for the climate modelling community by mentioning a wide range of studies that are currently being explored.

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Huntingford, C., B. B. B. Booth, S. Sitch, N. Gedney, J. A. Lowe, S. K. Liddicoat, L. M. Mercado, et al. "IMOGEN: an intermediate complexity model to evaluate terrestrial impacts of a changing climate." Geoscientific Model Development Discussions 3, no. 3 (August 4, 2010): 1161–84. http://dx.doi.org/10.5194/gmdd-3-1161-2010.

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Abstract. We present a computationally efficient modelling system, IMOGEN, designed to undertake global and regional assessment of climate change impacts on the physical and biogeochemical behaviour of the land surface. A pattern-scaling approach to climate change drives a gridded land surface and vegetation model MOSES/TRIFFID. The structure allows extrapolation of General Circulation Model (GCM) simulations to different future pathways of greenhouse gases, including rapid first-order assessments of how the land surface and associated biogeochemical cycles might change. Evaluation of how new terrestrial process understanding influences such predictions can also be made with relative ease.

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Farneti, R., and G. K. Vallis. "An Intermediate Complexity Climate Model (ICCMp1) based on the GFDL flexible modelling system." Geoscientific Model Development 2, no. 2 (July 21, 2009): 73–88. http://dx.doi.org/10.5194/gmd-2-73-2009.

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Abstract. An intermediate complexity coupled ocean-atmosphere-land-ice model, based on the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modelling System (FMS), has been developed to study mechanisms of ocean-atmosphere interactions and natural climate variability at interannual to interdecadal and longer time scales. The model uses the three-dimensional primitive equations for both ocean and atmosphere but is simplified from a "state of the art" coupled model by using simplified atmospheric physics and parameterisation schemes. These simplifications provide considerable savings in computational expense and, perhaps more importantly, allow mechanisms to be investigated more cleanly and thoroughly than with a more elaborate model. For example, the model allows integrations of several millennia as well as broad parameter studies. For the ocean, the model uses the free surface primitive equations Modular Ocean Model (MOM) and the GFDL/FMS sea-ice model (SIS) is coupled to the oceanic grid. The atmospheric component consists of the FMS B-grid moist primitive equations atmospheric dynamical core with highly simplified physical parameterisations. A simple bucket model is implemented for our idealised land following the GFDL/FMS Land model. The model is supported within the standard MOM releases as one of its many test cases and the source code is thus freely available. Here we describe the model components and present a climatology of coupled simulations achieved with two different geometrical configurations. Throughout the paper, we give a flavour of the potential for this model to be a powerful tool for the climate modelling community by mentioning a wide range of studies that are currently being explored.

31

Ganopolski, Audrey, R. Calov, E. Bauer, and V. Brovkin. "An earth system model of intermediate complexity for studies of Quaternary climate variability." IOP Conference Series: Earth and Environmental Science 6, no. 5 (January 1, 2009): 052015. http://dx.doi.org/10.1088/1755-1307/6/5/052015.

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32

Zaplotnik, Žiga, Nedjeljka Žagar, and Nils Gustafsson. "An intermediate-complexity model for four-dimensional variational data assimilation including moist processes." Quarterly Journal of the Royal Meteorological Society 144, no. 715 (July 2018): 1772–87. http://dx.doi.org/10.1002/qj.3338.

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33

Hannah, Charles, Alain Vezina, and Mike St John. "The case for marine ecosystem models of intermediate complexity." Progress in Oceanography 84, no. 1-2 (January 2010): 121–28. http://dx.doi.org/10.1016/j.pocean.2009.09.015.

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34

Baranowski, L., B. Gadomski, P. Majewski, and J. Szymonik. "Explicit “ballistic M-model”: a refinement of the implicit “modified point mass trajectory model”." Bulletin of the Polish Academy of Sciences Technical Sciences 64, no. 1 (March 1, 2016): 81–89. http://dx.doi.org/10.1515/bpasts-2016-0010.

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Abstract Various models of a projectile in a resisting medium are used. Some are very simple, like the “point mass trajectory model”, others, like the “rigid body trajectory model”, are complex and hard to use, especially in Fire Control Systems due to the fact of numeric complexity and an excess of less important corrections. There exist intermediate ones - e.g. the “modified point mass trajectory model”, which unfortunately is given by an implicitly defined differential equation as Sec. 1 discusses. The main objective of this paper is to present a way to reformulate the model obtaining an easy to solve explicit system having a reasonable complexity yet not being parameter-overloaded. The final form of the M-model, after being carefully derived in Sec. 2, is presented in Subsec. 2.5.

35

Alter, George. "Reflections on the Intermediate Data Structure (IDS)." Historical Life Course Studies 10 (March 31, 2021): 71–75. http://dx.doi.org/10.51964/hlcs9570.

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The Intermediate Data Structure (IDS) encourages sharing historical life course data by storing data in a common format. To encompass the complexity of life histories, IDS relies on data structures that are unfamiliar to most social scientists. This article examines four features of IDS that make it flexible and expandable: the Entity-Attribute-Value model, the relational database model, embedded metadata, and the Chronicle file. I also consider IDS from the perspective of current discussions about sharing data across scientific domains. We can find parallels to IDS in other fields that may lead to future innovations.

36

Li, F., X. D. Zeng, and S. Levis. "A process-based fire parameterization of intermediate complexity in a Dynamic Global Vegetation Model." Biogeosciences Discussions 9, no. 3 (March 16, 2012): 3233–87. http://dx.doi.org/10.5194/bgd-9-3233-2012.

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Abstract. A process-based fire parameterization of intermediate complexity has been developed for global simulations in the framework of a Dynamic Global Vegetation Model (DGVM) in an Earth System Model (ESM). Burned area in a grid cell is estimated by the product of fire counts and average burned area per fire. The scheme comprises three parts: fire occurrence, fire spread, and fire impact. In the fire occurrence part, fire counts rather than fire occurrence probability is calculated in order to capture the observed high burned area fraction in regions where fire occurs frequently. In the fire spread part, post-fire region of a fire is assumed to be elliptical in shape. Mathematical properties of ellipses and mathematical derivation are applied to remove redundant and unreasonable equation and assumptions in existing fire spread parameterization. In the fire impact part, trace gas and aerosol emissions due to biomass burning are estimated, which offers an interface with atmospheric chemistry and aerosol models in ESMs. In addition, flexible time-step length makes the new fire parameterization easily applied to various DGVMs. Global performance of the new fire parameterization is assessed by using an improved version of the Community Land Model version 3 with the Dynamic Global Vegetation Model (CLM-DGVM). Simulations are compared against the latest satellite-based Global Fire Emission Database version 3 (GFED3) for 1997–2004. Results show that simulated global totals and spatial patterns of burned area and fire carbon emissions, global annual burned area fractions for various vegetation types and interannual variability of burned area are in close agreement with the GFED3, and more accurate than CLM-DGVM simulations with the commonly used Glob-FIRM fire parameterization and the old fire module of CLM-DGVM. Furthermore, the average relative error of simulated trace gas and aerosol emissions due to biomass burning is 7 %. Results suggest that the new fire parameterization may improve the global performance of ESMs and help to quantify fire-vegetation-climate interactions on a global scale and from an earth system perspective.

37

Goosse, H., F. M. Selten, R. J. Haarsma, and J. D. Opsteegh. "Decadal variability in high northern latitudes as simulated by an intermediate-complexity climate model." Annals of Glaciology 33 (2001): 525–32. http://dx.doi.org/10.3189/172756401781818482.

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AbstractA 2500 year integration has been performed with a global coupled atmospheric-sea-ice-ocean model of intermediate complexity with the main objective of studying the climate variability in polar regions on decadal time-scales and longer. The atmospheric component is the ECBILT model, a spectral T21 three-level quasi-geostrophic model that includes a representation of horizontal and vertical heat transfers as well as of the hydrological cycle. ECBILT is coupled to the CLIO model, which consists of a primitive-equation free-surface ocean general circulation model and a dynamic-thermodynamic sea-ice model. Comparison of model results with observations shows that the ECBILT-CLIO model is able to reproduce reasonably well the climate of the high northern latitudes. The dominant mode of coupled variability between the atmospheric circulation and sea-ice cover in the simulation consists of an annular mode for geopotential height at 800 hPa and of a dipole between the Barents and Labrador Seas for the sea-ice concentration which are similar to observed patterns of variability. In addition, the simulation displays strong decadal variability in the sea-ice volume, with a significant peak at about 18 years. Positive volume anomalies are caused by (1) a decrease in ice export through Fram Strait associated with more anticyclonic winds at high latitudes, (2) modifications in the freezing/melting rates in the Arctic due to lower air temperature and higher surface albedo, and (3) a weaker heat flux at the ice base in the Barents and Kara seas caused by a lower inflow of warm Atlantic water. Opposite anomalies occur during the volume-decrease phase of the oscillation.

38

Sriver, Ryan L., Axel Timmermann, Michael E. Mann, Klaus Keller, and Hugues Goosse. "Improved Representation of Tropical Pacific Ocean–Atmosphere Dynamics in an Intermediate Complexity Climate Model." Journal of Climate 27, no. 1 (January 1, 2014): 168–85. http://dx.doi.org/10.1175/jcli-d-12-00849.1.

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Abstract A new anomaly coupling technique is introduced into a coarse-resolution dynamic climate model [the Liège Ocean Carbon Heteronomous model (LOCH)–Vegetation Continuous Description model (VECODE)–Earth System Models of Intermediate Complexity Climate deBilt (ECBILT)–Coupled Large-Scale Ice–Ocean model (CLIO)–Antarctic and Greenland Ice Sheet Model (AGISM) ensemble (LOVECLIM)], improving the model’s representation of eastern equatorial Pacific surface temperature variability. The anomaly coupling amplifies the surface diabatic atmospheric forcing within a Gaussian-shaped patch applied in the tropical Pacific Ocean. It is implemented with an improved predictive cloud scheme based on empirical relationships between cloud cover and key state variables. Results are presented from a perturbed physics ensemble systematically varying the parameters controlling the anomaly coupling patch size, location, and amplitude. The model’s optimal parameter combination is chosen through calibration against the observed power spectrum of monthly-mean surface temperature anomalies in the Niño-3 region. The calibrated model exhibits substantial improvement in equatorial Pacific interannual surface temperature variability and robustly reproduces El Niño–Southern Oscillation (ENSO)-like variability. The authors diagnose some of the key atmospheric and oceanic feedbacks in the model important for simulating ENSO-like variability, such as the positive Bjerknes feedback and the negative heat flux feedback, and analyze the recharge–discharge of the equatorial Pacific ocean heat content. They find LOVECLIM robustly captures important ocean dynamics related to thermocline adjustment and equatorial Kelvin waves. The calibrated model demonstrates some improvement in simulating atmospheric feedbacks, but the coupling between ocean and atmosphere is relatively weak. Because of the tractability of LOVECLIM and its consequent utility in exploring long-term climate variability and large ensemble perturbed physics experiments, improved representation of tropical Pacific ocean–atmosphere dynamics in the model may more readily allow for the investigation of the role of tropical Pacific ocean–atmosphere dynamics in past climate changes.

39

Li, F., X. D. Zeng, and S. Levis. "A process-based fire parameterization of intermediate complexity in a Dynamic Global Vegetation Model." Biogeosciences 9, no. 7 (July 30, 2012): 2761–80. http://dx.doi.org/10.5194/bg-9-2761-2012.

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Abstract. A process-based fire parameterization of intermediate complexity has been developed for global simulations in the framework of a Dynamic Global Vegetation Model (DGVM) in an Earth System Model (ESM). Burned area in a grid cell is estimated by the product of fire counts and average burned area of a fire. The scheme comprises three parts: fire occurrence, fire spread, and fire impact. In the fire occurrence part, fire counts rather than fire occurrence probability are calculated in order to capture the observed high burned area fraction in areas of high fire frequency and realize parameter calibration based on MODIS fire counts product. In the fire spread part, post-fire region of a fire is assumed to be elliptical in shape. Mathematical properties of ellipses and some mathematical derivations are applied to improve the equation and assumptions of an existing fire spread parameterization. In the fire impact part, trace gas and aerosol emissions due to biomass burning are estimated, which offers an interface with atmospheric chemistry and aerosol models in ESMs. In addition, flexible time-step length makes the new fire parameterization easily applied to various DGVMs. Global performance of the new fire parameterization is assessed by using an improved version of the Community Land Model version 3 with the Dynamic Global Vegetation Model (CLM-DGVM). Simulations are compared against the latest satellite-based Global Fire Emission Database version 3 (GFED3) for 1997–2004. Results show that simulated global totals and spatial patterns of burned area and fire carbon emissions, regional totals and spreads of burned area, global annual burned area fractions for various vegetation types, and interannual variability of burned area are reasonable, and closer to GFED3 than CLM-DGVM simulations with the commonly used Glob-FIRM fire parameterization and the old fire module of CLM-DGVM. Furthermore, average error of simulated trace gas and aerosol emissions due to biomass burning is 7% relative to GFED3. Results suggest that the new fire parameterization may improve the global performance of ESMs and help to quantify fire-vegetation-climate interactions on a global scale and from an Earth system perspective.

40

Ganopolski, Andrey, Stefan Rahmstorf, Vladimir Petoukhov, and Martin Claussen. "Simulation of modern and glacial climates with a coupled global model of intermediate complexity." Nature 391, no. 6665 (January 1998): 351–56. http://dx.doi.org/10.1038/34839.

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41

Annan, J. D., J. C. Hargreaves, N. R. Edwards, and R. Marsh. "Parameter estimation in an intermediate complexity earth system model using an ensemble Kalman filter." Ocean Modelling 8, no. 1-2 (January 2005): 135–54. http://dx.doi.org/10.1016/j.ocemod.2003.12.004.

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42

Lammers, Roderick W., and Brian P. Bledsoe. "A network scale, intermediate complexity model for simulating channel evolution over years to decades." Journal of Hydrology 566 (November 2018): 886–900. http://dx.doi.org/10.1016/j.jhydrol.2018.09.036.

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43

Weber, S. L. "The impact of orbital forcing on the climate of an intermediate-complexity coupled model." Global and Planetary Change 30, no. 1-2 (September 2001): 7–12. http://dx.doi.org/10.1016/s0921-8181(01)00077-7.

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44

Schoenemann, Spruce W., and Eric J. Steig. "Seasonal and spatial variations of17Oexcessanddexcessin Antarctic precipitation: Insights from an intermediate complexity isotope model." Journal of Geophysical Research: Atmospheres 121, no. 19 (October 6, 2016): 11,215–11,247. http://dx.doi.org/10.1002/2016jd025117.

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45

Wang, Tao, Catherine Ottlé, Aaron Boone, Philippe Ciais, Eric Brun, Samuel Morin, Gerhard Krinner, Shilong Piao, and Shushi Peng. "Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model." Journal of Geophysical Research: Atmospheres 118, no. 12 (June 20, 2013): 6064–79. http://dx.doi.org/10.1002/jgrd.50395.

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46

Ramesh, Nandini, and Mark A. Cane. "The Predictability of Tropical Pacific Decadal Variability: Insights from Attractor Reconstruction." Journal of the Atmospheric Sciences 76, no. 3 (March 1, 2019): 801–19. http://dx.doi.org/10.1175/jas-d-18-0114.1.

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Abstract Tropical Pacific decadal variability (TPDV), though not the totality of Pacific decadal variability, has wide-ranging climatic impacts. It is currently unclear whether this phenomenon is predictable. In this study, we reconstruct the attractor of the tropical Pacific system in long, unforced simulations from an intermediate-complexity model, two general circulation models (GCMs), and the observations with the aim of assessing the predictability of TPDV in these systems. We find that in the intermediate-complexity model, positive (high variance, El Niño–like) and negative (low variance, La Niña–like) phases of TPDV emerge as a pair of regime-like states. The observed system bears resemblance to this behavior, as does one GCM, while the other GCM does not display this structure. However, these last three time series are too short to confidently characterize the full distribution of interdecadal variability. The intermediate-complexity model is shown to lie in highly predictable parts of its attractor 37% of the time, during which most transitions between TPDV regimes occur. The similarities between the observations and this system suggest that the tropical Pacific may be somewhat predictable on interdecadal time scales.

47

Joshi, M., M. Stringer, K. van der Wiel, A. O'Callaghan, and S. Fueglistaler. "IGCM4: a fast, parallel and flexible intermediate climate model." Geoscientific Model Development 8, no. 4 (April 23, 2015): 1157–67. http://dx.doi.org/10.5194/gmd-8-1157-2015.

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Abstract. The IGCM4 (Intermediate Global Circulation Model version 4) is a global spectral primitive equation climate model whose predecessors have extensively been used in areas such as climate research, process modelling and atmospheric dynamics. The IGCM4's niche and utility lies in its speed and flexibility allied with the complexity of a primitive equation climate model. Moist processes such as clouds, evaporation, atmospheric radiation and soil moisture are simulated in the model, though in a simplified manner compared to state-of-the-art global circulation models (GCMs). IGCM4 is a parallelised model, enabling both very long integrations to be conducted and the effects of higher resolutions to be explored. It has also undergone changes such as alterations to the cloud and surface processes and the addition of gravity wave drag. These changes have resulted in a significant improvement to the IGCM's representation of the mean climate as well as its representation of stratospheric processes such as sudden stratospheric warmings. The IGCM4's physical changes and climatology are described in this paper.

48

Weber, Susanne L. "The utility of Earth system Models of Intermediate Complexity (EMICs)." Wiley Interdisciplinary Reviews: Climate Change 1, no. 2 (January 11, 2010): 243–52. http://dx.doi.org/10.1002/wcc.24.

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49

Famiglietti, Caroline A., T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, et al. "Optimal model complexity for terrestrial carbon cycle prediction." Biogeosciences 18, no. 8 (April 30, 2021): 2727–54. http://dx.doi.org/10.5194/bg-18-2727-2021.

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Abstract. The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at six globally distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.

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Petoukhov, V., A. Ganopolski, V. Brovkin, M. Claussen, A. Eliseev, C. Kubatzki, and S. Rahmstorf. "CLIMBER-2: a climate system model of intermediate complexity. Part I: model description and performance for present climate." Climate Dynamics 16, no. 1 (January 3, 2000): 1–17. http://dx.doi.org/10.1007/pl00007919.

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