scholarly journals Variations in Ocean Deoxygenation Across Earth System Models: Isolating the Role of Parameterized Lateral Mixing

2019 ◽  
Vol 33 (6) ◽  
pp. 703-724 ◽  
Author(s):  
A. Bahl ◽  
A. Gnanadesikan ◽  
M.‐A. Pradal
Keyword(s):  
Earth System ◽  
System Models ◽  
Lateral Mixing ◽  
Earth System Models ◽  
Ocean Deoxygenation

GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics

2012 ◽  
Vol 25 (19) ◽  
pp. 6646-6665 ◽  
Author(s):  
John P. Dunne ◽  
Jasmin G. John ◽  
Alistair J. Adcroft ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
...  
Keyword(s):  
Climate Changes ◽  
Southern Oscillation ◽  
Heat Content ◽  
Ocean Dynamics ◽  
Thermocline Depth ◽  
Earth System ◽  
System Models ◽  
Model Version ◽  
Earth System Models

Abstract The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Niño–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.

scholarly journals Physics–Dynamics Coupling in Weather, Climate, and Earth System Models: Challenges and Recent Progress

2018 ◽  
Vol 146 (11) ◽  
pp. 3505-3544 ◽  
Author(s):  
Markus Gross ◽  
Hui Wan ◽  
Philip J. Rasch ◽  
Peter M. Caldwell ◽  
David L. Williamson ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Recent Progress ◽  
Earth System ◽  
System Models ◽  
Thermodynamic Compatibility ◽  
Emerging Issues ◽  
Microphysical Processes ◽  
Model Components ◽  
Earth System Models

Abstract Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions.

scholarly journals Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

2021 ◽  
Vol 12 (4) ◽  
pp. 1295-1369
Author(s):  
Sebastian Landwehr ◽  
Michele Volpi ◽  
F. Alexander Haumann ◽  
Charlotte M. Robinson ◽  
Iris Thurnherr ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Environmental Data ◽  
Sea Surface ◽  
Latitudinal Gradients ◽  
Earth System ◽  
System Models ◽  
Environmental Processes ◽  
The Antarctic ◽  
Earth System Models

Abstract. The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.

scholarly journals The evaluation of Earth System Models: discussion summary

2011 ◽  
Vol 6 ◽  
pp. 216-221
Author(s):  
Sönke Zaehle ◽  
Colin Prentice ◽  
Sarah Cornell
Keyword(s):  
Earth System ◽  
System Models ◽  
Earth System Models

scholarly journals Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)

2015 ◽  
Vol 8 (4) ◽  
pp. 3235-3292 ◽  
Author(s):  
A. L. Atchley ◽  
S. L. Painter ◽  
D. R. Harp ◽  
E. T. Coon ◽  
C. J. Wilson ◽  
...  
Keyword(s):  
Carbon Sink ◽  
Thermal Response ◽  
Field Measurements ◽  
Early Summer ◽  
Active Layer Thickness ◽  
Earth System ◽  
Model Refinement ◽  
System Models ◽  
Developed Surface ◽  
Earth System Models

Abstract. Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.

scholarly journals Evolution of the Arabian Sea Upwelling from the Last Millennium to the Future as Simulated by Earth System Models

Climate ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 72
Author(s):  
Xing Yi ◽  
Birgit Hünicke ◽  
Eduardo Zorita
Keyword(s):  
Arabian Sea ◽  
Positive Trend ◽  
Last Millennium ◽  
Earth System ◽  
System Models ◽  
Sediment Records ◽  
The Future ◽  
Water Stratification ◽  
Arabian Sea Upwelling ◽  
Earth System Models

Arabian Sea upwelling in the past has been generally studied based on the sediment records. We apply two earth system models and analyze the simulated water vertical velocity to investigate coastal upwelling in the western Arabian Sea over the last millennium. In addition, two models with slightly different configurations are also employed to study the upwelling in the 21st century under the strongest and the weakest greenhouse gas emission scenarios. With a negative long-term trend caused by the orbital forcing of the models, the upwelling over the last millennium is found to be closely correlated with the sea surface temperature, the Indian summer Monsoon and the sediment records. The future upwelling under the Representative Concentration Pathway (RCP) 8.5 scenario reveals a negative trend, in contrast with the positive trend displayed by the upwelling favorable along-shore winds. Therefore, it is likely that other factors, like water stratification in the upper ocean layers caused by the stronger surface warming, overrides the effect from the upwelling favorable wind. No significant trend is found for the upwelling under the RCP2.6 scenario, which is likely due to a compensation between the opposing effects of the increase in upwelling favorable winds and the water stratification.

Assessing the capacity of Earth System Models to simulate spatiotemporal variability in fire weather indicators

2021 ◽  
Author(s):  
Carolina Gallo Granizo ◽  
Jonathan Eden ◽  
Bastien Dieppois ◽  
Matthew Blackett
Keyword(s):  
Climate Change ◽  
Spatial Scales ◽  
Fire Danger ◽  
Spatiotemporal Variability ◽  
Global Evaluation ◽  
Fire Weather ◽  
Earth System ◽  
Fire Weather Index ◽  
System Models ◽  
Earth System Models

<p>Weather and climate play an important role in shaping global fire regimes and geographical distributions of burnable areas. At the global scale, fire danger is likely to increase in the near future due to warmer temperatures and changes in precipitation patterns, as projected by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). There is a need to develop the most reliable projections of future climate-driven fire danger to enable decision makers and forest managers to take both targeted proactive actions and to respond to future fire events.</p><p>Climate change projections generated by Earth System Models (ESMs) provide the most important basis for understanding past, present and future changes in the climate system and its impacts. ESMs are, however, subject to systematic errors and biases, which are not fully taken into account when developing risk scenarios for wild fire activity. Projections of climate-driven fire danger have often been limited to the use of single models or the mean of multi-model ensembles, and compared to a single set of observational data (e.g. one index derived from one reanalysis).</p><p>Here, a comprehensive global evaluation of the representation of a series of fire weather indicators in the latest generation of ESMs is presented. Seven fire weather indices from the Canadian Forest Fire Weather Index System were generated using daily fields realisations simulated by 25 ESMs from the 6<sup>th</sup> Coupled Model Intercomparison Project (CMIP6). With reference to observational and reanalysis datasets, we quantify the capacity of each model to realistically simulate the variability, magnitude and spatial extent of fire danger. The highest-performing models are identified and, subsequently, the limitations of combining models based on independency and equal performance when generating fire danger projections are discussed. To conclude, recommendations are given for the development of user- and policy-driven model evaluation at spatial scales relevant for decision-making and forest management.</p>

A stationary tropospheric sulphur cycle for Earth system models of intermediate complexit

2021 ◽  
Author(s):  
Alexey V. Eliseev ◽  
Rustam D. Gizatullin ◽  
Alexandr V. Timazhev
Keyword(s):  
Atmospheric Chemistry ◽  
Sulphur Dioxide ◽  
Wet Deposition ◽  
Earth System ◽  
Sulphur Compounds ◽  
Coupled Models ◽  
System Models ◽  
Sulphur Cycle ◽  
Intercomparison Project ◽  
Earth System Models

<p>A stationary, computationally efficient  scheme, ChAP-1.0 (Chemistry and Aerosol Processes, version 1.0) for the sulphur cycle in the troposphereis developed. This scheme is envisaged to be implemented into Earth system models of intermediate complexity (EMICs). The scheme accounts for sulphur dioxide emissions into the atmosphere, its deposition to the surface, oxidation to sulphates, and dry and wet deposition of sulphates on the surface.<br>The calculations with the scheme were performed with the anthropogenic emissions of sulphur compounds into the atmosphere for 1850-2000 according to the CMIP5 (Coupled Models Intercomparison Project, phase 5) 'historical' protocol, with the ERA-Interim meteorology, and assuming that natural sources of sulphur into the atmosphere remain unchanged during this period. The model reasonably reproduces characteristics of the tropospheric sulphur cycle known from observations and other simulations (e.g., in the Atmospheric Chemistry and Climate Model Intercomparison Project phase II (ACCMIP) simulations, Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, and the Meteorological Synthesizing Centre–West of the European Monitoring and Evaluation Programme (EMEP MSC-W) data). In particular, in 1980's and 1990's, , when the global anthropogenic emission of sulphur, global atmospheric burdens of SO<sub>2</sub> and SO<sub>4</sub> account, correspondingly, 0.2 TgS and 0.4 TgS. In our scheme, about half of the emitted sulphur dioxide is deposited to the surface and the rest in oxidised into sulphates. The latter mostly removed from the atmosphere by wet deposition. The lifetime of the SO<sub>2</sub> and SO<sub>4</sub> in the atmosphere is, respectively, 1.0±0.1 days and 4.1±0.3 days.<br>Despite its simplicity, our scheme may be successfully used to simulate sulphur/sulphates pollution in the atmosphere at coarse spatial and time scales and an impact of this pollution to direct radiative effect of sulphates on climate, their respective indirect (cloud- and precipitation-related) effects, as well as an impact of sulphur compounds on the terrestrial carbon cycle.</p>

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