scholarly journals Towards in-situ visualization integrated earth system models: RegESM 1.1 regional modelling system

2018 ◽  
Author(s):  
Ufuk Utku Turuncoglu
Keyword(s):  
Data Analysis ◽  
System Model ◽  
Earth System ◽  
System Models ◽  
Modeling Systems ◽  
Temporal And Spatial ◽  
Model Components ◽  
Earth System Models ◽  
Modelling System

Abstract. The data volume being produced by regional and global multi-component earth system models are rapidly increasing due to the improved spatial and temporal resolution of the model components, sophistication of the used numerical models in terms of represented physical processes and their non-linear complex interactions. In particular, very short time steps have to be defined in multi-component and multi-scale non-hydrostatic modelling systems to represent the evolution of the fast-moving processes such as turbulence, extra-tropical cyclones, convective lines, jet streams, internal waves, vertical turbulent mixing and surface gravity waves. Consequently, the used small time steps cause extra computation and disk I/O overhead in the used modelling system even if today's most powerful high-performance computing and data storage systems are being considered. Analysis of the high volume of data from multiple earth system model components at different temporal and spatial resolution also poses a challenging problem to efficiently perform integrated data analysis of the massive amounts of data by relying on the conventional post-processing methods available today. This study basically aims to explore the feasibility and added value of integrating existing in-situ visualization and data analysis methods with the model coupling framework (ESMF) to increase interoperability between multi-component simulation code and data processing pipelines by providing easy to use, efficient, generic and standardized modeling environment for earth system science applications. The new data analysis approach enables simultaneous analysis of the vast amount of data produced by multi-component regional earth system models (atmosphere, ocean etc.) during the run process. The methodology aims to create an integrated modeling environment for analyzing fast-moving processes and their evolution in both time and space to support better understanding of the underplaying physical mechanisms. The state-of-art approach can also be used to solve common problems in earth system model development workflow such as designing new sub-grid scale parametrizations (convection, air–sea interaction etc.) that requires inspecting the integrated model behavior in a higher temporal and spatial scale during the run or supporting visual debugging of the multi-component modeling systems, which usually are not facilitated by existing model coupling libraries and modeling systems.

scholarly journals Toward modular in situ visualization in Earth system models: the regional modeling system RegESM 1.1

2019 ◽  
Vol 12 (1) ◽  
pp. 233-259 ◽  
Author(s):  
Ufuk Utku Turuncoglu
Keyword(s):  
Data Analysis ◽  
Small Time ◽  
Earth System ◽  
System Models ◽  
Modeling Systems ◽  
In Situ Visualization ◽  
Temporal And Spatial ◽  
Model Components ◽  
Earth System Models

Abstract. The data volume produced by regional and global multicomponent Earth system models is rapidly increasing because of the improved spatial and temporal resolution of the model components and the sophistication of the numerical models regarding represented physical processes and their complex non-linear interactions. In particular, very small time steps need to be defined in non-hydrostatic high-resolution modeling applications to represent the evolution of the fast-moving processes such as turbulence, extratropical cyclones, convective lines, jet streams, internal waves, vertical turbulent mixing and surface gravity waves. Consequently, the employed small time steps cause extra computation and disk input–output overhead in the modeling system even if today's most powerful high-performance computing and data storage systems are considered. Analysis of the high volume of data from multiple Earth system model components at different temporal and spatial resolutions also poses a challenging problem to efficiently perform integrated data analysis of the massive amounts of data when relying on the traditional postprocessing methods today. This study mainly aims to explore the feasibility and added value of integrating existing in situ visualization and data analysis methods within the model coupling framework. The objective is to increase interoperability between Earth system multicomponent code and data-processing systems by providing an easy-to-use, efficient, generic and standardized modeling environment. The new data analysis approach enables simultaneous analysis of the vast amount of data produced by multicomponent regional Earth system models during the runtime. The presented methodology also aims to create an integrated modeling environment for analyzing fast-moving processes and their evolution both in time and space to support a better understanding of the underplaying physical mechanisms. The state-of-the-art approach can also be employed to solve common problems in the model development cycle, e.g., designing a new subgrid-scale parameterization that requires inspecting the integrated model behavior at a higher temporal and spatial scale simultaneously and supporting visual debugging of the multicomponent modeling systems, which usually are not facilitated by existing model coupling libraries and modeling systems.

First global assessment of modelled aerosol hygroscopicity in the context of other aerosol optical properties

2021 ◽  
Author(s):  
Maria Ángeles Burgos Simón ◽  
Elisabeth Andrews ◽  
Gloria Titos ◽  
Angela Benedetti ◽  
Huisheng Bian ◽  
...  
Keyword(s):  
Optical Properties ◽  
Light Scattering ◽  
Relative Humidity ◽  
Water Uptake ◽  
Chem Phys ◽  
Earth System ◽  
Aerosol Optical Properties ◽  
System Models ◽  
Earth System Models

<p>The particle hygroscopic growth impacts the optical properties of aerosols and, in turn, affects the aerosol-radiation interaction and calculation of the Earth’s radiative balance. The dependence of particle light scattering on relative humidity (RH) can be described by the scattering enhancement factor f(RH), defined as the ratio between the particle light scattering coefficient at a given RH divided by its dry value.</p><p>The first effort of the AeroCom Phase III – INSITU experiment was to develop an observational dataset of scattering enhancement values at 26 sites to study the uptake of water by atmospheric aerosols, and evaluate f(RH) globally (Burgos et al., 2019). Model outputs from 10 Earth System Models (CAM, CAM-ATRAS, CAM-Oslo, GEOS-Chem, GEOS-GOCART, MERRAero, TM5, OsloCTM3, IFS-AER, and ECMWF) were then evaluated against this in-situ dataset. Building on these results, we investigate f(RH) in the context of other aerosol optical and chemical properties, making use of the same 10 Earth System Models (ESMs) and in-situ measurements as in Burgos et al. (2020) and Titos et al. (2021).</p><p>Given the difficulties of deploying and maintaining instrumentation for long-term, accurate and comprehensive f(RH) observations, it is desirable to find an observational proxy for f(RH). This observation-based proxy would also need to be reproduced in modelling space. Our aim here is to evaluate how ESMs currently represent the relationship between f(RH), scattering Ångström exponent (SAE), and single scattering albedo (SSA). This work helps to identify current challenges in modelling water-uptake by aerosols and their impact on aerosol optical properties within Earth system models.</p><p>We start by analyzing the behavior of SSA with RH, finding the expected increase with RH for all site types and models. Then, we analyze the three variables together (f(RH)-SSA-SAE relationship). Results show that hygroscopic particles tend to be bigger and scatter more than non-hygroscopic small particles, though variability within models is noticeable. This relationship can be further studied by relating SAE to model chemistry, by selecting those grid points dominated by a single chemical component (mass mixing ratios > 90%). Finally, we analyze model performance at three specific sites representing different aerosol types: Arctic, marine and rural. At these sites, the model data can be exactly temporally and spatially collocated with the observations, which should help to identify the models which exhibit better agreement with measurements and for which aerosol type.</p><p> </p><p>Burgos, M.A. et al.: A global view on the effect of water uptake on aerosol particle light scattering. Sci Data 6, 157. https://doi.org/10.1038/s41597-019-0158-7, 2019.</p><p>Burgos, M.A. et al.: A global model–measurement evaluation of particle light scattering coefficients at elevated relative humidity, Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, 2020.</p><p>Titos, G. et al.: A global study of hygroscopicity-driven light scattering enhancement in the context of other in-situ aerosol optical properties, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-1250, in review, 2020.</p>

scholarly journals Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution

Ocean Science ◽  
2016 ◽  
Vol 12 (2) ◽  
pp. 561-575 ◽  
Author(s):  
Tihomir S. Kostadinov ◽  
Svetlana Milutinović ◽  
Irina Marinov ◽  
Anna Cabré
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Ocean Color ◽  
Earth System ◽  
System Models ◽  
Size Classes ◽  
Carbon Biomass ◽  
Earth System Models

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the “unit of accounting” in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) and microphytoplankton (20–50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield  ∼  0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

scholarly journals OMEN-SED 0.9: A novel, numerically efficient organic matter sediment diagenesis module for coupling to Earth system models

2018 ◽  
Author(s):  
Dominik Hülse ◽  
Sandra Arndt ◽  
Stuart Daines ◽  
Pierre Regnier ◽  
Andy Ridgwell
Keyword(s):  
Organic Matter ◽  
Marine Sediments ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Framework ◽  
System Models ◽  
Wide Range ◽  
Earth System Models ◽  
Sediment Model

Abstract. We present the first version of OMEN-SED (Organic Matter ENabled SEDiment model), a new, one-dimensional analytical early diagenetic model resolving organic matter cycling and associated biogeochemical dynamics in marine sediments designed to be coupled to Earth system models. OMEN-SED explicitly describes organic matter (OM) cycling as well as associated dynamics of the most important terminal electron acceptors (i.e. O2, NO3, SO4) and methane (CH4), related reduced substances (NH4, H2S), macronutrients (PO4) and associated pore water quantities (ALK, DIC). Its reaction network accounts for the most important primary and secondary redox reactions, equilibrium reactions, mineral dissolution and precipitation, as well as adsorption and desorption processes associated with OM dynamics that affect the dissolved and solid species explicitly resolved in the model. To represent a redox-dependent sedimentary P cycle we also include a representation of the formation and burial of Fe-bound P and authigenic Ca-P minerals. Thus, OMEN-SED is able to capture the main features of diagenetic dynamics in marine sediments and, therefore, offers similar predictive abilities than a complex, numerical diagenetic model. Yet, its computational efficiency allows its coupling to global Earth system models and therefore the investigation of coupled global biogeochemical dynamics over a wide range of climate relevant timescales. This paper provides a detailed description of the new sediment model, an extensive sensitivity analysis, as well as an evaluation of OMEN-SED's performance through comprehensive comparisons with observations and results from a more complex numerical model. We find solid phase and dissolved pore water profiles for different ocean depths are reproduced with good accuracy and simulated terminal electron acceptor fluxes fall well within the range of globally observed fluxes. Finally, we illustrate its application in an Earth system model framework by coupling OMEN-SED to the Earth system model cGENIE and tune the OM degradation rate constants to optimise the fit of simulated benthic OM contents to global observations. We find simulated sediment characteristics of the coupled model framework, such as OM degradation rates, oxygen penetration depths and sediment-water interface fluxes are generally in good agreement with observations and in line with what one would expect on a global scale. Coupled to an Earth system model, OMEN-SED is thus a powerful tool that will not only help elucidate the role of benthic-pelagic exchange processes in the evolution and, in particular, the termination of a wide range of climate events, but will also allow a direct comparison of model output with the sedimentary record – the most important climate archive on Earth.

scholarly journals Evaluating the simulated mean soil carbon transit times by Earth system models using observations

2019 ◽  
Vol 16 (4) ◽  
pp. 917-926 ◽  
Author(s):  
Jing Wang ◽  
Jianyang Xia ◽  
Xuhui Zhou ◽  
Kun Huang ◽  
Jian Zhou ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Soil Carbon ◽  
Earth System ◽  
Soil C ◽  
Global Database ◽  
System Models ◽  
Transit Times ◽  
Negative Linear Correlation ◽  
Earth System Models

Abstract. One known bias in current Earth system models (ESMs) is the underestimation of global mean soil carbon (C) transit time (τsoil), which quantifies the age of the C atoms at the time they leave the soil. However, it remains unclear where such underestimations are located globally. Here, we constructed a global database of measured τsoil across 187 sites to evaluate results from 12 ESMs. The observations showed that the estimated τsoil was dramatically shorter from the soil incubation studies in the laboratory environment (median = 4 years; interquartile range = 1 to 25 years) than that derived from field in situ measurements (31; 5 to 84 years) with shifts in stable isotopic C (13C) or the stock-over-flux approach. In comparison with the field observations, the multi-model ensemble simulated a shorter median (19 years) and a smaller spatial variation (6 to 29 years) of τsoil across the same site locations. We then found a significant and negative linear correlation between the in situ measured τsoil and mean annual air temperature. The underestimations of modeled τsoil are mainly located in cold and dry biomes, especially tundra and desert. Furthermore, we showed that one ESM (i.e., CESM) has improved its τsoil estimate by incorporation of the soil vertical profile. These findings indicate that the spatial variation of τsoil is a useful benchmark for ESMs, and we recommend more observations and modeling efforts on soil C dynamics in regions limited by temperature and moisture.

scholarly journals Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model using WAVEWATCH III version 6.07

2021 ◽  
Vol 14 (5) ◽  
pp. 2917-2938
Author(s):  
Steven R. Brus ◽  
Phillip J. Wolfram ◽  
Luke P. Van Roekel ◽  
Jessica D. Meixner
Keyword(s):  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Wave Modeling ◽  
Wavewatch Iii ◽  
Computational Costs ◽  
System Models ◽  
The Us ◽  
Wave Models ◽  
Earth System Models

Abstract. Wind-wave processes have generally been excluded from coupled Earth system models due to the high computational expense of spectral wave models, which resolve a frequency and direction spectrum of waves across space and time. Existing uniform-resolution wave modeling approaches used in Earth system models cannot appropriately represent wave climates from global to coastal ocean scales, largely because of tradeoffs between coastal resolution and computational costs. To resolve this challenge, we introduce a global unstructured mesh capability for the WAVEWATCH III (WW3) model that is suitable for coupling within the US Department of Energy's Energy Exascale Earth System Model (E3SM). The new unstructured WW3 global wave modeling approach can provide the accuracy of higher global resolutions in coastal areas at the relative cost of lower uniform global resolutions. This new capability enables simulation of waves at physically relevant scales as needed for coastal applications.

scholarly journals Evaluating the simulated mean soil carbon transit times by Earth system models using observations

2018 ◽  
Author(s):  
Jing Wang ◽  
Jianyang Xia ◽  
Xuhui Zhou ◽  
Kun Huang ◽  
Jian Zhou ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Soil Carbon ◽  
Interquartile Range ◽  
Earth System ◽  
Soil C ◽  
Global Database ◽  
System Models ◽  
Transit Times ◽  
Earth System Models

Abstract. One known bias in current Earth system models (ESMs) is the underestimation of global mean soil carbon (C) transit time (τsoil), which quantifies the mean age of the C atoms at the time they leave the soil. However, it remains unclear where such underestimations are located globally. Here, we constructed a global database of measured τsoil across 187 sites to evaluated results from twelve ESMs. The observations showed that the estimated τsoil was dramatically shorter from the soil incubations studies in the laboratory environment (median as 4 with the interquartile range of 1–25 years) than that derived from field in-situ measurements (31 with 5–84 years) with the shifts of stable isotopic C (13C) or the stock-over-flux approach. In comparison with the field observations, the multi-model ensemble simulated a shorter median (19 years) and a smaller spatial variation (interquartile range of 6–28 years) of τsoil across the same site locations. We then found a significant and negative linear correlation between the in-situ measured τsoil and mean annual air temperature, and the underestimations of modeled τsoil are mainly located in cold and dry biomes especially tundra and desert. Furthermore, we showed that one ESM (i.e., CESM) has improved its τsoil estimate by incorporation of the soil vertical profile. These findings indicate that the spatial variation of τsoil is a useful benchmark for ESMs, and we recommend more observation and modeling efforts on soil C dynamics in hydrothermal limited regions.

scholarly journals Observing carbon cycle–climate feedbacks from space

2018 ◽  
Vol 115 (31) ◽  
pp. 7860-7868 ◽  
Author(s):  
Piers J. Sellers ◽  
David S. Schimel ◽  
Berrien Moore ◽  
Junjie Liu ◽  
Annmarie Eldering
Keyword(s):  
Carbon Dioxide ◽  
Earth System ◽  
Climate Feedbacks ◽  
System Models ◽  
Component Processes ◽  
The Impact ◽  
Atmospheric Concentrations ◽  
Earth System Models

The impact of human emissions of carbon dioxide and methane on climate is an accepted central concern for current society. It is increasingly evident that atmospheric concentrations of carbon dioxide and methane are not simply a function of emissions but that there are myriad feedbacks forced by changes in climate that affect atmospheric concentrations. If these feedbacks change with changing climate, which is likely, then the effect of the human enterprise on climate will change. Quantifying, understanding, and articulating the feedbacks within the carbon–climate system at the process level are crucial if we are to employ Earth system models to inform effective mitigation regimes that would lead to a stable climate. Recent advances using space-based, more highly resolved measurements of carbon exchange and its component processes—photosynthesis, respiration, and biomass burning—suggest that remote sensing can add key spatial and process resolution to the existing in situ systems needed to provide enhanced understanding and advancements in Earth system models. Information about emissions and feedbacks from a long-term carbon–climate observing system is essential to better stewardship of the planet.

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.

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