scholarly journals ISSM-SESAW v1.0: mesh-based computation of gravitationally consistent sea-level and geodetic signatures caused by cryosphere and climate driven mass change

2016 ◽  
Vol 9 (3) ◽  
pp. 1087-1109 ◽  
Author(s):  
Surendra Adhikari ◽  
Erik R. Ivins ◽  
Eric Larour
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Computational Cost ◽  
Wave Number ◽  
Time Varying ◽  
Earth System ◽  
Viscous Effects ◽  
Legendre Series ◽  
System Models ◽  
Earth System Models

Abstract. A classical Green's function approach for computing gravitationally consistent sea-level variations associated with mass redistribution on the earth's surface employed in contemporary sea-level models naturally suits the spectral methods for numerical evaluation. The capability of these methods to resolve high wave number features such as small glaciers is limited by the need for large numbers of pixels and high-degree (associated Legendre) series truncation. Incorporating a spectral model into (components of) earth system models that generally operate on a mesh system also requires repetitive forward and inverse transforms. In order to overcome these limitations, we present a method that functions efficiently on an unstructured mesh, thus capturing the physics operating at kilometer scale yet capable of simulating geophysical observables that are inherently of global scale with minimal computational cost. The goal of the current version of this model is to provide high-resolution solid-earth, gravitational, sea-level and rotational responses for earth system models operating in the domain of the earth's outer fluid envelope on timescales less than about 1 century when viscous effects can largely be ignored over most of the globe. The model has numerous important geophysical applications. For example, we compute time-varying computations of global geodetic and sea-level signatures associated with recent ice-sheet changes that are derived from space gravimetry observations. We also demonstrate the capability of our model to simultaneously resolve kilometer-scale sources of the earth's time-varying surface mass transport, derived from high-resolution modeling of polar ice sheets, and predict the corresponding local and global geodetic signatures.

scholarly journals Two-way coupling between the sub-grid land surface and river networks in Earth system models

2020 ◽  
Author(s):  
Nathaniel W. Chaney ◽  
Laura Torres-Rojas ◽  
Noemi Vergopolan ◽  
Colby K. Fisher
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Environmental Data ◽  
Added Value ◽  
Earth System ◽  
Field Scale ◽  
System Models ◽  
Routing Scheme ◽  
Earth System Models ◽  
River Routing

Abstract. Over the past decade, there has been appreciable progress towards modeling the water, energy, and carbon cycles at field-scales (10–100 m) over continental to global extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid tiles, or Hydrologic Response Units (HRUs), learned via a hierarchical clustering approach from available global high-resolution environmental data. However, until now, there has yet to be a macroscale river routing approach that is able to leverage HydroBlocks' approach to sub-grid heterogeneity, thus limiting the added value of field-scale land surface modeling in Earth System Models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). This paper introduces a novel dynamic river routing scheme in HydroBlocks that is intertwined with the modeled field-scale land surface heterogeneity. The primary features of the routing scheme include: 1) the fine-scale river network of each macroscale grid cell's is derived from very high resolution (

scholarly journals Use of various remote sensing land cover products for PFT mapping over Siberia

2013 ◽  
Vol 6 (1) ◽  
pp. 255-296
Author(s):  
C. Ottlé ◽  
J. Lescure ◽  
F. Maignan ◽  
B. Poulter ◽  
T. Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Land Cover Classification ◽  
Classification Systems ◽  
Tree Cover ◽  
Surface Model ◽  
Earth System ◽  
System Models ◽  
Earth System Models

Abstract. High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT) classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern latitudes. Updated land cover datasets are critical for improving and maintaining the relevance of earth system models for assessing climate and human impacts on biogeochemistry and biophysics. The new PFT map at 5 km scale is available for download from the PANGAEA website, at: doi:10.1594/PANGAEA.810709.

scholarly journals Physically regularized machine learning emulators of aerosol activation

2021 ◽  
Vol 14 (5) ◽  
pp. 3067-3077
Author(s):  
Sam J. Silva ◽  
Po-Lun Ma ◽  
Joseph C. Hardin ◽  
Daniel Rothenberg
Keyword(s):  
Machine Learning ◽  
Model Development ◽  
Computational Cost ◽  
Earth System ◽  
Cloud Droplets ◽  
Physical Constraints ◽  
System Models ◽  
Machine Learning Model ◽  
Aerosol Activation ◽  
Earth System Models

Abstract. The activation of aerosol into cloud droplets is an important step in the formation of clouds and strongly influences the radiative budget of the Earth. Explicitly simulating aerosol activation in Earth system models is challenging due to the computational complexity required to resolve the necessary chemical and physical processes and their interactions. As such, various parameterizations have been developed to approximate these details at reduced computational cost and accuracy. Here, we explore how machine learning emulators can be used to bridge this gap in computational cost and parameterization accuracy. We evaluate a set of emulators of a detailed cloud parcel model using physically regularized machine learning regression techniques. We find that the emulators can reproduce the parcel model at higher accuracy than many existing parameterizations. Furthermore, physical regularization tends to improve emulator accuracy, most significantly when emulating very low activation fractions. This work demonstrates the value of physical constraints in machine learning model development and enables the implementation of improved hybrid physical and machine learning models of aerosol activation into next-generation Earth system models.

scholarly journals Evaluation and optimisation of the I/O scalability for the next generation of Earth system models: IFS CY43R3 and XIOS 2.0 integration as a case study

2021 ◽  
Author(s):  
Xavier Yepes-Arbós ◽  
Gijs van den Oord ◽  
Mario C. Acosta ◽  
Glenn D. Carver
Keyword(s):  
Message Passing Interface ◽  
Climate Model ◽  
Critical Path ◽  
Computational Cost ◽  
Earth System ◽  
Post Processing ◽  
Input Output ◽  
System Models ◽  
Computational Performance ◽  
Earth System Models

Abstract. Earth system models have considerably increased their spatial resolution to solve more complex problems and achieve more realistic solutions. However, this generates an enormous amount of model data which requires proper management. Some Earth system models use inefficient sequential Input/Output (I/O) schemes that do not scale well when many parallel resources are used. In order to address this issue, the most commonly adopted approach is to use scalable parallel I/O solutions that offer both computational performance and efficiency. In this paper we analyse the I/O process of the European Centre for Medium-Range Weather Forecasts (ECMWF) operational Integrated Forecasting System (IFS) CY43R3. IFS can use two different output schemes: a parallel I/O server developed by MeteoFrance used operationally, and an obsolescent sequential I/O scheme. The latter is the only scheme that is being exposed by the OpenIFS variant of IFS. “Downstream” Earth system models that have adopted older versions of an IFS derivative as a component – such as the EC-Earth 3 climate model – also face a bottleneck due to the limited I/O capabilities and performance of the sequential output scheme. Moreover it is often desirable to produce gridpoint-space Network Common Data Format (NetCDF) files instead of the IFS native spectral and gridpoint output fields in General Regularly-distributed Information in Binary form (GRIB) format, which requires the development of model-specific post-processing tools. We present the integration of the XML Input/Output Server (XIOS) 2.0 into IFS CY43R3. XIOS is an asynchronous Message Passing Interface (MPI) I/O server that offers features especially targeted at climate models: NetCDF format output files, inline diagnostics, regridding, and when properly configured, the capability to produce CMOR-compliant data. We therefore expect our work to reduce the computational cost of data-intensive (high-resolution) climate runs, thereby shortening the critical path of EC-Earth 4 experiments. The performance evaluation suggests that the use of XIOS 2.0 in IFS CY43R3 to output data achieves an adequate performance as well outperforming the sequential I/O scheme. Furthermore, when we also take into account the post-processing task, needed to convert GRIB files to NetCDF files, and also transform IFS spectral output fields to gridpoint space, our integration not only surpasses the sequential output scheme but also the IFS I/O server.

scholarly journals Evaluation of iterative Kalman smoother schemes for multi-decadal past climate analysis with comprehensive Earth system models

2018 ◽  
Vol 11 (12) ◽  
pp. 5051-5084
Author(s):  
Javier García-Pintado ◽  
André Paul
Keyword(s):  
Cost Function ◽  
Weather Prediction ◽  
Computational Cost ◽  
Small Scale ◽  
Earth System ◽  
Control Variables ◽  
System Models ◽  
Kalman Smoother ◽  
Non Linear ◽  
Earth System Models

Abstract. Paleoclimate reconstruction based on assimilation of proxy observations requires specification of the control variables and their background statistics. As opposed to numerical weather prediction (NWP), which is mostly an initial condition problem, the main source of error growth in deterministic Earth system models (ESMs) regarding the model low-frequency response comes from errors in other inputs: parameters for the small-scale physics, as well as forcing and boundary conditions. Also, comprehensive ESMs are non-linear and only a few ensemble members can be run in current high-performance computers. Under these conditions we evaluate two assimilation schemes, which (a) count on iterations to deal with non-linearity and (b) are based on low-dimensional control vectors to reduce the computational need. The practical implementation would assume that the ESM has been previously globally tuned with current observations and that for a given situation there is previous knowledge of the most sensitive inputs (given corresponding uncertainties), which should be selected as control variables. The low dimension of the control vector allows for using full-rank covariances and resorting to finite-difference sensitivities (FDSs). The schemes are then an FDS implementation of the iterative Kalman smoother (FDS-IKS, a Gauss–Newton scheme) and a so-called FDS-multistep Kalman smoother (FDS-MKS, based on repeated assimilation of the observations). We describe the schemes and evaluate the analysis step for a data assimilation window in two numerical experiments: (a) a simple 1-D energy balance model (Ebm1D; which has an adjoint code) with present-day surface air temperature from the NCEP/NCAR reanalysis data as a target and (b) a multi-decadal synthetic case with the Community Earth System Model (CESM v1.2, with no adjoint). In the Ebm1D experiment, the FDS-IKS converges to the same parameters and cost function values as a 4D-Var scheme. For similar iterations to the FDS-IKS, the FDS-MKS results in slightly higher cost function values, which are still substantially lower than those of an ensemble transform Kalman filter (ETKF). In the CESM experiment, we include an ETKF with Gaussian anamorphosis (ETKF-GA) implementation as a potential non-linear assimilation alternative. For three iterations, both FDS schemes obtain cost functions values that are close between them and (with about half the computational cost) lower than those of the ETKF and ETKF-GA (with similar cost function values). Overall, the FDS-IKS seems more adequate for the problem, with the FDS-MKS potentially more useful to damp increments in early iterations of the FDS-IKS.

scholarly journals ISSM-SESAW v1.0: mesh-based computation of gravitationally consistent sea level and geodetic signatures caused by cryosphere and climate driven mass change

2015 ◽  
Vol 8 (11) ◽  
pp. 9769-9816 ◽  
Author(s):  
S. Adhikari ◽  
E. R. Ivins ◽  
E. Larour
Keyword(s):  
Sea Level ◽  
Computational Cost ◽  
Ice Sheet ◽  
Global Scale ◽  
Computational Method ◽  
Wave Number ◽  
High Wave Number ◽  
Legendre Series ◽  
Large Numbers ◽  
High Degree

Abstract. A classical Green's function approach to computing gravitationally consistent sea level variations, following mass redistribution on the earth surface, employed in contemporary state-of-the-art sea-level models naturally suits the spectral methods for numerical evaluation. The capability of these methods to resolve high wave number features such as small glaciers is limited by the need for large numbers of pixels and high-degree (associated Legendre) series truncation. Incorporating a spectral model into (components of) earth system models that generally operate on an unstructured mesh system also requires cumbersome and repetitive forward and inverse transform of solutions. In order to overcome these limitations of contemporary models, we present a novel computational method that functions efficiently on a flexible mesh system, thus capturing the physics operating at kilometer-scale yet capable of simulating geophysical observables that are inherently of global scale with minimal computational cost. The model has numerous important geophysical applications. Coupling to a local mesh of 3-D ice-sheet model, for example, allows for a refined and realistic simulation of fast-flowing outlet glaciers, while simultaneously retaining its global predictive capability. As an example model application, we provide time-varying computations of global geodetic and sea level signatures associated with recent ice sheet changes that are derived from space gravimetry observations.

scholarly journals Workshop on the Initialization of High-Resolution Earth System Models

2018 ◽  
Author(s):  
Dorothy Koch ◽  
Dan Barrie ◽  
Annarita Mariotti ◽  
Steve Penny ◽  
Todd Ringler ◽  
...  
Keyword(s):  
High Resolution ◽  
Earth System ◽  
System Models ◽  
Earth System Models

scholarly journals A machine learning-guided adaptive algorithm to reduce the computational cost of atmospheric chemistry in Earth System models: application to GEOS-Chem versions 12.0.0 and 12.9.1

2021 ◽  
Author(s):  
Lu Shen ◽  
Daniel J. Jacob ◽  
Mauricio Santillana ◽  
Kelvin Bates ◽  
Jiawei Zhuang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Atmospheric Chemistry ◽  
Computational Cost ◽  
Coupled System ◽  
Atmospheric Composition ◽  
Earth System ◽  
Major Barrier ◽  
System Models ◽  
Computational Bottleneck ◽  
Earth System Models

Abstract. Atmospheric composition plays a crucial role in determining the evolution of the atmosphere, but the high computational cost has been the major barrier to include atmospheric chemistry into Earth system models. Here we present an adaptive and efficient algorithm that can remove this barrier. Our approach is inspired by unsupervised machine learning clustering techniques and traditional asymptotic analysis ideas. We first partition species into 13 blocks, using a novel machine learning approach that analyzes the species network structures and their production and loss rates. Building on these blocks, we pre-select 20 submechanisms, as defined by unique assemblages of the species blocks, and then pick locally on the fly which submechanism to use based on local chemical conditions. In each submechanism, we isolate slow species and unimportant reactions from the coupled system. Application to a global 3-D model shows that we can cut the computational costs of the chemical integration by 50 % with accuracy losses smaller than 1 % that do not propagate in time. Tests show that this algorithm is highly chemically coherent making it easily portable to new models without compromising its performance. Our algorithm will significantly ease the computational bottleneck and will facilitate the development of next generation of earth system models.

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