Geoscientific Model Development

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Combined list of the recent articles of the journal Geoscientific Model Development and the recent discussion forum Geoscientific Model Development Discussions
Updated: 5 hours 21 min ago

The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

Tue, 10/22/2019 - 18:49
The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, 2019
This paper presents an overview of the ESCAPE project. Dwarfs (key patterns in terms of computation and communication) are identified in weather prediction models. They are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain-specific languages. Different numerical techniques are compared in terms of energy efficiency and performance for a variety of computing technologies.

Automated Monte Carlo-based Quantification and Updating of Geological Uncertainty with Borehole Data (AutoBEL v1.0)

Tue, 10/22/2019 - 18:49
Automated Monte Carlo-based Quantification and Updating of Geological Uncertainty with Borehole Data (AutoBEL v1.0)
Zhen Yin, Sebastien Strebelle, and Jef Caers
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-232,2019
Manuscript under review for GMD (discussion: open, 0 comments)

We provide an automated method for uncertainty quantification and updating of geological models using borehole data for subsurface developments (groundwater, geothermal, oil & gas, and CO2 sequestration, etc.) within a Bayesian framework. Our methodologies are developed with the Bayesian Evidential Learning protocol for uncertainty quantification. Under such framework, newly acquired borehole data directly and jointly update geological models (structure, lithology, petrophysics and fluids), globally and spatially, without time-consuming model re-buildings. To address the above, an ensemble of prior geological models is first constructed by Monte Carlo simulation from prior distribution. Once the prior model is tested by means of falsification process, a sequential direct forecasting is designed to perform the joint uncertainty quantification. The direct forecasting is a data-scientific method that learns from a series of bijective operations to establish “Bayes-linear-Gauss” statistical relationships between model and data variables. Such statistical relationships, once conditioned to actual borehole measurements, allows for fast computation posterior geological models. The proposed framework is completely automated in an opensource project. We demonstrate its application by applying to a generalized synthetic dataset motivated by a gas reservoir from Australia. The posterior results show significant uncertainty reduction in both spatial geological model and gas volume prediction, and cannot be falsified by new borehole observations. Furthermore, our automated framework completes the entire uncertainty quantification process efficiently for such large models.

Simulating lightning NO production in CMAQv5.2: performance evaluations

Mon, 10/21/2019 - 18:49
Simulating lightning NO production in CMAQv5.2: performance evaluations
Daiwen Kang, Kristen M. Foley, Rohit Mathur, Shawn J. Roselle, Kenneth E. Pickering, and Dale J. Allen
Geosci. Model Dev., 12, 4409–4424, https://doi.org/10.5194/gmd-12-4409-2019, 2019
This paper provides a comprehensive evaluation of the lightning production schemes in CMAQ as described in https://www.geosci-model-dev.net/12/3071/2019/gmd-12-3071-2019.html on model performance. The impact of lightning NOx from different schemes is evaluated in time and space using both ground–level network measurements and aloft (ozonesonde and aircraft) observations. These results provide users the benchmark model performance when the lightning NOx production schemes are applied.

A Lagrangian convective transport scheme including a simulation of the time air parcels spend in updrafts (LaConTra v1.0)

Fri, 10/18/2019 - 18:49
A Lagrangian convective transport scheme including a simulation of the time air parcels spend in updrafts (LaConTra v1.0)
Ingo Wohltmann, Ralph Lehmann, Georg A. Gottwald, Karsten Peters, Alain Protat, Valentin Louf, Christopher Williams, Wuhu Feng, and Markus Rex
Geosci. Model Dev., 12, 4387–4407, https://doi.org/10.5194/gmd-12-4387-2019, 2019
We present a trajectory-based model for simulating the transport of air parcels by convection. Our model extends the approach of existing models by explicitly simulating vertical updraft velocities inside the clouds and the time that an air parcel spends inside the convective event.

EXPLUME v1.0: a model for personal exposures to ambient O3 and PM2.5

Fri, 10/18/2019 - 18:49
EXPLUME v1.0: a model for personal exposures to ambient O3 and PM2.5
Myrto Valari, Konstandinos Markakis, Emilie Powaga, Bernard Collignan, and Olivier Perrussel
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-259,2019
Manuscript under review for GMD (discussion: open, 0 comments)
To understand how atmospheric pollution affects human health, we need to know the inhaled dose of pollutants. We develop a model that follows the individuals of a population during their daily activities and estimates pollutant concentration levels in the ambient air. We show that certain practices, such as biking in the city, expose people to PM2.5 concentration levels higher that the WHO recommendations. We also show that living in green buildings will decrease significantly exposure to ozone.

A computationally efficient model for probabilistic local warming projections constrained by history matching and pattern scaling

Thu, 10/17/2019 - 18:49
A computationally efficient model for probabilistic local warming projections constrained by history matching and pattern scaling
Philip Goodwin, Martin Leduc, Antti-Ilari Partanen, H. Damon Matthews, and Alex Rogers
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-264,2019
Manuscript under review for GMD (discussion: open, 0 comments)
Numerical climate models are used to make projections of future surface warming for different pathways of future greenhouse gass emissions, where future surface warming will vary from place to place. However, it is so expensive to run complex models using supercomputers that future projections can only be produced for a small number of possible future emissions pathways. This study presents an efficient climate model to make projections of local surface warming using a desktop computer.

The Zero Emissions Commitment Model Intercomparison Project (ZECMIP) contribution to C4MIP: quantifying committed climate changes following zero carbon emissions

Tue, 10/15/2019 - 18:49
The Zero Emissions Commitment Model Intercomparison Project (ZECMIP) contribution to C4MIP: quantifying committed climate changes following zero carbon emissions
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
Geosci. Model Dev., 12, 4375–4385, https://doi.org/10.5194/gmd-12-4375-2019, 2019
Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description

Mon, 10/14/2019 - 18:49
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, 2019
Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America

Mon, 10/14/2019 - 18:49
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, 2019
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.

The interactive global fire module pyrE

Mon, 10/14/2019 - 18:49
The interactive global fire module pyrE
Keren Mezuman, Konstantinos Tsigaridis, Gregory Faluvegi, and Susanne E. Bauer
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-263,2019
Manuscript under review for GMD (discussion: open, 0 comments)
Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth System Model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS interactive fire emissions module. The main motivation behind this work, is to have fire emissions reacting to climate change and anthropogenic activities.

Tracking water masses using passive-tracer transport in NEMO v3.4 with NEMOTAM: application to North Atlantic Deep Water and North Atlantic Subtropical Mode Water

Mon, 10/14/2019 - 18:49
Tracking water masses using passive-tracer transport in NEMO v3.4 with NEMOTAM: application to North Atlantic Deep Water and North Atlantic Subtropical Mode Water
Dafydd Stephenson, Simon Müller, and Florian Sévellec
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-245,2019
Manuscript under review for GMD (discussion: open, 0 comments)
Different water types are created at the sea surface with a signature based on the local conditions of the atmosphere. They then take these conditions with them into the deeper ocean, and so their journey is an important climate process to understand. In this study, we modify and repurpose a specialised model which simulates the ocean forward and backward in time to determine where new ocean water goes, where at the surface existing water comes from, and how old it is, by tracking it as a dye.

Parallel I/O in FMS and MOM5

Fri, 10/11/2019 - 18:49
Parallel I/O in FMS and MOM5
Rui Yang, Marshall Ward, and Ben Evans
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-257,2019
Manuscript under review for GMD (discussion: open, 0 comments)
Parallel I/O is implemented in the Modular Ocean Model (MOM) with optimal performance over a range of tuning parameters at model configuration, netCDF, MPI-IO and Lustre filesystem. The scalable parallel I/O performance is observed at 0.1° resolution global model and it could achieve up to 60 times faster in write speed relative to serial single-file I/O running on 960PEs.

What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models

Thu, 10/10/2019 - 18:49
What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models
Razi Sheikholeslami, Saman Razavi, and Amin Haghnegahdar
Geosci. Model Dev., 12, 4275–4296, https://doi.org/10.5194/gmd-12-4275-2019, 2019
The ever-growing complexity of Earth and environmental system models can pose many types of software development and implementation issues such as parameter-induced simulation crashes, which are mainly caused by the violation of numerical stability conditions. Here, we introduce a new approach to handle crashed simulations when performing sensitivity analysis. Our results show that this approach can comply well with the dimensionality of the model, sample size, and the number of crashes.

Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model

Thu, 10/10/2019 - 18:49
Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model
Jiali Wang, Prasanna Balaprakash, and Rao Kotamarthi
Geosci. Model Dev., 12, 4261–4274, https://doi.org/10.5194/gmd-12-4261-2019, 2019
Parameterizations are frequently used in models representing physical phenomena and are often the computationally expensive portions of the code. Using model output from simulations performed using a weather model, we train deep neural networks to provide an accurate alternative to a physics-based parameterization. We demonstrate that a domain-aware deep neural network can successfully simulate the entire diurnal cycle of the boundary layer physics and the results are transferable.

Incorporation of inline warm rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation

Thu, 10/10/2019 - 18:49
Incorporation of inline warm rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation
Takuro Michibata, Kentaroh Suzuki, Tomoo Ogura, and Xianwen Jing
Geosci. Model Dev., 12, 4297–4307, https://doi.org/10.5194/gmd-12-4297-2019, 2019
A new diagnostic tool for cloud and precipitation microphysics has been added to the latest version of the Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP2). The tool generates warm rain process statistics from several instrument simulators online during the COSP execution. This online diagnostic is intended to serve as a tool that facilitates efficient model development and the evaluation of multiple climate models.

Development of turbulent scheme in the FLEXPART-AROME v1.2.1 Lagrangian particle dispersion model

Wed, 10/09/2019 - 18:49
Development of turbulent scheme in the FLEXPART-AROME v1.2.1 Lagrangian particle dispersion model
Bert Verreyken, Jérome Brioude, and Stéphanie Evan
Geosci. Model Dev., 12, 4245–4259, https://doi.org/10.5194/gmd-12-4245-2019, 2019
The Lagrangian particle dispersion model FLEXPART-AROME was built to study air mass transport around La Réunion, a volcanic island in the southwest Indian Ocean. To harmonize turbulent transport between the numerical weather prediction model and the transport model, turbulent kinetic energy from AROME is directly used in FLEXPART-AROME using discrete interfaces between different turbulent regions. An adaptive time step was implemented to satisfy physical constraints on turbulent transport.

SKRIPS v1.0: a regional coupled ocean–atmosphere modeling framework (MITgcm–WRF) using ESMF/NUOPC, description and preliminary results for the Red Sea

Tue, 10/08/2019 - 18:49
SKRIPS v1.0: a regional coupled ocean–atmosphere modeling framework (MITgcm–WRF) using ESMF/NUOPC, description and preliminary results for the Red Sea
Rui Sun, Aneesh C. Subramanian, Arthur J. Miller, Matthew R. Mazloff, Ibrahim Hoteit, and Bruce D. Cornuelle
Geosci. Model Dev., 12, 4221–4244, https://doi.org/10.5194/gmd-12-4221-2019, 2019
A new regional coupled ocean–atmosphere model, SKRIPS, is developed and presented. The oceanic component is the MITgcm and the atmospheric component is the WRF model. The coupler is implemented using ESMF according to NUOPC protocols. SKRIPS is demonstrated by simulating a series of extreme heat events occurring in the Red Sea region. We show that SKRIPS is capable of performing coupled ocean–atmosphere simulations. In addition, the scalability test shows SKRIPS is computationally efficient.

APIFLAME v2.0 trace gas and aerosol emissions from biomass burning: application to Portugal during the summer of 2016 and evaluation against satellite observations of CO (IASI) and AOD (MODIS)

Tue, 10/08/2019 - 18:49
APIFLAME v2.0 trace gas and aerosol emissions from biomass burning: application to Portugal during the summer of 2016 and evaluation against satellite observations of CO (IASI) and AOD (MODIS)
Solène Turquety, Laurent Menut, Guillaume Siour, Sylvain Mailler, Juliette Hadji-Lazaro, Maya George, Cathy Clerbaux, Daniel Hurtmans, and Pierre-François Coheur
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-210,2019
Manuscript under review for GMD (discussion: open, 0 comments)
Biomass burning emissions are a major source of trace gases and aerosols that needs to be accounted for for air quality assessment and forecasting. The APIFLAME model presented in this publication allows the calculation of these emissions based on satellite observations at hourly time-step and kilometric scale. An illustration for the simulation of the pollution plume associated with the large wildfires that burned in Portugal in August 2016 is presented.

Description of the MIROC-ES2L Earth system model and evaluation of its climate–biogeochemical processes and feedbacks

Tue, 10/08/2019 - 18:49
Description of the MIROC-ES2L Earth system model and evaluation of its climate–biogeochemical processes and feedbacks
Tomohiro Hajima, Michio Watanabe, Akitomo Yamamoto, Hiroaki Tatebe, Maki A. Noguchi, Manabu Abe, Rumi Ohgaito, Akinori Ito, Dai Yamazaki, Hideki Okajima, Akihiko Ito, Kumiko Takata, Koji Ogochi, Shingo Watanabe, and Michio Kawamiya
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-275,2019
Manuscript under review for GMD (discussion: open, 0 comments)
We developed a new Earth system model (ESM) named MIROC-ES2L. This model is based on a state-of-the-art climate model, and includes carbon–nitrogen cycles for the land and multiple biogeochemical cycles for the ocean. The model's performances on reproducing historical climate and biogeochemical changes are confirmed to be reasonable, and the new model is likely to be an optimistic model in projecting future climate change, among ESMs in the Coupled Model Intercomparison Project Phase 6.

Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)

Tue, 10/08/2019 - 18:49
Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
Jorge Vicent, Jochem Verrelst, Neus Sabater, Luis Alonso, Juan Pablo Rivera-Caicedo, Luca Martino, Jordi Muñoz-Marí, and José Moreno
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-188,2019
Manuscript under review for GMD (discussion: open, 3 comments)
The modelling of light propagation through the atmosphere is key to process satellite images and to understand atmospheric processes. However, existing atmospheric models can be complex for using them in practical applications. Here we aim at providing a new software tool to facilitate using advanced models and to generate large databases of simulated data. As a test case, we use this tool to analyze differences between several atmospheric models, showing the capabilities of this freesource tool

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