Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-575-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-575-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
08 Feb 2018
Development and technical paper |
| 08 Feb 2018
Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses
Thomas Rößler
CORRESPONDING AUTHOR
Forschungszentrum Jülich, Jülich Supercomputing Centre,
Jülich, Germany
Department of Mathematics,
University of Wisconsin–Milwaukee, Milwaukee, WI, USA
Olaf Stein
Forschungszentrum Jülich, Jülich Supercomputing Centre,
Jülich, Germany
Yi Heng
School of Chemical Engineering and Technology, Sun
Yat-sen University, Guangzhou, China
Paul Baumeister
Forschungszentrum Jülich, Jülich Supercomputing Centre,
Jülich, Germany
Lars Hoffmann
Forschungszentrum Jülich, Jülich Supercomputing Centre,
Jülich, Germany
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Sabine Griessbach, Lars Hoffmann, Reinhold Spang, Peggy Achtert, Marc von Hobe, Nina Mateshvili, Rolf Müller, Martin Riese, Christian Rolf, Patric Seifert, and Jean-Paul Vernier
Atmos. Meas. Tech., 13, 1243–1271, https://doi.org/10.5194/amt-13-1243-2020, https://doi.org/10.5194/amt-13-1243-2020, 2020
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Neil P. Hindley, Corwin J. Wright, Nathan D. Smith, Lars Hoffmann, Laura A. Holt, M. Joan Alexander, Tracy Moffat-Griffin, and Nicholas J. Mitchell
Atmos. Chem. Phys., 19, 15377–15414, https://doi.org/10.5194/acp-19-15377-2019, https://doi.org/10.5194/acp-19-15377-2019, 2019
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Lars Hoffmann, Gebhard Günther, Dan Li, Olaf Stein, Xue Wu, Sabine Griessbach, Yi Heng, Paul Konopka, Rolf Müller, Bärbel Vogel, and Jonathon S. Wright
Atmos. Chem. Phys., 19, 3097–3124, https://doi.org/10.5194/acp-19-3097-2019, https://doi.org/10.5194/acp-19-3097-2019, 2019
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ECMWF's new ERA5 reanalysis provides higher spatiotemporal resolution, yielding an improved representation of meso- and synoptic-scale features of the atmosphere. We assessed the impact of this challenging new data set on Lagrangian trajectory calculations for the free troposphere and stratosphere. Key findings are considerable transport deviations between the ERA5 and ERA-Interim simulations as well as significantly improved conservation of potential temperature in the stratosphere for ERA5.
Xue Wu, Sabine Griessbach, and Lars Hoffmann
Atmos. Chem. Phys., 18, 15859–15877, https://doi.org/10.5194/acp-18-15859-2018, https://doi.org/10.5194/acp-18-15859-2018, 2018
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Volcanic aerosol is an important source of sulfur for Antarctica, where local sources of sulfur are rare. Midlatitude and high-latitude volcanism can directly influence the aerosol budget of the polar stratosphere, but tropical volcanic eruptions can also enhance polar aerosols by transport. Our study investigates pathway and transport processes of volcanic aerosol from the tropics to the lower stratosphere over Antarctica by combining Lagrangian transport simulation and satellite observations.
Reinhold Spang, Lars Hoffmann, Rolf Müller, Jens-Uwe Grooß, Ines Tritscher, Michael Höpfner, Michael Pitts, Andrew Orr, and Martin Riese
Atmos. Chem. Phys., 18, 5089–5113, https://doi.org/10.5194/acp-18-5089-2018, https://doi.org/10.5194/acp-18-5089-2018, 2018
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This paper represents an unprecedented pole-covering day- and nighttime climatology of the polar stratospheric clouds (PSCs) based on satellite measurements, their spatial distribution, and composition of different particle types. The climatology has a high potential for the validation and improvement of PSC schemes in chemical transport and chemistry–climate models, which is important for a better prediction of future polar ozone loss in a changing climate.
Catrin I. Meyer, Manfred Ern, Lars Hoffmann, Quang Thai Trinh, and M. Joan Alexander
Atmos. Meas. Tech., 11, 215–232, https://doi.org/10.5194/amt-11-215-2018, https://doi.org/10.5194/amt-11-215-2018, 2018
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We investigate stratospheric gravity wave observations by the Atmospheric InfraRed Sounder (AIRS) and the High Resolution Dynamics Limb Sounder (HIRDLS). Waves seen by AIRS contribute significantly to momentum flux, which indicates a calculated momentum flux factor. AIRS and HIRDLS agree well in the phase structure of the wave events and also in the seasonal and latitudinal patterns of gravity wave activity and can be used complementary to each other.
Xue Wu, Sabine Griessbach, and Lars Hoffmann
Atmos. Chem. Phys., 17, 13439–13455, https://doi.org/10.5194/acp-17-13439-2017, https://doi.org/10.5194/acp-17-13439-2017, 2017
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This study is focused on the Sarychev eruption in 2009. Based on Lagrangian model simulations and satellite data, the equatorward transport of the plume and aerosol from the Sarychev eruption is confirmed, and the transport is facilitated by the Asian summer monsoon anticyclonic circulations. The aerosol transported to the tropics remained for months and dispersed upward, which could make the Sarychev eruption have a similar global climate impact as a tropical volcanic eruption.
Corwin J. Wright, Neil P. Hindley, Lars Hoffmann, M. Joan Alexander, and Nicholas J. Mitchell
Atmos. Chem. Phys., 17, 8553–8575, https://doi.org/10.5194/acp-17-8553-2017, https://doi.org/10.5194/acp-17-8553-2017, 2017
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We introduce a novel 3-D method of measuring atmospheric gravity waves, based around a 3-D Stockwell transform. Our method lets us measure new properties, including wave intrinsic frequencies and phase and group velocities. We apply it to data from the AIRS satellite instrument over the Southern Andes for two consecutive winters. Our results show clear evidence that the waves measured are primarily orographic in origin, and that their group velocity vectors are focused into the polar night jet.
Lars Hoffmann, Albert Hertzog, Thomas Rößler, Olaf Stein, and Xue Wu
Atmos. Chem. Phys., 17, 8045–8061, https://doi.org/10.5194/acp-17-8045-2017, https://doi.org/10.5194/acp-17-8045-2017, 2017
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We present an intercomparison of temperatures and horizontal winds of five meteorological data sets (ECMWF operational analysis, ERA-Interim, MERRA, MERRA-2, and NCEP/NCAR) in the Antarctic lower stratosphere. The assessment is based on 19 superpressure balloon flights during the Concordiasi field campaign in September 2010 to January 2011. The balloon data are used to successfully validate trajectory calculations with the new Lagrangian particle dispersion model MPTRAC.
Lars Hoffmann, Reinhold Spang, Andrew Orr, M. Joan Alexander, Laura A. Holt, and Olaf Stein
Atmos. Chem. Phys., 17, 2901–2920, https://doi.org/10.5194/acp-17-2901-2017, https://doi.org/10.5194/acp-17-2901-2017, 2017
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We introduce a 10-year record (2003–2012) of AIRS/Aqua observations of gravity waves in the polar lower stratosphere. The data set was optimized to study the impact of gravity waves on the formation of polar stratospheric clouds (PSCs). We discuss the temporal and spatial patterns of gravity wave activity, validate explicitly resolved small-scale temperature fluctuations in the ECMWF data, and present a survey of gravity-wave-induced PSC formation events using joint AIRS and MIPAS observations.
Sabine Griessbach, Lars Hoffmann, Reinhold Spang, Marc von Hobe, Rolf Müller, and Martin Riese
Atmos. Meas. Tech., 9, 4399–4423, https://doi.org/10.5194/amt-9-4399-2016, https://doi.org/10.5194/amt-9-4399-2016, 2016
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A new method for detecting aerosol in the UTLS based on infrared limb emission measurements is presented. The method was developed using radiative transfer simulations (including scattering) and Envisat MIPAS measurements. Results are presented for volcanic ash and sulfate aerosol originating from the Grimsvötn (Iceland), Puyehue–Cordon Caulle (Chile), and Nabro (Eritrea) eruptions in 2011 and compared with AIRS volcanic ash and SO2 measurements.
Reinhold Spang, Lars Hoffmann, Michael Höpfner, Sabine Griessbach, Rolf Müller, Michael C. Pitts, Andrew M. W. Orr, and Martin Riese
Atmos. Meas. Tech., 9, 3619–3639, https://doi.org/10.5194/amt-9-3619-2016, https://doi.org/10.5194/amt-9-3619-2016, 2016
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We present a new classification approach for different polar stratospheric cloud types. The so-called Bayesian classifier estimates the most likely probability that one of the three PSC types (ice, NAT, or STS) dominates the characteristics of a measured infrared spectrum. The entire measurement period of the satellite instrument MIPAS from July 2002 to April 2013 is processed using the new classifier.
Lars Hoffmann, Alison W. Grimsdell, and M. Joan Alexander
Atmos. Chem. Phys., 16, 9381–9397, https://doi.org/10.5194/acp-16-9381-2016, https://doi.org/10.5194/acp-16-9381-2016, 2016
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We present a 12-year record (2003-2014) of stratospheric gravity wave activity at Southern Hemisphere orographic hotspots as observed by the AIRS/Aqua satellite instrument. We introduce a method to discriminate between gravity waves from orographic or other sources and propose a simple model to predict the occurrence of mountain waves using zonal wind thresholds. The prediction model can help to disentangle upper level wind effects from low level source and other influences.
Yi Heng, Lars Hoffmann, Sabine Griessbach, Thomas Rößler, and Olaf Stein
Geosci. Model Dev., 9, 1627–1645, https://doi.org/10.5194/gmd-9-1627-2016, https://doi.org/10.5194/gmd-9-1627-2016, 2016
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A new inverse modeling and simulation system is developed to enable efficient and reliable transport simulations of volcanic SO2 at large scale. The complex time- and altitude-dependent volcanic emission pattern of the Nabro eruption is identified by our inversion algorithm. The simulation results show good agreements with different satellite observations in terms of SO2 horizontal distributions, and help to further reveal the complex transport processes such as the Asian monsoon circulation.
A. Wagner, A.-M. Blechschmidt, I. Bouarar, E.-G. Brunke, C. Clerbaux, M. Cupeiro, P. Cristofanelli, H. Eskes, J. Flemming, H. Flentje, M. George, S. Gilge, A. Hilboll, A. Inness, J. Kapsomenakis, A. Richter, L. Ries, W. Spangl, O. Stein, R. Weller, and C. Zerefos
Atmos. Chem. Phys., 15, 14005–14030, https://doi.org/10.5194/acp-15-14005-2015, https://doi.org/10.5194/acp-15-14005-2015, 2015
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The Monitoring Atmospheric Composition and Climate project (MACC) operationally produces global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the model to simulate concentrations of reactive gases (carbon monoxide, nitrogen dioxide and ozone) between 2009 and 2012. The model reproduced reactive gas concentrations with consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations.
E. Katragkou, P. Zanis, A. Tsikerdekis, J. Kapsomenakis, D. Melas, H. Eskes, J. Flemming, V. Huijnen, A. Inness, M. G. Schultz, O. Stein, and C. S. Zerefos
Geosci. Model Dev., 8, 2299–2314, https://doi.org/10.5194/gmd-8-2299-2015, https://doi.org/10.5194/gmd-8-2299-2015, 2015
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This work is an extended evaluation of near-surface ozone as part of the global reanalysis of atmospheric composition, produced within the European-funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003-2012 and provides an overall assessment of the modelling system performance with respect to near surface ozone for specific European subregions.
J. Flemming, V. Huijnen, J. Arteta, P. Bechtold, A. Beljaars, A.-M. Blechschmidt, M. Diamantakis, R. J. Engelen, A. Gaudel, A. Inness, L. Jones, B. Josse, E. Katragkou, V. Marecal, V.-H. Peuch, A. Richter, M. G. Schultz, O. Stein, and A. Tsikerdekis
Geosci. Model Dev., 8, 975–1003, https://doi.org/10.5194/gmd-8-975-2015, https://doi.org/10.5194/gmd-8-975-2015, 2015
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We describe modules for atmospheric chemistry, wet and dry deposition and lightning NO production, which have been newly introduced in ECMWF's weather forecasting model. With that model, we want to forecast global air pollution as part of the European Copernicus Atmosphere Monitoring Service. We show that the new model results compare as well or better with in situ and satellite observations of ozone, CO, NO2, SO2 and formaldehyde as the previous model.
K. Lefever, R. van der A, F. Baier, Y. Christophe, Q. Errera, H. Eskes, J. Flemming, A. Inness, L. Jones, J.-C. Lambert, B. Langerock, M. G. Schultz, O. Stein, A. Wagner, and S. Chabrillat
Atmos. Chem. Phys., 15, 2269–2293, https://doi.org/10.5194/acp-15-2269-2015, https://doi.org/10.5194/acp-15-2269-2015, 2015
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We validate and discuss the analyses of stratospheric ozone delivered in near-real time between 2009 and 2012 by four different data assimilation systems: IFS-MOZART, BASCOE, SACADA and TM3DAM. It is shown that the characteristics of the assimilation systems are much less important than those of the assimilated data sets. A correct representation of the vertical distribution of ozone requires satellite observations which are well resolved vertically and extend into the lowermost stratosphere.
A. Orr, J. S. Hosking, L. Hoffmann, J. Keeble, S. M. Dean, H. K. Roscoe, N. L. Abraham, S. Vosper, and P. Braesicke
Atmos. Chem. Phys., 15, 1071–1086, https://doi.org/10.5194/acp-15-1071-2015, https://doi.org/10.5194/acp-15-1071-2015, 2015
R. Spang, G. Günther, M. Riese, L. Hoffmann, R. Müller, and S. Griessbach
Atmos. Chem. Phys., 15, 927–950, https://doi.org/10.5194/acp-15-927-2015, https://doi.org/10.5194/acp-15-927-2015, 2015
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Here we present observations of the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) of cirrus cloud and water vapour in August 1997 in the upper troposphere and lower stratosphere (UTLS) region. The observations indicate a considerable flux of moisture from the upper tropical troposphere into the extra-tropical lowermost stratosphere (LMS), resulting in the occurrence of high-altitude optically thin cirrus clouds in the LMS.
L. Hoffmann, M. J. Alexander, C. Clerbaux, A. W. Grimsdell, C. I. Meyer, T. Rößler, and B. Tournier
Atmos. Meas. Tech., 7, 4517–4537, https://doi.org/10.5194/amt-7-4517-2014, https://doi.org/10.5194/amt-7-4517-2014, 2014
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We present stratospheric gravity wave observations from 4.3 micron radiance measurements by the nadir sounders AIRS and IASI. Three case studies demonstrate that AIRS and IASI provide a consistent picture of the temporal development of individual gravity wave events. Statistical comparisons based on five years of data (2008-2012) also showed similar patterns of gravity wave activity. Long-term records from combined satellite data are an exciting prospect for future gravity wave research.
R. Pommrich, R. Müller, J.-U. Grooß, P. Konopka, F. Ploeger, B. Vogel, M. Tao, C. M. Hoppe, G. Günther, N. Spelten, L. Hoffmann, H.-C. Pumphrey, S. Viciani, F. D'Amato, C. M. Volk, P. Hoor, H. Schlager, and M. Riese
Geosci. Model Dev., 7, 2895–2916, https://doi.org/10.5194/gmd-7-2895-2014, https://doi.org/10.5194/gmd-7-2895-2014, 2014
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A version of the chemical transport model CLaMS is presented, which features a simplified (numerically inexpensive) chemistry scheme. The model results using this version of CLaMS show a good representation of anomaly fields of CO, CH4, N2O, and CFC-11 in the lower stratosphere. CO measurements of three instruments (COLD, HAGAR, and Falcon-CO) in the lower tropical stratosphere (during the campaign TROCCINOX in 2005) have been compared and show a good agreement within the error bars.
L. Hoffmann, C. M. Hoppe, R. Müller, G. S. Dutton, J. C. Gille, S. Griessbach, A. Jones, C. I. Meyer, R. Spang, C. M. Volk, and K. A. Walker
Atmos. Chem. Phys., 14, 12479–12497, https://doi.org/10.5194/acp-14-12479-2014, https://doi.org/10.5194/acp-14-12479-2014, 2014
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Stratospheric lifetimes determine the global warming and ozone depletion potentials of chlorofluorocarbons. We present new estimates of the CFC-11/CFC-12 lifetime ratio from satellite and model data (ACE-FTS, HIRDLS, MIPAS, and EMAC/CLaMS). Our estimates of 0.46+/-0.04 (satellites) and 0.48+/-0.07 (model) are in excellent agreement with the recent SPARC reassessment. Having smaller uncertainties than other studies, our results can help to better constrain future CFC lifetime recommendations.
C. M. Hoppe, L. Hoffmann, P. Konopka, J.-U. Grooß, F. Ploeger, G. Günther, P. Jöckel, and R. Müller
Geosci. Model Dev., 7, 2639–2651, https://doi.org/10.5194/gmd-7-2639-2014, https://doi.org/10.5194/gmd-7-2639-2014, 2014
O. Stein, M. G. Schultz, I. Bouarar, H. Clark, V. Huijnen, A. Gaudel, M. George, and C. Clerbaux
Atmos. Chem. Phys., 14, 9295–9316, https://doi.org/10.5194/acp-14-9295-2014, https://doi.org/10.5194/acp-14-9295-2014, 2014
S. Griessbach, L. Hoffmann, R. Spang, and M. Riese
Atmos. Meas. Tech., 7, 1487–1507, https://doi.org/10.5194/amt-7-1487-2014, https://doi.org/10.5194/amt-7-1487-2014, 2014
C. Kalicinsky, J.-U. Grooß, G. Günther, J. Ungermann, J. Blank, S. Höfer, L. Hoffmann, P. Knieling, F. Olschewski, R. Spang, F. Stroh, and M. Riese
Atmos. Chem. Phys., 13, 10859–10871, https://doi.org/10.5194/acp-13-10859-2013, https://doi.org/10.5194/acp-13-10859-2013, 2013
J. Ungermann, L. L. Pan, C. Kalicinsky, F. Olschewski, P. Knieling, J. Blank, K. Weigel, T. Guggenmoser, F. Stroh, L. Hoffmann, and M. Riese
Atmos. Chem. Phys., 13, 10517–10534, https://doi.org/10.5194/acp-13-10517-2013, https://doi.org/10.5194/acp-13-10517-2013, 2013
M. von Hobe, S. Bekki, S. Borrmann, F. Cairo, F. D'Amato, G. Di Donfrancesco, A. Dörnbrack, A. Ebersoldt, M. Ebert, C. Emde, I. Engel, M. Ern, W. Frey, S. Genco, S. Griessbach, J.-U. Grooß, T. Gulde, G. Günther, E. Hösen, L. Hoffmann, V. Homonnai, C. R. Hoyle, I. S. A. Isaksen, D. R. Jackson, I. M. Jánosi, R. L. Jones, K. Kandler, C. Kalicinsky, A. Keil, S. M. Khaykin, F. Khosrawi, R. Kivi, J. Kuttippurath, J. C. Laube, F. Lefèvre, R. Lehmann, S. Ludmann, B. P. Luo, M. Marchand, J. Meyer, V. Mitev, S. Molleker, R. Müller, H. Oelhaf, F. Olschewski, Y. Orsolini, T. Peter, K. Pfeilsticker, C. Piesch, M. C. Pitts, L. R. Poole, F. D. Pope, F. Ravegnani, M. Rex, M. Riese, T. Röckmann, B. Rognerud, A. Roiger, C. Rolf, M. L. Santee, M. Scheibe, C. Schiller, H. Schlager, M. Siciliani de Cumis, N. Sitnikov, O. A. Søvde, R. Spang, N. Spelten, F. Stordal, O. Sumińska-Ebersoldt, A. Ulanovski, J. Ungermann, S. Viciani, C. M. Volk, M. vom Scheidt, P. von der Gathen, K. Walker, T. Wegner, R. Weigel, S. Weinbruch, G. Wetzel, F. G. Wienhold, I. Wohltmann, W. Woiwode, I. A. K. Young, V. Yushkov, B. Zobrist, and F. Stroh
Atmos. Chem. Phys., 13, 9233–9268, https://doi.org/10.5194/acp-13-9233-2013, https://doi.org/10.5194/acp-13-9233-2013, 2013
K. Minschwaner, L. Hoffmann, A. Brown, M. Riese, R. Müller, and P. F. Bernath
Atmos. Chem. Phys., 13, 4253–4263, https://doi.org/10.5194/acp-13-4253-2013, https://doi.org/10.5194/acp-13-4253-2013, 2013
A. Inness, F. Baier, A. Benedetti, I. Bouarar, S. Chabrillat, H. Clark, C. Clerbaux, P. Coheur, R. J. Engelen, Q. Errera, J. Flemming, M. George, C. Granier, J. Hadji-Lazaro, V. Huijnen, D. Hurtmans, L. Jones, J. W. Kaiser, J. Kapsomenakis, K. Lefever, J. Leitão, M. Razinger, A. Richter, M. G. Schultz, A. J. Simmons, M. Suttie, O. Stein, J.-N. Thépaut, V. Thouret, M. Vrekoussis, C. Zerefos, and the MACC team
Atmos. Chem. Phys., 13, 4073–4109, https://doi.org/10.5194/acp-13-4073-2013, https://doi.org/10.5194/acp-13-4073-2013, 2013
Related subject area
Numerical methods
LISFLOOD-FP 8.1: new GPU-accelerated solvers for faster fluvial/pluvial flood simulations
Fast approximate Barnes interpolation: illustrated by Python-Numba implementation fast-barnes-py v1.0
Strategies for conservative and non-conservative monotone remapping on the sphere
Modeling large‐scale landform evolution with a stream power law for glacial erosion (OpenLEM v37): benchmarking experiments against a more process-based description of ice flow (iSOSIA v3.4.3)
A mixed finite-element discretisation of the shallow-water equations
Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling
Leveraging Google’s Tensor Processing Units for tsunami-risk mitigation planning in the Pacific Northwest and beyond
Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN
Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes
A Model Instability Issue in the NCEP Global Forecast System Version 16 and Potential Solutions
The Intelligent Prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning
ISMIP-HOM benchmark experiments using Underworld
spyro: a Firedrake-based wave propagation and full-waveform-inversion finite-element solver
A Comparison of 3-D Spherical Shell Thermal Convection results at Low to Moderate Rayleigh Number using ASPECT (version 2.2.0) and CitcomS (version 3.3.1)
Spatial filtering in a 6D hybrid-Vlasov scheme to alleviate adaptive mesh refinement artifacts: a case study with Vlasiator (versions 5.0, 5.1, and 5.2.1)
A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1
A fast, single-iteration ensemble Kalman smoother for sequential data assimilation
An improved subgrid channel model with upwind form artificial diffusion for river hydrodynamics and floodplain inundation simulation
Characterizing uncertainties of Earth system modeling with heterogeneous many-core architecture computing
Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models
Impact of the numerical solution approach of a plant hydrodynamic model (v0.1) on vegetation dynamics
Islet: interpolation semi-Lagrangian element-based transport
Multi-dimensional hydrological–hydraulic model with variational data assimilation for river networks and floodplains
Assessing the robustness and scalability of the accelerated pseudo-transient method
Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation
University of Warsaw Lagrangian Cloud Model (UWLCM) 2.0: adaptation of a mixed Eulerian–Lagrangian numerical model for heterogeneous computing clusters
Prediction error growth in a more realistic atmospheric toy model with three spatiotemporal scales
On numerical broadening of particle-size spectra: a condensational growth study using PyMPDATA 1.0
Lossy checkpoint compression in full waveform inversion: a case study with ZFPv0.5.5 and the overthrust model
Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
Improved double Fourier series on a sphere and its application to a semi-implicit semi-Lagrangian shallow-water model
SciKit-GStat 1.0: a SciPy-flavored geostatistical variogram estimation toolbox written in Python
Flow-Py v1.0: a customizable, open-source simulation tool to estimate runout and intensity of gravitational mass flows
Emulation of high-resolution land surface models using sparse Gaussian processes with application to JULES
A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations
Implementation of a Gaussian Markov random field sampler for forward uncertainty quantification in the Ice-sheet and Sea-level System Model v4.19
A method for assessment of the general circulation model quality using the K-means clustering algorithm: a case study with GETM v2.5
An explicit GPU-based material point method solver for elastoplastic problems (ep2-3De v1.0)
MagIC v5.10: a two-dimensional message-passing interface (MPI) distribution for pseudo-spectral magnetohydrodynamics simulations in spherical geometry
Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets
Recalculation of error growth models' parameters for the ECMWF forecast system
How biased are our models? – a case study of the alpine region
B-flood 1.0: an open-source Saint-Venant model for flash-flood simulation using adaptive refinement
A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea
SymPKF (v1.0): a symbolic and computational toolbox for the design of parametric Kalman filter dynamics
NDCmitiQ v1.0.0: a tool to quantify and analyse greenhouse gas mitigation targets
Combining ensemble Kalman filter and reservoir computing to predict spatiotemporal chaotic systems from imperfect observations and models
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
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This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
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We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
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In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
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This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
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This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Ian Madden, Simone Marras, and Jenny Suckale
EGUsphere, https://doi.org/10.5194/egusphere-2023-116, https://doi.org/10.5194/egusphere-2023-116, 2023
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To aid risk managers who may wish to rapidly assess tsunami-risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
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We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
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We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
Xiaqiong Zhou and Hann-Ming Henry Juang
EGUsphere, https://doi.org/10.5194/egusphere-2022-1235, https://doi.org/10.5194/egusphere-2022-1235, 2023
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GFS is one of the most important operational global weather forecast systems at NCEP/EMC. The stability of GFS on model integration is as important as its forecast skills to deliver dependable real-time products to its users and downstream forecast systems. The model instability issue of GFSv16 caught our attention when several cases in its real-time parallel runs failed to finish 16-day forecasts. Potential solutions were proposed to fix the model instability issue.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
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In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
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While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
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Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
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Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Grant Thomas Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott David King
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-252, https://doi.org/10.5194/gmd-2022-252, 2022
Revised manuscript accepted for GMD
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Due to the increasing availability of high-performance computing over the past decades numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously-known information to modern methodologies.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
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Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
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Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-234, https://doi.org/10.5194/gmd-2022-234, 2022
Revised manuscript accepted for GMD
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A novel subgrid channel model (SGC) is developed for river-floodplain modelling, allowing utilization of sub-grid scale bathymetric information while performing computations on relatively coarse grids. By including an adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low friction regions such as the urban areas is addressed. Evaluation of the new SGC model through a structured tests confirmed that the accuracy and stability has been improved.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
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To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Vijay S. Mahadevan, Jorge E. Guerra, Xiangmin Jiao, Paul Kuberry, Yipeng Li, Paul Ullrich, David Marsico, Robert Jacob, Pavel Bochev, and Philip Jones
Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
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Coupled Earth system models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity, and local feature preservation of four different remapper algorithms for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
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Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
Léo Pujol, Pierre-André Garambois, and Jérôme Monnier
Geosci. Model Dev., 15, 6085–6113, https://doi.org/10.5194/gmd-15-6085-2022, https://doi.org/10.5194/gmd-15-6085-2022, 2022
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This contribution presents a new numerical model for representing hydraulic–hydrological quantities at the basin scale. It allows modeling large areas at a low computational cost, with fine zooms where needed. It allows the integration of local and satellite measurements, via data assimilation methods, to improve the model's match to observations. Using this capability, good matches to in situ observations are obtained on a model of the complex Adour river network with fine zooms on floodplains.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
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Continuum mechanics-based modelling of physical processes at large scale requires huge computational resources provided by massively parallel hardware such as graphical processing units. We present a suite of numerical algorithms, implemented using the Julia language, that efficiently leverages the parallelism. We demonstrate that our implementation is efficient, scalable and robust and showcase applications to various geophysical problems.
Meriem Krouma, Pascal Yiou, Céline Déandreis, and Soulivanh Thao
Geosci. Model Dev., 15, 4941–4958, https://doi.org/10.5194/gmd-15-4941-2022, https://doi.org/10.5194/gmd-15-4941-2022, 2022
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We evaluated the skill of a stochastic weather generator (SWG) to forecast precipitation at different time scales and in different areas of western Europe from analogs of Z500 hPa. The SWG has the skill to simulate precipitation for 5 and 10 d. We found that forecast weaknesses can be associated with specific weather patterns. The comparison with ECMWF forecasts confirms the skill of our model. This work is important because it provides information about weather forecasts over specific areas.
Piotr Dziekan and Piotr Zmijewski
Geosci. Model Dev., 15, 4489–4501, https://doi.org/10.5194/gmd-15-4489-2022, https://doi.org/10.5194/gmd-15-4489-2022, 2022
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Detailed computer simulations of clouds are important for understanding Earth's atmosphere and climate. The paper describes how the UWLCM has been adapted to work on supercomputers. A distinctive feature of UWLCM is that air flow is calculated by processors at the same time as cloud droplets are modeled by graphics cards. Thanks to this, use of computing resources is maximized and the time to complete simulations of large domains is not affected by communications between supercomputer nodes.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 15, 4147–4161, https://doi.org/10.5194/gmd-15-4147-2022, https://doi.org/10.5194/gmd-15-4147-2022, 2022
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A scale-dependent error growth described by a power law or by a quadratic hypothesis is studied in Lorenz’s system with three spatiotemporal levels. The validity of power law is extended by including a saturation effect. The quadratic hypothesis can only serve as a first guess. In addition, we study the initial error growth for the ECMWF forecast system. Fitting the parameters, we conclude that there is an intrinsic limit of predictability after 22 days.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
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In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, John Washbourne, Paul H. J. Kelly, and Gerard J. Gorman
Geosci. Model Dev., 15, 3815–3829, https://doi.org/10.5194/gmd-15-3815-2022, https://doi.org/10.5194/gmd-15-3815-2022, 2022
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Full waveform inversion (FWI) is a partial-differential equation (PDE)-constrained optimization problem that is notorious for its high computational load and memory footprint. In this paper we present a method that combines recomputation with lossy compression to accelerate the computation with minimal loss of precision in the results. We show this using experiments running FWI with a variety of compression settings on a popular academic dataset.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
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This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Romit Maulik, Vishwas Rao, Jiali Wang, Gianmarco Mengaldo, Emil Constantinescu, Bethany Lusch, Prasanna Balaprakash, Ian Foster, and Rao Kotamarthi
Geosci. Model Dev., 15, 3433–3445, https://doi.org/10.5194/gmd-15-3433-2022, https://doi.org/10.5194/gmd-15-3433-2022, 2022
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In numerical weather prediction, data assimilation is frequently utilized to enhance the accuracy of forecasts from equation-based models. In this work we use a machine learning framework that approximates a complex dynamical system given by the geopotential height. Instead of using an equation-based model, we utilize this machine-learned alternative to dramatically accelerate both the forecast and the assimilation of data, thereby reducing need for large computational resources.
Hiromasa Yoshimura
Geosci. Model Dev., 15, 2561–2597, https://doi.org/10.5194/gmd-15-2561-2022, https://doi.org/10.5194/gmd-15-2561-2022, 2022
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This paper proposes a new double Fourier series (DFS) method on a sphere that improves the numerical stability of a model compared with conventional DFS methods. The shallow-water model and the advection model using the new DFS method give stable results without the appearance of high-wavenumber noise near the poles. The model using the new DFS method is faster than the model using spherical harmonics (especially at high resolutions) and gives almost the same results.
Mirko Mälicke
Geosci. Model Dev., 15, 2505–2532, https://doi.org/10.5194/gmd-15-2505-2022, https://doi.org/10.5194/gmd-15-2505-2022, 2022
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I preset SciKit-GStat, a well-documented and tested Python package for variogram estimation. The variogram is the core means of geostatistics, which almost all other methods rely on. Geostatistical interpolation and field generation are widely spread in geoscience, i.e., for data assimilation or modeling.
While SciKit-GStat focuses on effective and intuitive variogram estimation, it can interface with other prominent packages and make its variograms available for a multitude of methods.
Christopher J. L. D'Amboise, Michael Neuhauser, Michaela Teich, Andreas Huber, Andreas Kofler, Frank Perzl, Reinhard Fromm, Karl Kleemayr, and Jan-Thomas Fischer
Geosci. Model Dev., 15, 2423–2439, https://doi.org/10.5194/gmd-15-2423-2022, https://doi.org/10.5194/gmd-15-2423-2022, 2022
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The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.
Evan Baker, Anna B. Harper, Daniel Williamson, and Peter Challenor
Geosci. Model Dev., 15, 1913–1929, https://doi.org/10.5194/gmd-15-1913-2022, https://doi.org/10.5194/gmd-15-1913-2022, 2022
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We have adapted machine learning techniques to build a model of the land surface in Great Britain. The model was trained using data from a very complex land surface model called JULES. Our model is faster at producing simulations and predictions and can investigate many different scenarios, which can be used to improve our understanding of the climate and could also be used to help make local decisions.
Daichun Wang, Wei You, Zengliang Zang, Xiaobin Pan, Yiwen Hu, and Yanfei Liang
Geosci. Model Dev., 15, 1821–1840, https://doi.org/10.5194/gmd-15-1821-2022, https://doi.org/10.5194/gmd-15-1821-2022, 2022
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This paper presents a 3D variational data assimilation system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, which was developed for a size-resolved sectional model in WRF-Chem. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was designed. The results show that Himawari-8 AOT assimilation can significantly improve model aerosol analyses and forecasts.
Kevin Bulthuis and Eric Larour
Geosci. Model Dev., 15, 1195–1217, https://doi.org/10.5194/gmd-15-1195-2022, https://doi.org/10.5194/gmd-15-1195-2022, 2022
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We present and implement a stochastic solver to sample spatially and temporal varying uncertain input parameters in the Ice-sheet and Sea-level System Model, such as ice thickness or surface mass balance. We represent these sources of uncertainty using Gaussian random fields with Matérn covariance function. We generate random samples of this random field using an efficient computational approach based on solving a stochastic partial differential equation.
Urmas Raudsepp and Ilja Maljutenko
Geosci. Model Dev., 15, 535–551, https://doi.org/10.5194/gmd-15-535-2022, https://doi.org/10.5194/gmd-15-535-2022, 2022
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A model's ability to reproduce the state of a simulated object is always a subject of discussion. A new method for the multivariate assessment of numerical model skills uses the K-means algorithm for clustering model errors. All available data that fall into the model domain and simulation period are incorporated into the skill assessment. The clustered errors are used for spatial and temporal analysis of the model accuracy. The method can be applied to different types of geoscientific models.
Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov
Geosci. Model Dev., 14, 7749–7774, https://doi.org/10.5194/gmd-14-7749-2021, https://doi.org/10.5194/gmd-14-7749-2021, 2021
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We propose an implementation of the material point method using graphical processing units (GPUs) to solve elastoplastic problems in three-dimensional configurations, such as the granular collapse or the slumping mechanics, i.e., landslide. The computational power of GPUs promotes fast code executions, compared to a traditional implementation using central processing units (CPUs). This allows us to study complex three-dimensional problems tackling high spatial resolution.
Rafael Lago, Thomas Gastine, Tilman Dannert, Markus Rampp, and Johannes Wicht
Geosci. Model Dev., 14, 7477–7495, https://doi.org/10.5194/gmd-14-7477-2021, https://doi.org/10.5194/gmd-14-7477-2021, 2021
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In this work we discuss a two-dimensional distributed parallelization of MagIC, an open-source code for the numerical solution of the magnetohydrodynamics equations. Such a parallelization involves several challenges concerning the distribution of work and data. We detail our algorithm and compare it with the established, optimized, one-dimensional distribution in the context of the dynamo benchmark and discuss the merits of both implementations.
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021, https://doi.org/10.5194/gmd-14-7411-2021, 2021
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This study aims to replicate computationally expensive high-resolution large-eddy simulations (LESs) with regression models to simulate urban air quality and pollutant dispersion. The model development, including feature selection, model training and cross-validation, and detection of concept drift, has been described in detail. Of the models applied, log-linear regression shows the best performance. A regression model can replace LES unless high accuracy is needed.
Hynek Bednář, Aleš Raidl, and Jiří Mikšovský
Geosci. Model Dev., 14, 7377–7389, https://doi.org/10.5194/gmd-14-7377-2021, https://doi.org/10.5194/gmd-14-7377-2021, 2021
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Forecast errors in numerical weather prediction systems grow in time. To quantify the impacts of this growth, parametric error growth models may be employed. This study recalculates and newly defines parameters for several statistic models approximating error growth in the ECMWF forecasting system. Accurate values of parameters are important because they are used to evaluate improvements of the forecasting systems or to estimate predictability.
Denise Degen, Cameron Spooner, Magdalena Scheck-Wenderoth, and Mauro Cacace
Geosci. Model Dev., 14, 7133–7153, https://doi.org/10.5194/gmd-14-7133-2021, https://doi.org/10.5194/gmd-14-7133-2021, 2021
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In times of worldwide energy transitions, an understanding of the subsurface is increasingly important to provide renewable energy sources such as geothermal energy. To validate our understanding of the subsurface we require data. However, the data are usually not distributed equally and introduce a potential misinterpretation of the subsurface. Therefore, in this study we investigate the influence of measurements on temperature distribution in the European Alps.
Geoffroy Kirstetter, Olivier Delestre, Pierre-Yves Lagrée, Stéphane Popinet, and Christophe Josserand
Geosci. Model Dev., 14, 7117–7132, https://doi.org/10.5194/gmd-14-7117-2021, https://doi.org/10.5194/gmd-14-7117-2021, 2021
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The development of forecasting tools may help to limit the impacts of flash floods. Our purpose here is to demonstrate the possibility of using b-flood, which is a 2D tool based on shallow-water equations and adaptive mesh refinement.
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021, https://doi.org/10.5194/gmd-14-6241-2021, 2021
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One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
Olivier Pannekoucke and Philippe Arbogast
Geosci. Model Dev., 14, 5957–5976, https://doi.org/10.5194/gmd-14-5957-2021, https://doi.org/10.5194/gmd-14-5957-2021, 2021
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This contributes to research on uncertainty prediction, which is important either for determining the weather today or estimating the risk in prediction. The problem is that uncertainty prediction is numerically very expensive. An alternative has been proposed wherein uncertainty is presented in a simplified form with only the dynamics of certain parameters required. This tool allows for the determination of the symbolic equations of these parameter dynamics and their numerical computation.
Annika Günther, Johannes Gütschow, and Mairi Louise Jeffery
Geosci. Model Dev., 14, 5695–5730, https://doi.org/10.5194/gmd-14-5695-2021, https://doi.org/10.5194/gmd-14-5695-2021, 2021
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The mitigation components of the nationally determined contributions (NDCs) under the Paris Agreement are essential in our fight against climate change. Regular updates with increased ambition are requested to limit global warming to 1.5–2 °C. The new and easy-to-update open-source tool NDCmitiQ can be used to quantify the NDCs' mitigation targets and construct resulting emissions pathways. In use cases, we show target uncertainties from missing clarity, data, and methodological challenges.
Futo Tomizawa and Yohei Sawada
Geosci. Model Dev., 14, 5623–5635, https://doi.org/10.5194/gmd-14-5623-2021, https://doi.org/10.5194/gmd-14-5623-2021, 2021
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A new method to predict chaotic systems from observation and process-based models is proposed by combining machine learning with data assimilation. Our method is robust to the sparsity of observation networks and can predict more accurately than a process-based model when it is biased. Our method effectively works when both observations and models are imperfect, which is often the case in geoscience. Therefore, our method is useful to solve a wide variety of prediction problems in this field.
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Short summary
In this study, we performed an assessment of truncation errors and computational efficiency of trajectory calculations using six popular numerical integration schemes of the Runge–Kutta family. More than 5000 transport simulations for different seasons and regions of the free troposphere and stratosphere were conducted, driven by the latest version of ECMWF operational analyses and forecasts. The study provides guidelines to achieve the most accurate and efficient trajectory calculations.
In this study, we performed an assessment of truncation errors and computational efficiency of...
