Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-3135-2014
https://doi.org/10.5194/gmd-7-3135-2014
Model description paper
 | 
19 Dec 2014
Model description paper |  | 19 Dec 2014

MeteoIO 2.4.2: a preprocessing library for meteorological data

M. Bavay and T. Egger

Related authors

A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022,https://doi.org/10.5194/hess-26-3447-2022, 2022
Short summary
Inishell 2.0: semantically driven automatic GUI generation for scientific models
Mathias Bavay, Michael Reisecker, Thomas Egger, and Daniela Korhammer
Geosci. Model Dev., 15, 365–378, https://doi.org/10.5194/gmd-15-365-2022,https://doi.org/10.5194/gmd-15-365-2022, 2022
Short summary
Cold-to-warm flow regime transition in snow avalanches
Anselm Köhler, Jan-Thomas Fischer, Riccardo Scandroglio, Mathias Bavay, Jim McElwaine, and Betty Sovilla
The Cryosphere, 12, 3759–3774, https://doi.org/10.5194/tc-12-3759-2018,https://doi.org/10.5194/tc-12-3759-2018, 2018
Short summary
Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment
Nander Wever, Francesco Comola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 21, 4053–4071, https://doi.org/10.5194/hess-21-4053-2017,https://doi.org/10.5194/hess-21-4053-2017, 2017
Short summary
Distributed snow and rock temperature modelling in steep rock walls using Alpine3D
Anna Haberkorn, Nander Wever, Martin Hoelzle, Marcia Phillips, Robert Kenner, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 585–607, https://doi.org/10.5194/tc-11-585-2017,https://doi.org/10.5194/tc-11-585-2017, 2017
Short summary

Related subject area

Cryosphere
Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev., 16, 1395–1425, https://doi.org/10.5194/gmd-16-1395-2023,https://doi.org/10.5194/gmd-16-1395-2023, 2023
Short summary
Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023,https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary
SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0
Anne M. Felden, Daniel F. Martin, and Esmond G. Ng
Geosci. Model Dev., 16, 407–425, https://doi.org/10.5194/gmd-16-407-2023,https://doi.org/10.5194/gmd-16-407-2023, 2023
Short summary
Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023,https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
The Multiple Snow Data Assimilation System (MuSA v1.0)
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022,https://doi.org/10.5194/gmd-15-9127-2022, 2022
Short summary

Cited articles

Ballou, D. P. and Pazer, H. L.: Modeling data and process quality in multi-input, multi-output information systems, Manage. Sci., 31, 150–162, 1985.
Barrenetxea, G., Ingelrest, F., Schaefer, G., Vetterli, M., Couach, O., and Parlange, M.: Sensorscope: Out-of-the-box environmental monitoring, In Information Processing in Sensor Networks, 2008, IPSN'08, International Conference, 332–343, IEEE, 2008.
Beck, K. and Andres, C.: Extreme Programming Explained: Embrace Change, Addison-Wesley Professional, 2nd Edn., 2004.
Brutsaert, W.: On a derivable formula for long-wave radiation from clear skies, Water Resour. Res., 11, 742–744, 1975.
Butterworth, S.: On the theory of filters amplifiers, Experimental Wireless & the Wireless Engineer, 7, 536–541, 1930.
Download
Short summary
The open-source MeteoIO library has been designed to perform the data preprocessing required by numerical models using large meteorological data sets, with a strong emphasis on simplicity and modularity. It retrieves, filters and resamples the data if necessary as well as provides spatial interpolations and parameterizations. It presents a uniform interface to meteorological data in the models, hides the complexity of the preprocessing and guarantees a robust behaviour in case of data errors.