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1. Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model

Author

Olivier Boucher, Jérôme Servonnat, Anna Lea Albright, Olivier Aumont, Yves Balkanski, Vladislav Bastrikov, Slimane Bekki, Rémy Bonnet, Sandrine Bony, Laurent Bopp, Pascale Braconnot, Patrick Brockmann, Patricia Cadule, Arnaud Caubel, Frederique Cheruy, Francis Codron, Anne Cozic, David Cugnet, Fabio D'Andrea, Paolo Davini, Casimir deLavergne, Sébastien Denvil, Julie Deshayes, Marion Devilliers, Agnes Ducharne, Jean‐Louis Dufresne, Eliott Dupont, Christian Éthé, Laurent Fairhead, Lola Falletti, Simona Flavoni, Marie‐Alice Foujols, Sébastien Gardoll, Guillaume Gastineau, Josefine Ghattas, Jean‐Yves Grandpeix, Bertrand Guenet, Lionel, E. Guez, Eric Guilyardi, Matthieu Guimberteau, Didier Hauglustaine, Frédéric Hourdin, Abderrahmane Idelkadi, Sylvie Joussaume, Masa Kageyama, Myriam Khodri, Gerhard Krinner, Nicolas Lebas, Guillaume Levavasseur, Claire Lévy, Laurent Li, François Lott, Thibaut Lurton, Sebastiaan Luyssaert, Gurvan Madec, Jean‐Baptiste Madeleine, Fabienne Maignan, Marion Marchand, Olivier Marti, Lidia Mellul, Yann Meurdesoif, Juliette Mignot, Ionela Musat, Catherine Ottlé, Philippe Peylin, Yann Planton, Jan Polcher, Catherine Rio, Nicolas Rochetin, Clément Rousset, Pierre Sepulchre, Adriana Sima, Didier Swingedouw, Rémi Thiéblemont, Abdoul Khadre Traore, Martin Vancoppenolle, Jessica Vial, Jérôme Vialard, Nicolas Viovy, and Nicolas Vuichard

Subjects
IPSL‐CM6A‐LR, climate model, climate metrics, CMIP6, climate sensitivity, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract

Abstract This study presents the global climate model IPSL‐CM6A‐LR developed at Institut Pierre‐Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone [ITCZ], frequency of midlatitude wintertime blockings, and El Niño–Southern Oscillation [ENSO] dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850–2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.

Published
2020
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2. En el postprint el titulo es: Climate models underpredict North Atlantic atmospheric circulation changes

Author

Wolfgang A. Müller, Leon Hermanson, Reinel Sospedra-Alfonso, Stephen Yeager, Adam A. Scaife, Holger Pohlmann, Gokhan Danabasoglu, Roberto Bilbao, William J. Merryfield, Masahide Kimoto, Jon Robson, Pablo Ortega, Leonard Borchert, Rosie Eade, Paolo Ruggieri, Klaus Pankatz, Victor Estella-Perez, Ingo Bethke, Dario Nicolì, Yiguo Wang, Simon Wild, Kameswarrao Modali, Takashi Mochizuki, Doug Smith, Alessio Bellucci, Xiaosong Yang, Nick Dunstone, Noel Keenlyside, Francois Counillon, Liping Zhang, Paul-Arthur Monerie, Viatcheslav Kharin, Simona Flavoni, Juliette Mignot, Panos Athanasiadis, Didier Swingedouw, Thomas L. Delworth, Louis-Philippe Caron, Francisco J. Doblas-Reyes, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Centro Euro-Mediterraneo per i Cambiamenti Climatici [Bologna] (CMCC), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Nansen Environmental and Remote Sensing Center [Bergen] (NERSC), National Center for Atmospheric Research [Boulder] (NCAR), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Institució Catalana de Recerca i Estudis Avançats (ICREA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Atmosphere and Ocean Research Institute [Kashiwa-shi] (AORI), The University of Tokyo (UTokyo), Department of Earth and Planetary Sciences [Fukuoka], Kyushu University [Fukuoka], Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, Deutscher Wetterdienst [Offenbach] (DWD), Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), European Project: 776613,Fighting and adapting to climate change,H2020-EU.3.5.1,EUCP(2017), European Project: 727852,Blue-Action(2016), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Kyushu University, Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Barcelona Supercomputing Center, Smith D.M., Scaife A.A., Eade R., Athanasiadis P., Bellucci A., Bethke I., Bilbao R., Borchert L.F., Caron L.-P., Counillon F., Danabasoglu G., Delworth T., Doblas-Reyes F.J., Dunstone N.J., Estella-Perez V., Flavoni S., Hermanson L., Keenlyside N., Kharin V., Kimoto M., Merryfield W.J., Mignot J., Mochizuki T., Modali K., Monerie P.-A., Muller W.A., Nicoli D., Ortega P., Pankatz K., Pohlmann H., Robson J., Ruggieri P., Sospedra-Alfonso R., Swingedouw D., Wang Y., Wild S., Yeager S., Yang X., and Zhang L.

Subjects
010504 meteorology & atmospheric sciences, Atmospheric circulation, Climatologia -- Models matemàtics, SEASONAL PREDICTIONS, ATMOSPHERIC CIRCULATION, DECADAL PREDICTION, OSCILLATION, VARIABILITY, SKILL, CMIP5, NAO, INITIALIZATION, UNCERTAINTY, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Climatology--Computer programs, 010502 geochemistry & geophysics, 01 natural sciences, Climate models, Predictable signal, Simulació per ordinador, Projection of climate change, Precipitation, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Desenvolupament humà i sostenible [Àrees temàtiques de la UPC], Decadal predictions, Multidisciplinary, Mode (statistics), Variance (land use), Computer simulation, Climatic changes, 13. Climate action, North Atlantic oscillation, Climatology, North Atlantic atmospheric circulation, Environmental science, Errors-in-variables models, Climate model
Abstract

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1,2,3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7,8,9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models10, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade. DMS, AAS, NJD, LH and RE were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP project (GA 776613). FJDR, LPC, SW and RB also acknowledge the support from the EUCP project (GA 776613) and from the Ministerio de Econom´ıa y Competitividad (MINECO) as part of the CLINSA project (Grant No. CGL2017-85791-R). SW received funding from the innovation programme under the Marie Sk´lodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433 and PO from the Ramon y Cajal senior tenure programme of MINECO. The EC-Earth simulations were performed on Marenostrum 4 (hosted by the Barcelona Supercomputing Center, Spain) using Auto-Submit through computing hours provided by PRACE.WAM, HP, KMand KP were supported by the German FederalMinistry for Education and Research (BMBF) project MiKlip (grant 01LP1519A). NK, IB, FC and YW were supported by the Norwegian Research Council projects SFE (grant 270733) the Nordic Center of excellent ARCPATH (grant 76654) and the Trond Mohn Foundation, under the project number : BFS2018TMT01 and received grants for computer time from the Norwegian Program for supercomputing (NOTUR2, NN9039K) and storage grants (NORSTORE, NS9039K). JM, LFB and DS are supported by Blue-Action (European Union Horizon 2020 research and innovation program, Grant Number: 727852) and EUCP (European Union Horizon 2020 research and innovation programme under grant agreement no 776613) projects. The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the US National Science Foundation (NSF) under Cooperative Agreement No. 1852977. NCAR contribution was partially supported by the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under Climate Variability and Predictability Program Grant NA13OAR4310138 and by the US NSF Collaborative Research EaSM2 Grant OCE-1243015.

Published
2020

3. NEMO ocean engine

Author

Madec Gurvan, Romain Bourdallé-Badie, Pierre-Antoine Bouttier, Clément Bricaud, Diego Bruciaferri, Daley Calvert, Jérôme Chanut, Emanuela Clementi, Andrew Coward, Damiano Delrosso, Christian Ethé, Simona Flavoni, Tim Graham, James Harle, Doroteaciro Iovino, Dan Lea, Claire Lévy, Tomas Lovato, Nicolas Martin, Sébastien Masson, Silvia Mocavero, Julien Paul, Clément Rousset, Dave Storkey, Andrea Storto, and Martin Vancoppenolle

Subjects
modelling, ocean, Physics::Atmospheric and Oceanic Physics, Physics::Geophysics
Abstract

The ocean engine of NEMO is a primitive equation model adapted to regional and global ocean circulation problems. It is intended to be a flexible tool for studying the ocean and its interactions with the others components of the earth climate system over a wide range of space and time scales.

Published
2017
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4. The Louvain-la-Neuve sea ice model LIM3.5: global and regional capabilities

Author

Martin Vancoppenolle, Jérôme Chanut, Clément Rousset, Frédéric Vivier, Thierry Fichefet, Sébastien Masson, Gurvan Madec, Claire Levy, Rachid Benshila, Simona Flavoni, Antoine Barthélemy, Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Processus de couplage à Petite Echelle, Ecosystèmes et Prédateurs Supérieurs (PEPS), Institut d'Astronomie et de Géophysique Georges Lemaître (UCL-ASTR), Université Catholique de Louvain = Catholic University of Louvain (UCL), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Mercator Océan, Société Civile CNRS Ifremer IRD Météo-France SHOM, Interactions et Processus au sein de la couche de Surface Océanique (IPSO), ANR-09-BLAN-0227,OPTIMISM(2009), European Project: 283367,EC:FP7:SPA,FP7-SPACE-2011-1,MYOCEAN2(2012), and Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)

Subjects
geography, Ice formation, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, 010505 oceanography, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 01 natural sciences, Global simulation, Louvain la neuve, Robustness (computer science), Climatology, Range (statistics), Sea ice, Transient (computer programming), 14. Life underwater, Boundary value problem, Geology, 0105 earth and related environmental sciences
Abstract

We present the new 3.5 version of the Louvain-la-Neuve sea ice model (LIM) integrated in NEMO 3.6. The main novelty is the improvement of model robustness and versatility for a wide range of applications, from global to regional scales. Several modifications to the code were required. First, the time stepping scheme of the model was changed from parallel to sequential (ice dynamics first, then thermodynamics). Such a scheme enables to diagnose the different physical processes responsible for exchanges through the air–ice–ocean interfaces, as well as the online inspection of mass, heat and salt conservation properties of the code. In the course of these developments, several minor conservation leaks were found and fixed, so that LIM3.5 is exactly conservative. Second, lateral boundary conditions for regional ice-covered configurations have been implemented. To illustrate the new capabilities, two simulations are performed. One is a global simulation at a nominal 2° resolution forced by atmospheric climatologies and is found reasonably realistic although no specific tuning was done. The other is a regional simulation at 2 km resolution around the Svalbard Archipelago in the Arctic Ocean, with prescribed conditions at the four boundaries including tides. The simulation is able to resolve small-scale features and transient events such as the opening and closing of coastal polynyas. The ice mass budgets for both simulations are illustrated and mostly differ by the strength of ice formation in open water. LIM3.5 now forms a solid base for future scientific studies and model developments.

Published
2015

5. QPF performance of the updated SIMM forecasting system using reforecasts

Author

Christophe Accadia, S. Mariani, Alexandre Lanciani, M. Casaioli, Simona Flavoni, Instituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), Instituto Superiore per la Protezione e la Ricerca Ambientale, Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636))

Subjects
Atmospheric Science, Meteorology, Advection, Limited area model, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Grid, Forecast verification, Improved performance, SIMM, 13. Climate action, Quantitative precipitation forecast, Environmental science, Turbulent flux, ComputingMilieux_MISCELLANEOUS
Abstract

In late 2009, the meteorological component of the Institute for Environmental Protection and Research (ISPRA)'s Hydro-Meteo-Marine Forecasting System (Sistema Idro-Meteo-Mare – SIMM), namely the hydrostatic Quadrics BOlogna Limited Area Model (QBOLAM), was replaced by an up-to-date version of the same model. This new version, which is simply referred to as BOLAM, deploys advanced parameterization schemes for cumulus convection, radiation, soil, and exchange of turbulent fluxes and uses the explicit advection of five hydrometeors. As a part of the SIMM verification programme, it was judged objectively how these changes affected the quality of quantitative precipitation forecasts (QPFs). This was done by intercomparing the current operational BOLAM against QBOLAM. Observational analyses, from April to September 2001, deployed earlier to evaluate the QBOLAM performance, were considered for this intercomparison. An ad hoc reforecast campaign was performed to generate the database of the corresponding retrospective QPFs for BOLAM. A multimethod verification approach was used to assess the spatial scales resolved by the intercompared model versions and the skill at forecasting both frequent, high-base rate and rare, low-base rate precipitation events. The effect on performance measures of differences in bias between the intercompared versions was also evaluated. The results indicate an improved performance of BOLAM compared with the older version not only when considering the native 0.1° model grid, where the intercomparison may be affected by differences in the resolved scales, but also when using a coarser 0.5° grid, where the two remapped QPF series show similar spatial scales. Fewer false alarms are produced by BOLAM during the verification time period.

Published
2015

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