Added value of assimilating springtime Arctic sea ice concentration in summer-fall climate predictions

Prediction skill of continental climate in the Northern Hemisphere (NH) midlatitudes is generally limited throughout the year in dynamical seasonal forecast systems. Such limitations narrow the range of possible applications by different stakeholders. Improving the predictive capacity in these regions has been a challenging task. Sea ice is a central component of the Arctic climate system and a local source of climate predictability, yet its state is often not fully constrained in dynamical forecast systems. Using the EC-Earth3 climate model, we study the added value of assimilating observed Arctic sea ice concentration on the NH extratropical climate in retrospective forecasts of summer and fall, initialized every spring over 1992–2019. Predictions in the North Atlantic and Eurasia benefit from better initialization of sea ice in the Atlantic sector of the Arctic in a two-step mechanism. Initially, sea ice influences the central North Atlantic Ocean through an atmospheric bridge that develops in the first forecast weeks, subsequently leading to preserved skill in the sea surface temperatures (SSTs) throughout summer and early fall. Secondly, these long-lasting SST improvements provide better surface boundary conditions for the atmosphere and lead to more skillful predictions of circulation and surface climate in the Euro-Atlantic and Asian regions. In addition, our findings suggest that fully coupled ocean-atmosphere-sea ice models are likely necessary to study linkages between Arctic sea ice and midlatitudes, by better representing the interactions and feedbacks between the different components of the climate system.The data that support the findings of this study are available upon reasonable request from the authors. This work was funded by the European Union projects APPLICATE (Grant 727862), INTAROS (Grant 727890), and ESA/CMUG-CCI3. J C A N received financial support from the Spanish Ministerio de Ciencia, Innovación y Universidades through a Juan de la Cierva personal grant (FJCI-2017-34027). J G-S was supported by the Spanish 'Ramón y Cajal' programme (RYC-2016-21181). All the data were downloaded from their original source, converted to NetCDF in a format designed for efficient analysis and quality checked at several levels. Etienne Tourigny, Pierre-Antoine Bretonnière, Margarida Samsó Cabré, Núria Pérez Zanón and An Chi Ho are acknowledged for their help with technical aspects. We thank the two anonymous reviewers for their valuable comments on the manuscript.Peer ReviewedPostprint (published version

Trends, variability and predictive skill of the ocean heat content in North Atlantic: an analysis with the EC-Earth3 model

This study investigates linear trends, variability and predictive skill of the upper ocean heat content (OHC) in the North Atlantic basin. This is a region where strong decadal variability superimposes the externally forced trends, introducing important differences in the local warming rates and leading in the case of the Central Subpolar North Atlantic to an overall long-term cooling. Our analysis aims to better understand these regional differences, by investigating how internal and forced variability contribute to local trends, exploring also their role on the local prediction skill. The analysis combines the study of three ocean reanalyses to document the uncertainties related to observations with two sets of CMIP6 experiments performed with the global coupled climate model EC-Earth3: a historical ensemble to characterise the forced signals, and a retrospective decadal prediction system to additionally characterise the contributions from internal climate variability. Our results show that internal variability is essential to understand the spatial pattern of North Atlantic OHC trends, contributing decisively to the local trends and providing high levels of predictive skill in the Eastern Subpolar North Atlantic and the Irminger and Iceland Seas, and to a lesser extent in the Labrador Sea. Skill and trends in other areas like the Subtropical North Atlantic, or the Gulf Stream Extension are mostly externally forced. Large observational and modeling uncertainties affect the trends and interannual variability in the Central Subpolar North Atlantic, the only region exhibiting a cooling during the study period, uncertainties that might explain the very poor local predictive skill.Teresa Carmo-Costa, Ana Teles-Machado and Emanuel Dutra would like to acknowledge the financial support from FCT through projects FCT-UIDB/50019/2020 and PD/BD/142785/2018. Furthermore, Ana Teles-Machado acknowledges SARDINHA2020 (MAR2020) and ROADMAP (JPIOCEANS/ 0001/2019). Roberto Bilbao was supported by the European Commission H2020 projects EUCP (Grant no. 776613). Pablo Ortega was supported by the Spanish Ministry of Economy, Industry and Competitiveness through the Ramon y Cajal grant RYC-2017-22772.Peer ReviewedPostprint (published version

Summer predictions of Arctic sea ice edge in multi-model seasonal re-forecasts

In this study, the forecast quality of 1993–2014 summer seasonal predictions of five global coupled models, of which three are operational seasonal forecasting systems contributing to the Copernicus Climate Change Service (C3S), is assessed for Arctic sea ice. Beyond the Pan-Arctic sea ice concentration and extent deterministic re-forecast assessments, we use sea ice edge error metrics such as the Integrated Ice Edge Error (IIEE) and Spatial Probability Score (SPS) to evaluate the advantages of a multi-model approach. Skill in forecasting the September sea ice minimum from late April to early May start dates is very limited, and only one model shows significant correlation skill over the period when removing the linear trend in total sea ice extent. After bias and trend-adjusting the sea ice concentration data, we find quite similar results between the different systems in terms of ice edge forecast errors. The highest values of September ice edge error in the 1993–2014 period are found for the sea ice minima years (2007 and 2012), mainly due to a clear overestimation of the total extent. Further analyses of deterministic and probabilistic skill over the Barents–Kara, Laptev–East Siberian and Beaufort–Chukchi regions provide insight on differences in model performance. For all skill metrics considered, the multi-model ensemble, whether grouping all five systems or only the three operational C3S systems, performs among the best models for each forecast time, therefore confirming the interest of multi-system initiatives building on model diversity for providing the best forecasts.This study was partly funded by the H2020-APPLICATE project, EU grant number 727862. JCAN acknowledges the Spanish Ministry of Science, Innovation and Universities for the personal grant Juan de la Cierva FJCI-2017-34027, PRACE for awarding access to MareNostrum at Barcelona Supercomputing Center (BSC), and ESA/CMUG-CCI3 for financial support. PO work was funded by the Ramon y Cajal grant RYC-2017-22772.Peer ReviewedPostprint (author's final draft

How Credibly Do CMIP6 Simulations Capture Historical Mean and Extreme Precipitation Changes?

Abstract Future precipitation changes are typically estimated from climate model simulations, while the credibility of such projections needs to be assessed by their ability to capture observed precipitation changes. Here we evaluate how skillfully historical climate simulations contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6) capture observed changes in mean and extreme precipitation. We find that CMIP6 historical simulations skillfully represent observed precipitation changes over large parts of Europe, Asia, northeastern North America, parts of South America and western Australia, whereas a lack of skill is apparent in western North America and parts of Africa. In particular in regions with moderate skill the availability of very large ensembles can be beneficial to improve the simulation accuracy. CMIP6 simulations are regionally skillful where they capture observed (positive or negative) trends, whereas a lack of skill is found in regions characterized by negative observed precipitation trends where CMIP6 simulates increases.We are grateful for support by the Departament de Recerca i Universitats de la Generalitat de Catalunya for the Climate Variability and Change (CVC) Research Group (Reference: 2021 SGR 00786), and research funding by the Horizon 2020 LANDMARC project (grant agreement no. 869367), the Horizon Europe ASPECT project (Grant 101081460), and the AXA Research Fund. CDT acknowledges financial support from the Spanish Ministry for Science and Innovation (FPI PRE2019–509 08864 financed by MCIN/AEI/http://doi.org/10.13039/501100011033). PDL received funding from the Horizon Europe Research and Innovation Programme, Grant 101059659. We thank the climate modeling groups contributing to CMIP6 for producing and making available their model output. We are grateful to Margarida Samsó and Pierre–Antoine Bretonnière for downloading, formatting and managing the large data sets of climate simulations and observations used in this study.Peer ReviewedPostprint (published version

PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

We introduce PARASO, a novel five-component fully coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are the fast Elementary Thermomechanical Ice Sheet model (f.ETISh) v1.7 (ice sheet), the Nucleus for European Modelling of the Ocean (NEMO) v3.6 (ocean), the Louvain-la-Neuve sea-ice model (LIM) v3.6 (sea ice), the COnsortium for Small-scale MOdeling (COSMO) model v5.0 (atmosphere) and its CLimate Mode (CLM) v4.5 (land), which are here run at a horizontal resolution close to 1/4°. One key feature of this tool resides in a novel two-way coupling interface for representing ocean–ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM–f.ETISh surface mass exchange. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO–f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice-covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled 2-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.This research has been supported by the Fonds De La Recherche Scientifique – FNRS (grant no. O0100718F).Peer ReviewedArticle signat per 23 autors/es: Charles Pelletier (1), Thierry Fichefet (1), Hugues Goosse (1), Konstanze Haubner (2), Samuel Helsen (3), Pierre-Vincent Huot (1), Christoph Kittel (4), François Klein (1), Sébastien Le clec'h (5), Nicole P. M. van Lipzig (3), Sylvain Marchi (3), François Massonnet (1), Pierre Mathiot (6,7), Ehsan Moravveji (3,8), Eduardo Moreno-Chamarro (9), Pablo Ortega (9), Frank Pattyn (2), Niels Souverijns (3,10), Guillian Van Achter (1), Sam Vanden Broucke (3), Alexander Vanhulle (5), Deborah Verfaillie (1), and Lars Zipf (2) // (1) Earth and Life Institute (ELI), UCLouvain, Louvain-la-Neuve, Belgium / (2) Laboratoire de Glaciologie, Université Libre de Bruxelles, Brussels, Belgium / (3) Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium / (4) Laboratory of Climatology, Department of Geography, SPHERES, University of Liège, Liège, Belgium / (5) Earth System Science and Departement Geografie, Vrije Universiteit Brussel, Brussels, Belgium, (6) Met Office, Exeter, United Kingdom / (7) Université Grenoble Alpes/CNRS/IRD/G-INP, IGE, Grenoble, France / (8) ICTS, KU Leuven, Leuven, Belgium / (9) Barcelona Supercomputing Center (BSC), Barcelona, Spain / (10) Environmental Modelling Unit, Flemish Institute for Technological Research (VITO), Mol, BelgiumPostprint (published version

Effect of Vitamin A, Zinc and multivitamin supplementation on the nutritional status and retinol serum values in school-age children

Micronutrient deficiency or “Hidden Hunger” represents the most widespread form of malnutrition in the world. The aim of this study was to evaluate the effect of supplementation with Vitamin A as a single dose, Zinc and Vitamin A + Zinc on nutritional status, and on serum retinol and zinc levels in schoolchildren. A database total of 80 schoolchildren (girls = 47 and boys = 33) were evaluated about the effect of supplementation with vitamin A (VA), Zinc (Zn) and VA + Zn on nutritional anthropometric status, and on serum retinol and zinc values. Serum retinol concentrations were determined by HPLC, according to Bieri method, considering 30 μg/dL normal VA; serum zinc was analyzed by Flame Atomic Absorption Spectrometry, considering ≥0.72 μg/dL normal zinc and <0.72 μg/dL zinc deficiency (DZn). Data were analyzed using SAS program Statgraphics XVI, and a significant p < 0.05 was considered. The deficiency of the nutritional consumption of zinc was high in the students, contrary to the consumption of vitamin A which was normal. The observed prevalence of DVA was 6.25%, RDVA 23.75% and DZn 97.50%. The isolated or combined supplementation of vitamin A and Zinc contributes to the maintenance of the anthropometric state; however, they are ineffective in the cases of low consumption of these nutrients to reach optimum circulating values

Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE

The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.The results discussed in this article were supported by the project APPLICATE (727862), funded by the European Union's Horizon 2020 research and innovation programme. PO was additionally supported by the Spanish fellowship RYC-2017-22772.Peer ReviewedArticle signat per 29 autors/es: Pablo Ortega (1), Edward W. Blockley (2), Morten Køltzow (3), François Massonnet (4), Irina Sandu (5), Gunilla Svensson (6), Juan C. Acosta Navarro (1), Gabriele Arduini (5), Lauriane Batté (7), Eric Bazile (7), Matthieu Chevallier (8), Rubén Cruz-García (1), Jonathan J. Day (5), Thierry Fichefet (4), Daniela Flocco (9), Mukesh Gupta (4), Kerstin Hartung (6,10), Ed Hawkins (9), Claudia Hinrichs (11), Linus Magnusson (5), Eduardo Moreno-Chamarro (1), Sergio Pérez-Montero (1), Leandro Ponsoni (4), Tido Semmler (11), Doug Smith (2), Jean Sterlin (4), Michael Tjernström (6), Ilona Välisuo (7,12), and Thomas Jung (11,13) // (1) Barcelona Supercomputing Center, Barcelona, Spain | (2) Met Office, Exeter, UK | (3) Norwegian Meteorological Institute, Oslo, Norway | (4) Université catholique de Louvain, Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Louvain-la-Neuve, Belgium | (5) European Centre for Medium-Range Weather Forecasts, Reading, UK | (6) Department of Meteorology, Stockholm University, Stockholm, Sweden | (7) CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France | (8) Météo-France, Toulouse, France | (9) National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK. | (10) Now at: Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany | (11) Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany | (12) Now at: Meteorology Unit, Finnish Meteorological Institute, Helsinki, Finland | (13) Department of Physics and Electrical Engineering, University of Bremen, Bremen, GermanyPostprint (published version

Atlantic circulation change still uncertain

Deep oceanic overturning circulation in the Atlantic (Atlantic Meridional Overturning Circulation, AMOC) is projected to decrease in the future in response to anthropogenic warming. Caesar et al. 1 argue that an AMOC slowdown started in the 19 th century and intensified during the mid-20th century. Although the argument and selected evidence proposed have some merits, we find that their conclusions might be different if a more complete array of data available in the North Atlantic region had been considered. We argue that the strength of AMOC over recent centuries is still poorly constrained and the expected slowdown may not have started yet.K.H.K. acknowledges funding from NOAA grant NA20OAR4310481. D.E.A. and B.L.O.-B. acknowledge support from the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977. N.M.W. acknowledges support from a NOAA Climate and Global Change Postdoctoral Fellowship. M.F.J. acknowledges support from NSF award OCE-1846821 and C.M.L. acknowledges support from NSF award OCE-1805029. This is UMCES contribution 6062.Peer ReviewedArticle signat per 17 autors/es: University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, Solomons, MD, USA: K. Halimeda Kilbourne / Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, USA: Alan D. Wanamaker / Geography Department, Durham University, Durham, UK: Paola Moffa-Sanchez / Centre for Geography and Environmental Sciences, University of Exeter, Penryn, UK: David J. Reynolds, Paul G. Butler & James Scourse / Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA: Daniel E. Amrhein & Bette L. Otto-Bliesner / Woods Hole Oceanographic Institution, Falmouth, MA, USA: Geoffrey Gebbie & Nina M. Whitney / Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA: Marlos Goes / Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, Miami, FL, USA: Marlos Goes / Department of the Geophysical Sciences, The University of Chicago, Chicago, IL, USA: Malte F. Jansen / Oceanography Department, Atmospheric and Environmental Research, Inc., Texas, TX, USA: Christopher M. Little / US Geological Survey, St Petersburg Coastal and Marine Science Center, St Petersburg, FL, USA: Madelyn Mette / Barcelona Supercomputing Center, Barcelona, Spain: Eduardo Moreno-Chamarro & Pablo Ortega / Graduate School of Oceanography, University of Rhode Island, Kingston, RI, USA: Thomas Rossby / University Corporation of Atmospheric Research, Boulder, CO, USA: Nina M. WhitneyPostprint (author's final draft)Matters Arising published on 17 February 2022. The Original Article was published on 25 February 2021

The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.The development of EC-Earth3 was supported by the European Union's Horizon 2020 research and innovation program under project IS-ENES3, the third phase of the distributed e-infrastructure of the European Network for Earth System Modelling (ENES) (grant agreement no. 824084, PRIMAVERA grant no. 641727, and CRESCENDO grant no. 641816). Etienne Tourigny and Raffaele Bernardello have received funding from the European Union’s Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement nos. 748750 (SPFireSD project) and 708063 (NeTNPPAO project). Ivana Cvijanovic was supported by Generalitat de Catalunya (Secretaria d'Universitats i Recerca del Departament d’Empresa i Coneixement) through the Beatriu de Pinós program. Yohan Ruprich-Robert was funded by the European Union's Horizon 2020 research and innovation program in the framework of Marie Skłodowska-Curie grant INADEC (grant agreement 800154). Paul A. Miller, Lars Nieradzik, David Wårlind, Roland Schrödner, and Benjamin Smith acknowledge financial support from the strategic research area “Modeling the Regional and Global Earth System” (MERGE) and the Lund University Centre for Studies of Carbon Cycle and Climate Interactions (LUCCI). Paul A. Miller, David Wårlind, and Benjamin Smith acknowledge financial support from the Swedish national strategic e-science research program eSSENCE. Paul A. Miller further acknowledges financial support from the Swedish Research Council (Vetenskapsrådet) under project no. 621-2013-5487. Shuting Yang acknowledges financial support from a Synergy Grant from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC (grant agreement 610055) as part of the ice2ice project and the NordForsk-funded Nordic Centre of Excellence project (award 76654) ARCPATH. Marianne Sloth Madsen acknowledges financial support from the Danish National Center for Climate Research (NCKF). Andrea Alessandri and Peter Anthoni acknowledge funding from the Helmholtz Association in its ATMO program. Thomas Arsouze, Arthur Ramos, and Valentina Sicardi received funding from the Ministerio de Ciencia, Innovación y Universidades as part of the DeCUSO project (CGL2017-84493-R).​​​​​​​Peer Reviewed"Article signat per 61 autors/es: Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho11, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang"Postprint (author's final draft

Seguimiento de las guías españolas para el manejo del asma por el médico de atención primaria: un estudio observacional ambispectivo

Objetivo Evaluar el grado de seguimiento de las recomendaciones de las versiones de la Guía española para el manejo del asma (GEMA 2009 y 2015) y su repercusión en el control de la enfermedad. Material y métodos Estudio observacional y ambispectivo realizado entre septiembre del 2015 y abril del 2016, en el que participaron 314 médicos de atención primaria y 2.864 pacientes. Resultados Utilizando datos retrospectivos, 81 de los 314 médicos (25, 8% [IC del 95%, 21, 3 a 30, 9]) comunicaron seguir las recomendaciones de la GEMA 2009. Al inicio del estudio, 88 de los 314 médicos (28, 0% [IC del 95%, 23, 4 a 33, 2]) seguían las recomendaciones de la GEMA 2015. El tener un asma mal controlada (OR 0, 19, IC del 95%, 0, 13 a 0, 28) y presentar un asma persistente grave al inicio del estudio (OR 0, 20, IC del 95%, 0, 12 a 0, 34) se asociaron negativamente con tener un asma bien controlada al final del seguimiento. Por el contrario, el seguimiento de las recomendaciones de la GEMA 2015 se asoció de manera positiva con una mayor posibilidad de que el paciente tuviera un asma bien controlada al final del periodo de seguimiento (OR 1, 70, IC del 95%, 1, 40 a 2, 06). Conclusiones El escaso seguimiento de las guías clínicas para el manejo del asma constituye un problema común entre los médicos de atención primaria. Un seguimiento de estas guías se asocia con un control mejor del asma. Existe la necesidad de actuaciones que puedan mejorar el seguimiento por parte de los médicos de atención primaria de las guías para el manejo del asma. Objective: To assess the degree of compliance with the recommendations of the 2009 and 2015 versions of the Spanish guidelines for managing asthma (Guía Española para el Manejo del Asma [GEMA]) and the effect of this compliance on controlling the disease. Material and methods: We conducted an observational ambispective study between September 2015 and April 2016 in which 314 primary care physicians and 2864 patients participated. Results: Using retrospective data, we found that 81 of the 314 physicians (25.8%; 95% CI 21.3–30.9) stated that they complied with the GEMA2009 recommendations. At the start of the study, 88 of the 314 physicians (28.0%; 95% CI 23.4–33.2) complied with the GEMA2015 recommendations. Poorly controlled asthma (OR, 0.19; 95% CI 0.13–0.28) and persistent severe asthma at the start of the study (OR, 0.20; 95% CI 0.12–0.34) were negatively associated with having well-controlled asthma by the end of the follow-up. In contrast, compliance with the GEMA2015 recommendations was positively associated with a greater likelihood that the patient would have well-controlled asthma by the end of the follow-up (OR, 1.70; 95% CI 1.40–2.06). Conclusions: Low compliance with the clinical guidelines for managing asthma is a common problem among primary care physicians. Compliance with these guidelines is associated with better asthma control. Actions need to be taken to improve primary care physician compliance with the asthma management guidelines