Suchergebnisse

This study assesses the impact of low-frequency climate modes on Rossby Wave Packets (RWPs) during southern hemisphere summer. In particular, we focus on long-lived RWPs (lifespan above 8 days) and determine how El Niño-Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) influence their statistics, that is, their duration, frequency of occurrence, and activity areas. We used daily mean meridional winds at 300 hPa from December to March between 1979 and 2020 from the ERA5 and NCEP-DOE 2 reanalyses. We found that long-lived wave packets, which are a small percentage of the total number of wave packets, show large interannual variability; there are years in which these types of waves do not occur and years that present up to 9 wave packets. This suggests that large-scale circulation conditions set up by low-frequency climate modes can modulate their occurrence. Classifying years according to SAM phases reveals that the occurrence of long-lived RWPs is highest (lowest) during intense negative (positive) SAM events. ENSO influence, on the other hand, was found to be weak and not robust. Analysis of large scale circulation conditions shows that during negative SAM phases the jet shifts northward, strengthens in the Indian sector, and extends further into the Pacific basin, so that it acts as a better waveguide favoring the propagation of long-lived RWPs. Conversely, during positive phases of SAM, the jet shifts southward and an anticyclonic center develops to the southwest of Australia blocking the jet and the progression of the wave packets. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844 (ITN CAFÉ). C.M acknowledges partial support from Span-ish Ministerio de Ciencia, Innovación y Universidades (PGC2018-099442-B-I00) and from ICREA ACADEMIA program of Generalitat de Catalunya. ; Postprint (published version)

Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models. ; Lidar data analysis were supported by the ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) Research Infrastructure Project funded by the European Union's Horizon 2020 research and innovation programme under grant agreement n. 654169; by the Spanish Ministry of Economy and Competitivity (project TEC2015-63832-P) and of Science and Innovation (project UNPC10-4E-442) and EFRD (European Fund for Regional Development); by the Department of Economy and Knowledge of the Catalan autonomous government (grant 2014 SGR 583). This work is contributing to the ICTA 'Unit of Excellence' (Spanish Ministry of Economy and Competitivity, project MDM2015-0552). ; Postprint (published version)

Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models. ; Lidar data analysis were supported by the ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) Research Infrastructure Project funded by the European Union's Horizon 2020 research and innovation programme under grant agreement n. 654169; by the Spanish Ministry of Economy and Competitivity (project TEC2015-63832-P) and of Science and Innovation (project UNPC10-4E-442) and EFRD (European Fund for Regional Development); by the Department of Economy and Knowledge of the Catalan autonomous government (grant 2014 SGR 583). This work is contributing to the ICTA 'Unit of Excellence' (Spanish Ministry of Economy and Competitivity, project MDM2015-0552). ; Postprint (published version)

A set of ensemble integrations from the Coupled Model Intercomparison Project phase 5, with historical forcing plus RCP4.5 scenario, are used to explore if state-of-the-art climate models are able to simulate previously reported linkages between sea-ice concentration (SIC) anomalies over the eastern Arctic, namely in the Greenland–Barents–Kara Seas, and lagged atmospheric circulation that projects on the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO). The study is focused on variability around the long-term trends, so that all anomalies are detrended prior to analysis; the period of study is 1979–2013. The model linkages are detected by applying maximum covariance analysis. As also found in observational data, all the models considered here show a statistically significant link with sea-ice reduction over the eastern Arctic followed by a negative NAO/AO-like pattern. If the simulated relationship is found at a lag of one month, the results suggest that a stratospheric pathway could be at play as the driving mechanism; in observations this is preferentially shown for SIC in November. The interference of a wave-like anomaly over Eurasia, accompanying SIC changes, with the climatological wave pattern appears to be key in setting the mediating role of the stratosphere. On the other hand, if the simulated relationship is found at a lag of two months, the results suggest that tropospheric dynamics are dominant, presumably due to transient eddy feedback; in observations this is preferentially shown for SIC in December. The results shown here and previous evidence from atmosphere-only experiments emphasize that there could be a detectable influence of eastern Arctic SIC variability on mid-latitude atmospheric circulation anomalies. Even if the mechanisms are robust among the models, the timing of the simulated linkages strongly depends on the model and does not generally mimic the observational ones. This implies that the atmospheric sensitivity to sea-ice changes largely depends on the mean-flow and parameterizations, which could lead to misleading conclusions elsewhere if a multi-model ensemble-mean approach is adopted. It might also represent an important source of uncertainty in climate prediction and projection. Modelling efforts are hence further required to improve representation of the background atmospheric circulation and reduce biases, in order to attain more accurate covariability. ; The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement No. 308299 (NACLIM—www.naclim.eu). JG-S was partially supported by the H2020-funded MSCA-IF-EF DPETNA project (GA No. 655339). This work was also supported by the BMBF project CLIMPRE Inter-Dec (FKZ:01LP1609A; DM) and the RCN project KLIMAFORSK InterDec (260393; YG) within the framework of JPI CLIM Belmont-Forum InterDec consortial project. JG-S and MPK thank the 6th Severo Ochoa mobility programme for funding the visit of the latter to BSC-CNS in October 2015. The authors thank Ileana Bladé (UB, Spain) and Lantao Sun (CIRES-NOAA/ESRL, USA) for useful discussions, and Neven S. Fuckar (BSC-CNS) for his help during the review process. Technical support at BSC-CNS (Computational Earth Sciences group) is sincerely acknowledged. The authors are also grateful to the anonymous reviewers for their comments, which helped to improve the clarity of the manuscript. ; Peer Reviewed ; Postprint (author's final draft)

A set of ensemble integrations from the Coupled Model Intercomparison Project phase 5, with historical forcing plus RCP4.5 scenario, are used to explore if state-of-the-art climate models are able to simulate previously reported linkages between sea-ice concentration (SIC) anomalies over the eastern Arctic, namely in the Greenland–Barents–Kara Seas, and lagged atmospheric circulation that projects on the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO). The study is focused on variability around the long-term trends, so that all anomalies are detrended prior to analysis; the period of study is 1979–2013. The model linkages are detected by applying maximum covariance analysis. As also found in observational data, all the models considered here show a statistically significant link with sea-ice reduction over the eastern Arctic followed by a negative NAO/AO-like pattern. If the simulated relationship is found at a lag of one month, the results suggest that a stratospheric pathway could be at play as the driving mechanism; in observations this is preferentially shown for SIC in November. The interference of a wave-like anomaly over Eurasia, accompanying SIC changes, with the climatological wave pattern appears to be key in setting the mediating role of the stratosphere. On the other hand, if the simulated relationship is found at a lag of two months, the results suggest that tropospheric dynamics are dominant, presumably due to transient eddy feedback; in observations this is preferentially shown for SIC in December. The results shown here and previous evidence from atmosphere-only experiments emphasize that there could be a detectable influence of eastern Arctic SIC variability on mid-latitude atmospheric circulation anomalies. Even if the mechanisms are robust among the models, the timing of the simulated linkages strongly depends on the model and does not generally mimic the observational ones. This implies that the atmospheric sensitivity to sea-ice changes largely depends on the mean-flow and parameterizations, which could lead to misleading conclusions elsewhere if a multi-model ensemble-mean approach is adopted. It might also represent an important source of uncertainty in climate prediction and projection. Modelling efforts are hence further required to improve representation of the background atmospheric circulation and reduce biases, in order to attain more accurate covariability. ; The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement No. 308299 (NACLIM—www.naclim.eu). JG-S was partially supported by the H2020-funded MSCA-IF-EF DPETNA project (GA No. 655339). This work was also supported by the BMBF project CLIMPRE Inter-Dec (FKZ:01LP1609A; DM) and the RCN project KLIMAFORSK InterDec (260393; YG) within the framework of JPI CLIM Belmont-Forum InterDec consortial project. JG-S and MPK thank the 6th Severo Ochoa mobility programme for funding the visit of the latter to BSC-CNS in October 2015. The authors thank Ileana Bladé (UB, Spain) and Lantao Sun (CIRES-NOAA/ESRL, USA) for useful discussions, and Neven S. Fuckar (BSC-CNS) for his help during the review process. Technical support at BSC-CNS (Computational Earth Sciences group) is sincerely acknowledged. The authors are also grateful to the anonymous reviewers for their comments, which helped to improve the clarity of the manuscript. ; Peer Reviewed ; Postprint (author's final draft)

Northern Chile is one of the most arid regions in the world, with precipitation mainly occurring during austral summer, between December and April. The aim of this study is to classify the main weather regimes derived from sea level pressure, surface wind speed, 500 or 250 hPa geopotential heights, in order to measure their influence on precipitation anomalies and determine if they can be considered sources of predictability of rainfall in this region. Four weather regimes were found to optimally describe atmospheric circulation in the study area during 1966-2015 and for each of the four levels described above. Using daily precipitation data from a network of 161 meteorological stations across the region, the rainfall anomalies associated with each weather regime were quantified. They are coherent with the direction of flow derived from pressure and geopotential anomalies, bringing humid air masses from the Amazon Basin or the Pacific. The transitions between the different regimes are also coherent, representing transitions to and from similar regimes. A few negative and significant trends in the persistence of different regimes were detected, most likely linked to the absence of anthropogenic warming in the Antarctic as opposed to the Arctic. Finally, two of the regimes derived from surface wind speed exhibit a negative and significant trend in its frequency of occurrence, determining a precipitation decrease in the south of the study area (28–30°S), which can be compared with the Megadrought experienced in central Chile. ; The authors want to thank the support of the FONDECYT Project 11160059, the Climatology Group (2017 SGR 1362, Catalan Government), the Spanish Ministry of Economy and Competitiveness (MINECO) as part of the Juan de la Cierva - Incorporación grant (BOE-A-2010-3694), the New European Wind Atlas (NEWA) project (PCIN-2016-029), the Subseasonal to Seasonal for Energy (S2S4E) project (H2020-SC5-2016-2017), and the CLICES Project (CGL2017-83866-C3-2-R). The authors also acknowledge the s2d verification R-language-based software package developers, as this package was used for the data analysis and the visualization of the results presented in this work. ; Peer Reviewed ; Postprint (author's final draft)

We assessed the impact of the microphysical parameterization of natural and anthropogenic aerosols on simulated short-wave radiative effects due to Aerosol-Radiation Interaction (ARI). Layer radiative properties (optical depth, single scattering albedo and asymmetry factor) of dry mineral dust, organic carbon and a black carbon-sulfate mixture have been calculated with a T-matrix code in the short-wave spectral region, after perturbing relevant particle microphysical properties (size distribution, refractive index, mixing state). For each aerosol species, an idealized atmospheric layer and three events of increasing intensity have been set. Then, short-wave direct radiative effects (clear-sky) have been simulated at the top-of-atmosphere (TOA) and at surface (SFC) using the radiative transfer model RRTMG_SW (widely used in atmospheric models), separately for each aerosol species. We observed considerably variable impacts of the particle microphysical perturbations on the layer radiative properties for mineral dust and organic carbon, mainly due to the different sizes of the two species. For the black carbon-sulfate mixture, the single scattering albedo has been found to be much lower in the internal mixing case. Regarding the direct radiative effects, we observed perturbation-induced variability ranges (evaluated against the base net fluxes in absence of aerosols) always within the perturbation range set for the particle microphysical properties . This work, therefore, quantitatively demonstrates that small uncertainties on the aerosol microphysical parameterization propagate on the simulated direct radiative effects mainly with a loss of strength. Considerable perturbation-induced absolute variations of the direct radiative effects have been found (above all for large aerosol amounts), which could significantly affect the model assessments of the ARI radiative effects and therefore meteorological forecasts and climate predictions. ; This work has been funded by the Spanish Ministry of Economy and Competitiveness [grant: CGL2013-46736-R] and by the ACTRIS Research Infrastructure Project of the European Union's Horizon 2020 research and innovation programme [grant agreement: No. 654169]. Further support has been provided by the Severo Ochoa Program, awarded by the Spanish Government [grant: SEV-2011-00067]. Vincenzo Obiso is funded by the Spanish Ministry of Economy and Competitiveness ['FPI-SO' grant: SVP-2013- 067953]. ; Peer Reviewed ; Postprint (published version)

We assessed the impact of the microphysical parameterization of natural and anthropogenic aerosols on simulated short-wave radiative effects due to Aerosol-Radiation Interaction (ARI). Layer radiative properties (optical depth, single scattering albedo and asymmetry factor) of dry mineral dust, organic carbon and a black carbon-sulfate mixture have been calculated with a T-matrix code in the short-wave spectral region, after perturbing relevant particle microphysical properties (size distribution, refractive index, mixing state). For each aerosol species, an idealized atmospheric layer and three events of increasing intensity have been set. Then, short-wave direct radiative effects (clear-sky) have been simulated at the top-of-atmosphere (TOA) and at surface (SFC) using the radiative transfer model RRTMG_SW (widely used in atmospheric models), separately for each aerosol species. We observed considerably variable impacts of the particle microphysical perturbations on the layer radiative properties for mineral dust and organic carbon, mainly due to the different sizes of the two species. For the black carbon-sulfate mixture, the single scattering albedo has been found to be much lower in the internal mixing case. Regarding the direct radiative effects, we observed perturbation-induced variability ranges (evaluated against the base net fluxes in absence of aerosols) always within the perturbation range set for the particle microphysical properties . This work, therefore, quantitatively demonstrates that small uncertainties on the aerosol microphysical parameterization propagate on the simulated direct radiative effects mainly with a loss of strength. Considerable perturbation-induced absolute variations of the direct radiative effects have been found (above all for large aerosol amounts), which could significantly affect the model assessments of the ARI radiative effects and therefore meteorological forecasts and climate predictions. ; This work has been funded by the Spanish Ministry of Economy and Competitiveness [grant: CGL2013-46736-R] and by the ACTRIS Research Infrastructure Project of the European Union's Horizon 2020 research and innovation programme [grant agreement: No. 654169]. Further support has been provided by the Severo Ochoa Program, awarded by the Spanish Government [grant: SEV-2011-00067]. Vincenzo Obiso is funded by the Spanish Ministry of Economy and Competitiveness ['FPI-SO' grant: SVP-2013- 067953]. ; Peer Reviewed ; Postprint (published version)

The influence of the Atlantic multidecadal variability (AMV) on the North Atlantic storm track and eddy-driven jet in the winter season is assessed via a coordinated analysis of idealized simulations with state-of-the-art coupled models. Data used are obtained from a multimodel ensemble of AMV± experiments conducted in the framework of the Decadal Climate Prediction Project component C. These experiments are performed by nudging the surface of the Atlantic Ocean to states defined by the superimposition of observed AMV± anomalies onto the model climatology. A robust extratropical response is found in the form of a wave train extending from the Pacific to the Nordic seas. In the warm phase of the AMV compared to the cold phase, the Atlantic storm track is typically contracted and less extended poleward and the low-level jet is shifted toward the equator in the eastern Atlantic. Despite some robust features, the picture of an uncertain and model-dependent response of the Atlantic jet emerges and we demonstrate a link between model bias and the character of the jet response. ; The authors are thankful to three anonymous reviewers for valuable comments on an early version of the manuscript. PR, AB, DN, SG, ND, RE, LH, DS, and SW were supported by the H2020 EUCP project (Grant GA 776613). ND, RE, LH, and DS were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. CC, ESG, and SQ would like to thank Marie-Pierre Moine for her help in model output post-processing and publication on CMIP6 database. BH acknowledges support from the NERC North Atlantic Climate System: Integrated Study (ACSIS) project. YRR was founded by the European Union's Horizon 2020 Research and Innovation Programme in the framework of the Marie Sklodowska-Curie Grant INADEC (Grant Agreement 800154). The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the U.S. National Science Foundation (NSF) under Cooperative Agreement 1852977. The NCAR contribution was supported by the U.S. NSF under the Collaborative Research EaSM2 Grant OCE-1243015 and the U.S. National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under the Climate Variability and Predictability Program Grant NA13OAR4310138. SW has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement H2020-MSCA-COFUND-2016-754433. ; Peer Reviewed ; "Article signat per 20 autors/es: Paolo Ruggieri, Alessio Bellucci, Dario Nicolí, Panos J. Athanasiadis, Silvio Gualdi, Christophe Cassou, Fred Castruccio, Gokhan Danabasoglu, Paolo Davini, Nick Dunstone, Rosemary Eade, Guillaume Gastineau, Ben Harvey, Leon Hermanson, Saïd Qasmi, Yohan Ruprich-Robert, Emilia Sanchez-Gomez, Doug Smith, Simon Wild, and Matteo Zampieri" ; Postprint (author's final draft)

Many recent studies have revealed the importance of the climatic state in November on the seasonal climate of the subsequent winter. In particular, it has been shown that interannual variability of sea ice concentration (SIC) over the Barents-Kara (BK) seas in November is linked to winter atmospheric circulation anomaly that projects on the North Atlantic Oscillation. Understanding the lead lag processes involving the different components of the climate system from autumn to winter is therefore important. This note presents dynamical interpretation for the ice-oceanatmosphere relationships that can affect the BK SIC anomaly in late autumn. It is found that cyclonic (anticyclonic) wind anomaly over the Arctic in October, by Ekman drift, can be responsible for positive (negative) SIC in theBKseas in November. The results also suggest that ocean heat transport via the Barents Sea Opening in September and October can contribute to BK SIC anomaly in November. ; JG-S has been supported by the European Union's FP7-funded NACLIM project (ENV-308299) and H2020-funded DPETNA grant (MSCA-IF-EF 655339). MPK acknowledges the Severo Ochoa Visiting Fellowship at the Barcelona Supercomputing Center and the Nordforsk GREENICE project (61841). Mehmet Ilicak and MariusA˚ rthun provided suggestions related to ocean heat transport. Suggestions from the reviewer had also led to improvement in the analyses. ; Peer Reviewed ; Postprint (published version)

Many recent studies have revealed the importance of the climatic state in November on the seasonal climate of the subsequent winter. In particular, it has been shown that interannual variability of sea ice concentration (SIC) over the Barents-Kara (BK) seas in November is linked to winter atmospheric circulation anomaly that projects on the North Atlantic Oscillation. Understanding the lead lag processes involving the different components of the climate system from autumn to winter is therefore important. This note presents dynamical interpretation for the ice-oceanatmosphere relationships that can affect the BK SIC anomaly in late autumn. It is found that cyclonic (anticyclonic) wind anomaly over the Arctic in October, by Ekman drift, can be responsible for positive (negative) SIC in theBKseas in November. The results also suggest that ocean heat transport via the Barents Sea Opening in September and October can contribute to BK SIC anomaly in November. ; JG-S has been supported by the European Union's FP7-funded NACLIM project (ENV-308299) and H2020-funded DPETNA grant (MSCA-IF-EF 655339). MPK acknowledges the Severo Ochoa Visiting Fellowship at the Barcelona Supercomputing Center and the Nordforsk GREENICE project (61841). Mehmet Ilicak and MariusA˚ rthun provided suggestions related to ocean heat transport. Suggestions from the reviewer had also led to improvement in the analyses. ; Peer Reviewed ; Postprint (published version)

Dynamical forecast systems have low to moderate skill in continental winter predictions in the extratropics. Here we assess the multimodel predictive skill over Northern Hemisphere high latitudes and midlatitudes using four state‐of‐the‐art forecast systems. Our main goal was to quantify the impact of the Arctic sea ice state during November on the sea level pressure (SLP), surface temperature, and precipitation skill during the following winter. Interannual variability of the November Barents and Kara Sea ice is associated with an important fraction of December to February (DJF) prediction skill in regions of Eurasia. We further show that skill related to sea ice in these regions is accompanied with enhanced skill of DJF SLP in western Russia, established by a sea ice‐atmosphere teleconnection mechanism. The teleconnection is strongest when atmospheric blocking conditions in Scandinavia/western Russia in November reduce a systematic SLP bias that is present in all systems. ; This work was funded by the European Union projects APPLICATE (Grant 727862), PRIMAVERA (Grant 641727), INTAROS (Grant 727890), and ESA/CMUG‐CCI3. We acknowledge PRACE for awarding us access to MareNostrum IV at Barcelona Supercomputing Center (BSC), Spain. 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). E. T. received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska‐Curie grant Agreement 748750 (SPFireSD project). V. G. received funding from the Agence Nationale de la Recherche through the Make Our Planet Great Again Grant ANR‐17‐MPGA‐003. The data from EC‐Earth3.2 and CNRM‐CM6‐1 are publicly available (at https://applicate.eu/data/data‐portal). GloSea5 (v13) and SEAS5 data are publicly available (at https://cds.climate.copernicus.eu/cdsapp#!/dataset/seasonal‐ monthly‐single‐levels?tab=overview). All the data were downloaded from their original source, converted to NetCDF in a format designed for efficient analysis with the tools mentioned before, and quality checked at several levels. ; Peer Reviewed ; Postprint (published version)