The influence of ENSO events on the stratospheric QBO in a multi-model ensemble

AbstractThe Quasi-Biennial Oscillation (QBO) and the El Niño–Southern Oscillation (ENSO) are two dominant modes of climate variability at the Equator. There exist observational evidences of mutual interactions between these two phenomena, but this possibility has not been widely studied using climate model simulations. In this work we assess how current models represent the ENSO/QBO relationship, in terms of the response of the amplitude and descent rate of stratospheric wind regimes, by analyzing atmosphere-only and ocean–atmosphere coupled simulations from a large multi-model ensemble. The annual cycle of the QBO descent rate is well represented in both coupled and uncoupled models. Previous results regarding the phase alignment of the QBO after the 1997/98 strong warm ENSO event are confirmed in a larger ensemble of uncoupled experiments. However, in general we find that a relatively high horizontal resolution is necessary to reproduce the observed modulation of the QBO descent rate under strong ENSO events, while the amplitude response is generally weak at any horizontal resolution. We argue that biases in the mean state and over-dependence on parameterized wave forcing undermine the realism of the simulated coupling between the ocean and the stratosphere in the tropics in current climate models. The modulation of the QBO by the ENSO in a high emission scenario consistently differs from that in the historical period, suggesting that this relationship is sensitive to changes in the large-scale circulation

Negative ozone anomalies at a high mountain site in northern Italy during 2020: a possible role of COVID-19 lockdowns?

Several studies investigated the possible impacts of the restriction measures related to the containment of the spread of the COrona VIrus Disease (COVID-19) to atmospheric ozone (O3) at global, regional, and local scales during 2020. O3 is a secondary pollutant with adverse effects on population health and ecosystems and with negative impacts on climate, acting as greenhouse gas. Most of these studies focused on spring 2020 (i.e. March–May) and on observations in the planetary boundary layer (PBL), mostly in the vicinity of urban agglomerates. Here, we analyzed the variability of O3 above the PBL of northern Italy in 2020 by using continuous observations carried out at a high mountain WMO/GAW global station in Italy (Mt. Cimone–CMN; 44°12' N, 10°42' E, 2165 m a.s.l.). Low O3 monthly anomalies were observed during spring (MAM) and summer (JJA), when periods of low O3 intertwined with periods with higher O3, within climatological ranges. A similar variability was observed for O3 precursors like NO2 and 15 anthropogenic non-methane volatile organic carbons, but the systematic O3 anomalies were not reflected in these variables. The analysis of meteorological variables and diel O3 cycles did not suggest major changes in the vertical transport related to the thermal circulation system in the mountain area. The analysis of five days back-trajectories suggested that the observed O3 anomalies cannot be explained by differences in the synoptic-scale circulation with respect to the previous years alone. On the other hand, the characterization of two transport patterns (i.e. air masses from the regional PBL or from the free troposphere) and the analysis of back-trajectories suggested an important contribution of transport from the continental PBL during the periods with the lowest O3 at CMN. When proxies of air mass transport from the regional PBL are considered, a lower NOx content was pointed out with respect to the previous years, suggesting a lower O3 production in a NOx-limited atmosphere. Our study suggested for the first time that, during MAM and JJA 2020, the reduced anthropogenic emissions related to the COVID-19 restrictions lowered the amount of this short-lived climate forcer/pollutant at remote locations above the PBL over northern Italy. This work suggests the importance of limiting anthropogenic precursor emissions for decreasing the O3 amount at remote locations and in upper atmospheric layers

Teleconnections of the Quasi‐Biennial Oscillation in a multi‐model ensemble of QBO‐resolving models

The Quasi-biennial Oscillation (QBO) dominates the interannual variability of the tropical stratosphere and influences other regions of the atmosphere. The high predictability of the QBO implies that its teleconnections could lead to increased skill of seasonal and decadal forecasts provided the relevant mechanisms are accurately represented in models. Here modelling and sampling uncertainties of QBO teleconnections are examined using a multi-model ensemble of QBO-resolving atmospheric general circulation models that have carried out a set of coordinated experiments as part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) QBO initiative (QBOi). During Northern Hemisphere winter, the stratospheric polar vortex in most of these models strengthens when the QBO near 50 hPa is westerly and weakens when it is easterly, consistent with, but weaker than, the observed response. These weak responses are likely due to model errors, such as systematically weak QBO amplitudes near 50 hPa, affecting the teleconnection. The teleconnection to the North Atlantic Oscillation is less well captured overall, but of similar strength to the observed signal in the few models that do show it. The models do not show clear evidence of a QBO teleconnection to the Northern Hemisphere Pacific-sector subtropical jet

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.Peer reviewe

THRawS

THRawS is a new dataset of raw Sentinel-2 (S-2) satellite data containing warm temperature hotspots such as wildfires and volcanic eruptions from around the world. The dataset aims to promote the development of energy-efficient pre-processing algorithms and AI models for onboard-satellite applications. A custom methodology was designed to identify events in raw data using corresponding Level-1C (L1C) products and a lightweight coarse coregistration and georeferencing strategy was employed to deal with unprocessed data. The dataset comprises over 100 samples, including wildfire, volcanic eruption, and event-free volcanic areas, to enable warm-events detection and general classification applications. Finally, the performances of the proposed coarse spatial coregistration technique and the SuperGlue Deep Neural Network method were compared to highlight different constraints in terms of timing and quality of spatial registration to minimize spatial displacement error for a specific scene. Github Repo: https://github.com/ESA-PhiLab/PyRawS- The json file includes the corresponding L1C files. - Github Repo:https://github.com/ESA-PhiLab/PyRaw

Uncertainties on Climate Extreme Indices Estimated From U.S. Climate Reference Network (USCRN) Near-Surface Temperatures

Changes in the frequency of temperature extremes are often attributed to global warming. The recent availability of near-surface temperature data records from reference networks, such as the U.S. Climate Reference Network (USCRN), enables the quantification of measurement uncertainties. Within an activity of the Copernicus Climate Change Service, the estimation of the measurement uncertainty has been provided for USCRN temperature data, using metadata made available by the National Oceanic and Atmospheric Administration (NOAA). In this paper, four climate extreme indices (Frost Days, Summer Days, Ice Days, Tropical Nights) and the related uncertainties are calculated for the period 2006-2020 from the USCRN data set and compared with traditional indices. Moreover, the asymmetric USCRN measurement uncertainties are propagated to estimate the uncertainties of climate indices. The comparison shows expanded uncertainties homogeneously distributed with the latitude and typically within 15 days per year for Frost Days and within 10 days for Ice Days, while smaller uncertainties are estimated for Summer Days and Tropical Nights, with values typically within six to seven days per year. Positive uncertainties are typically larger than negative ones for all the indices. The values of Frost and Ice Days with the related uncertainties for USCRN have also been compared with the corresponding values calculated from reanalyses data, showing differences typically within 60 days for median values, quite often smaller than USCRN and inconsistent within the related uncertainties, Overall, the results show that USCRN measurement uncertainties increase confidence in the estimation of climate extreme indices and decisions for adaptation

Spectrophotometric techniques for the characterization of strains involved in the blue pigmentation of food: Preliminary results

Near infrared spectroscopy (NIRs) and ultraviolet visible spectroscopy (UV-vis) have been investigated as rapid techniques to characterize foodborne bacteria through the analysis of the spectra of whole cells or microbial suspensions. The use of spectra collected from broth cultures could be used as a fingerprint for strain classification using a combined polyphasic approach. The aim of this study was to evaluate the feasibility of NIRs and UV-vis for the characterization of blue strains belonging to the Pseudomonas fluorescens group. The bacteria were isolated from different food matrices, including some spoiled samples (blue discoloration). Eightyone strains previously identified at the species level were grown in Minimal Bacterial Medium broth under standard conditions at 22°C. Two biological replicates were centrifuged in order to separate the bacterial cells from the extracellular products. Six aliquots per strain were analyzed on a small ring cup in transflectance mode (680-2500 nm, gap 2 nm). A subset of 39 strains was evaluated by UV-vis to determine changes in the spectral characteristics at 48 and 72 hours. Several chemometric approaches were tested to assess the performance of NIRs and UVvis. According to the variable importance in projection (VIP), the 1892-2020 nm spectral region showed the highest level of discrimination between blue strains and others. Additional information was provided in the 680-886 and 1454-1768 nm regions (aromatic C-H bonds) and in the 2036-2134 nm region (fatty acids). Changes in UV-vis spectral data (at 48 and 72 hours) appear to indicate the presence of phenazine and catecholic compounds in extracellular products

CHARACTERIZATION OF BLUE PSEUDOMONAS FLUORESCENS THROUGH NEAR-INFRARED SPECTROSCOPY

Abstract Content: Near infrared spectroscopy (NIRs) has been widely suggested as a rapid technique to characterize foodborne bacteria through the analysis of spectra of whole cells or microbial suspensions. The use of spectra collected from broth cultures could be used as a fingerprint for strains classification in a combined polyphasic approach. The aim of this study was to evaluate the feasibility of the NIRs technique in the characterization of strains belonging to the Pseudomonas fluorescens group. The bacteria were isolated from different food matrices and during some cases of spoilage (e.g Blue discoloration). A total of 81 strains (field and Type strains) previously identified at species level through a Multilocus Sequence Typing approach were grown in Minimal Bacterial Medium broth in standardized condition at 22 \ub0C. This medium was composed by salts with trisodium citrate and glucose as carbon sources and exalts the production of blue pigment. Two biological replicates were centrifuged in order to separate the bacterial cells from the extracellular products. Six aliquots per strain were analyzed on small ring cup in transflectance mode (680-2500 nm, gap 2 nm) at room temperature. Several chemometrics approaches were tested to assess the NIRs performances. Principal component analysis and Principal coordinate analysis showed a clear distinction among the blue producing strains and all the others strains according to the raw spectral data. Soft Independent Modelling of Class Analogy approach was applied to build several models using PLS Discriminant Analysis (PLS-DA). According to the variable importance criterion (VIP) the 1892-2020 nm spectral region showed the highest level of discrimination between blue strains and others (93.43% accuracy). Other additional information were provided by 680-886 region and 1454-1768 nm region (aromatic CH) and 2036-2134 nm (fatty acid). This approach suggests the use of NIRs as instrument for the extracellular products characterization and the strains classification

Molecular Fingerprints of Hydrophobicity at Aqueous Interfaces from Theory and Vibrational Spectroscopies

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