95 research outputs found

    Robustness of precipitation Emergent Constraints in CMIP6 models

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    An Emergent Constraint (EC) is a physically-explainable relationship between model simulations of a past climate variable (predictor) and projections of a future climate variable (predictand). If a significant correlation exists between the predictand and the predictor, observations of the latter can be used to constrain model projections of the former and to narrow their uncertainties. In the present study, the EC technique has been applied to the analysis of precipitation, one of the variables most affected by model uncertainties and still insufficiently analysed in the context of ECs, particularly for the recent CMIP6 model ensemble. The main challenge in determining an EC is establishing if the relationship found is physically meaningful and robust to the composition of the model ensemble. Four precipitation ECs already documented in the literature and so far tested only with CMIP3/CMIP5, three of them involving the analysis of extreme precipitation, have been reconsidered in this paper. Their existence and robustness are evaluated using different subsets of CMIP5 and CMIP6 models, verifying if the EC is still present in the most recent ensemble and assessing its sensitivity to the detailed ensemble composition. Most ECs considered do not pass this test: we found one EC not to be robust in both CMIP5 and CMIP6, other two exist and are robust in CMIP5 but not in CMIP6, and only one is verified and is robust in both model ensembles

    Mountain Observations: Monitoring, Data, and Information for Science, Policy, and Society

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    Observations play a key role in tracking mountain global change and its impacts, understanding the various processes and feedback mechanisms involved, and delivering more reliable projections of the future to society. This Policy Brief provides an overview of the current state of multi-disciplinary mountain observations. It represents a contribution of the Global Network on Observations and Information in Mountain Environments (GEO Mountains) to the observance of the International Year of Sustainable Mountain Development 2022

    Diagnostics of the tropical tropopause layer from in-situ observations and CCM data

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    A suite of diagnostics is applied to in-situ aircraft measurements and one Chemistry-Climate Model (CCM) data to characterize the vertical structure of the Tropical Tropopause Layer (TTL). The diagnostics are based on vertical tracer profiles and relative vertical tracer gradients, using tropopause-referenced coordinates, and tracer-tracer relationships in the tropical Upper Troposphere/Lower Stratosphere (UT/LS). Observations were obtained during four tropical campaigns performed from 1999 to 2006 with the research aircraft Geophysica and have been compared to the output of the ECHAM5/MESSy CCM. The model vertical resolution in the TTL (~500 m) allows for appropriate comparison with high-resolution aircraft observations and the diagnostics used highlight common TTL features between the model and the observational data. The analysis of the vertical profiles of water vapour, ozone, and nitrous oxide, in both the observations and the model, shows that concentration mixing ratios exhibit a strong gradient change across the tropical tropopause, due to the role of this latter as a transport barrier and that transition between the tropospheric and stratospheric regimes occurs within a finite layer. The use of relative vertical ozone and carbon monoxide gradients, in addition to the vertical profiles, helps to highlight the region where this transition occurs and allows to give an estimate of its thickness. The analysis of the CO-O3 and H2O-O3 scatter plots and of the Probability Distribution Function (PDF) of the H2O-O3 pair completes this picture as it allows to better distinguish tropospheric and stratospheric regimes that can be identified by their different chemical composition. The joint analysis and comparison of observed and modelled data allows to state that the model can represent the background TTL structure and its seasonal variability rather accurately. The model estimate of the thickness of the interface region between tropospheric and stratospheric regimes agrees well with average values inferred from observations. On the other hand, the measurements can be influenced by regional scale variability, local transport processes as well as deep convection, that can not be captured by the model

    Diagnostics of the tropical tropopause layer from in-situ observations and CCM data

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    A suite of diagnostics is applied to in-situ aircraft measurements and one Chemistry-Climate Model (CCM) data to characterize the vertical structure of the Tropical Tropopause Layer (TTL). The diagnostics are based on the vertical tracers profiles, relative vertical tracers gradients, and tracer-tracer relationships in the tropical Upper Troposphere/Lower Stratosphere (UT/LS), using tropopause coordinates. Observations come from the four tropical campaigns performed from 1998 to 2006 with the research aircraft Geophysica and have been directly compared to the output of the ECHAM5/MESSy CCM. The model vertical resolution in the TTL allows for appropriate comparison with high-resolution aircraft observations and the diagnostics used highlight common TTL features between the model and the observational data. The analysis of the vertical profiles of water vapour, ozone, and nitrous oxide, in both the observations and the model, shows that concentration mixing ratios exhibit a strong gradient change across the tropical tropopause, due to the role of this latter as a transport barrier and that transition between the tropospheric and stratospheric regimes occurs within a finite layer. The use of relative vertical ozone gradients, in addition to the vertical profiles, helps to highlight the region where this transition occurs and allows to give an estimate of its thickness. The analysis of the CO-O3 and H2O-O3 scatter plots and of the Probability Distribution Function (PDF) of the H2O-O3 pair completes this picture as it allows to better distinguish tropospheric and stratospheric regimes that can be identified, first, by their differing chemical composition. The joint analysis and comparison of observed and modelled data allows us to evaluate the capability of the model in reproducing the observed vertical structure of the TTL and its variability, and also to assess whether observations from particular regions on a monthly timescale can be representative of the fine scale mean structure of the Tropical Tropopause Layer

    MOCRA: a Monte Carlo code for the simulation of radiative transfer in the atmosphere.

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    This paper describes the radiative transfer model (RTM) MOCRA (MOnte Carlo Radiance Analysis), developed in the frame of DOAS (Differential Optical Absorption Spectroscopy) to correctly interpret remote sensing measurements of trace gas amounts in the atmosphere through the calculation of the Air Mass Factor. Besides the DOAS-related quantities, the MOCRA code yields: 1- the atmospheric transmittance in the vertical and sun directions, 2- the direct and global irradiance, 3- the single- and multiple- scattered radiance for a detector with assigned position, line of sight and field of view. Sample calculations of the main radiometric quantities calculated with MOCRA are presented and compared with the output of another RTM (MODTRAN4). A further comparison is presented between the NO2 slant column densities (SCDs) measured with DOAS at Evora (Portugal) and the ones simulated with MOCRA. Both comparisons (MOCRA-MODTRAN4 and MOCRA-observations) gave more than satisfactory results, and overall make MOCRA a versatile tool for atmospheric radiative transfer simulations and interpretation of remote sensing measurements

    Dynamic QuantiFERON Response in Psoriasis Patients Taking Long-Term Biologic Therapy

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    INTRODUCTION: The risk of active tuberculosis is increased in psoriasis patients receiving biologic drug therapy. The QuantiFERON-TB Gold In-Tube assay (QFT) is used for latent tuberculosis screening in these patients. This study presents a retrospective analysis on repeated QFT assays, investigating the influence of biologic drugs and isoniazid therapy on the outcome of the assay. METHODS: Serial QFTs of 58 psoriasis patients, who received biologic drug therapy, were evaluated at baseline and after 12 months of treatment. Patients were retrospectively divided in four groups according to QFT results at baseline and at follow-up: patients having a QFT reversion (from positive to negative results); patients with a conversion (from negative to positive); patients confirming the baseline results, either positive or negative. RESULTS: At the end of the 12-months period, 11.1% of patients with a negative QFT result at baseline presented a conversion, showing low interferon (IFN)-gamma values, whereas 6.9% of positive patients presented a QFT reversion. When the test was repeated after 2–3 months without isoniazid chemoprophylaxis, patients with QFT conversion showed negative results. No patient developed active tuberculosis. CONCLUSIONS: In patients undergoing biologic therapy, a positive QFT assay needs to be further confirmed, as false-positive results may occur after long-term therapy. Repeating QFT tests in patients with low IFN-gamma values could reduce the incidence of false-positive latent tuberculosis infection diagnosis, thus preventing unnecessary tuberculosis chemoprophylaxis. In conclusion, a dynamic QFT response is possible in psoriasis patients undergoing biologic therapy

    Hydrological impacts of large fires and future climate: modeling approach supported by satellite data

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    Fires have significant impacts on soil erosion and water supply that may be exacerbated by future climate. The aims of this study were: To simulate the effects of a large fire event in the SWAT (Soil and Water Assessment Tool) hydrological model previously calibrated to a medium-sized watershed in Portugal; and to predict the hydrological impacts of large fires and future climate on water supply and soil erosion. For this, post-fire recovery was parametrized in SWAT based on satellite information, namely, the fraction of vegetation cover (FVC) calculated from the normalized difference vegetation index (NDVI). The impact of future climate was based on four regional climate models under the stabilization (RCP 4.5) and high emission (RCP 8.5) scenarios, focusing on mid-century projections (2020–2049) compared to a historical period (1970–1999). Future large fire events (>3000 ha) were predicted from a multiple linear regression model, which uses the daily severity rating (DSR) fire weather index, precipitation anomaly, and burnt area in the previous three years; and subsequently simulated in SWAT under each climate model/scenario. Results suggest that time series of satellite indices are useful to inform SWAT about vegetation growth and post-fire recovery processes. Different land cover types require different time periods for returning to the pre-fire fraction of vegetation cover, ranging from 3 years for pines, eucalypts, and shrubs, to 6 years for sparsely vegetated low scrub. Future climate conditions are expected to include an increase in temperatures and a decrease in precipitation with marked uneven seasonal distribution, and this will likely trigger the growth of burnt area and an increased frequency of large fires, even considering differences across climate models. The future seasonal pattern of precipitation will have a strong influence on river discharge, with less water in the river during spring, summer, and autumn, but more discharge in winter, the latter being exacerbated under the large fire scenario. Overall, the decrease in water supply is more influenced by climate change, whereas soil erosion increase is more dependent on fire, although with a slight increase under climate change. These results emphasize the need for adaptation measures that target the combined hydrological consequences of future climate, fires, and post-fire vegetation dynamics.The project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641762. FCT—Fundação para a Ciência e a Tecnologia, I.P.,under the project FirESmart “PCIF/MOG/0083/2017”

    A multi-input UV-VIS airborne GASCOD/A4r spectroradiometer for the validation of satellite remote sensing measurements

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    The present paper describes a UV-VIS spectroradiometer named GASCOD/A4r developed at ISAC-CNR for remote sensing measurements aboard stratospheric M55-Geophysica aircraft, flying up to 21 km. Obtained experimental data are used for retrieving of NO2, O3 and of other minor gases atmospheric content, applying the DOAS (Differential Optical Absorption Spectroscopy) method. UV actinic flux and J(NO2) are also derived. All these parameters are used for satellite data validation tasks. The specific results obtained during dedicated aircraft missions in different geographical areas have already been utilized for ENVISAT validation

    Latitudinal dependence of the ExTL from in situ observations

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    Multiple in-situ datasets are combined and a consistent set of dynamical diagnostics is derived from ECMWF wind fields. These tools are used to investigate the extra tropical transition layer (ExTL) region in terms of potential temperature – equivalent latitude coordinates and distance relative to the local dynamical (PV) tropopause. The location and structure of the maximal vertical gradient of CO is studied as a mean to define a chemical tropopause. The same methods applied to other tracers (e.g. ozone) give different results since different tracers have different chemical tropopauses. Iso-PV following vertical coordinates can be used to relate the dynamical/PV based tropopause and the tracer gradient based tropopause taking into account latitudinal dependence and seasonal variability. The resulting information is intended to derive diagnostics useful to test the performance of global chemical models and establish comparisons with Lagrangian models
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