North Atlantic MOC variability and the Mediterranean Outflow: A box-model study

A simple box-model is used to investigate the effect of intermediate level heat/freshwater fluxes on the variability of the oceanic meridional overturning circulation. The model includes a simple representation of the spreading of the Mediterranean Outflow Water in the North Atlantic. We identify an internal advective feedback affecting the amplitude of the thermohaline oscillations. When a salinity gradient is maintained in the ocean interior the oscillations are amplified. Instead, if the intermediate level fluxes are spread in the ocean deep layers, the model variability is reduced. We suggest that this mechanism may be relevant for climate variability on interdecadal timescales

Thermohaline circulation sensitivity to intermediate‐level anomalies

A two-dimensional Boussinesq ocean model has been used to investigate the effect ofintermediate-level thermal and saline anomalies on the known multiple equilibria structure ofthe thermohaline circulation. These anomalies are taken as a crude representation of theMediterranean outflow in the Atlantic Ocean. The associated perturbation drives the systemtowards an overturning which resembles the present average Atlantic thermohaline circulation.The sensitivity to the depth at which the anomaly is placed is also investigated. We found thatnear-surface anomalies are more efficient in affecting the structure of the equilibria.DOI: 10.1034/j.1600-0870.2002.01284.

Does the subtropical jet catalyze the mid-latitude atmospheric regimes?

Understanding the atmospheric low-frequency variability is of crucial importance in fields such as climate studies, climate change detection, and extended-range weather forecast. The Northern Hemisphere climate features the planetary waves as a relevant ingredient of the atmospheric variability. Several observations and theoretical arguments seem to support the idea that winter planetary waves indicator obey a non-Gaussian statistics and may present a multimodal probability density function, thus characterizing the low-frequency portion of the climate system. We show that the upper tropospheric jet strength is a critical parameter in determining whether the planetary waves indicator exhibits a uni- or bimodal behavior, and we determine the relevant threshold value of the jet. These results are obtained by considering the data of the NCEP-NCAR and ECMWF reanalyses for the overlapping period. Our results agree with the non-linear orographic theory, which explains the statistical non-normality of the low-frequency variability of the atmosphere and its possible bimodality.Comment: Final version of the pape

Intercomparison of the northern hemisphere winter mid-latitude atmospheric variability of the IPCC models

We compare, for the overlapping time frame 1962-2000, the estimate of the northern hemisphere (NH) mid-latitude winter atmospheric variability within the XX century simulations of 17 global climate models (GCMs) included in the IPCC-4AR with the NCEP and ECMWF reanalyses. We compute the Hayashi spectra of the 500hPa geopotential height fields and introduce an integral measure of the variability observed in the NH on different spectral sub-domains. Only two high-resolution GCMs have a good agreement with reanalyses. Large biases, in most cases larger than 20%, are found between the wave climatologies of most GCMs and the reanalyses, with a relative span of around 50%. The travelling baroclinic waves are usually overestimated, while the planetary waves are usually underestimated, in agreement with previous studies performed on global weather forecasting models. When comparing the results of various versions of similar GCMs, it is clear that in some cases the vertical resolution of the atmosphere and, somewhat unexpectedly, of the adopted ocean model seem to be critical in determining the agreement with the reanalyses. The GCMs ensemble is biased with respect to the reanalyses but is comparable to the best 5 GCMs. This study suggests serious caveats with respect to the ability of most of the presently available GCMs in representing the statistics of the global scale atmospheric dynamics of the present climate and, a fortiori, in the perspective of modelling climate change.Comment: 39 pages, 8 figures, 2 table

Destabilization of the thermohaline circulation by transient perturbations to the hydrological cycle

We reconsider the problem of the stability of the thermohaline circulation as described by a two-dimensional Boussinesq model with mixed boundary conditions. We determine how the stability properties of the system depend on the intensity of the hydrological cycle. We define a two-dimensional parameters' space descriptive of the hydrology of the system and determine, by considering suitable quasi-static perturbations, a bounded region where multiple equilibria of the system are realized. We then focus on how the response of the system to finite-amplitude surface freshwater forcings depends on their rate of increase. We show that it is possible to define a robust separation between slow and fast regimes of forcing. Such separation is obtained by singling out an estimate of the critical growth rate for the anomalous forcing, which can be related to the characteristic advective time scale of the system.Comment: 37 pages, 8 figures, submitted to Clim. Dy

Dynamical and statistical downscaling of a global seasonal hindcast in eastern Africa

Within the FP7 EUPORIAS project we have assessed the utility of dynamical and statistical downscaling to provide seasonal forecast for impact modelling in eastern Africa. An ensemble of seasonal hindcasts was generated by the global climate model (GCM) EC-EARTH and then downscaled by four regional climate models and by two statistical methods over eastern Africa with focus on Ethiopia. The five-month hindcast includes 15 members, initialised on May 1?st covering 1991?2012. There are two sub-regions where the global hindcast has some skill in predicting June?September rainfall (northern Ethiopia ? northeast Sudan and southern Sudan - northern Uganda). The regional models are able to reproduce the predictive signal evident in the driving EC-EARTH hindcast over Ethiopia in June?September showing about the same performance as their driving GCM. Statistical downscaling, in general, loses a part of the EC-EARTH signal at grid box scale but shows some improvement after spatial aggregation. At the same time there are no clear evidences that the dynamical and statistical downscaling provide added value compared to the driving EC-EARTH if we define the added value as a higher forecast skill in the downscaled hindcast, although there is a tendency of improved reliability through the downscaling. The use of the global and downscaled hindcasts as input for the Livelihoods, Early Assessment and Protection (LEAP) platform of the World Food Programme in Ethiopia shows that the performance of the LEAP platform in predicting humanitarian needs at the national and sub-national levels is not improved by using downscaled seasonal forecasts.This work was done in the EUPORIAS project that received funding from the European Union Seventh Framework Programme (FP7) for Research, under grant agreement 308291. The authors thank the European Centre for Medium-Range Weather Forecasts (ECMWF), the Global Precipitation Climatology Centre (GPCC), the British Atmospheric Data Centre (BADC), the University of East Anglia (UEA), the University of Delaware, the University of Reading, the University of California, the Climate Prediction Center (CPC), the US Agency for International Development’s Famine Early Warning Network (FEWS NET) and the WATCH project for providing data. For the WRF simulations, the UCAN group acknowledges Santander Supercomputacion support group at the University of Cantabria, who provided access to the Altamira Supercomputer at the Institute of Physics of Cantabria (IFCA-CSIC), member of the Spanish Supercomputing Network. DWD wants to thank ECMWF for the support during the CCLM4 simulations which have been carried out at the ECMWF computing system. The SMHI RCA4 simulations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at National Supercomputer Centre (NSC) and the PDC Center for High Performance Computing (PDC-HPC)

Thermal (Catalyst-Free) Transesterification of Diols and Glycerol with Dimethyl Carbonate: A Flexible Reaction for Batch and Continuous Flow Applications

An innovative thermal transesterification protocol for the synthesis of linear and alkylene carbonates was investigated under both batch and continuous-flow (CF) conditions. Accordingly, model 1,n-diols (n = 2-4) and glycerol were set to react with dimethyl carbonate (DMC) at T and p of 150-260 degrees C and 1-50 bar, respectively, in the absence of any catalyst. 1,2-diols afforded the corresponding five-membered ring carbonates as the main products with a quantitative conversion and a selectivity up to 94%, whereas 1,3-diols gave the six-membered ring products along with linear mono- and dicarbonate derivatives. A complete conversion was attained also for glycerol, but the products distribution depended on reaction conditions: the CF mode allowed the synthesis of glycerol carbonate, whereas batch reactions yielded either glycerol carbonate or its derivative from a further transesterification reaction, i.e., methyl (2-oxo-1,3-dioxolan-4-yl)methyl carbonate. The selectivity toward these two compounds was in the range of 83%-94%. An addition of gaseous CO2 (up to 20 bar) allowed to control further the selectivity of batch reactions

A Novel Bias Correction Method for Extreme Events

When one is using climate simulation outputs, one critical issue to consider is the systematic bias affecting the modelled data. The bias correction of modelled data is often used when one is using impact models to assess the effect of climate events on human activities. However, the efficacy of most of the currently available methods is reduced in the case of extreme events because of the limited number of data for these low probability and high impact events. In this study, a novel bias correction methodology is proposed, which corrects the bias of extreme events. To do so, we extended one of the most popular bias correction techniques, i.e., quantile mapping (QM), by improving the description of extremes through a generalised extreme value distribution (GEV) fitting. The technique was applied to the daily mean temperature and total precipitation data from three seasonal forecasting systems: SEAS5, System7 and GCFS2.1. The bias correction efficiency was tested over the Southern African Development Community (SADC) region, which includes 15 Southern African countries. The performance was verified by comparing each of the three models with a reference dataset, the ECMWF reanalysis ERA5. The results reveal that this novel technique significantly reduces the systematic biases in the forecasting models, yielding further improvements over the classic QM. For both the mean temperature and total precipitation, the bias correction produces a decrease in the Root Mean Squared Error (RMSE) and in the bias between the simulated and the reference data. After bias correcting the data, the ensemble forecasts members that correctly predict the temperature extreme increases. On the other hand, the number of members identifying precipitation extremes decreases after the bias correction

Evaluation of simulated decadal variations over the Euro-Mediterranean region from ENSEMBLES to Med-CORDEX

International audienceMed-CORDEX simulations over the period 1979–2011 are evaluated with regard to their capability to represent observed decadal variations over the Euro-Mediterranean region and improve upon previous generation simulations from the ENSEMBLES project in their various experimental set-ups. Such an evaluation is needed to inform the use of these simulations and also future model development. For temperature, both Med-CORDEX and ENSEMBLES simulations tend to provide comparable results: they generally capture the sign and timing of the anomalies but not the amplitude. In general, no clear stratification appears when considering different types of Med-CORDEX regional modeling systems. Rather, it is remarkable that certain periods are poorly represented by all systems with a general underestimation of the observed long-term temperature trend, mostly in the summer season, even with respect to the corresponding global drivers. For precipitation, the Med-CORDEX simulations are closer to observations than the other datasets, with some improvement with respect to ENSEMBLES dataset. In general, all the systems experience difficulties in representing anomalies during specific periods or for specific regions. These appear in part due to limitations in the reanalysis boundary forcing data. For instance, in the second part of 1980s, the spatial patterns of surface air temperature during DJF/MAM are generally poorly represented, as well as the regionally averaged MAM/JJA surface air temperature decadal anomalies. Overall, the evaluation suggests limited improvement in Med-CORDEX simulations compared to ENSEMBLES, and a lack of sensitivity to resolution or coupling configuration, with persisting problems in part likely related to the representation of surface processes that could also affect the viability of future projections (e.g. the estimation of temperature trends). A set of decadal variability evaluation metrics, as applied in this study, could be useful in the context of a broader evaluation framework