Atmospheric Simulations Research Articles

Health and economic cost estimates of short-term total and wildfire PM2.5 exposure on work loss: using the consecutive California Health Interview Survey (CHIS) data 2015–2018

InstructionTo help determine the health protectiveness of government regulations and policies for air pollutant control for Americans, our study aimed to investigate the health and economic impacts of work loss...

Atmospheric Rivers are Responsible for Cyclicity in Sierra Nevada Precipitation

Abstract Cool-season (November–March) precipitation contributes critically to California’s water resources and flood risk. In the Sierra Nevada, approximately half of cool-season precipitation is derived from a small proportion of storms classified as atmospheric rivers (ARs). The frequency and intensity of ARs are highly variable from year to year and unreliable climate teleconnections limit forecasting. However, previous research provides intriguing evidence of cycles with biennial (2.2 years) and decadal (10–20 years) periodicities in Sierra Nevada cool-season precipitation, suggesting it is not purely stochastic. To identify the source of this cyclicity, we decompose daily precipitation records (1949–2022) into contributions from ARs versus non-ARs, as well as into variations in frequency and intensity. We find that the biennial and decadal spectral peaks in Sierra Nevada precipitation totals are entirely due to precipitation delivered by ARs, and primarily due to variations in the frequency of days with AR precipitation. While total non-AR precipitation correlates with sea surface temperature (SST) and atmospheric pressure patterns associated with the El Niño–Southern Oscillation, AR precipitation shows no consistent remote teleconnections at any periodicity. Supporting this finding, atmospheric simulations forced by observed SSTs do not reproduce the biennial or decadal precipitation variations identified in observations. These results, combined with the lack of long-term stable cycles in previously published tree-ring reconstructions, suggest that the observed biennial and decadal quasi-cyclicity in Sierra Nevada precipitation is unreliable as a forecasting tool. Significance Statement In California’s Sierra Nevada, where most of the state’s above-ground water resources originate, cool-season precipitation totals exhibited year-to-year and decadal cyclicity over the past century. Long-range forecasts are notoriously unskillful in this region, so nonrandom cycles would be intriguing to water managers challenged to simultaneously minimize flood and drought risk. Over 1949–2022, precipitation cycles were driven by variations in the number of atmospheric river (AR) storms per year even though ARs account for just half of total precipitation. These findings bring us a step closer to understanding the causes of precipitation cyclicity, but we find no evidence that the cycles were underpinned by larger-scale ocean–atmosphere circulations so we caution against relying on continued cycles into the future.

Accelerated particle beams in a 3D simulation of the quiet Sun

Context. Charged particles are constantly accelerated to non-thermal energies by the reconnecting magnetic field in the solar atmosphere. Our understanding of the interactions between the accelerated particles and their environment can benefit considerably from three-dimensional atmospheric simulations that account for non-thermal particle beam generation and propagation. In a previous publication, we presented the first results from such a simulation, which considers quiet Sun conditions. However, the original treatment of beam propagation ignores potentially important phenomena such as the magnetic gradient forces associated with a converging or diverging magnetic field. Aims. Here we present a more general beam propagation model incorporating magnetic gradient forces, the return current, acceleration by the ambient electric field, corrected collision rates due to the ambient temperature, and collisions with heavier elements than hydrogen and the free electrons they contribute. Neglecting collisional velocity randomisation makes the model sufficiently lightweight to simulate millions of beams. We investigate how each new physical effect in the model changes the non-thermal energy transport in a realistic three-dimensional atmosphere. Methods. We applied the method of characteristics to the steady-state continuity equation for electron flux to derive ordinary differential equations for the mean evolution of energy, pitch angle, and flux with distance. For each beam, we solved these numerically for a range of initial energies to obtain the evolving flux spectrum, from which we computed the energy deposited into the ambient plasma. Results. Magnetic gradient forces significantly influence the spatial distribution of deposited beam energy. The magnetic field converges strongly with depth in the corona above loop footpoints. This convergence leads to a small coronal peak in deposited energy followed by a heavy dip caused by the onset of magnetic mirroring. Magnetically reflected electrons carry away 5 to 10% of the injected beam energy on average. The remaining electrons are relatively energetic and produce a peak in deposited energy below the transition region a few hundred kilometres deeper than they would in a uniform magnetic field. A diverging magnetic field at the beginning of the trajectory, which is common in the simulation, enhances the subsequent impact of magnetic mirroring. The other new physical effects do not qualitatively alter the picture of non-thermal energy transport for the atmospheric conditions under consideration.

Improvement of Stable Atmospheric Boundary Simulation with High-Spatiotemporal-Resolution Nudging over the North China Plain

The WRF model often struggles to accurately replicate specific characteristics of the atmospheric boundary layer, particularly under highly stable conditions. In this study, we reconstructed an OBS-nudging module using meteorological data with high spatiotemporal resolution, then coupled it in the WRF model (WRF-OBS) to improve stable boundary layer (SBL) simulation over the North China Plain (NCP). The results showed that WRF-OBS improved the simulation of SBL characteristics and reduced the deviation from observations significantly. The correlations (R2) between WRF-OBS simulations and observations of 2 m temperature, relative humidity, and 10 m wind speed at 460 stations across the NCP were 0.72, 0.56, and 0.75, respectively, which were much higher than the values for results from the unassimilated WRF model (WRF-BS). The simulated vertical profiles of temperature, relative humidity, and wind were generally consistent with observations at Pingyuan station. The meteorological factors which caused heavy air pollution was also investigated based on WRF-OBS simulation. The SBL characteristics obtained from WRF-OBS showed that light wind persisted over the NCP region during the period of heavy pollution, and Pingyuan was affected by warm and humid air. Vertically, the persistent temperature inversion at Pingyuan station was one of the main drivers of the heavy pollution. The WRF-OBS simulation captured the characteristics of the two temperature inversion layers very well. The two inversion layers covered the NCP, with a horizontal scale of approximately 200 km, and created very stable conditions, preventing the vertical diffusion of pollutants and maintaining high PM2.5 concentrations.

Prediction of turbine gas Meter error in high-pressure by CFD techniques: A novel approach to reduce high-pressure calibration (HPC) costs

Calibrating gas meters to their operating conditions are ideal for defining accuracy, but obstacles like economics, time, physical limitations, and a lack of high-pressure calibration facilities often prevent this. A Computational Fluid Dynamics (CFD) model was created using the motion equations simultaneously angular momentum balance in steady state and the standard k-ε turbulence model to improve the prediction of Turbine Gas Meter (TGM) performance at both high-pressure and atmospheric conditions. Utilizing the Multiple Reference Frame (MRF) model, numerical simulations for a 2-inch turbine gas meter (DN 50, G65, and PN/ANSI 150) were conducted, and the proposed model's accuracy was validated by comparing atmospheric calibration simulation results with experimental data, demonstrating a Weighted Mean Error (WME) of −0.162%. According to the performance analysis results, the accuracy of the turbine gas meter deteriorated as pressure increased, and the rotor's maximum rise in angular velocity increased by 12% compared to atmospheric pressure. Additionally, it was discovered that pressure variations had a more significant impact on angular velocity at lower flow rates. Also, it was found that pressure has a considerable effect on gas turbine meter performance up to 50 bar (Re = 2.5 × 106). Angular velocity variations are negligible at more tremendous pressures and can be disregarded. Finally, a correlation for turbine gas meter was developed, which can be used to forecast angular velocity at various pressures and the error percentage compared to atmospheric conditions.

Spatiotemporal Variability of Tropical Cyclone Genesis Density in the Northwest Pacific

Abstract The small sample size of tropical cyclone (TC) genesis in the observations prevents us from fully characterizing its spatiotemporal variations. Here we take advantage of a large ensemble of 60-km-resolution atmospheric simulations to address this issue over the northwest Pacific (NWP) during 1951–2010. The variations in annual TC genesis density are explored separately on interannual and decadal time scales. The interannual variability is dominated by two leading modes. One is characterized by a dipole pattern, and its temporal evolution is closely linked to the developing ENSO. The other mode features high loadings in the central part of the basin, with out-of-phase changes near the equator and date line, and tends to occur during ENSO decay years. On decadal time scales, TC genesis density variability is primarily controlled by one mode, which exhibits an east–west dipole pattern with strong signals confined to south of 20°N and is tied to the interdecadal Pacific oscillation–like sea surface temperature anomalies. Further, we investigate the seasonal evolution of the ENSO effect on TC genesis density. The results highlight the distinct impacts of the two types of ENSO (i.e., eastern Pacific vs central Pacific) on TC genesis density in the NWP during a specific season and show the strong seasonal dependency of the TC genesis response to ENSO. Although the results from the observations are not as prominent as those from the simulations because of the small sample size, the high consistency between them demonstrates the fidelity of the model in reproducing TC statistics and variability in the observations.

A Global Assessment of Heatwaves Since 1850 in Different Observational and Model Data Sets

AbstractWe show that ModE‐Sim, a global ensemble of atmospheric model simulations that uses observed ocean boundary conditions and radiative forcings providing 36 members with daily climate information can be used to in‐depth analyze the known spatial and temporal variability of heatwaves in the Northern Hemisphere and Australia during the past 160 years. It can also be used to study actual past extreme events like heatwaves during the El Nino 1877/1878. To analyze past heatwaves we use a novel approach of a transient baseline climatology and compare to different observational data sets. Furthermore, we analyze sea surface temperature anomalies during the most extreme heatwave summers in North America, Europe and Australia and identify the most prominent anomaly patterns over the Subpolar North Atlantic and in the Central Pacific. Using a large ensemble of forced simulations, like ModE‐Sim can consequently contribute to a better understanding of preindustrial heatwaves, their decadal variability and their driving mechanisms.

The Projected Poleward Shift of Tropical Cyclogenesis at a Global Scale Under Climate Change in MRI‐AGCM3.2H

AbstractFuture climate projections suggest a poleward shift of the maximum intensity of tropical cyclones (TCs) over the western North Pacific. However, the global nature of the latitudinal change in TC genesis under global warming remains poorly understood. We show, using large‐ensemble high‐resolution atmospheric model simulations (d4PDF) with four warming scenarios, that the poleward shift is a robust change over the globe, attributable to the weakening of the Hadley circulation. The weakened ascent driven by the upper‐tropospheric warming suppresses the TC genesis within 5°–20° latitudes, whereas the weakened descent enhances the TC genesis in the poleward latitudes. We further estimate the poleward shift of TC genesis to emerge at the 2 K global warming over the Arabian Sea, South Atlantic and Pacific Oceans and at the 4 K warming over the North Pacific. The present results underscore the potential for increasing social and economic risks associated with TCs at higher latitudes.

Innovative and automated method for vortex identification

Context. Ubiquitous small-scale vortical motions are seen to occur in the solar atmosphere both in simulations and observations. They are thought to play a significant role in the local heating of the quiet chromosphere and corona. In a previous paper, we proposed a new method for the automated identification of vortices based on the accurate estimation of curvature centers; this method was implemented in the SWIRL algorithm. Aims. We aim to assess the applicability of the SWIRL algorithm to self-consistent numerical simulations of the solar atmosphere. The highly turbulent and dynamical solar flow poses a challenge to any vortex-detection method. We also conduct a statistical analysis of the properties and characteristics of photospheric and chromospheric small-scale swirling motions in numerical simulations. Methods. We applied the SWIRL algorithm to realistic, three-dimensional, radiative, magneto-hydrodynamical simulations of the solar atmosphere carried out with the CO5BOLD code. In order to achieve statistical validity, we analyzed 30 time instances of the simulation covering 2 h of physical time. Results. The SWIRL algorithm accurately identified most of the photospheric and chromospheric swirls, which are perceived as spiraling instantaneous streamlines of the horizontal component of the flow. Part of the identified swirls form three-dimensional coherent structures that are generally rooted in magnetically dominated intergranular lanes and extend vertically into the chromospheric layers. From a statistical analysis, we find that the average number densities of swirls in the photosphere and chromosphere are 1 Mm−2 and 4 Mm−2, respectively, while the average radius is 50 − 60 km throughout the simulated atmosphere. We also find an approximately linear correlation between the rotational speed of chromospheric swirls and the local Alfvén speed. We find evidence that more than 80% of the identified, coherent, vortical structures may be Alfvénic in nature. Conclusions. The SWIRL algorithm is a reliable tool for the identification of vortical motions in magnetized, turbulent, and complex astrophysical flows. It can serve to expand our understanding of the nature and properties of swirls in the solar atmosphere. A statistical analysis shows that swirling structures may be smaller, more numerous, and may rotate faster than previously thought, and also suggests a tight relation between swirls and the propagation of Alfvénic waves in the solar atmosphere.

Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation

AbstractParameterization of subgrid‐scale processes is a major source of uncertainty in global atmospheric model simulations. Global storm‐resolving simulations use a finer grid (less than 5 km) to reduce this uncertainty by explicitly resolving deep convection and details of orography. This study uses machine learning to replace the physical parameterizations of heating and moistening rates, but not wind tendencies, in a coarse‐grid (200 km) global atmosphere model, using training data obtained by spatially coarse‐graining a 40‐day realistic geography global storm‐resolving simulation. The training targets are the three‐dimensional fields of effective heating and moistening rates, including the effect of grid‐scale motions that are resolved but imperfectly simulated by the coarse model. A neural network is trained to predict the time‐dependent heating and moistening rates in each grid column using the coarse‐grained temperature, specific humidity, surface turbulent heat fluxes, cosine of solar zenith angle, land‐sea mask and surface geopotential of that grid column as inputs. The coefficient of determination R2 for offline prediction ranges from 0.4 to 0.8 at most vertical levels and latitudes. Online, we achieve stable 35‐day simulations, with metrics of skill such as the time‐mean pattern of near‐surface temperature and precipitation comparable or slightly better than a baseline simulation with conventional physical parameterizations. However, the structure of tropical circulation and relative humidity in the upper troposphere are unrealistic. Overall, this study shows potential for the replacement of human‐designed parameterizations with data‐driven ones in a realistic setting.

Momentum Transport in Organized Shallow Cumulus Convection

Abstract This study investigates momentum transport in shallow cumulus clouds as simulated with the Dutch Atmospheric Large Eddy Simulation (DALES) for a 150 × 150 km2 domain east of Barbados during 9 days of EUREC4A. DALES is initialized and forced with the mesoscale weather model HARMONIE–AROME and subjectively reproduces observed cloud patterns. This study examines the evolution of momentum transport, which scales contribute to it, and how they modulate the trade winds. Daily-mean momentum flux profiles show downgradient zonal momentum transport in the subcloud layer, which turns countergradient in the cloud layer. The meridional momentum transport is nontrivial, with mostly downgradient transport throughout the trade wind layer except near the top of the surface layer and near cloud tops. Substantial spatial and temporal heterogeneity in momentum flux is observed with much stronger tendencies imposed in areas of organized convection. The study finds that while scales < 2 km dominate momentum flux at 200 m in unorganized fields, submesoscales carry up to 50% of the zonal momentum flux in the cloud layer in organized fields. For the meridional momentum flux, this fraction is even larger near the surface and in the subcloud layer. The scale dependence of the momentum flux is not explained by changes in convective or boundary layer depth. Instead, the results suggest the importance of spatial heterogeneity, increasing horizontal length scales, and countergradient transport in the presence of organized convection.

Numerical Performance of Correlated-k Distribution Method in Atmospheric Escape Simulation

Atmospheric escape is crucial to understanding the evolution of planets in and out of the solar system and to interpreting atmospheric observations. While hydrodynamic escape simulations have been actively developed incorporating detailed processes such as UV heating, chemical reactions, and radiative cooling, the radiative cooling by molecules has been treated as emission from selected lines or rotational/vibrational bands to reduce its numerical cost. However, ad hoc selections of radiative lines would risk estimating inaccurate cooling rates because important lines or wavelengths for atmospheric cooling depend on emitting conditions such as temperature and optical thickness. In this study, we apply the correlated-k distribution (CKD) method to cooling rate calculations for H2-dominant transonic atmospheres containing H2O or CO as radiative species, to investigate its numerical performance and the importance of considering all lines of the molecules. Our simulations demonstrate that the sum of weak lines, which provides only 1% of the line emission energy in total at optically thin conditions, can become the primary source of radiative cooling in optically thick regions, especially for H2O-containing atmospheres. Also, in our hydrodynamic simulations, the CKD method with a wavelength resolution of 1000 is found to be effective, allowing the calculation of escape rate and temperature profiles with acceptable numerical cost. Our results show the importance of treating all radiative lines and the usefulness of the CKD method in hydrodynamic escape simulations. It is particularly practical for heavy-element-enriched atmospheres considered in small exoplanets, including super-Earths, without any prior selections for effective lines.

Delayed Onset of Indian Summer Monsoon in Response to CO2 Removal

AbstractUnderstanding the response of the Indian summer monsoon (ISM) onset to CO2 forcing is of utmost importance for rain‐fed agriculture and water management. In this study, we utilized an idealized symmetric CO2 removal scenario from the sixth phase of the Coupled Model Intercomparison Project to analyze the reversibility of monsoon onset. The results show that ISM onset is reversible but exhibits strong asymmetry: it undergoes minimal changes during the ramp‐up phase, but experiences rapid postponement as the CO2 begins to decline; Eventually, it is delayed more than 1 week when the CO2 concentration is restored to the initial level. To investigate the possible underlying mechanisms, we decomposed the climate response to CO2 forcing into the fast and slow processes. Notably, it is the enhanced slow response, which is driven by long‐term sea surface temperature (SST) changes, that dominates the asymmetric response of ISM onset. This slow response delays the ISM onset by strengthening near‐surface poleward land‐sea moist static energy contrast, thereby weakening the lower‐tropospheric monsoonal circulation. Based on the atmospheric component model simulations, we found that both the uniform SST change and patterned SST changes in the slow response contribute to the delay of ISM onset, but the latter plays a dominant role. Our results emphasize the importance of thoroughly assessing regional hydrological cycle features when designing the CO2 removal pathways.

Signal‐to‐noise errors in free‐running atmospheric simulations and their dependence on model resolution

AbstractEnsemble forecasts have been shown to better predict observed Atlantic climate variability than that of their own ensemble members. This phenomenon—termed the signal‐to‐noise paradox—is found to be widespread across models, timescales, and climate variables, and has wide implications. The signal‐to‐noise paradox can be interpreted as forecasts underestimating the amplitude of predictable signals on seasonal‐to‐decadal timescales. The cause of this remains unknown. Here, we examine sea level pressure variability from a very large multi‐model ensemble of uninitialized atmosphere‐only simulations, focusing on boreal winter. To assess signal‐to‐noise errors, the ratio of predictable components (RPC) is examined globally, as well as for regional climate indices: the North Atlantic Oscillation, Arctic Oscillation, Southern Annular Mode, and an Arctic index. Our analyses reveal significant correlations between the multi‐model ensemble‐mean and observations over large portions of the globe, particularly the tropics, North Atlantic, and North Pacific. However, RPC values greater than one are apparent over many extratropical regions and in all four climate indices. Higher‐resolution models produce greater observation‐model correlations and greater RPC values than lower‐resolution models in all four climate indices. We find that signal‐to‐noise errors emerge more clearly at higher resolution, but the amplitudes of predictable signals do not increase with resolution, at least across the range of resolutions considered here. Our results suggest that free‐running atmospheric models underestimate predictable signals in the absence of sea surface temperature biases, implying that signal‐to‐noise errors originate in the atmosphere or in ocean–atmosphere coupling.

Meteorological characteristics of extreme ozone pollution events in China and their future predictions

Abstract. Ozone (O3) has become one of the most concerning air pollutants in China in recent decades. In this study, based on surface observations, reanalysis data, global atmospheric chemistry model simulations, and multi-model future predictions, meteorological characteristics conducive to extreme O3 pollution in various regions of China are investigated, and their historical changes and future trends are analyzed. During the most severe O3 polluted months, the chemical production of O3 is enhanced under the hot and dry conditions over the North China Plain (NCP) in June 2018 and the Yangtze River Delta (YRD) in July 2017, while regional transport is the main reason for the severe O3 pollution over the Sichuan Basin (SCB) in July 2015 and the Pearl River Delta (PRD) in September 2019. Over the last 4 decades, the frequencies of high-temperature and low-relative-humidity conditions increased in 2000–2019 relative to 1980–1999, indicating that O3 pollution in both the NCP and YRD has become more frequent under historical climate change. In the SCB and PRD, the occurrence of atmospheric circulation patterns similar to those during the most polluted months increased, together with the more frequent hot and dry conditions, contributing to the increases in severe O3 pollution in the SCB and PRD during 1980–2019. In the future (by 2100), the frequencies of months with anomalous high temperature show stronger increasing trends in the high-forcing scenario (Shared Socioeconomic Pathway (SSP5-8.5)) compared to the sustainable scenario (SSP1-2.6) in China. It suggests that high anthropogenic forcing will not only lead to slow economic growth and climate warming but also likely result in environmental pollution issues.

A numerical study of ocean surface‐layer response to atmospheric shallow convection: Impact of cloud shading, rain, and cold pools

AbstractThe response of the oceanic surface layer to atmospheric shallow convection is explored using realistic atmospheric large eddy simulations coupled with an oceanic 1D model with high vertical resolution. The effects of cloud shading, rain, and enhanced heat loss due to gust fronts on the edge of cold pools and their interactions are investigated in a case study of the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the Madden–Julian Oscillation experiment in the tropical Indian Ocean, during a suppressed phase of the Madden–Julian Oscillation. Conditions of low surface wind and strong solar heating result in diurnal warming of the oceanic surface of 2 °C over a depth of 1 m. Analysis of specific periods covering the diurnal cycle shows the contrasting effects of cloud shading, rain, and turbulent heat fluxes under the cold pools on the sea temperature at the surface and below. On the one hand, decreasing the solar radiation (cloud shading) results in slight cooling extended horizontally and penetrating down to 1–2 m depth, depending on the time of the day. On the other hand, turbulent heat fluxes enhanced up to 300 Wm by gusts and freshwater lenses due to rain act together and more locally. They isolate and strongly cool a thin inner layer at the surface, which eventually destabilizes the surface layer and propagates the cooling downward. The exact relative part and efficiency of these processes depend on the time evolution of the thermal stratification and vertical turbulent mixing in the oceanic upper layer. Surface cooling of up to 0.5 °C may occur in a few tens of minutes and last for several hours, significantly mitigating the effects of diurnal warming over large extents.

Oceanic Influence and Lapse Rate Changes Dominate the Recent Amplified Saharan Warming

AbstractThe surface air temperature (SAT) over the Sahara Desert has increased at a much faster rate than average tropical land in recent decades. This study examines the relative roles of anthropogenic greenhouse gas (GHG) forcing and sea surface temperature (SST) change in the observed Saharan temperature increase during boreal warm season from 1979 to 2020 using atmospheric general circulation model simulations. It is found that the SST forcing dominates the observed Saharan warming. Further analysis shows that the warming ocean forces the Saharan SAT increase by moving more energy to the Sahara Desert, while the water vapor feedback plays a secondary role. The reason for the stronger Saharan warming than the average tropical land given the same SST forcing is also explored. We found that the largest contributor to the warming contrast is the lapse‐rate feedback, which is attributable to the difference in the vertical warming profile.

Genetic algorithm based three-dimensional shape optimization of rotor blade for a Mars multi-rotor aircraft

In the context of Mars exploration, the Mars multi-rotor aircraft plays a significant role, with its blades being the key components for achieving flight. Due to the thin Martian atmosphere, conventional Earth blades struggle to generate the required thrust for comprehensive aerial missions on the Red Planet. To solve these challenging conditions, there arises a compelling need to refine the rotor’s design, optimizing it to provide sufficient thrust while minimizing power consumption. In this research, a novel method is introduced, combining genetic algorithms and computational fluid dynamics simulations. This approach focuses on enhancing the three-dimensional structure of the rotor blade. The results of this research are verified in experiments conducted within the Martain Atmosphere Simulator, where the blade after optimization demonstrated the ability to achieve the same level of thrust while significantly reducing power consumption. Consequently, this study represents a promising avenue for improving the efficiency of Mars multi-rotor aircraft.

ModE-RA: a global monthly paleo-reanalysis of the modern era 1421 to 2008

The Modern Era Reanalysis (ModE-RA) is a global monthly paleo-reanalysis covering the period between 1421 and 2008. To reconstruct past climate fields an offline data assimilation approach is used, blending together information from an ensemble of transient atmospheric model simulations and observations. In the early period, ModE-RA utilizes natural proxies and documentary data, while from the 17th century onward instrumental measurements are also assimilated. The impact of each observation on the reconstruction is stored in the observation feedback archive, which provides additional information on the input data such as preprocessing steps and the regression-based forward models. The monthly resolved reconstructions include estimates of the most important climate fields. Furthermore, we provide a reconstruction, ModE-RAclim, which together with ModE-RA and the model simulations allows to disentangle the role of observations and model forcings. ModE-RA is best suited to study intra-annual to multi-decadal climate variability and to analyze the causes and mechanisms of past extreme climate events.

Policiklični aromatični ugljovodonici kao limitirajući parametar tradicionalne proizvodnje suhomesnatih proizvoda

The goal of the study was to investigate the concentration of 16 US EPA polycyclic aromatic hydrocarbons (PAHs) and check the sensory properties in 11 dry-cured meat products, smoked in three different ways (atmospheric simulation chamber (ATMOS), industrial chamber and traditional craft smokehouse) in one meat industry facility in Serbia. Controlled industrial production cannot provide all distinguishable and specific sensory properties of traditional dry-cured products, so more and more frequently meat industries decide to include the products smoked in traditional craft smokehouses in their product assortment. 16 US EPA PAHs were determined using a gas chromatography-mass spectrometry method (GC-MS). The obtained results are part of the production technology validating process of the tested smoked meat products. Total concentrations of benzo(a)pyrene, benzo(a)anthracene, benzo(b)fluranthene and chrysene (comprising the so-called "PAH4" group) in traditional homemade smoked bacon produced in compliance with all the guidelines of good manufacturing and hygiene practice, reached 15.82 µg/kg what was above the legal limits set by Serbian legislation. This indicates that there is a need for monitoring the PAH content compounds in traditional smoked meat products, and quite likely the revision of the current rulebook on traditional dry-cured meat products following the EU practice.