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Arctic sea ice is declining at an increasing rate with potentially important repercussions. To understand better the atmospheric changes that may have occurred in response to Arctic sea ice loss, this study presents results from atmospheric general circulation model (AGCM) experiments in which the only time-varying forcings prescribed were observed variations in Arctic sea ice and accompanying changes in Arctic sea surface temperatures from 1979 to 2009. Two independent AGCMs are utilized in order to assess the robustness of the response across different models. The results suggest that the atmospheric impacts of Arctic sea ice loss have been manifested most strongly within the maritime and coastal Arctic and in the lowermost atmosphere. Sea ice loss has driven increased energy transfer from the ocean to the atmosphere, enhanced warming and moistening of the lower troposphere, decreased the strength of the surface temperature inversion, and increased lower-tropospheric thickness; all of these changes are most pronounced in autumn and early winter (September–December). The early winter (November–December) atmospheric circulation response resembles the negative phase of the North Atlantic Oscillation (NAO); however, the NAO-type response is quite weak and is often masked by intrinsic (unforced) atmospheric variability. Some evidence of a late winter (March–April) polar stratospheric cooling response to sea ice loss is also found, which may have important implications for polar stratospheric ozone concentrations. The attribution and quantification of other aspects of the possible atmospheric response are hindered by model sensitivities and large intrinsic variability. The potential remote responses to Arctic sea ice change are currently hard to confirm and remain uncertain.

Purpose of Review Atmospheric blocking events represent some of the most high-impact weather patterns in the mid-latitudes, yet they have often been a cause for concern in future climate projections. There has been low confidence in predicted future changes in blocking, despite relatively good agreement between climate models on a decline in blocking. This is due to the lack of a comprehensive theory of blocking and a pervasive underestimation of blocking occurrence by models. This paper reviews the state of knowledge regarding blocking under climate change, with the aim of providing an overview for those working in related fields. Recent Findings Several avenues have been identified by which blocking can be improved in numerical models, though a fully reliable simulation remains elusive (at least, beyond a few days lead time). Models are therefore starting to provide some useful information on how blocking and its impacts may change in the future, although deeper understanding of the processes at play will be needed to increase confidence in model projections. There are still major uncertainties regarding the processes most important to the onset, maintenance and decay of blocking and advances in our understanding of atmospheric dynamics, for example in the role of diabatic processes, continue to inform the modelling and prediction efforts. Summary The term ‘blocking’ covers a diverse array of synoptic patterns, and hence a bewildering range of indices has been developed to identify events. Results are hence not considered fully trustworthy until they have been found using several different methods. Examples of such robust results are the underestimation of blocking by models, and an overall decline in future occurrence, albeit with a complex regional and seasonal variation. In contrast, hemispheric trends in blocking over the recent historical period are not supported by different methods, and natural variability will likely dominate regional variations over the next few decades.

Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), z/L. However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes.

The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis is the latest global reanalysis dataset of atmospheric composition produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), consisting of three-dimensional time-consistent atmospheric composition fields, including aerosols and chemical species. The dataset currently covers the period 2003–2016 and will be extended in the future by adding 1 year each year. A reanalysis for greenhouse gases is being produced separately. The CAMS reanalysis builds on the experience gained during the production of the earlier Monitoring Atmospheric Composition and Climate (MACC) reanalysis and CAMS interim reanalysis. Satellite retrievals of total column CO; tropospheric column NO2; aerosol optical depth (AOD); and total column, partial column and profile ozone retrievals were assimilated for the CAMS reanalysis with ECMWF's Integrated Forecasting System. The new reanalysis has an increased horizontal resolution of about 80 km and provides more chemical species at a better temporal resolution (3-hourly analysis fields, 3-hourly forecast fields and hourly surface forecast fields) than the previously produced CAMS interim reanalysis. The CAMS reanalysis has smaller biases compared with most of the independent ozone, carbon monoxide, nitrogen dioxide and aerosol optical depth observations used for validation in this paper than the previous two reanalyses and is much improved and more consistent in time, especially compared to the MACC reanalysis. The CAMS reanalysis is a dataset that can be used to compute climatologies, study trends, evaluate models, benchmark other reanalyses or serve as boundary conditions for regional models for past periods.

The mixing layer is an important meteorological factor that affects air pollution. In this study, the atmospheric mixing layer height (MLH) was observed in Beijing from July 2009 to December 2012 using a ceilometer. By comparison with radiosonde data, we found that the ceilometer underestimates the MLH under conditions of neutral stratification caused by strong winds, whereas it overestimates the MLH when sand-dust is crossing. Using meteorological, PM2.5, and PM10 observational data, we screened the observed MLH automatically; the ceilometer observations were fairly consistent with the radiosondes, with a correlation coefficient greater than 0.9. Further analysis indicated that the MLH is low in autumn and winter and high in spring and summer in Beijing. There is a significant correlation between the sensible heat flux and MLH, and the diurnal cycle of the MLH in summer is also affected by the circulation of mountainous plain winds. Using visibility as an index to classify the degree of air pollution, we found that the variation in the sensible heat and buoyancy term in turbulent kinetic energy (TKE) is insignificant when visibility decreases from 10 to 5 km, but the reduction of shear term in TKE is near 70 %. When visibility decreases from 5 to 1 km, the variation of the shear term in TKE is insignificant, but the decrease in the sensible heat and buoyancy term in TKE is approximately 60 %. Although the correlation between the daily variation of the MLH and visibility is very poor, the correlation between them is significantly enhanced when the relative humidity increases beyond 80 %. This indicates that humidity-related physicochemical processes is the primary source of atmospheric particles under heavy pollution and that the dissipation of atmospheric particles mainly depends on the MLH. The presented results of the atmospheric mixing layer provide useful empirical information for improving meteorological and atmospheric chemistry models and the forecasting and warning of air pollution.

Mercury (Hg) is emitted to the atmosphere mainly as volatile elemental Hg0. Oxidation to water-soluble HgII plays a major role in Hg deposition to ecosystems. Here, we implement a new mechanism for atmospheric Hg0 ∕ HgII redox chemistry in the GEOS-Chem global model and examine the implications for the global atmospheric Hg budget and deposition patterns. Our simulation includes a new coupling of GEOS-Chem to an ocean general circulation model (MITgcm), enabling a global 3-D representation of atmosphere–ocean Hg0 ∕ HgII cycling. We find that atomic bromine (Br) of marine organobromine origin is the main atmospheric Hg0 oxidant and that second-stage HgBr oxidation is mainly by the NO2 and HO2 radicals. The resulting chemical lifetime of tropospheric Hg0 against oxidation is 2.7 months, shorter than in previous models. Fast HgII atmospheric reduction must occur in order to match the  ∼  6-month lifetime of Hg against deposition implied by the observed atmospheric variability of total gaseous mercury (TGM  ≡  Hg0 + HgII(g)). We implement this reduction in GEOS-Chem as photolysis of aqueous-phase HgII–organic complexes in aerosols and clouds, resulting in a TGM lifetime of 5.2 months against deposition and matching both mean observed TGM and its variability. Model sensitivity analysis shows that the interhemispheric gradient of TGM, previously used to infer a longer Hg lifetime against deposition, is misleading because Southern Hemisphere Hg mainly originates from oceanic emissions rather than transport from the Northern Hemisphere. The model reproduces the observed seasonal TGM variation at northern midlatitudes (maximum in February, minimum in September) driven by chemistry and oceanic evasion, but it does not reproduce the lack of seasonality observed at southern hemispheric marine sites. Aircraft observations in the lowermost stratosphere show a strong TGM–ozone relationship indicative of fast Hg0 oxidation, but we show that this relationship provides only a weak test of Hg chemistry because it is also influenced by mixing. The model reproduces observed Hg wet deposition fluxes over North America, Europe, and China with little bias (0–30 %). It reproduces qualitatively the observed maximum in US deposition around the Gulf of Mexico, reflecting a combination of deep convection and availability of NO2 and HO2 radicals for second-stage HgBr oxidation. However, the magnitude of this maximum is underestimated. The relatively low observed Hg wet deposition over rural China is attributed to fast HgII reduction in the presence of high organic aerosol concentrations. We find that 80 % of HgII deposition is to the global oceans, reflecting the marine origin of Br and low concentrations of organic aerosols for HgII reduction. Most of that deposition takes place to the tropical oceans due to the availability of HO2 and NO2 for second-stage HgBr oxidation.

NOAA’s National Centers for Environmental Prediction (NCEP) Production Suite (NPS) currently includes over 20 operational weather forecast systems, providing forecasts from the mesoscale to global seasonal outlooks. In an effort to optimize resources, the NPS is being simplified to far fewer systems within the Unified Forecast System (UFS) framework that nevertheless span NOAA’s weather prediction mission: short-range regional and atmospheric composition (RRFS, WoF), medium-range subseasonal (GEFS) to seasonal (SFS), marine and coastal (GFS, GEFS, NWPS, GLWU), hurricanes (HAFS), on-demand atmospheric dispersion (HySPLIT), hydrology (NWM), and space weather (WAM/IPE) (see appendix for a full list of abbreviation definitions). An international constellation of low-Earth-orbit and geosynchronous-equatorial-orbit satellites are expanding our Earth intelligence; for example, polar-orbiting satellites now provide 85% of the data used in global weather models. In addition to the advancement of DA research, the Joint Effort for Data assimilation Integration (JEDI), operated by the UCAR Joint Center for Satellite Data Assimilation (JCSDA), provides a common software infrastructure for full community engagement in the testing, research, and development of new observations and DA methods.

The present work aims at better understanding regional climate–aerosol interactions by studying the relationships between aerosols and synoptic atmospheric circulation over the Euro-Mediterranean region. Two 40-year simulations (1979–2018) have been carried out with version 6.3 of the Centre National de Recherches Météorologiques (National Centre for Meteorological Research) – Aire Limitée Adaptation dynamique Développement InterNational (CNRM-ALADIN) regional climate model, one using interactive aerosols and the other one without any aerosol. The simulation with aerosols has been evaluated in terms of different climate and aerosol parameters. This evaluation shows a good agreement between the model and observations, significant improvements compared to the previous model version and consequently the relevance of using this model for the study of climate–aerosol interactions over this region. A first attempt to explain the climate variability of aerosols is based on the use of the North Atlantic Oscillation (NAO) index. The latter explains a significant part of the interannual variability, notably in winter for the export of dust aerosols over the Atlantic Ocean and the eastern Mediterranean, and in summer for the positive anomalies of anthropogenic aerosols over western Europe. This index is however not sufficient to fully understand the variations of aerosols in this region, notably at daily scale. The use of “weather regimes”, namely persisting meteorological patterns, stable at synoptic scale for a few days, provides a relevant description of atmospheric circulation, which drives the emission, transport and deposition of aerosols. The four weather regimes usually defined in this area in winter and in summer bring significant information to answer this question. The blocking and NAO+ regimes are largely favourable to strong aerosol effects on shortwave surface radiation and near-surface temperature, either because of higher aerosol loads or because of weaker cloud fraction, which reinforces the direct aerosol effect. Inversely, the NAO− and Atlantic Ridge regimes are unfavourable to aerosol radiative effects, because of weaker aerosol concentrations and increased cloud cover. This study thus puts forward the strong dependence of aerosol loads on the synoptic circulation from interannual to daily scales and, as a consequence, the important modulation of the aerosol effects on shortwave surface radiation and near-surface temperature by atmospheric circulation. The role of cloud cover is essential in this modulation as shown by the use of weather regimes.

The literature on atmospheric particulate matter (PM), or atmospheric aerosol, has increased enormously over the last 2 decades and amounts now to some 1500–2000 papers per year in the refereed literature. This is in part due to the enormous advances in measurement technologies, which have allowed for an increasingly accurate understanding of the chemical composition and of the physical properties of atmospheric particles and of their processes in the atmosphere. The growing scientific interest in atmospheric aerosol particles is due to their high importance for environmental policy. In fact, particulate matter constitutes one of the most challenging problems both for air quality and for climate change policies. In this context, this paper reviews the most recent results within the atmospheric aerosol sciences and the policy needs, which have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate–aerosol interactions and effects of PM on human health and the environment. However, while airborne particulate matter is responsible for globally important influences on premature human mortality, we still do not know the relative importance of the different chemical components of PM for these effects. Likewise, the magnitude of the overall effects of PM on climate remains highly uncertain. Despite the uncertainty there are many things that could be done to mitigate local and global problems of atmospheric PM. Recent analyses have shown that reducing black carbon (BC) emissions, using known control measures, would reduce global warming and delay the time when anthropogenic effects on global temperature would exceed 2 °C. Likewise, cost-effective control measures on ammonia, an important agricultural precursor gas for secondary inorganic aerosols (SIA), would reduce regional eutrophication and PM concentrations in large areas of Europe, China and the USA. Thus, there is much that could be done to reduce the effects of atmospheric PM on the climate and the health of the environment and the human population. A prioritized list of actions to mitigate the full range of effects of PM is currently undeliverable due to shortcomings in the knowledge of aerosol science; among the shortcomings, the roles of PM in global climate and the relative roles of different PM precursor sources and their response to climate and land use change over the remaining decades of this century are prominent. In any case, the evidence from this paper strongly advocates for an integrated approach to air quality and climate policies.

Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990-2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g. 1 to 3 percent per year in aerosols over the USA and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990-2015 period increased by 0.17 plus or minus 0.08 watts per square meter, with approximately one-third due to ozone. This increase is more strongly positive than that reported in IPCC AR5 (Intergovernmental Panel on Climate Change Fifth Assessment Report). The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions.