ALBERT

Beschreibung: Atmospheric variability as a function of scale has been divided in various dynamical regimes with alternating increasing and decreasing fluctuations: weather, macroweather, climate, macroclimate, and megaclimate. Although a vast amount of data are available at small scales, the larger picture is not well constrained due to the scarcity and low resolution of long paleoclimatic time series. Using statistical techniques originally developed for the study of turbulence, we analyse the fluctuations of a centimetric-resolution dust flux time series from the EPICA Dome C ice core in Antarctica that spans the past 800 000 years. The temporal resolution ranges from annual at the top of the core to 25 years at the bottom, enabling the detailed statistical analysis and comparison of eight glaciation cycles and the subdivision of each cycle into eight consecutive phases. The unique span and resolution of the dataset allows us to analyse the macroweather and climate scales in detail. We find that the interglacial and glacial maximum phases of each cycle showed particularly large macroweather to climate transition scale τc (around 2 kyr), whereas mid-glacial phases feature centennial transition scales (average of 300 years). This suggests that interglacials and glacial maxima are exceptionally stable when compared with the rest of a glacial cycle. The Holocene (with τc≈7.9 kyr) had a particularly large τc, but it was not an outlier when compared with the phases 1 and 2 of other cycles. We hypothesize that dust variability at larger (climate) scales appears to be predominantly driven by slow changes in glaciers and vegetation cover, whereas at small (macroweather) scales atmospheric processes and changes in the hydrological cycles are the main drivers. For each phase, we quantified the drift, intermittency, amplitude, and extremeness of the variability. Phases close to the interglacials (1, 2, 8) show low drift, moderate intermittency, and strong extremes, while the “glacial” middle phases 3–7 display strong drift, weak intermittency, and weaker extremes. In other words, our results suggest that glacial maxima, interglacials, and glacial inceptions were characterized by relatively stable atmospheric conditions but punctuated by frequent and severe droughts, whereas the mid-glacial climate was inherently more unstable.

Beschreibung: Atmospheric ozone plays a key role in air quality and the radiation budget of the Earth, both directly and through its chemical influence on other trace gases. Assessments of the atmospheric ozone distribution and associated climate change therefore demand accurate vertically resolved ozone observations with both stratospheric and tropospheric sensitivity, on both global and regional scales, and both in the long term and at shorter timescales. Such observations have been acquired by two series of European nadir-viewing ozone profilers, namely the scattered-light UV–visible spectrometers of the GOME family, launched regularly since 1995 (GOME, SCIAMACHY, OMI, GOME-2A/B, TROPOMI, and the upcoming Sentinel-5 series), and the thermal infrared emission sounders of the IASI type, launched regularly since 2006 (IASI on Metop platforms and the upcoming IASI-NG on Metop-SG). In particular, several Level-2 retrieved, Level-3 monthly gridded, and Level-4 assimilated nadir ozone profile data products have been improved and harmonized in the context of the ozone project of the European Space Agency's Climate Change Initiative (ESA Ozone_cci). To verify their fitness for purpose, these ozone datasets must undergo a comprehensive quality assessment (QA), including (a) detailed identification of their geographical, vertical, and temporal domains of validity; (b) quantification of their potential bias, noise, and drift and their dependences on major influence quantities; and (c) assessment of the mutual consistency of data from different sounders. For this purpose we have applied to the Ozone_cci Climate Research Data Package (CRDP) released in 2017 the versatile QA and validation system Multi-TASTE, which has been developed in the context of several heritage projects (ESA's Multi-TASTE, EUMETSAT's O3M-SAF, and the European Commission's FP6 GEOmon and FP7 QA4ECV). This work, as the second in a series of four Ozone_cci validation papers, reports for the first time on data content studies, information content studies and ground-based validation for both the GOME- and IASI-type climate data records combined. The ground-based reference measurements have been provided by the Network for the Detection of Atmospheric Composition Change (NDACC), NASA's Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other ozonesonde and lidar stations contributing to the World Meteorological Organisation's Global Atmosphere Watch (WMO GAW). The nadir ozone profile CRDP quality assessment reveals that all nadir ozone profile products under study fulfil the GCOS user requirements in terms of observation frequency and horizontal and vertical resolution. Yet all L2 observations also show sensitivity outliers in the UTLS and are strongly correlated vertically due to substantial averaging kernel fluctuations that extend far beyond the kernel's 15 km FWHM. The CRDP typically does not comply with the GCOS user requirements in terms of total uncertainty and decadal drift, except for the UV–visible L4 dataset. The drift values of the L2 GOME and OMI, the L3 IASI, and the L4 assimilated products are found to be overall insignificant, however, and applying appropriate altitude-dependent bias and drift corrections make the data fit for climate and atmospheric composition monitoring and modelling purposes. Dependence of the Ozone_cci data quality on major influence quantities – resulting in data screening suggestions to users – and perspectives for the Copernicus Sentinel missions are additionally discussed.

Beschreibung: The inhabitants of Santiago, Chile have been exposed to harmful levels of air pollutants for decades. The city's poor air quality is a result of steady economic growth, and stable atmospheric conditions adverse to mixing and ventilation that favor the formation of oxidants and secondary aerosols. Identifying and quantifying the sources that contribute to the ambient levels of pollutants is key for designing adequate mitigation measures. Estimating the evolution of source contributions to ambient pollution levels is also paramount to evaluating the effectiveness of pollution reduction measures that have been implemented in recent decades. Here, we quantify the main sources that have contributed to fine particulate matter (PM2. 5) between April 1998 and August 2012 in downtown Santiago by using two different source-receptor models (PMF 5.0 and UNMIX 6.0) that were applied to elemental measurements of 1243 24 h filter samples of ambient PM2.5. PMF resolved six sources that contributed to ambient PM2. 5, with UNMIX producing similar results: motor vehicles (37.3 ± 1.1 %), industrial sources (18.5 ± 1.3 %), copper smelters (14.4 ± 0.8 %), wood burning (12.3 ± 1.0 %), coastal sources (9.5 ± 0.7 %) and urban dust (3.0 ± 1.2 %). Our results show that over the 15 years analyzed here, four of the resolved sources significantly decreased [95 % confidence interval]: motor vehicles 21.3 % [2.6, 36.5], industrial sources 39.3 % [28.6, 48.4], copper smelters 81.5 % [75.5, 85.9], and coastal sources 58.9 % [38.5, 72.5], while wood burning did not significantly change and urban dust increased by 72 % [48.9, 99.9]. These changes are consistent with emission reduction measures, such as improved vehicle emission standards, cleaner smelting technology, introduction of low-sulfur diesel for vehicles and natural gas for industrial processes, public transport improvements, etc. However, it is also apparent that the mitigation expected from the above regulations has been partially offset by the increasing amount of private vehicle use in the city, with motor vehicles becoming the dominant source of ambient PM2. 5 in recent years. Consequently, Santiago still experiences ambient PM2. 5 levels above the annual and 24 h Chilean and World Health Organization standards, and further regulations are required to reach ambient air quality standards.

Beschreibung: We investigate the accuracy and precision of polar lower stratospheric temperatures (100–10 hPa during 2008–2013) reported in several contemporary reanalysis datasets comprising two versions of the Modern-Era Retrospective analysis for Research and Applications (MERRA and MERRA-2), the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-I), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (NCEP-CFSR). We also include the Goddard Earth Observing System model version 5.9.1 near-real-time analysis (GEOS-5.9.1). Comparisons of these datasets are made with respect to retrieved temperatures from the Aura Microwave Limb Sounder (MLS), Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Global Positioning System (GPS) radio occultation (RO) temperatures, and independent absolute temperature references defined by the equilibrium thermodynamics of supercooled ternary solutions (STSs) and ice clouds. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of polar stratospheric clouds are used to determine the cloud particle types within the Aura MLS geometric field of view. The thermodynamic calculations for STS and the ice frost point use the colocated MLS gas-phase measurements of HNO3 and H2O. The estimated bias and precision for the STS temperature reference, over the 68 to 21 hPa pressure range, are 0.6–1.5 and 0.3–0.6 K, respectively; for the ice temperature reference, they are 0.4 and 0.3 K, respectively. These uncertainties are smaller than those estimated for the retrieved MLS temperatures and also comparable to GPS RO uncertainties (bias    0.7 K) in the same pressure range. We examine a case study of the time-varying temperature structure associated with layered ice clouds formed by orographic gravity waves forced by flow over the Palmer Peninsula and compare how the wave amplitudes are reproduced by each reanalysis dataset. We find that the spatial and temporal distribution of temperatures below the ice frost point, and hence the potential to form ice polar stratospheric clouds (PSCs) in model studies driven by the reanalyses, varies significantly because of the underlying differences in the representation of mountain wave activity. High-accuracy COSMIC temperatures are used as a common reference to intercompare the reanalysis temperatures. Over the 68–21 hPa pressure range, the biases of the reanalyses with respect to COSMIC temperatures for both polar regions fall within the narrow range of −0.6 K to +0.5 K. GEOS-5.9.1, MERRA, MERRA-2, and JRA-55 have predominantly cold biases, whereas ERA-I has a predominantly warm bias. NCEP-CFSR has a warm bias in the Arctic but becomes substantially colder in the Antarctic. Reanalysis temperatures are also compared with the PSC reference temperatures. Over the 68–21 hPa pressure range, the reanalysis temperature biases are in the range −1.6 to −0.3 K with standard deviations  ∼  0.6 K for the CALIOP STS reference, and in the range −0.9 to +0.1 K with standard deviations  ∼  0.7 K for the CALIOP ice reference. Comparisons of MLS temperatures with the PSC reference temperatures reveal vertical oscillations in the MLS temperatures and a significant low bias in MLS temperatures of up to 3 K.

Beschreibung: The representation of upper tropospheric–lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution – for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry–climate models.

Beschreibung: The Network for the Detection of Atmospheric Composition Change (NDACC) is an international global network of more than 90 stations making high-quality measurements of atmospheric composition that began official operations in 1991 after 5 years of planning. Apart from sonde measurements, all measurements in the network are performed by ground-based remote-sensing techniques. Originally named the Network for the Detection of Stratospheric Change (NDSC), the name of the network was changed to NDACC in 2005 to better reflect the expanded scope of its measurements. The primary goal of NDACC is to establish long-term databases for detecting changes and trends in the chemical and physical state of the atmosphere (mesosphere, stratosphere, and troposphere) and to assess the coupling of such changes with climate and air quality. NDACC's origins, station locations, organizational structure, and data archiving are described. NDACC is structured around categories of ground-based observational techniques (sonde, lidar, microwave radiometers, Fourier-transform infrared, UV-visible DOAS (differential optical absorption spectroscopy)-type, and Dobson–Brewer spectrometers, as well as spectral UV radiometers), timely cross-cutting themes (ozone, water vapour, measurement strategies, cross-network data integration), satellite measurement systems, and theory and analyses. Participation in NDACC requires compliance with strict measurement and data protocols to ensure that the network data are of high and consistent quality. To widen its scope, NDACC has established formal collaborative agreements with eight other cooperating networks and Global Atmosphere Watch (GAW). A brief history is provided, major accomplishments of NDACC during its first 25 years of operation are reviewed, and a forward-looking perspective is presented.

Beschreibung: We compare simulations from three high-top (with upper lid above 120 km) and five medium-top (with upper lid around 80 km) atmospheric models with observations of odd nitrogen (NOx  =  NO + NO2), temperature, and carbon monoxide from seven satellite instruments (ACE-FTS on SciSat, GOMOS, MIPAS, and SCIAMACHY on Envisat, MLS on Aura, SABER on TIMED, and SMR on Odin) during the Northern Hemisphere (NH) polar winter 2008/2009. The models included in the comparison are the 3-D chemistry transport model 3dCTM, the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model, FinROSE, the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA), the modelling tools for SOlar Climate Ozone Links studies (SOCOL and CAO-SOCOL), and the Whole Atmosphere Community Climate Model (WACCM4). The comparison focuses on the energetic particle precipitation (EPP) indirect effect, that is, the polar winter descent of NOx largely produced by EPP in the mesosphere and lower thermosphere. A particular emphasis is given to the impact of the sudden stratospheric warming (SSW) in January 2009 and the subsequent elevated stratopause (ES) event associated with enhanced descent of mesospheric air. The chemistry climate model simulations have been nudged toward reanalysis data in the troposphere and stratosphere while being unconstrained above. An odd nitrogen upper boundary condition obtained from MIPAS observations has further been applied to medium-top models. Most models provide a good representation of the mesospheric tracer descent in general, and the EPP indirect effect in particular, during the unperturbed (pre-SSW) period of the NH winter 2008/2009. The observed NOx descent into the lower mesosphere and stratosphere is generally reproduced within 20 %. Larger discrepancies of a few model simulations could be traced back either to the impact of the models' gravity wave drag scheme on the polar wintertime meridional circulation or to a combination of prescribed NOx mixing ratio at the uppermost model layer and low vertical resolution. In March–April, after the ES event, however, modelled mesospheric and stratospheric NOx distributions deviate significantly from the observations. The too-fast and early downward propagation of the NOx tongue, encountered in most simulations, coincides with a temperature high bias in the lower mesosphere (0.2–0.05 hPa), likely caused by an overestimation of descent velocities. In contrast, upper-mesospheric temperatures (at 0.05–0.001 hPa) are generally underestimated by the high-top models after the onset of the ES event, being indicative for too-slow descent and hence too-low NOx fluxes. As a consequence, the magnitude of the simulated NOx tongue is generally underestimated by these models. Descending NOx amounts simulated with medium-top models are on average closer to the observations but show a large spread of up to several hundred percent. This is primarily attributed to the different vertical model domains in which the NOx upper boundary condition is applied. In general, the intercomparison demonstrates the ability of state-of-the-art atmospheric models to reproduce the EPP indirect effect in dynamically and geomagnetically quiescent NH winter conditions. The encountered differences between observed and simulated NOx, CO, and temperature distributions during the perturbed phase of the 2009 NH winter, however, emphasize the need for model improvements in the dynamical representation of elevated stratopause events in order to allow for a better description of the EPP indirect effect under these particular conditions.

Beschreibung: The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a level-3 data record, which combines individual sensor products into one single cohesive record covering the 22-year period from 1995 to 2016, generated in the frame of the European Space Agency's Climate Change Initiative Phase II. It is based on level-2 total ozone data produced by the GODFIT (GOME-type Direct FITting) v4 algorithm as applied to the GOME/ERS-2, OMI/Aura, SCIAMACHY/Envisat and GOME-2/Metop-A and Metop-B observations. In this paper we examine whether GTO-ECV meets the specific requirements set by the international climate–chemistry modelling community for decadal stability long-term and short-term accuracy. In the following, we present the validation of the 2017 release of the Climate Research Data Package Total Ozone Column (CRDP TOC) at both level 2 and level 3. The inter-sensor consistency of the individual level-2 data sets has mean differences generally within 0.5 % at moderate latitudes (±50°), whereas the level-3 data sets show mean differences with respect to the OMI reference data record that span between −0.2 ± 0.9 % (for GOME-2B) and 1.0 ± 1.4 % (for SCIAMACHY). Very similar findings are reported for the level-2 validation against independent ground-based TOC observations reported by Brewer, Dobson and SAOZ instruments: the mean bias between GODFIT v4 satellite TOC and the ground instrument is well within 1.0 ± 1.0 % for all sensors, the drift per decade spans between −0.5 % and 1.0 ± 1.0 % depending on the sensor, and the peak-to-peak seasonality of the differences ranges from ∼ 1 % for GOME and OMI to  ∼ 2 % for SCIAMACHY. For the level-3 validation, our first goal was to show that the level-3 CRDP produces findings consistent with the level-2 individual sensor comparisons. We show a very good agreement with 0.5 to 2 % peak-to-peak amplitude for the monthly mean difference time series and a negligible drift per decade of the differences in the Northern Hemisphere of −0.11 ± 0.10 % decade−1 for Dobson and +0.22 ± 0.08 % decade−1 for Brewer collocations. The exceptional quality of the level-3 GTO-ECV v3 TOC record temporal stability satisfies well the requirements for the total ozone measurement decadal stability of 1–3 % and the short-term and long-term accuracy requirements of 2 and 3 %, respectively, showing a remarkable inter-sensor consistency, both in the level-2 GODFIT v4 and in the level-3 GTO-ECV v3 datasets, and thus can be used for longer-term analysis of the ozone layer, such as decadal trend studies, chemistry–climate model evaluation and data assimilation applications.

Beschreibung: Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1°  ×  1° TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995–2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40 % over polluted scenes. The first validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (−2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

Beschreibung: The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This paper summarizes the motivation and goals of the S-RIP activity and extensively reviews key technical aspects of the reanalysis data sets that are the focus of this activity. The special issue The SPARC Reanalysis Intercomparison Project (S-RIP) in this journal serves to collect research with relevance to the S-RIP in preparation for the publication of the planned two (interim and full) S-RIP reports.