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Aerosol–cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, in which cloud droplet number concentration (Nd) sensitivity to aerosol (S) is a key term for the overall estimation. However, satellite-based estimates of S are especially challenging, mainly due to the difficulty in disentangling aerosol effects on Nd from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of (a) updraft, (b) precipitation, (c) retrieval errors, and (d) vertical co-location between aerosol and cloud on the assessment of S in the context of marine warm (liquid) clouds. Our analysis suggests that S increases remarkably with both cloud-base height and cloud geometric thickness (proxies for vertical velocity at cloud base), consistent with stronger aerosol–cloud interactions at larger updraft velocity for midlatitude and low-latitude clouds. In turn, introducing the confounding effect of aerosol–precipitation interaction can artificially amplify S by an estimated 21 %, highlighting the necessity of removing precipitating clouds from analyses of S. It is noted that the retrieval biases in aerosol and cloud appear to underestimate S, in which cloud fraction acts as a key modulator, making it practically difficult to balance the accuracies of aerosol–cloud retrievals at aggregate scales (e.g., 1∘×1∘ grid). Moreover, we show that using column-integrated sulfate mass concentration (SO4C) to approximate sulfate concentration at cloud base (SO4B) can result in a degradation of correlation with Nd, along with a nearly twofold enhancement of S, mostly attributed to the inability of SO4C to capture the full spatiotemporal variability of SO4B. These findings point to several potential ways forward to practically account for the major influential factors by means of satellite observations and reanalysis, aiming at optimal observational estimates of global radiative forcings due to the Twomey effect and also cloud adjustments.

The marine stratocumulus clouds are highly sensitive to aerosol perturbations. In this study, we have explored the cloud susceptibility to aerosol using satellite observation and multi-model simulations over the Southeast Pacific Ocean (SEP). The climatology of satellite observation indicates that SEP is a relatively clean area with low aerosol optical depth (AOD). The SEP is a region of marine stratocumulus deck with cloud fraction (CF) reaching as high as 90% in many regions, with relatively low (140 cm−3) cloud droplet number concentration (CDNC) over the marine environment, and it increases as it moves towards the coast. The joint histogram analysis shows that the AOD-CDNC relation shows positive sensitivity and a non-linear CDNC-LWP (liquid water path) relationship; however, a negative sensitivity is dominant. The multimodel analysis shows that most models have a strong positive AOD-CDNC sensitivity, suggesting that the cloud albedo effect leads to net cooling. The general circulation models (GCM) reveal a negative radiative forcing (-0.28 to -1.36Wm−2) at the top of the atmosphere (TOA) when using the flux method. It supports the positive AODCDNC sensitivity and the resulting negative radiative forcing in GCMs. However, the CDNC-LWP shows a diverse relation in the models. In the GCMs, the effect of cloud microphysics is not considered while estimating the net radiative forcing. To include the effect of cloud microphysics in the radiative forcing estimates, we have proposed a statistical approach to calculate the net radiative forcing. The results show that the net radiative forcing is sensitive to the LWP change due to the aerosol perturbation. Die marinen Stratocumulus-Wolken reagieren sehr empfindlich auf Aerosol-Störungen. In dieser Studie haben wir die Anfälligkeit der Wolken für Aerosol anhand von Satellitenbeobachtungen und Multi-Modellsimulationen über dem Südostpazifik (SEP) untersucht. Die Klimatologie der Satellitenbeobachtung zeigt, dass der SEP ein relativ sauberes Gebiet mit geringer Aerosol optischer Dicke (AOD) ist. Der SEP ist eine Region mit mariner Stratocumulus-Decke mit einer Wolkbedeckungsgrad (CF), der in vielen Regionen bis zu 90% erreicht, mit einer relativ niedrigen (140 cm−3) Wolkentröpfchenanzahlkonzentration (CDNC) über der marinen Umgebung, und sie nimmt in Richtung Küste zu. Die gemeinsame Histogramm-Analyse zeigt, dass die AOD-CDNC-Beziehung eine positive Sensitivität und eine nicht-lineare CDNC-LWP-Beziehung (Flüssigwasserpfad) aufweist; allerdings ist eine negative Sensitivität vorherrschend. Die Multi-Modellanalyse zeigt, dass die meisten Modelle eine stark positive AOD-CDNC-Empfindlichkeit aufweisen, was darauf hindeutet, dass der Wolkenalbedo-Effekt eine Nettokühlung bewirkt. Die allgemeinen Zirkulationsmodelle (GCM) zeigen einen negativen Strahlungsantrieb (-0,28 bis -1,36Wm−2) am Oberrand der Atmosphäre (TOA), wenn die Flussmethode verwendet wird. Dies unterstützt die positive AOD-CDNC-Empfindlichkeit und den daraus resultierenden negativen Strahlungsantrieb in GCMs. Der CDNC-LWP zeigt jedoch unterschiedliche Abhängigkeiten in den Modellen. In den GCMs wird die Wirkung der Wolkenmikrophysik bei der Abschätzung des Netto-Strahlungsantriebs nicht berücksichtigt. Um die Auswirkungen der Wolkenmikrophysik auf den Strahlungsantrieb einzubeziehen, haben wir einen statistischen Ansatz zur Berechnung des Nettostrahlungsantriebs gewählt. Die Ergebnisse zeigen, dass der Nettostrahlungsantrieb empfindlich auf die LWP-Änderung durch die Aerosolstörung reagiert.

The thermosphere-ionosphere regions are mainly controlled by the solar, but also by geomagnetic activity. In this case study, the Earth’s ionospheric response to the 25-26 August 2018 intense geomagnetic storm is investigated using the International GNSS System (IGS) Total Electron Content (TEC) observations. During this major storm, the minimum disturbance storm time (Dst) index reached -174 nT. We use observations and model simulations to analyse the ionospheric response during the initial phase and the main phase of the magnetic storm. A significant difference between storm day and quiet day TEC is observed. The O/N2 ratio observed from the GUVI instrument onboard the TIMED satellite is used to analyse the storm effect. The result shows a clear depletion of the O/N2 ratio in the high latitude region, and an enhancement in the low latitude region during the main phase of the storm. Furthermore, the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model simulations were used. The results suggest that the CTIPe model can capture the ionospheric variations during storms. Die Regionen der Ionosphären und Thermosphäre werden hauptsächlich von der Sonne sowie auch von geomagnetische Aktivität beeinflusst. In dieser Fallstudie wurde die ionosphärische Reaktion der Erde auf den starken geomagnetischen Sturm vom 25./26. August 2018 unter Verwendung der Gesamtelektronengehaltsdaten (Total Electron Content, TEC) vom Internationalen GNSS Service untersucht. Während dieses großen Sturms wurde ein ”Disturbance Storm Time Index” Dst von -174 nT erreicht. Beobachtungen und Modellsimulationen wurden verwendet, um die ionosphärische Reaktion während der Anfangsphase und der Hauptphase des magnetischen Sturms zu untersuchen. Ein signifikanter Unterschied zwischen TEC während eines Sturmtages und eines ruhigen Tages wurde beobachtet. Das vom GUVI-Instrument an Bord des TIMED-Satelliten beobachtete O/N2 -Verhältnis wurde verwendet, um den Sturmeffekt weiter zu untersuchen. Das Ergebnis zeigt eine deutliche Abnahme/Zunahme des O/N2 Verhältnis in hohen/niedrigen Breiten während der Hauptphase des Sturms. Darüber hinaus wurde das Coupled Thermosphere Ionosphere Plasmasphere ectrodynamics (CTIPe) Modell verwendet. Die Ergebnisse legen nahe, dass das CTIPe-Modell die ionosphärischen Schwankungen während eines Sturms erfassen kann.

A new German research consortium is investigating the causes and effects of the rapid rise of near-surface air temperatures in the Artic. Within the last 25 years a remarkable increase of the Arctic near-surface air temperature exceeding the global warming by a factor of two to three has been observed. The phenomenon is commonly referred to as Arctic Amplification. The warming results in rather drastic changes of a variety of climate parameters. For example, the Arctic sea ice has declined significantly. This ice retreat has been well identified by satellite measurements. However, coupled regional and global climate models still fail to reproduce it adequately; they tend to systematically underestimate the observed sea ice decline. This model observation difference implies that the underlying physical processes and feedback mechanisms are not appropriately represented in Arctic climate models. Thus, the predictions of these models are also likely to be inadequate. It is mandatory to identify the origin of this disagreement. Ein neu geschaffenes deutsches Forschungskonsortium untersucht die Ursachen und Effekte des rapiden Anstiegs der bodennahen Lufttemperatur in der Arktis. Innerhalb der letzten 25 Jahre wurde ein bemerkenswerter Anstieg der Bodenlufttemperatur in der Arktis beobachtet, welcher die globale Erwärmung um den Faktor 2 bis 3 übersteigt. Dieses Phänomen wird als arktische Verstärkung bezeichnet. Diese Erwärmung resultiert vielmehr in einer drastischen Änderung einer Vielzahl von Klimarparametern. Beispielsweise ist das arktische Meereis deutlich zurückgegangen. Dieser Eisrückgang wurde durch Satellitenbeobachtungen gut beobachtet. Dagegen haben regionale und globale Klimamodelle immer noch Probleme, den Rückgang entsprechend zu reproduzieren. Sie tendieren dazu, den Meereisrückgang systematisch zu unterschätzen. Die Unterschiede zwischen Modell und Beobachtungen legen nahe, dass die grundlegenden physikalischen Prozesse und Rückkopplungsmechanismen nicht entsprechend in arktischen Klimamodellen repräsentiert werden. Somit sind wahrscheinlich auch die Vorhersagen der Modelle unzureichend. Es ist notwendig, den Ursprung dieser Unstimmigkeit zu identifizieren.

The feedback between clouds and sea ice got more importance in the last years, because of the declining Arctic sea ice extent. Previous observations show the formation of low clouds over newly formed open water. These low clouds are very important for the Arctic Energy Budget, because they warm the surface. This leads to increasing temperatures and stronger sea ice loss. To assess the relationship between sea ice cover and cloudiness, satellite observations by DARDAR were compared with both global climate reanalyses ERA–Interim and MACC. The analysis focuses on 2007 – 2010 and the relationship between different parameters from the different datasets. It is found that the reanalyses only poorly approximate the cloud cover in the Arctic. Consequently no strong correlation was found for the time period 2007 – 2010. Das Wolken–Albedo–Feedback in der Arktis gewann in den letzten Jahren immer mehr an Bedeutung aufgrund des Rückganges der Meereisfläche. Vorhergehende Arbeiten zeigten die Bildung von tiefer Bewölkung über kürzlich aufgebrochenen Meereisstellen. Diese tiefen Wolken sind sehr wichtig für das arktische Energiebudget, wegen des Erwärmens der Oberfläche. Daraus folgt ein Anstieg in der bodennahen Temperatur und ein verstärkter Rückgang des Meereises. Um den Einfluss der Meereiskonzentration auf die Wolkenbildung zu untersuchen, werden in dieser Arbeit Satellitendaten von DARDAR mit den beiden globalen Klimareanalysen Era–interim und MACC verglichen. Analysiert werden Daten aus den Jahren 2007 bis 2010 und für verschiedene Oberflächenbedingungen werden Korrelationen der einzelnen Datensätze erstellt. Es hat sich gezeigt, dass die Darstellung der Wolkenbedeckung in der Arktis durch die Reanalyse Daten nicht geeignet ist. Aus diesem Grund wurden keine signifikanten Korrelationen in der Zeitspanne von 2007 bis 2010 gefunden.

International audience; Radiation management (RM), as an option to engineer the climate, is highly controversial and suffers from a number of ethical and regulatory concerns, usually studied in the context of the objective to mitigate the global mean temperature. In this article, we discuss the idea that RM can be differentiated and scaled in several dimensions with potential objectives being to influence a certain climate parameter in a specific region. Some short-lived climate forcers (e.g., tropospheric aerosols) exhibit strong geographical and temporal variability, potentially leading to limited-area climate responses. Marine cloud brightening and thinning or dissolution of cirrus clouds could be operated at a rather local scale. It is therefore conceivable that such schemes could be applied with the objective to influence the climate at a regional scale. From a governance perspective, it is desirable to avoid any substantial climate effects of regional RM outside the target region. This, however, could prove impossible for a sustained, long-term RM. In turn, regional RM during limited time periods could prove more feasible without effects beyond the target area. It may be attractive as it potentially provides the opportunity to target the suppression of some extreme events such as heat waves. Research is needed on the traceability of regional RM, for example, using detection and attribution methods. Incentives and implications of regional RM need to be examined, and new governance options have to be conceived.

This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Nudged simulations of the year 2000 are carried out to compare the aerosol properties and global distribution in HAM1 and HAM2, and to evaluate them against various observations. Sensitivity experiments are performed to help identify the impact of each individual update in model formulation. Results indicate that from HAM1 to HAM2 there is a marked weakening of aerosol water uptake in the lower troposphere, reducing the total aerosol water burden from 75 Tg to 51 Tg. The main reason is the newly introduced κ-Köhler-theory-based water uptake scheme uses a lower value for the maximum relative humidity cutoff. Particulate organic matter loading in HAM2 is considerably higher in the upper troposphere, because the explicit treatment of secondary organic aerosols allows highly volatile oxidation products of the precursors to be vertically transported to regions of very low temperature and to form aerosols there. Sulfate, black carbon, particulate organic matter and mineral dust in HAM2 have longer lifetimes than in HAM1 because of weaker in-cloud scavenging, which is in turn related to lower autoconversion efficiency in the newly introduced two-moment cloud microphysics scheme. Modification in the sea salt emission scheme causes a significant increase in the ratio (from 1.6 to 7.7) between accumulation mode and coarse mode emission fluxes of aerosol number concentration. This leads to a general increase in the number concentration of smaller particles over the oceans in HAM2, as reflected by the higher Ångström parameters. Evaluation against observation reveals that in terms of model performance, main improvements in HAM2 include a marked decrease of the systematic negative bias in the absorption aerosol optical depth, as well as smaller biases over the oceans in Ångström parameter and in the accumulation mode number concentration. The simulated geographical distribution of aerosol optical depth (AOD) is better correlated with the MODIS data, while the surface aerosol mass concentrations are very similar to those in the old version. The total aerosol water content in HAM2 is considerably closer to the multi-model average from Phase I of the AeroCom intercomparison project. Model deficiencies that require further efforts in the future include (i) positive biases in AOD over the ocean, (ii) negative biases in AOD and aerosol mass concentration in high-latitude regions, and (iii) negative biases in particle number concentration, especially that of the Aitken mode, in the lower troposphere in heavily polluted regions., Atmospheric Chemistry and Physics, 12 (19), ISSN:1680-7375, ISSN:1680-7367

Current climate models often predict fractional cloud cover on the basis of a diagnostic probability density function (PDF) describing the subgrid-scale variability of the total water specific humidity, qt, favouring schemes with limited complexity. Standard shapes are uniform or triangular PDFs the width of which is assumed to scale with the gridbox mean qt or the grid-box mean saturation specific humidity, qs. In this study, the qt variability is analysed from large-eddy simulations for two stratocumulus, two shallow cumulus, and one deep convective cases. We find that in most cases, triangles are a better approximation to the simulated PDFs than uniform distributions. In two of the 24 slices examined, the actual distributions were so strongly skewed that the simple symmetric shapes could not capture the PDF at all. The distribution width for either shape scales acceptably well with both the mean value of qt and qs, the former being a slightly better choice. The qt variance is underestimated by the fitted PDFs, but overestimated by the existing parameterisations. While the cloud fraction is in general relatively well diagnosed from fitted or parameterised uniform or triangular PDFs, it fails to capture cases with small partial cloudiness, and in 10 – 30% of the cases misdiagnoses clouds in clear skies or vice-versa. The results suggest choosing a parameterisation with a triangular shape, where the distribution width would scale with the grid-box mean qt using a scaling factor of 0.076. This, however, is subject to the caveat that the reference simulations examined here were partly for rather small domains and driven by idealised boundary conditions.

A simple way to diagnose fractional cloud cover in general circulation models is to relate it to the simulated relative humidity, and allowing for fractional cloud cover above a “critical relative humidity” of less than 100%. In the formulation chosen here, this is equivalent to assuming a uniform “top-hat” distribution of subgrid-scale total water content with a variance related to saturation. Critical relative humidity has frequently been treated as a “tunable” constant, yet it is an observable. Here, this parameter, and its spatial distribution, is examined from Atmospheric Infrared Sounder (AIRS) satellite retrievals, and from a combination of relative humidity from the ECMWF Re-Analyses (ERA-Interim) and cloud fraction obtained from CALIPSO lidar satellite data. These observational data are used to evaluate results from different simulations with the ECHAM general circulation model (GCM). In sensitivity studies, a cloud feedback parameter is analyzed from simulations applying the original parameter choice, and applying parameter choices guided by the satellite data. Model sensitivity studies applying parameters adjusted to match the observations show larger positive cloud-climate feedbacks, increasing by up to 30% compared to the standard simulation.

Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects ofmeteorology fromthose of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing.Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing.

Large uncertainties exist in estimations of aerosol direct radiative forcing and indirect radiative forcing, and the values derived from globalmodeling differ substantially with satellite-based calculations. Following the approach of Quaas et al. (2008; hereafter named Quaas2008),we reassess satellite-based clear- and cloudy-sky radiative forcings and their seasonal variations by employing updated satellite products from 2004 to 2011 in combination with the anthropogenic aerosol optical depth (AOD) fraction obtained frommodel simulations using the Goddard Earth Observing System-Chemistry-Advanced ParticleMicrophysics (GEOS-Chem-APM). Our derived annual mean aerosol clear-sky forcing (-0.59 W m-2) is lower, while the cloudy-sky forcing (-0.34 W m-2) is higher than the corresponding results (-0.9Wm-2 and -0.2W m-2, respectively) reported in Quaas2008. Our study indicates that the derived forcings are sensitive to the anthropogenic AOD fraction and its spatial distribution but insensitive to the temporal resolution used to obtain the regression coefficients, i.e.,monthly or seasonal based. The forcing efficiency (i.e., the magnitude per anthropogenic AOD) for the clear-sky forcing based on this study is 19.9Wm-2, which is about 5% smaller than Quaas2008’s value of 21.1Wm-2. In contrast, the efficiency for the cloudy-sky forcing of this study (11 W m-2) is more than a factor of 2 larger than Quaas2008’s value of 4.7 W m-2. Uncertainties tests indicate that anthropogenic fraction of AOD strongly affects the computed forcings while using aerosol index instead of AOD from satellite data as aerosol proxy does not appear to cause any significant differences in regression slopes and derived forcings.

Regimes of tropical low-level clouds are commonly identified according to large-scale subsidence and lower tropospheric stability (LTS). This definition alone is insufficient for the distinction between regimes and limits the comparison of low-level clouds from CloudSat radar observations and the ECHAM5 GCM run with the COSP radar simulator. Comparisons of CloudSat radar cloud altitude-reflectivity histograms for stratocumulus and shallow cumulus regimes, as defined above, show nearly identical reflectivity profiles, because the distinction between the two regimes is dependent upon atmospheric stability below 700 hPa and observations above 1.5 km. Regional subsets, near California and Hawaii, for example, have large differences in reflectivity profiles than the dynamically defined domain; indicating different reflectivity profiles exist under a given large-scale environment. Regional subsets are better for the evaluation of low-level clouds in CloudSat and ECHAM5 as there is less contamination between 2.5 km and 7.5 km from precipitating hydrometeors which obscured cloud reflectivities.

The scale dependency of variance of total water mixing ratio is explored by analyzing data from a general circulation model (GCM), a numerical weather prediction model (NWP), and large-eddy simulations (LESs). For clarification, direct numerical simulation (DNS) data are additionally included, but the focus is placed on defining a general scaling behavior for scales ranging from global down to cloud resolving. For this, appropriate power-law exponents are determined by calculating and approximating the power density spectrum. The large-scale models (GCM and NWP) show a consistent scaling with a power-law exponent of approximately 22. For the high-resolution LESs, the slope of the power density spectrum shows evidence of being somewhat steeper, although the estimates are more uncertain. Also the transition between resolved and parameterized scales in a current GCM is investigated. Neither a spectral gap nor a strong scale break is found, but a weak scale break at high wavenumbers cannot be excluded. The evaluation of the parameterized total water variance of a state-of-the-art statistical scheme shows that the scale dependency is underestimated by this parameterization. This study and the discovered general scaling behavior emphasize the need for a development of scale-dependent parameterizations.

The influence of anthropogenic emissions on aerosol distributions and the hydrological cycle are examined with a focus on monsoon precipitation over the Indian subcontinent, during January 2001 to December 2005, using the European Centre for Medium-Range Weather Forecasts-Hamburg (ECHAM5.5) general circulation model extended by the Hamburg Aerosol Module (HAM). The seasonal variability of aerosol optical depth (AOD) retrieved from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellite is broadly well simulated (R approximate to 0.6-0.85) by the model. The spatial distribution and seasonal cycle of the precipitation observed over the Indian region are reasonably well simulated (R approximate to 0.5 to 0.8) by the model, while in terms of absolute magnitude, the model underestimates precipitation, in particular in the south-west (SW) monsoon season. The model simulates significant anthropogenic aerosol-induced changes in clear-sky net surface solar radiation (dimming greater than -7 W m-2), which agrees well with the observed trends over the Indian region. A statistically significant decreasing precipitation trend is simulated only for the SW monsoon season over the central-north Indian region, which is consistent with the observed seasonal trend over the Indian region. In the model, this decrease results from a reduction in convective precipitation, where there is an increase in stratiform cloud droplet number concentration (CDNC) and solar dimming that resulted from increased stability and reduced evaporation. Similarities in spatial patterns suggest that surface cooling, mainly by the aerosol indirect effect, is responsible for this reduction in convective activity. When changes in large-scale dynamics are allowed by slightly disturbing the initial state of the atmosphere, aerosol absorption in addition leads to a further stabilization of the lower troposphere, further reducing convective precipitation.

This study explores the viability of parameter estimation in the comprehensive general circulation model ECHAM6 using ensemble Kalman filter data assimilation techniques. Four closure parameters of the cumulus-convection scheme are estimated using increasingly less idealized scenarios ranging from perfect-model experiments to the assimilation of conventional observations. Updated parameter values from experiments with real observations are used to assess the error of the model state on short 6 h forecasts and on climatological timescales. All parameters converge to their default values in single parameter perfect-model experiments. Estimating parameters simultaneously has a neutral effect on the success of the parameter estimation, but applying an imperfect model deteriorates the assimilation performance. With real observations, single parameter estimation generates the default parameter value in one case, converges to different parameter values in two cases, and diverges in the fourth case. The implementation of the two converging parameters influences the model state: Although the estimated parameter values lead to an overall error reduction on short timescales, the error of the model state increases on climatological timescales.

In this study we examine the performance of 31 global model radiative transfer schemes in cloudfree conditions with prescribed gaseous absorbers and no aerosols (Rayleigh atmosphere), with prescribed scatteringonly aerosols, and with more absorbing aerosols. Results are compared to benchmark results from high-resolution, multiangular line-by-line radiation models. For purely scattering aerosols, model bias relative to the line-by-line models in the top-of-the atmosphere aerosol radiative forcing ranges from roughly −10 to 20 %, with over- and underestimates of radiative cooling at lower and higher solar zenith angle, respectively. Inter-model diversity (relative standard deviation) increases from ~ 10 to 15% as solar zenith angle decreases. Inter-model diversity in atmospheric and surface forcing decreases with increased aerosol absorption, indicating that the treatment of multiple-scattering is more variable than aerosol absorption in the models considered. Aerosol radiative forcing results from multi-stream models are generally in better agreement with the line-by-line results than the simpler two-stream schemes. Considering radiative fluxes, model performance is generally the same or slightly better than results from previous radiation scheme intercomparisons. However, the inter-model diversity in aerosol radiative forcing remains large, primarily as a result of the treatment of multiple-scattering. Results indicate that global models that estimate aerosol radiative forcing with two-stream radiation schemes may be subject to persistent biases introduced by these schemes, particularly for regional aerosol forcing.

The Advanced Very High Resolution Radiometer (AVHRR) instruments onboard the series of National Oceanic and Atmospheric Administration (NOAA) satellites offer the longest available meteorological data records from space. These satellites have drifted in orbit resulting in shifts in the local time sampling during the life span of the sensors onboard. Depending upon the amplitude of the diurnal cycle of the geophysical parameters derived, orbital drift may cause spurious trends in their time series. We investigate tropical deep convective clouds, which show pronounced diurnal cycle amplitude, to estimate an upper bound of the impact of orbital drift on their time series. We carry out a rotated empirical orthogonal function analysis (REOF) and show that the REOFs are useful in delineating orbital drift signal and, more importantly, in subtracting this signal in the time series of convective cloud amount. These results will help facilitate the derivation of homogenized data series of cloud amount from NOAA satellite sensors and ultimately analyzing trends from them. However, we suggest detailed comparison of various methods and rigorous testing thereof applying final orbital drift corrections.

In this paper we analyse aerosol loading and its direct radiative effects over the Bay of Bengal (BoB) and Arabian Sea (AS) regions for the Integrated Campaign on Aerosols, gases and Radiation Budget (ICARB) undertaken during 2006, using satellite data from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, the Aerosol Index from the Ozone Monitoring Instrument (OMI) on board the Aura satellite, and the European-Community Hamburg (ECHAM5.5) general circulation model extended by Hamburg Aerosol Module (HAM). By statistically comparing with large-scale satellite data sets, we firstly show that the aerosol properties measured during the ship-based ICARB campaign and simulated by the model are representative for the BoB and AS regions and the pre-monsoon season. In a second step, the modelled aerosol distributions were evaluated by a comparison with the measurements from the ship-based sunphotometer, and the satellite retrievals during ICARB. It is found that the model broadly reproduces the observed spatial and temporal variability in aerosol optical depth (AOD) over BoB and AS regions. However, AOD was systematically underestimated during high-pollution episodes, especially in the BoB leg. We show that this underprediction of AOD is mostly because of the deficiencies in the coarse mode, where the model shows that dust is the dominant component. The analysis of dust AOD along with the OMI Aerosol Index indicate that missing dust transport that results from too low dust emission fluxes over the Thar Desert region in the model caused this deficiency. Thirdly, we analysed the spatio-temporal variability of AOD comparing the ship-based observations to the large-scale satellite observations and simulations. It was found that most of the variability along the track was from geographical patterns, with a minor influence by single events. Aerosol fields were homogeneous enough to yield a good statistical agreement between satellite data at a 1° spatial, but only twice-daily temporal resolution, and the shipbased sunphotometer data at a much finer spatial, but dailyaverage temporal resolution. Examination of the satellite data further showed that the year 2006 is representative for the five-year period for which satellite data were available. Finally, we estimated the clear-sky solar direct aerosol radiative forcing (DARF). We found that the cruise represents well the regional-seasonal mean forcings. Constraining simulated forcings using the observed AOD distributions yields a robust estimate of regional-seasonal mean DARF of −8.6, −21.4 and +12.9Wm−2 at the top of the atmosphere (TOA), at the surface (SUR) and in the atmosphere (ATM), respectively, for the BoB region, and over the AS, of, −6.8, −12.8, and +6Wm−2 at TOA, SUR, and ATM, respectively.

Observations from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud Feedback Model Intercomparison Project’s Observation Simulator Package are used. Comparison of ECHAM5 with CALIPSO and CloudSat found large-scale features resolved by the model, such as the Hadley circulation, are captured well. The lidar simulator demonstrated ECHAM5 overestimates the amount of high-level clouds, particularly optically thin clouds. High-altitude clouds in ECHAM5 consistently produced greater lidar scattering ratios compared with CALIPSO. Consequently, the lidar signal in ECHAM5 frequently attenuated high in the atmosphere. The large scattering ratios were due to an underestimation of effective ice crystal radii in ECHAM5. Doubling the effective ice crystal radii improved the scattering ratios and frequency of attenuation. Additionally, doubling the effective ice crystal radii improved the detection of ECHAM5’s highest-level clouds by the radar simulator, in better agreement with CloudSat. ECHAM5 was also shown to significantly underestimate midlevel clouds and (sub)tropical low-level clouds. The low-level clouds produced were consistently perceived by the lidar simulator as too optically thick. The radar simulator demonstrated ECHAM5 overestimates the frequency of precipitation, yet underestimates its intensity compared with CloudSat observations. These findings imply compensating mechanisms inECHAM5 balance out the radiative imbalance caused by incorrect optical properties of clouds and consistently large hydrometeors in the atmosphere.

Several studies have claimed to have found significant weekly cycles of meteorological variables appearing over large domains, which can hardly be related to urban effects exclusively. Nevertheless, there is still an ongoing scientific debate whether these large-scale weekly cycles exist or not, and some other studies fail to reproduce them with statistical significance. In addition to the lack of the positive proof for the existence of these cycles, their possible physical explanations have been controversially discussed during the last years. In this work we review the main results about this topic published during the recent two decades, including a summary of the existence or non-existence of significant weekly weather cycles across different regions of the world, mainly over the US, Europe and Asia. In addition, some shortcomings of common statistical methods for analyzing weekly cycles are listed. Finally, a brief summary of supposed causes of the weekly cycles, focusing on the aerosol-cloud-radiation interactions and their impact on meteorological variables as a result of the weekly cycles of anthropogenic activities, and possible directions for future research, is presented.

An evaluation of a statistical cloud scheme taking into account subgrid-scale variability for water vapour and cloud condensate in the ECHAM5 general circulation model of the atmosphere is presented. Three-dimensional modelled water vapour, cloud liquid water and cloud ice were distributed stochastically into subcolumns of each grid box and vertically integrated to total water path (TWP). Thus the lower atmosphere is emphasized in the evaluation of TWP due to its exponential profile. The edited model dataset was compared with the globally analyzed distribution of TWP measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument. The results show that the mean TWP and mean cloud cover are on average relatively well simulated. However, large deficiencies are revealed by the evaluation of both variance and skewness of the probability density function (PDF). Systematically negative deviations of variance are found for almost all regions of the globe. Skewness of theTWPis overestimated in the Tropics and underestimated at high latitudes. Moreover, sensitivity experiments were performed to reveal the deficiencies in the parametrization leading to the observed deviations of variance and skewness of TWP. It was found that the positive bias in skewness in the Tropics can be reduced by modifying the influence of convection on the PDF.

Ship tracks are regarded as the most obvious manifestations of the effect of anthropogenic aerosol particles on clouds (indirect effect). However, it is not yet fully quantified whether there are climatically relevant effects on large scales beyond the narrow ship tracks visible in selected satellite images. A combination of satellite and reanalysis data is used here to analyze regions in which major shipping lanes cut through otherwise pristine marine environments in subtropical and tropical oceans. We expect the region downwind of a shipping lane is affected by the aerosol produced by shipping emissions but not the one upwind. Thus, differences in microphysical and macrophysical cloud properties are analyzed statistically. We investigate microphysical and macrophysical cloud properties as well as the aerosol optical depth and its fine-mode fraction for the years 2005-2007 as provided for by retrievals of the two Moderate Resolution Imaging Spectroradiometer instruments. Water-cloud properties include cloud optical depth, cloud droplet effective radius, cloud top temperature, and cloud top pressure. Large-scale meteorological parameters are taken from ERA-Interim reanalysis data and microwave remote sensing (sea surface temperature). We analyze the regions of interest in a Eulerian and Lagrangian sense, i.e., sampling along shipping lanes and sampling along wind trajectories, respectively. No statistically significant impacts of shipping emissions on large-scale cloud fields could be found in any of the selected regions close to major shipping lanes. In conclusion, the net indirect effects of aerosols from ship emissions are not large enough to be distinguishable from the natural dynamics controlling cloud presence and formation. Copyright 2011 by the American Geophysical Union.

Variability and change of the Earth\''s climate are of fundamental importance to humankind. In particular anthropogenic climate change has been considered widely as one of the most urgent concerns for the society (United Nations, 1992, 2002). It is therefore vital to improve the understanding of the Earth\''s climate system and its variability.

Aerosols act as cloud condensation nuclei (CCN) for cloud water droplets, and changes in aerosol concentrations have significant microphysical impacts on the corresponding cloud properties. Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud properties are combined with NCEP Reanalysis data for six different regions around the globe between March 2000 and December 2005 to study the effects of different aerosol, cloud, and atmospheric conditions on the aerosol indirect effect (AIE). Emphasis is placed in examining the relative importance of aerosol concentration, type, and atmospheric conditions (mainly vertical motion) to AIE from region to region. Results show that in most regions, AIE has a distinct seasonal cycle, though the cycle varies in significance and period from region to region. In the Arabian Sea (AS), the sixyear mean anthropogenic + dust AIE is −0.27Wm−2 and is greatest during the summer months (

A weekly cycle in aerosol pollution and some meteorological quantities is observed over Europe. In the present study we exploit this effect to analyse aerosol-cloudradiation interactions. A weekly cycle is imposed on anthropogenic emissions in two general circulation models that include parameterizations of aerosol processes and cloud microphysics. It is found that the simulated weekly cycles in sulfur dioxide, sulfate, and aerosol optical depth in both models agree reasonably well with those observed indicating model skill in simulating the aerosol cycle. A distinct weekly cycle in cloud droplet number concentration is demonstrated in both observations and models. For other variables, such as cloud liquid water path, cloud cover, top-of-the-atmosphere radiation fluxes, precipitation, and surface temperature, large variability and contradictory results between observations, model simulations, and model control simulations without a weekly cycle in emissions prevent us from reaching any firm conclusions about the potential aerosol impact on meteorology or the realism of the modelled second aerosol indirect effects.

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (tau a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. cloud droplet number concentration (N d) compares relatively well to the satellite data at least over the ocean. The relationship between (tau a) and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and tau a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–tau a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - tau a relationship show a strong positive correlation between tau a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau a, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic tau a and satellite-retrieved Nd–tau a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2.

Strategies to detect and attribute aerosol global impacts on clouds and climate from synergetic approaches involving modeling and observational evidence at different spatial and temporal scales.

The indirect effects of anthropogenic aerosols are expected to cause a significant radiative forcing of the Earth’s climate whose magnitude, however, is still uncertain. Most climate models use parameterizations for the aerosol indirect effects based on so-called ‘‘empirical relationships’’ which link the cloud droplet number concentration to the aerosol concentration. New satellite datasets such as those from the POLDER and MODIS instruments are well suited to evaluate and improve such parameterizations at a global scale. We derive statistical relationships of cloud-top droplet radius and aerosol index (or aerosol optical depth) from satellite retrievals and fit an empirical parameterization in a general circulation model to match the relationships. When applying the fitted parameterizations in the model, the simulated radiative forcing by the first aerosol indirect effect is reduced by 50% as compared to our baseline simulation (down to -0.3 and -0.4 Wm-2 when using MODIS and POLDER satellite data, respectively).

In this study, we examine the time evolution of the relative contribution of sulfate aerosols and greenhouse gases to anthropogenic climate change. We use the new IPSL-CM4 coupled climate model for which the first indirect effect of sulfate aerosols has been calibrated using POLDER satellite data. For the recent historical period the sulfate aerosols play a key role on the temperature increase with a cooling effect of 0.5 K, to be compared to the 1.4 K warming due to greenhouse gas increase. In contrast, the projected temperature change for the 21st century is remarkably independent of the effects of anthropogenic sulfate aerosols for the SRES-A2 scenario. Those results are interpreted comparing the different radiative forcings, and can be extended to other scenarios. We also highlight that the first indirect effect of aerosol strongly depends on the land surface model by changing the cloud cover.

Realistic simulations of clouds are of uppermost importance for climate modelling using general circulation models. Satellite data are well suited to evaluate model parametrizations. In this study we use the Laboratoire de Me´te´orologie Dynamique general circulation model (LMDZ). We evaluate the current LMDZ cloud phase parametrization, in which the repartition of condensed cloud water between liquid and ice is a function of the local temperature. Three parameters are used to derive a relation between liquid cloud water content and temperature, two of which are not physically based. We use the POLDER-1 satellite data to infer more realistic parameters by establishing statistical relationships between cloud top thermodynamical phase and cloud top temperature, consistently in both satellite data and model results. We then perform a multitude of short model integrations and derive a best estimate for the lowest local temperature where liquid water can exist in a cloud (Tice = -32°C in our parametrization). The other parameter which describes the shape of the transition between ice and liquid water is also estimated. A longer simulation has then been performed with the new parameters, resulting in an improvement in the representation of the shortwave cloud radiative forcing.

Global climate change is considered to be one of the most serious concerns of humankind (United Nations, 1992; United Nations, 2002). Anthropogenic greenhouse gases and aerosols impact considerably the energy balance of the Earth system, possibly provoking adverse effects on social, ecological, and economical equilibria. This is one of the main reasons why the understanding of the Earth’s climate system is of major importance. If better predictions of the response of the climate system to anthropogenic perturbations were available, political decisions against negative impacts could be taken, and social adaptations to changed climate conditions would be possible.

The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the parameterizations. Finally, SCMs are run for a 24–48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24–48 hr runs suggest that most models have problems in simulating boundary layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.