Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations

The Community Intercomparison Suite (CIS) is an easy-to-use command-line tool which has been developed to allow the straightforward intercomparison of remote sensing, in situ and model data. While there are a number of tools available for working with climate model data, the large diversity of sources (and formats) of remote sensing and in situ measurements necessitated a novel software solution. Developed by a professional software company, CIS supports a large number of gridded and ungridded data sources "out-of-the-box", including climate model output in NetCDF or the UK Met Office pp file format, CloudSat, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS (MODerate resolution Imaging Spectroradiometer), Cloud and Aerosol CCI (Climate Change Initiative) level 2 satellite data and a number of in situ aircraft and ground station data sets. The open-source architecture also supports user-defined plugins to allow many other sources to be easily added. Many of the key operations required when comparing heterogenous data sets are provided by CIS, including subsetting, aggregating, collocating and plotting the data. Output data are written to CF-compliant NetCDF files to ensure interoperability with other tools and systems. The latest documentation, including a user manual and installation instructions, can be found on our website (http://cistools.net). Here, we describe the need which this tool fulfils, followed by descriptions of its main functionality (as at version 1.4.0) and plugin architecture which make it unique in the field

The effect of clouds and precipitation on the aerosol concentrations and composition in a boreal forest environment

Atmospheric aerosol particle concentrations are strongly affected by various wet processes, including below and in-cloud wet scavenging and in-cloud aqueous-phase oxidation. We studied how wet scavenging and cloud processes affect particle concentrations and composition during transport to a rural boreal forest site in northern Europe. For this investigation, we employed air mass history analysis and observational data. Long-term particle number size distribution (similar to 15 years) and composition measurements (similar to 8 years) were combined with air mass trajectories with relevant variables from reanalysis data. Some such variables were rainfall rate, relative humidity, and mixing layer height. Additional observational datasets, such as temperature and trace gases, helped further evaluate wet processes along trajectories with mixed effects models. All chemical species investigated (sulfate, black carbon, and organics) exponentially decreased in particle mass concentration as a function of accumulated precipitation along the air mass route. In sulfate (SO4) aerosols, clear seasonal differences in wet removal emerged, whereas organics (Org) and equivalent black carbon (eBC) exhibited only minor differences. The removal efficiency varied slightly among the different reanalysis datasets (ERA-Interim and Global Data Assimilation System; GDAS) used for the trajectory calculations due to the difference in the average occurrence of precipitation events along the air mass trajectories between the reanalysis datasets. Aqueous-phase processes were investigated by using a proxy for air masses travelling inside clouds. We compared air masses with no experience of approximated in-cloud conditions or precipitation during the past 24 h to air masses recently inside non-precipitating clouds before they entered SMEAR II (Station for Measuring Ecosystem-Atmosphere Relations). Significant increases in SO4 mass concentration were observed for the latter air masses (recently experienced non-precipitating clouds). Our mixed effects model considered other contributing factors affecting particle mass concentrations in SMEAR II: examples were trace gases, local meteorology, and diurnal variation. This model also indicated in-cloud SO4 production. Despite the reanalysis dataset used in the trajectory calculations, aqueous-phase SO4 formation was observed. Particle number size distribution measurements revealed that most of the in-cloud SO4 formed can be attributed to particle sizes larger than 200 nm (electrical mobility diameter). Aqueous-phase secondary organic aerosol (aqSOA) formation was non-significant.Peer reviewe

AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50% decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2/3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AOD(f), AOD(c)), Angstrom exponent (AE), dry surface scattering (SCdry), and absorption (AC(dry)) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21% +/- 20% (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from -37% (MODIS-Terra) to -16% (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R > 0.75), suggesting that the models are capable of capturing spatiotemporal variations in AOD. We find a much larger underestimate in coarse AOD(c) (similar to-45% +/- 25 %) than in fine AOD(f) (similar to-15% +/- 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AOD(c) bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AOD(c). Column AEs are underestimated by about 10% +/- 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140% if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of -35% +/- 25% and -20% +/- 18% for SCdry and AC(dry), respectively. The larger underestimate of SCdry than AC(dry) suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. -15 %, however, with a considerably large interquartile range, suggesting a spread between -35% and +10 %.Peer reviewe

Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations

We document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 (GC3.1) and UKESM1, which are contributing to the 6th Coupled Model Intercomparison Project (CMIP6). The simulation of aerosols in the present-day period of the historical ensemble of these models is evaluated against a range of observations. Updates to the aerosol microphysics scheme are documented as well as differences in the aerosol representation between the physical and Earth system configurations. The additional Earth-system interactions included in UKESM1 leads to differences in the emissions of natural aerosol sources such as dimethyl sulfide, mineral dust and organic aerosol and subsequent evolution of these species in the model. UKESM1 also includes a stratospheric-tropospheric chemistry scheme which is fully coupled to the aerosol scheme, while GC3.1 employs a simplified aerosol chemistry mechanism driven by prescribed monthly climatologies of the relevant oxidants. Overall, the simulated speciated aerosol mass concentrations compare reasonably well with observations. Both models capture the negative trend in sulfate aerosol concentrations over Europe and the eastern United States of America (US) although the models tend to underestimate the sulfate concentrations in both regions. Interactive emissions of biogenic volatile organic compounds in UKESM1 lead to an improved agreement of organic aerosol over the US. Simulated dust burdens are similar in both models despite a 2-fold difference in dust emissions. Aerosol optical depth is biased low in dust source and outflow regions but performs well in other regions compared to a number of satellite and ground-based retrievals of aerosol optical depth. Simulated aerosol number concentrations are generally within a factor of 2 of the observations with both models tending to overestimate number concentrations over remote ocean regions, apart from at high latitudes, and underestimate over Northern Hemisphere continents. Finally, a new primary marine organic aerosol source is implemented in UKESM1 for the first time. The impact of this new aerosol source is evaluated. Over the pristine Southern Ocean, it is found to improve the seasonal cycle of organic aerosol mass and cloud droplet number concentrations relative to GC3.1 although underestimations in cloud droplet number concentrations remain. This paper provides a useful characterization of the aerosol climatology in both models facilitating the understanding of the numerous aerosol-climate interaction studies that will be conducted as part of CMIP6 and beyond

Cloud cycling, scavenging and aerosol vertical profiles: process sensitivity and observational constraints

The effects of aerosol in the atmosphere account for some of the largest uncertainties in estimates of the human impact on climate. These effects depend not only on the total mass of aerosol, but also its size distribution, mixing state and vertical profile. Previous studies have suggested that both the size distribution and mixing state of aerosol may be strongly influenced by repeated cycling through non-precipitating cloud. The extent of this process is assessed in the HadGEM3–UKCA model; although fewer cycles are seen for all aerosol than in previous studies, the figure varies considerably between aerosol types. The role of scavenging by precipitating cloud is also considered, and several approaches to increasing the physical realism of its representation are considered. In particular, coupling convective scavenging into the convective transport scheme is shown to provide significant benefits over an operator-split approach (which underestimates removal and allows excess aerosol to reach the upper troposphere and be transported to remote regions). To evaluate the alternative convective scavenging schemes, a method is developed for carrying out a pointwise evaluation against vertically-resolved in-situ observations from large-scale aircraft campaigns, based on nudging and flight-track sampling in the model. It is demonstrated that this approach can help to constrain the choice between different model configurations with a degree of statistical confidence. Finally, the processes controlling the vertical profile of aerosol are investigated using a series of model-based sensitivity tests, along with the extent to which these processes can account for the large diversity in vertical profiles seen amongst current models. For mass profiles and number profiles of large particles (greater than about 100nm dry diameter), removal and secondary production processes are shown to be most important; for number profiles of smaller particles, microphysical processes are shown to become increasingly dominant.</p

An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF

International audienceAn aerosol climatology to represent aerosols in the radiation schemes of global atmospheric models was recently developed. We derived the climatology from a reanalysis of atmospheric composition produced by the Copernicus Atmosphere Monitoring Service (CAMS). As an example of an application in a global atmospheric model, we discuss the technical aspects of the implementation in the European Centre for Medium Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) and the impact of the new climatology on the medium-range weather forecasts and 1-year simulations. The new aerosol climatology was derived by combining a set of model simulations with constrained meteorological conditions and an atmospheric composition reanalysis for the period 2003–2013 produced by the IFS. The aerosol fields of the reanalysis are constrained by assimilating the aerosol optical thickness (AOT) retrievals product by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. In a further step, we used modelled aerosol fields to correct the aerosol speciation and the vertical profiles of the aerosol reanalysis fields. The new climatology provides the monthly-mean mass mixing ratio of five aerosol species constrained by assimilated MODIS AOT. Using the new climatology in the ECMWF-IFS leads to changes in the direct aerosol radiative effect compared to the climatology previously implemented, which have a small but non-impact on the forecast skill of large-scale weather patterns in the medium-range. However, details of the regional distribution of aerosol radiative forcing can have a large local impact. This is the case for the area of the Arabian Peninsula and the northern Indian Ocean. Here changes in the radiative forcing of the mineral dust significantly improve the summer monsoon circulation

Description and evaluation of the tropospheric aerosol scheme in the Integrated Forecasting System (IFS-AER, cycle 47R1) of ECMWF

Abstract. This article describes the Integrated Forecasting System aerosol scheme (IFS-AER) used operationally in the IFS cycle 47R1, which was operated by the European Centre for Medium Range Weather Forecasts (ECMWF) in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). It represents an update of the Rémy et al. (2019) article, which described cycle 45R1 of IFS-AER in detail. Here, we detail only the parameterisations of sources and sinks that have been updated since cycle 45R1, as well as recent changes in the configuration used operationally within CAMS. Compared to cycle 45R1, a greater integration of aerosol and chemistry has been achieved. Primary aerosol sources have been updated, with the implementation of new dust and sea salt aerosol emission schemes. New dry and wet deposition parameterisations have also been implemented. Sulfate production rates are now provided by the global chemistry component of IFS. This paper aims to describe most of the updates that have been implemented since cycle 45R1, not just the ones that are used operationally in cycle 47R1; components that are not used operationally will be clearly flagged. Cycle 47R1 of IFS-AER has been evaluated against a wide range of surface and total column observations. The final simulated products, such as particulate matter (PM) and aerosol optical depth (AOD), generally show a significant improvement in skill scores compared to results obtained with cycle 45R1. Similarly, the simulated surface concentration of sulfate, organic matter and sea salt aerosol are improved by cycle 47R1 compared to cycle 45R1. Some biases persist, such as the surface concentrations of nitrate and organic matter being simulated too high. The new wet and dry deposition schemes that have been implemented into cycle 47R1 have a mostly positive impact on simulated AOD, PM and speciated aerosol surface concentration

Assimilation of TROPOMI SO2 Layer Height Data in the CAMS System

The Copernicus Atmosphere Monitoring Service (CAMS), operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission, provides daily analyses and 5-day forecasts of atmospheric composition, including forecasts of volcanic sulfur dioxide (SO2) in near-real time (NRT). CAMS currently assimilates total column SO2 retrievals from the GOME-2 and TROPOMI instruments which give information about the location and strength of volcanic plumes. However, the operational TROPOMI and GOME-2 retrievals do not provide any information about the height of the volcanic plumes and therefore some prior assumptions need to be made in the CAMS data assimilation system about where to place the resulting SO2 increments in the vertical. Currently, the SO2 increments are placed in the mid-troposphere, around 550 hPa. While this gives good results for the majority of volcanic emissions, it will clearly be wrong for eruptions that inject SO2 at very different altitudes, in particular for exceptional events where part of the SO2 reaches the stratosphere. A new algorithm, developed by DLR for GOME-2 and now being adapted to TROPOMI in the frame of the ESA-funded Sentinel-5P Innovation–SO2 Layer Height Project (S5P+I: SO2LH), the Full-Physics Inverse Learning Machine (FP_ILM) algorithm, retrieves SO2 layer height from TROPOMI in NRT in addition to the SO2 column. CAMS is testing the assimilation of these data, making use of the NRT layer height information to place the SO2 increments at a better altitude. We present results from assimilation tests with the TROPOMI SO2 layer height data for several volcanic eruptions and show that making use of the additional layer height information leads to improved SO2 forecasts

Models transport Saharan dust too low in the atmosphere: a comparison of the MetUM and CAMS forecasts with observations

We investigate the dust forecasts from two operational global atmospheric models in comparison with in situ and remote sensing measurements obtained during the AERosol properties – Dust (AER-D) field campaign. Airborne elastic backscatter lidar measurements were performed on board the Facility for Airborne Atmospheric Measurements during August 2015 over the eastern Atlantic, and they permitted us to characterise the dust vertical distribution in detail, offering insights on transport from the Sahara. They were complemented with airborne in situ measurements of dust size distribution and optical properties, as well as datasets from the Cloud–Aerosol Transport System (CATS) spaceborne lidar and the Moderate Resolution Imaging Spectroradiometer (MODIS). We compare the airborne and spaceborne datasets to operational predictions obtained from the Met Office Unified Model (MetUM) and the Copernicus Atmosphere Monitoring Service (CAMS). The dust aerosol optical depth predictions from the models are generally in agreement with the observations but display a low bias. However, the predicted vertical distribution places the dust lower in the atmosphere than highlighted in our observations. This is particularly noticeable for the MetUM, which does not transport coarse dust high enough in the atmosphere or far enough away from the source. We also found that both model forecasts underpredict coarse-mode dust and at times overpredict fine-mode dust, but as they are fine-tuned to represent the observed optical depth, the fine mode is set to compensate for the underestimation of the coarse mode. As aerosol–cloud interactions are dependent on particle numbers rather than on the optical properties, this behaviour is likely to affect their correct representation. This leads us to propose an augmentation of the set of aerosol observations available on a global scale for constraining models, with a better focus on the vertical distribution and on the particle size distribution. Mineral dust is a major component of the climate system; therefore, it is important to work towards improving how models reproduce its properties and transport mechanisms

Description and evaluation of the tropospheric aerosol scheme in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS-AER, cycle 45R1)

International audienceThis article describes the IFS-AER aerosol module used operationally in the Integrated Forecasting System (IFS) cycle 45R1, operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). We describe the different parameterizations for aerosol sources, sinks, and its chemical production in IFS-AER, as well as how the aerosols are integrated in the larger atmospheric composition forecasting system. The focus is on the entire 45R1 code base, including some components that are not used operationally, in which case this will be clearly specified. This paper is an update to the Morcrette et al. (2009) article that described aerosol forecasts at the ECMWF using cycle 32R2 of the IFS. Between cycles 32R2 and 45R1, a number of source and sink processes have been reviewed and/or added, notably increasing the complexity of IFS-AER. A greater integration with the tropospheric chemistry scheme of the IFS has been achieved for the sulfur cycle and for nitrate production. Two new species, nitrate and am-monium, have also been included in the forecasting system. Global budgets and aerosol optical depth (AOD) fields are shown, as is an evaluation of the simulated particulate matter (PM) and AOD against observations, showing an increase in skill from cycle 40R2, used in the CAMS interim ReAnalysis (CAMSiRA), to cycle 45R1