The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided.

This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation dataset from advanced very-high-resolution radiometer (AVHRR) data, CLARA-A3. The content of earlier CLARA editions, namely cloud, surface albedo, and surface radiation products, has been extended with two additional surface albedo products (blue- and white-sky albedo), three additional surface radiation products (net shortwave and longwave radiation, and surface radiation budget), and two top of atmosphere radiation budget products (reflected solar flux and outgoing longwave radiation). The record length is extended to 42 years (1979–2020) by also incorporating results from the first version of the advanced very high resolution radiometer imager (AVHRR/1). A continuous extension of the climate data record (CDR) has also been implemented by processing an interim climate data record (ICDR) based on the same set of algorithms but with slightly changed ancillary input data. All products are briefly described together with validation results and intercomparisons with currently existing similar CDRs. The extension of the product portfolio and the temporal coverage of the data record, together with product improvements, is expected to enlarge the potential of using CLARA-A3 for climate change studies and, in particular, studies of potential feedback effects between clouds, surface albedo, and radiation. The CLARA-A3 data record is hosted by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) CM SAF and is freely available at https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003 (Karlsson et al., 2023b).

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude–longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.For each dataset a digital object identifier has been issued:Cloud_cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002Cloud_cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002Cloud_cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002Cloud_cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002Cloud_cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002Cloud_cci MERIS+AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002

Temperature inversions are one of the dominant features of the Arctic atmosphere and play a crucial role in various processes by controlling the transfer of mass and moisture fluxes through the lower troposphere. It is therefore essential that they are accurately quantified, monitored and simulated as realistically as possible over the Arctic regions. In the present study, the characteristics of inversions in terms of frequency and strength are quantified for the entire Arctic Ocean for summer and winter seasons of 2003 to 2008 using the AIRS data for the clear-sky conditions. The probability density functions (PDFs) of the inversion strength are also presented for every summer and winter month. Our analysis shows that although the inversion frequency along the coastal regions of Arctic decreases from June to August, inversions are still seen in almost each profile retrieved over the inner Arctic region. In winter, inversions are ubiquitous and are also present in every profile analysed over the inner Arctic region. When averaged over the entire study area (70° N–90° N), the inversion frequency in summer ranges from 69 to 86% for the ascending passes and 72–86% for the descending passes. For winter, the frequency values are 88–91% for the ascending passes and 89–92% for the descending passes of AIRS/AQUA. The PDFs of inversion strength for the summer months are narrow and right-skewed (or positively skewed), while in winter, they are much broader. In summer months, the mean values of inversion strength for the entire study area range from 2.5 to 3.9 K, while in winter, they range from 7.8 to 8.9 K. The standard deviation of the inversion strength is double in winter compared to summer. The inversions in the summer months of 2007 were very strong compared to other years. The warming in the troposphere of about 1.5–3.0 K vertically extending up to 400 hPa was observed in the summer months of 2007.

Water vapor intrusions (WVIs) explain a significant fraction of total moisture transport and its variability in the Arctic. WVIs can precondition the Arctic atmosphere for accelerated melting of sea ice through effects on surface longwave radiation. Using data from the NASA's A‐Train convoy of satellites to estimate the response of the lower troposphere to WVIs into the Arctic, we show that WVIs are associated with a surface warming of up to 5.3 K (±3.3 K) in winter and 2.3 K (±1.6 K) in summer, when averaged over the entire Arctic Ocean. The intrusions also lead to additional cloud radiative heating of up to 0.15 K/d via up to 30% increased cloudiness in the vertical and also cause a weakening of the stability in the lower troposphere. The lower tropospheric and surface warming during winter and spring highlights the importance of understanding contribution of preconditioning to accelerated ice melt in the Arctic.

We investigate the impact of the morphological properties of freshly emitted black carbon aerosols on optical properties and on radiative forcing. To this end, we model the optical properties of fractal black carbon aggregates by use of numerically exact solutions to Maxwell's equations within a spectral range from the UVC to the mid-IR. The results are coupled to radiative transfer computations, in which we consider six realistic case studies representing different atmospheric pollution conditions and surface albedos. The spectrally integrated radiative impacts of black carbon are compared for two different fractal morphologies, which brace the range of recently reported experimental observations of black carbon fractal structures. We also gauge our results by performing corresponding calculations based on the homogeneous sphere approximation, which is commonly employed in climate models. We find that at top of atmosphere the aggregate models yield radiative impacts that can be as much as 2 times higher than those based on the homogeneous sphere approximation. An aggregate model with a low fractal dimension can predict a radiative impact that is higher than that obtained with a high fractal dimension by a factor ranging between 1.1–1.6. Although the lower end of this scale seems like a rather small effect, a closer analysis reveals that the single scattering optical properties of more compact and more lacy aggregates differ considerably. In radiative flux computations there can be a partial cancellation due to the opposing effects of different error sources. However, this cancellation effect can strongly depend on atmospheric conditions and is therefore quite unpredictable. We conclude that the fractal morphology of black carbon aerosols and their fractal parameters can have a profound impact on their radiative forcing effect, and that the use of the homogeneous sphere model introduces unacceptably high biases in radiative impact studies. We emphasise that there are other potentially important morphological features that have not been addressed in the present study, such as sintering and coating of freshly emitted black carbon by films of organic material. Finally, we found that the spectral variation of the absorption cross section of black carbon significantly deviates from a simple 1/λ scaling law. We therefore discourage the use of single-wavelength absorption measurements in conjunction with a 1/λ scaling relation in broadband radiative forcing simulations of black carbon.