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Clouds are key to understanding the atmosphere and climate, and a long series of satellite observations provide invaluable information to study their properties. EUMETSAT has published Release 1 of the Optimal Cloud Analysis (OCA) Climate Data Record (CDR), which provides a homogeneous time series of cloud properties of up to two overlapping layers, together with uncertainties. The OCA product is derived using the 15 min Spinning Enhanced Visible and Infrared Imager (SEVIRI) measurements onboard Meteosat Second Generation (MSG) in geostationary orbit and covers the period from 19 January 2004 until 31 August 2019. This paper presents the validation of the OCA cloud-top pressure (CTP) against independent lidar-based estimates and the quality assessment of the cloud optical thickness (COT) and cloud particle effective radius (CRE) against a combination of products from satellite-based active and passive instruments. The OCA CTP is in good agreement with the CTP sensed by lidar for low thick liquid clouds and substantially below in the case of high ice clouds, in agreement with previous studies. The retrievals of COT and CRE are more reliable when constrained by solar channels and are consistent with other retrievals from passive imagers. The resulting cloud properties are stable and homogeneous over the whole period when compared against similar CDRs from passive instruments. For CTP, the OCA CDR and the near-real-time OCA products are consistent, allowing for the use of OCA near-real time products to extend the CDR beyond August 2019.

The response of low-level cloud properties to aerosol loading remains ambiguous, particularly due to the confounding influence of meteorological factors and water vapor availability. We utilize long-term data from Ka-band Zenith Radar, Clouds and the Earth’s Radiant Energy System, Modern-Era Retrospective analysis for Research and Applications Version 2, and European Centre for Medium-Range Weather Forecasts Reanalysis v5 to evaluate aerosol’s effects on low-level clouds under the constrains of meteorological conditions and liquid water path (LWP) over the Semi-Arid Climate and Environment Observatory of Lanzhou University during 2014–2019. To better constrain meteorological variability, we apply Principal Component Analysis to derive the first principal component (PC1), which strongly correlates with cloud properties, thereby enabling more accurate assessment of aerosol–cloud interaction (ACI) under constrained meteorological conditions delineated by PC1. Analysis suggests that under favorable meteorological conditions for low-level cloud formation (low PC1) and moderate LWP levels (25–150 g/m2), ACI is characterized by a significantly negative ACI index, with the cloud effective radius (CER) increasing in response to rising aerosol concentrations. When constrained by both PC1 and LWP, the relationship between CER and the aerosol optical depth shows a distinct bifurcation into positive and negative correlations. Different aerosol types show contrasting effects: dust aerosols increase CER under favorable meteorological conditions, whereas sulfate, organic carbon, and black carbon aerosols consistently decrease it, even under high-LWP conditions.

This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds.

As an important meteorological element, clouds play an important role in the radiative transfer process and atmospheric and water circulation. The Loess Plateau is the largest arid and semi-arid area in China, with a fragile ecological environment. However, few scholars have studied the spatial and temporal variations in cloud properties in the Loess Plateau. Therefore, in this study, cloud properties in the Loess Plateau were analyzed at the annual, seasonal, and diurnal scales based on Himawari-8 cloud products. The results show that cloud frequency (CF), cloud optical thickness (COT) and cloud effective radius (CER) show obvious spatial discrepancies in the Loess Plateau. Regions with high CF and COT values are mainly concentrated in the southern part of the Loess Plateau. In general, areas with high CER values also have low COT values. The highest CF values are observed in summer, and the highest COT values mainly appear in autumn. However, the highest CER values mainly appear in spring and winter. In terms of the diurnal variation, the CF is high at midday and low in the morning and afternoon, while the diurnal variation in COT values is the opposite: there are high COT values in the morning and afternoon and low values at midday. The CER values show an increasing trend from morning to afternoon and reach a maximum at 17:00 BJT. High CF values in the southern Loess Plateau and in summer relate to surface water and heat conditions; the vegetation cover, total column water vapor and temperature values are relatively high in this area. High COT values in the southern Loess Plateau are associated with sufficient water vapor levels and high levels of aerosol optical thickness. However, high CER levels in the northern Loess Plateau and in spring and winter may be caused by a higher nucleation rate related to the colder temperature. Moreover, more factors could influence CER, i.e., water vapor and aerosols, but they show complex relationships with the CER which need further explored.

Association of higher (lower) rainfall with lower (higher) Aerosol Optical Depth (AOD) is consistent with the understanding that increased washout (build-up) and shorter (longer) life-time of aerosols occur in wetter (drier) conditions. Given the life-time of aerosols, it is imperative to examine how aerosols impact active/break (wetter/drier than normal) spells, prominent intraseasonal variability (ISV) of Indian summer monsoon (ISM), through their composite analysis using recent satellite observations of aerosols and cloud properties, circulation and rainfall. Dust aerosols can act as CCN and participate efficiently in cloud processes during active phase. During breaks, build-up of desert dust transported by prevalent circulation, is associated with lower cloud effective radius implying aerosols’ indirect effect where they can inhibit cloud growth in the presence of reduced moisture and decrease precipitation efficiency/rainfall. Correspondingly, correlation albeit small, between intraseasonal anomalies of AOD and rainfall is negative, when AOD leads rainfall by 3–5 days implying that indirect aerosols impact is effective during breaks, though it is not the dominant responsible factor. During breaks, lower shortwave flux at top of atmosphere hints at dust-induced semi-direct effect. As breaks are permanent features of ISM, incorporation of dust-induced feedbacks in models, is essential for improved ISV simulation and ISM prediction. Highlights Active (break) spell of summer monsoon is found to be associated with lower (higher) aerosol optical depth over India. The build-up of desert dust transported to India by prevalent circulation during summer monsoon breaks, is associated with lower cloud effective radius which indicates the indirect effect of aerosols. Predominant indirect effect induced by dust aerosols along with secondary semi-direct effect can lead to further rainfall reduction during intense and persistent breaks. Proper incorporation of dust aerosol induced heating during breaks in models, is essential for simulation of intraseasonal variation inherent to Indian summer monsoon and thereby improving its prediction.

Using six flights observations in September 2015 over Hebei, China, this study shows a robust negative aerosol‐cloud droplet effective radius (re) relationship for liquid clouds, which is different from previous studies that found positive aerosol‐cloud re relationship over East China using satellite observations. A total of 27 cloud samples was analyzed with the classification of clean and polluted conditions using lower and upper 1/3 aerosol concentration at 200 m below the cloud bases. By normalizing the profiles of cloud droplet re, we found significant smaller values under polluted than under clean condition at most heights. Moreover, the averaged profiles of cloud liquid water content (LWC) show larger values under polluted than clean conditions, indicating even stronger negative aerosol‐cloud re relationship if LWC is kept constant. The droplet size distributions further demonstrate that more droplets concentrate within smaller size ranges under polluted conditions. Quantitatively, the aerosol‐cloud interaction is found around 0.10–0.19 for the study region. Key Points There are clearly more droplets within smaller size regime under polluted than under clean conditions The cloud re is significantly smaller for all in‐cloud heights even with less LWC under polluted than under clean conditions Robust negative aerosol‐cloud re relationship is found over Hebei, China region, with FIE values about 0.10–0.19

A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering absorption, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard MODIS/VIIRS continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR [Kou et al., 1993] and one in the MWIR [Wagner et al., 2005]. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1-2 μm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature results in more consistent retrievals between the two spectrally distinct 2.2 μm atmospheric window channels on MODIS and VIIRS. As a result, the 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.

Cloud liquid water content (LWC) and droplet effective radius (re) have an important influence on cloud physical processes and optical characteristics. The microphysical properties of a three-layer pure liquid stratus were measured by aircraft probes on 26 April 2014 over a coastal region in Huanghua, China. Vertical variations in aerosol concentration (Na), cloud condensation nuclei (CCN) at supersaturation (SS) 0.3%, cloud LWC and cloud re are examined. Large Na in the size range of 0.1–3 μm and CCN have been found within the planetary boundary layer (PBL) below ~1150 m. However, Na and CCN decrease quickly with height and reach a level similar to that over marine locations. Corresponding to the vertical distributions of aerosols and CCN, the cloud re is quite small (3.0–6 μm) at heights below 1150 m, large (7–13 μm) at high altitudes. In the PBL cloud layer, cloud re and aerosol Na show a negative relationship, while they show a clear positive relationship in the upper layer above PBL with much less aerosol Na. It also shows that the relationship between cloud re and aerosol Na changes from negative to positive when LWC increases. These results imply that the response of cloud re to aerosol Na depends on the combination effects of water-competency and collision-coalescence efficiency among droplets. The vertical structure of aerosol Na and cloud re implies potential cautions for the study of aerosol-cloud interaction using aerosol optical depth for cloud layers above the PBL altitude.

Geostationary satellites can retrieve the cloud droplet effective radius (re) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) imagery, over large areas in South America (5∘ N–30∘ S; 20∘–70∘ W), the Southeast Pacific (5∘ N–30∘ S; 70∘–120∘ W), and the Amazon (2∘ N–7∘ S; 54∘–73∘ W), for four months in each year from 2014–2017. Results were compared against in situ aircraft measurements and the Moderate Resolution Imaging Spectroradiometer cloud product for Terra and Aqua satellites. Monthly regression parameters approximately followed a seasonal pattern. With up to 108,009 of matchups, slope, intercept, and correlation for Terra (Aqua) ranged from about 0.71 to 1.17, −2.8 to 2.5 μm, and 0.61 to 0.91 (0.54 to 0.78, −1.5 to 1.8 μm, 0.63 to 0.89), respectively. We identified evidence for re overestimation (underestimation) correlated with shadowing (enhanced reflectance) in the forward (backscattering) hemisphere, and limitations to illumination and viewing configurations accessible by GOES-13, depending on the time of day and season. A proposition is hypothesized to ameliorate 3-D biases by studying relative illumination and cloud spatial inhomogeneity.

We present a theoretical study into the information content of solar reflectance measurements at multiple near‐infrared wavelengths in the context of deriving the vertical variation of cloud droplet size from marine stratocumulus. We employ a Bayesian optimal estimation approach to retrieve a profile of droplet effective radius as a function of optical depth in the cloud. This allows an assessment of the information content of the measurement of reflectance at different wavelengths and the potential for a new generation of hyperspectral sensors to improve the retrieval. Our results show that using the three absorbing near‐infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) centered at 1.6, 2.1 and 3.7 μm a retrieval of droplet sizes lower in the cloud is highly sensitive to small changes in reflectance. Consequently instrument and modeling errors must be reduced to <1% in order to gain a useful uncertainty constraint on droplet size near to cloud base. By introducing many high spectral resolution wavelength channels, such as those available from hyperspectral sensors, we find that the information content pertaining to all retrieval variables increases significantly. This results in a reduction in the uncertainty estimates on all retrieved quantities. We also test the ability of a vertical profile retrieval to provide improved liquid water path estimates by using several in situ profiling measurements of marine stratocumulus in the South‐East Pacific region. We find that a vertical profile retrieval significantly improves the liquid water path estimate when compared to a two‐band lookup table retrieval. Key Points MODIS has little information related to vertical variation of effective radius A hyperspectral measurement contains significantly more information Accounting for vertical variation improves the liquid water path estimate