Satellite remote sensing of regional and seasonal Arctic cooling showing a multi-decadal trend towards brighter and more liquid clouds

Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties from satellite passive remote sensing have been analyzed for their pan-Arctic, regional, and seasonal changes. The pan-Arctic loss of brightness, which is explained by the retreat of sea ice during the current warming period, is not compensated by a corresponding increase in cloud cover. A systematic change in the thermodynamic phase of clouds has taken place, shifting towards the liquid phase at the expense of the ice phase. Without significantly changing the total cloud optical thickness or the mass of condensed water in the atmosphere, liquid water content has increased, resulting in positive trends in liquid cloud optical thickness and albedo. This leads to a cooling trend by clouds being superimposed on top of the pan-Arctic amplified warming, induced by the anthropogenic release of greenhouse gases, the ice–albedo feedback, and related effects. Except over the permanent and parts of the marginal sea ice zone around the Arctic Circle, the rate of surface cooling by clouds has increased, both in spring (−32 % in total radiative forcing for the whole Arctic) and in summer (−14 %). The magnitude of this effect depends on both the underlying surface type and changes in the regional Arctic climate

Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model

Currently, no aerosol optical thickness (AOT) data set over the Arctic snow/ice-covered regions derived from space-borne passive remote sensing is available. The challenge is to develop an accurate and robust technique to derive AOT above highly variable and bright snow/ice surfaces. To extend data coverage of the eXtensible Bremen Aerosol/cloud and surfacE Retrieval (XBAER) AOT data product in the future, we propose a new algorithm for the retrieval of AOT and surface properties over snow/ice simultaneously. The algorithm utilizes the linear perturbation theory and does not use any simplified atmospheric correction techniques. Key issues like the selection of a proper aerosol type and optimal surface parameterization method for the retrieval of AOT over the Arctic have been investigated. The aerosol type is investigated using the aerosol climatology microphysical properties derived from four Aerosol Robotic Network (AERONET) sites (Barrow, Hornsund, Kangerlussuaq, and Tiksi). The three-parametric Ross-Li linear kernel model is used to describe the snow bidirectional reflectance distribution function (BRDF). The a priori knowledge of wavelength-dependent features of the coefficients in the Ross-Li linear kernel model is derived from Polarization and Directionality of the Earth's Reflectances (POLDER) measurements over the Arctic and utilized as constraints in the retrieval. The studies show that the combination of Ross-Li surface model and weakly absorbing aerosol parameterization provides an optimal way to derive AOT over the Arctic snow/ice-covered regions from passive remote sensing observations. The retrieved AOTs using POLDER show good agreement with AERONET observations

Aerosols in the central Arctic cryosphere: satellite and model integrated insights during Arctic spring and summer

The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of −12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is −10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by −9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period.</p

Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against “reference” satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10 × 10 km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results

Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci)

Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information content. This paper describes the lessons learned while developing and qualifying algorithms to generate aerosol Climate Data Records (CDR) within the European Space Agency (ESA) Aerosol_cci project. An iterative algorithm development and evaluation cycle involving core users is applied. It begins with the application-specific refinement of user requirements, leading to algorithm development, dataset processing and independent validation followed by user evaluation. This cycle is demonstrated for a CDR of total Aerosol Optical Depth (AOD) from two subsequent dual-view radiometers. Specific aspects of its applicability to other aerosol algorithms are illustrated with four complementary aerosol datasets. An important element in the development of aerosol CDRs is the inclusion of several algorithms evaluating the same data to benefit from various solutions to the ill-determined retrieval problem. The iterative approach has produced a 17-year AOD CDR, a 10-year stratospheric extinction profile CDR and a 35-year Absorbing Aerosol Index record. Further evolution cycles have been initiated for complementary datasets to provide insight into aerosol properties (i.e., dust aerosol, aerosol absorption).Peer reviewe

Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data.

In this study temporal variations of coccolithophore blooms are investigated using satellite data. Eight years, from 2003 to 2010, of data of SCIAMACHY, a hyper-spectral satellite sensor on-board ENVISAT, were processed by the PhytoDOAS method to 5 monitor the biomass of coccolithophores in three selected regions. These regions are characterized by frequent occurrence of large coccolithophore blooms. The retrieval results, shown as monthly mean time-series, were compared to related satellite products, including the total surface phytoplankton, i.e., total chlorophyll-a (from GlobColour merged data) and the particulate inorganic carbon (from MODIS-Aqua). The 10 inter-annual variations of the phytoplankton bloom cycles and their maximum monthly mean values have been compared in the three selected regions to the variations of the geophysical parameters: sea-surface temperature (SST), mixed-layer depth (MLD) and surface wind speed, which are known to affect phytoplankton dynamics. For each region the anomalies and linear trends of the monitored parameters over the period of this 15 study have been computed. The patterns of total phytoplankton biomass and specific dynamics of coccolithophores chlorophyll-a in the selected regions are discussed in relation to other studies. The PhytoDOAS results are consistent with the two other ocean color products and support the reported dependencies of coccolithophore biomass’ dynamics to the compared geophysical variables. This suggests, that PhytoDOAS 20 is a valid method for retrieving coccolithophore biomass and for monitoring its bloom developments in the global oceans. Future applications of time-series studies using the PhytoDOAS data set are proposed, also using the new upcoming generations of hyper-spectral satellite sensors with improved spatial resolution

The PhytoDOAS technique to retrieve phytoplankton groups from hyperspectral satellite data.

The PhytoDOAS algorithm by Bracher et al. (2009), modified by and Sadeghi et al. (2011), enables the concurrent retrieval of global chl-a of phytoplankton groups (diatoms, cyanobacteria, coccolithophores, dinoflagellates) from hyperspectral satellite data, such as measured by SCIAMACHY onboard ENVISAT. For applying the Differential Optical Absorption Spectroscopy (DOAS) fit from 430-530nm the following absorbers are considered in the analysis: atmosphere: O3, O4, NO2, H2Og, Glyoxal, Ring; ocean: inelastic scattering, water, PFTs; The non-differentisl absorption and scattering is approximated with low order polynomial. The global data set of the four phytoplankton groups is avaiable on a monthly resolution for July 2002 until today

Intercomparison of ocean color products identifying coccolithophore blooms on global and regional scales.

Nearly ten years (July 2002 to April 2012) of SCIAMACHY data, a hyper-spectral satellite sensor on-board ENVISAT, were processed by the improved, multi-target, PhytoDOAS method to monitor the biomass of coccolithophores besides diatoms and cyanobacteria. Data have been evaluated with other coccolithphore related satellite products and modeled coccolithophore distributions derived from the NASA Ocean Biogeochemical Model. The retrieval's sensitivity was assessed by using the coupled oceanic-atmospheric radiative transfer model SCIATRAN. Temporal variations of coccolithophores were investigated using satellite data in three selected regions characterized by frequent occurrence of large coccolithophore blooms. Monthly mean data were compared to related satellite products, including the total surface phytoplankton, i.e., total chlorophyll-a (from GlobColour merged data) and the particulate inorganic carbon (from MODIS-Aqua). In addition, the inter-annual variations of the phytoplankton bloom cycles and their maximum monthly mean values were compared in the three selected regions to the variations of the following geophysical parameters: sea-surface temperature (SST), mixed-layer depth (MLD) and surface wind speed, which are known to affect phytoplankton dynamics. PhytoDOAS data are consistent with the two other ocean color products and support the reported dependencies of coccolithophore biomass' dynamics to the compared geophysical variables. These results suggest that multi-target PhytoDOAS is a valid method for retrieving coccolithophores' biomass and for monitoring their bloom developments in the global oceans

Global Distribution of Cloud Top Height as Retrieved from SCIAMACHY Onboard ENVISAT Spaceborne Observations

The spatial and temporal analysis of the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT global cloud top height data for 2003–2006 is presented. The cloud top height is derived using a semi-analytical cloud top height retrieval algorithm based on an asymptotic solution of the radiative transfer equation in the oxygen A-band. The analysis is valid for thick clouds only. As expected, clouds are higher in the equatorial region. The cloud altitudes decrease towards the Poles due to the general decrease of the troposphere height. The global average cloud top height as derived from SCIAMACHY measurements is 7.3 km. We also studied the planetary reflectivity R at 443 nm and found that the annual average is R = 0.49 ± 0.08 for the years analyzed

Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018

This dataset contains spectral reflectances, measured at the top-of-atmosphere in the solar spectral range, by the three different sensors GOME, SCIAMACHY and GOME-2A respectively on board the ERS-2, ENVISAT and MetOpA satellites. The time interval covered is January 1996 up to and including December 2017. The temporal granularity is monthly. The geographic extent is from parallel 60 N to 85 N. The dataset is functional to inspect long-term changes in Arctic reflectivity and to analyze the relative contribution of mainly sea ice, snow and clouds. Data in this version has already been harmonized for the spatial footprint at the ground of the respective sensors and for subsequent analysis with complementary and independent datasets of cloud properties and radiative fluxes. As such, they are not suitable for in-situ validation of ground, air- or ship-borne reflectances. The underlying original reflectances at native resolution are available upon request