Retrieval of aerosol optical depth over the Arctic cryosphere during spring and summer using satellite observations

The climate in the Arctic has warmed much more quickly in the last 2 to 3 decades than at the mid-latitudes, i.e., during the Arctic amplification (AA) period. Radiative forcing in the Arctic is influenced both directly and indirectly by aerosols. However, their observation from ground or airborne instruments is challenging, and thus measurements are sparse. In this study, total aerosol optical depth (AOD) is determined from top-of-atmosphere reflectance measurements by the Advanced Along-Track Scanning Radiometer (AATSR) on board ENVISAT over snow and ice in the Arctic using a retrieval called AEROSNOW for the period 2003 to 2011. AEROSNOW incorporates an existing aerosol retrieval algorithm with a cloud-masking algorithm, alongside a novel quality-flagging methodology specifically designed for implementation in the high Arctic region (≥ 72∘ N). We use the dual-viewing capability of the AATSR instrument to accurately determine the contribution of aerosol to the reflection at the top of the atmosphere for observations over the bright surfaces of the cryosphere in the Arctic. The AOD is retrieved assuming that the surface reflectance observed by the satellite can be well parameterized by a bidirectional snow reflectance distribution function (BRDF). The spatial distribution of AOD shows that high values in spring (March, April, May) and lower values in summer (June, July, August) are observed. The AEROSNOW AOD values are consistent with those from collocated Aerosol Robotic Network (AERONET) measurements, with no systematic bias found as a function of time. The AEROSNOW AOD in the high Arctic was validated by comparison with ground-based measurements at the PEARL, OPAL, Hornsund, and Thule stations. The AEROSNOW AOD value is less than 0.15 on average, and the linear regression of AEROSNOW and AERONET total AOD yields a slope of 0.98, a Pearson correlation coefficient of R=0.86, and a root mean square error (RMSE) of =0.01 for the monthly scale in both spring and summer. The AEROSNOW observation of increased AOD values over the high Arctic cryosphere during spring confirms clearly that Arctic haze events were well captured by this dataset. In addition, the AEROSNOW AOD results provide a novel and unique total AOD data product for the springtime and summertime from 2003 to 2011. These AOD values, retrieved from spaceborne observation, provide a unique insight into the high Arctic cryospheric region at high spatial resolution and temporal coverage.</p

A cloud identification algorithm over the Arctic for use with AATSR–SLSTR measurements

The accurate identification of the presence of cloud in the ground scenes observed by remote-sensing satellites is an end in itself. The lack of knowledge of cloud at high latitudes increases the error and uncertainty in the evaluation and assessment of the changing impact of aerosol and cloud in a warming climate. A prerequisite for the accurate retrieval of aerosol optical thickness (AOT) is the knowledge of the presence of cloud in a ground scene. In our study, observations of the upwelling radiance in the visible (VIS), near infrared (NIR), shortwave infrared (SWIR) and the thermal infrared (TIR), coupled with solar extraterrestrial irradiance, are used to determine the reflectance. We have developed a new cloud identification algorithm for application to the reflectance observations of the Advanced Along-Track Scanning Radiometer (AATSR) on European Space Agency (ESA)-Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on board the ESA Copernicus Sentinel-3A and -3B. The resultant AATSR–SLSTR cloud identification algorithm (ASCIA) addresses the requirements for the study AOT at high latitudes and utilizes time-series measurements. It is assumed that cloud-free surfaces have unchanged or little changed patterns for a given sampling period, whereas cloudy or partly cloudy scenes show much higher variability in space and time. In this method, the Pearson correlation coefficient (PCC) parameter is used to measure the “stability” of the atmosphere–surface system observed by satellites. The cloud-free surface is classified by analysing the PCC values on the block scale 25×25&thinsp;km2. Subsequently, the reflection at 3.7&thinsp;µm is used for accurate cloud identification at scene level: with areas of either 1×1 or 0.5×0.5&thinsp;km2. The ASCIA data product has been validated by comparison with independent observations, e.g. surface synoptic observations (SYNOP), the data from AErosol RObotic NETwork (AERONET) and the following satellite products: (i) the ESA standard cloud product from AATSR L2 nadir cloud flag; (ii) the product from a method based on a clear-snow spectral shape developed at IUP Bremen (Istomina et al., 2010), which we call ISTO; and (iii) the Moderate Resolution Imaging Spectroradiometer (MODIS) products. In comparison to ground-based SYNOP measurements, we achieved a promising agreement better than 95&thinsp;% and 83&thinsp;% within ±2 and ±1 okta respectively. In general, ASCIA shows an improved performance in comparison to other algorithms applied to AATSR measurements for the identification of clouds in a ground scene observed at high latitudes.</p

Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project has been established in 2016. It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, ship-borne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data

The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multi-Platform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification

A consortium of polar scientists combined observational forces in a field campaign of unprecedented complexity to uncover the secrets of clouds and their role in Arctic amplification. Two research aircraft, an icebreaker research vessel, an ice-floe camp including an instrumented tethered balloon, and a permanent ground-based measurement station were employed in this endeavour. Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the ”Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD)” aircraft campaign, and the ”Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL (PASCAL)” ice breaker expedition. Both observational studies were performed in the framework of the German ”ArctiC Amplification:Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” project. They took place in the vicinity of Svalbard (Norway) in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: Cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent-dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft, the icebreaker research vessel (RV) Polarstern, an ice-floe camp including an instrumented tethered balloon, and the permanent, ground-based measurement station at Ny-Ålesund (Svalbard) were employed to observe Arctic low and mid-level, mixed-phase clouds, and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in-situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above RV Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results, and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns

Remote sensing of Arctic atmospheric aerosols

In this chapter remote sensing techniques as applied to studies of Arctic aerosol are surveyed. They include the analysis of ground and shipborne observations of atmospheric aerosol using sunphotometers and also airborne/satellite observations using optical instrumentation (lidars, imagers, radiometers)