Clouds/Aerosols 2

The ground-based station of Finokalia is situated in Greece (35^o 20'N, 25^o 40'E ) on the north coast of Crete. No significant human activities occut at a distance shorter than 15km from the station, which makes the site ideal for monitoring and characterizing natural aerosols in the Eastern Mediterranean basin. The station is equipped with advanced in-situ instrumentation for surface measurements, being operational for more than 20 years. It is recognized as one of the most significant locations in Europe for aerosol monitoring, being part of European Networks like EUSAR, ACTRIS and ICOS. From mid-2015, the station will be equipped with advanced ground-based remote sensing instrumentation including, (i) a multi-wavelength combined backscatter/Raman/depolarization PollyXT lidar system, (ii) a sun/lunar CIMEL photometer and (iii) a PANDORA instrument. The station will be included in EARLINET and AERONET networks, consituting an advanced European core site, unique in Mediterranean. 

We present here the upgrated instrumentation fleet of the Finokalia station and its potential for cal/val activities related to future ESA research- and service-oriented missions (Sentinels and Earth Explorers). Results from a recent ESA campaign (CHARADMexp) which has been implemented on June 2014, empoying all the aforementioned in-situ and remote sensing instrumentation are presented to demonstrate the potential of the site.

In the framework of the Sentinel-5 Precursor project, one pillar of the L2 working group (composed by the Royal Netherlands Meteorological Institute KNMI, the Institute of Environmental Physics IUP and the German Aerospace Center DLR) activity is the assessment of potential biases between aerosol and cloud products which will be inferred  by the respective algorithms from TROPOMI measurements. Specifically, Aerosol Layer Height (ALH) and Cloud Top Height (CTH) are the focus of the comparison. These quantities are derived by fitting reflectances in the oxygen A-band (755-775 nm), synthetically generated with radiative transfer models (RTM) and measured by sensors, appropriate in this context, such as SCIAMACHY and GOME-2. The verification of CTH, together with the analysis of cloud cover and optical thickness, has been accomplished upon synchronization of the respective forward RTMs for a variety of cases covering the full range of cloud properties in the troposphere. Then, seasonal biases have been assessed from real measurements of selected GOME-2 orbits. Verification of ALH is based on the evaluation of the altitude of the ash plume emitted by the icelandic volcano Eyjafjallajökull in May 2010 as seen by GOME-2. The retrievals were colocated with measurements derived from multiple passive sensors, such as CALIPSO, MISR, MERIS, and SCIAMACHY. Additionally, the feasibility of deriving Aerosol Optical Thickness (AOT) from TROPOMI (footprint size 7x7 km²) is assessed comparing AOT retrieved with two different approaches: the optimal estimation fit of the oxygen A-band SCIAMACHY (60x40 km²) spectra and the multi-channel surface-optimized residual minimization of the MERIS (1x1 km²) radiances. In this way, spatial scale effects can also be investigated.

Cloud information from UV/VIS/NIR spectrometers aboard spacecraft platforms is highly valuable for the construction of cloud property climatologies, since it is complementary to the information retrieved using IR spectrometers, imagers and active sensors (cloud radars and lidars).

Thick clouds scatter most of the incoming radiation back to space, thus preventing light from traversing the lowest layers of the atmosphere. Without cloud information, this cloud blocking effect would be interpreted as a reduced amount of atmospheric gas by the retrieval algorithm. On the other hand, other cloudy scenarios can lead to an increase of the photon path length due to scattering events, what would be interpreted as an artificial increase of the gas amount. These effects are just two of the many possible manners clouds can affect the quality of the trace gas retrievals. Therefore, precise cloud information is not only valuable by itself but it is mandatory for the accurate retrieval of atmospheric trace gases.

The ROCINN algorithm retrieves cloud top height (pressure), cloud optical depth and cloud albedo from GOME-2 measurements in and around the oxygen A-band (~760nm) taking as input the cloud fraction computed with the OCRA algorithm (a color space approach based on the PMD reflectances). This paper presents the latest version of the ROCINN algorithm. There are two variants of the ROCINN algorithm: one that treats clouds as reflecting boundaries (CRB) (i.e. Lambertian equivalent reflectors) and a second one that treats clouds as scattering layers (CAL). The ROCINN-CRB algorithm has been successfully used operationally for GOME/ERS-2 and GOME-2/MetOp-A and -B instruments since over one decade. The CAL algorithm treats clouds in a more realistic way and provides cloud properties closer to reality. ROCINN V3.0 in the CRB and CAL variants is incorporated into the latest UPAS operational processor and is meant to be the new operational algorithm for the official reprocessing of GOME-2-A and -B trace gas products generated at DLR in the framework of EUMETSAT O3M-SAF. In the same way, ROCINN V3.0 is the baseline algorithm for the generation of the official TROPOMI/S5P cloud products.

In this work, we present and analyze cloud properties from GOME-2 on both MetOp-A and Metop-B retrieved with the algorithms ROCINN-CAL and ROCINN-CRB. Additionally, we compare the GOME-2 cloud properties retrieved with ROCINN with independent cloud products, e.g. from the AVHRR sensor also flying on MetOp. Moreover, in order to assess the accuracy of ROCINN, sensitive studies to different observing and atmospheric scenarios using both, measured and synthetic spectra, will also be presented.

Desert dust storms strongly affect the environment and significantly contribute to climate forcing. The regional impact of desert dust storms depends on the vertical distribution of dust plumes resulting from long-range transport. Dust layers can impact chemical balances, atmospheric stability or cloud properties in the vicinity of the altitude at which they are transported and also at other altitudes. Near the surface, dust can directly affect air quality and settle down on the surface by dry deposition. The quantification of such impacts are highly uncertain, particularly due to the sporadic character of dust emissions as well as the large variability of dust properties and occurrence linked to the meteorological controls.

In the current presentation, we describe the daily evolution of the three-dimensional (3D) structure of a major dust outbreak initiated by an extratropical cyclone over East Asia in early March 2008, using new aerosol retrievals derived from satellite observations of IASI (Infrared Atmospheric Sounding Interferometer). For this, we have developed a novel auto-adaptive Tikhonov-Philips-type approach called AEROIASI to retrieve vertical profiles of dust extinction coefficient at 10 μm for most cloud-free IASI pixels, both over land and ocean. The dust vertical distribution derived from AEROIASI is shown to agree remarkably well with along-track transects of CALIOP space-borne lidar vertical profiles (mean biases less than 110 m, correlation of 0.95 and precision of 260 m for mean altitudes of the dust layers). AEROIASI allows the daily characterization of the 3D transport pathways across East Asia of two dust plumes originating from the Gobi and North Chinese deserts. From AEROIASI retrievals, we provide evidence that (i) both dust plumes are transported over the Beijing region and the Yellow Sea as elevated layers above a shallow boundary layer, (ii) as they progress eastwards, the dust layers are lifted up by the ascending motions near the core of the extratropical cyclone and (iii) when being transported over the warm waters of the Japan Sea, turbulent mixing in the deep marine boundary layer leads to high dust concentrations down to the surface. AEROIASI observations and model simulations also show that the progression of the dust plumes across East Asia is tightly related to the advancing cold front of the extratropical cyclone.

Desert dust is the most important aerosol in annual mass burden, mainly present in the Tropics but reaching Europe from time to time. Dust aerosols are a major actor in the climate: they absorb, scatter and reemit radiation, impacting the Earth energetic balance along the solar and terrestrial spectrum. Their presence in the atmosphere may lead to surface warming or cooling, and to atmospheric warming in the dusty layers, with possible impacts on the atmospheric circulation. Furthermore, dust aerosols are efficient cloud/ice condensation nuclei, therefore impacting the lifetime and physical properties of clouds, and the amount or location of rainfalls. For all these reasons, studies of dust atmospheric load and sources are of great scientific and societal interest.

In the last years, we have developed and improved a retrieval strategy to obtain vertical profiles of desert dust aerosols, from thermal infrared measurements performed by IASI (Vandenbussche et al, AMT 2013). This strategy has been used to process one year of IASI data in the major dust area. Here, we use this dataset to look at the desert dust sources in North Africa. Our dataset allows a new insight in the study of those sources since it provides vertical profiles (not only AOD) twice a day, making possible to partly distinguish local emissions from transported dust. In addition, IASI measurement times are of particular interest when desert dust sources are concerned. The mid-morning overpass (9h30 local time) allows to catch scenes right after the nocturnal low level jet breakdown, while the evening overpass (21h30 local time) gives insight at a time at which the solar spectrum based instruments cannot measure. On the other hand, MODIS onboard Terra, providing AOD above deserts thanks to the Deep Blue algorithm, has an overpass time of 13h30 local time, at which the dust emissions are the lowest.

In this contribution, we will quickly present the recent improvements to the retrieval strategy, show and discuss the results in term of dust source studies (including comparisons with literature dust source maps), then discuss the causes of uncertainties and possible biases.