From 25 May to 21 July 2017, the research vessel Polarstern performed the cruise PS106 to the high Arctic in the region north and northeast of Svalbard. The mobile remote-sensing platform OCEANET was ...deployed aboard Polarstern. Within a single container, OCEANET houses state-of-the-art remote-sensing equipment, including a multiwavelength Raman polarization lidar Polly.sup.XT and a 14-channel microwave radiometer HATPRO (Humidity And Temperature PROfiler). For the cruise PS106, the measurements were supplemented by a motion-stabilized 35 GHz cloud radar Mira-35. This paper describes the treatment of technical challenges which were immanent during the deployment of OCEANET in the high Arctic. This includes the description of the motion stabilization of the cloud radar Mira-35 to ensure vertical-pointing observations aboard the moving Polarstern as well as the applied correction of the vessels heave rate to provide valid Doppler velocities. The correction ensured a leveling accuracy of ±0.5.sup." during transits through the ice and an ice floe camp. The applied heave correction reduced the signal induced by the vertical movement of the cloud radar in the PSD of the Doppler velocity by a factor of 15. Low-level clouds, in addition, frequently prevented a continuous analysis of cloud conditions from synergies of lidar and radar within Cloudnet, because the technically determined lowest detection height of Mira-35 was 165 m above sea level. To overcome this obstacle, an approach for identification of the cloud presence solely based on data from the near-field receiver of Polly.sup.XT at heights from 50 m and 165 m above sea level is presented. We found low-level stratus clouds, which were below the lowest detection range of most automatic ground-based remote-sensing instruments during 25 % of the observation time.
The role of clouds in recent Arctic warming is not fully understood,
including their effects on the solar radiation and the surface
energy budget. To investigate relevant small-scale processes in ...detail, the intensive Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL
(PASCAL) drifting ice floe station field campaign was conducted during early summer in the central arctic. During this campaign, the small-scale spatiotemporal
variability of global irradiance was observed for the first time on an
ice floe with a dense network of autonomous pyranometers. A total of 15 stations
were deployed covering an area of 0.83 km×1.59 km from
4–16 June 2017. This unique, open-access dataset is described here,
and an analysis of the spatiotemporal variability deduced from this
dataset is presented for different synoptic conditions. Based on
additional observations, five typical sky conditions were identified and
used to determine the values of the mean and variance of atmospheric
global transmittance for these conditions. Overcast conditions were
observed 39.6 % of the time predominantly during the first week, with
an overall mean transmittance of 0.47. The second most frequent
conditions corresponded to multilayer clouds (32.4 %), which
prevailed in particular during the second week, with a mean
transmittance of 0.43. Broken clouds had a mean transmittance of 0.61
and a frequency of occurrence of 22.1 %. Finally, the least frequent
sky conditions were thin clouds and cloudless conditions, which both
had a mean transmittance of 0.76 and occurrence frequencies of 3.5 %
and 2.4 %, respectively. For overcast conditions, lower global
irradiance was observed for stations closer to the ice edge, likely
attributable to the low surface albedo of dark open water and a
resulting reduction of multiple reflections between the surface and
cloud base. Using a wavelet-based multi-resolution analysis, power
spectra of the time series of atmospheric transmittance were compared
for single-station and spatially averaged observations and for
different sky conditions. It is shown that both the absolute magnitude
and the scale dependence of variability contains characteristic
features for the different sky conditions.
Quantifying the role of clouds in the earth's radiation budget is essential for improving our understanding of the drivers and feedback mechanisms of climate change. This holds in particular for the ...Arctic, the region currently undergoing the most rapid changes. This region, however, also poses significant challenges to remote-sensing retrievals of clouds and radiative fluxes, introducing large uncertainties in current climate data records. In particular, low-level stratiform clouds are common in the Arctic but are, due to their low altitude, challenging to observe and characterize with remote-sensing techniques. The availability of reliable ground-based observations as reference is thus of high importance. In the present study, radiative transfer simulations using state-of-the-art ground-based remote sensing of clouds are contrasted with surface radiative flux measurements to assess their ability to constrain the cloud radiative effect. Cloud radar, lidar, and microwave radiometer observations from the PS106 cruise in the Arctic marginal sea ice zone in summer 2017 were used to derive cloud micro- and macrophysical properties by means of the instrument synergy approach of Cloudnet. Closure of surface radiative fluxes can only be achieved by a realistic representation of the low-level liquid-containing clouds in the radiative transfer simulations. The original, most likely erroneous, representation of these low-level clouds in the radiative transfer simulations led to errors in the cloud radiative effect of 54 W m−2. In total, the proposed method could be applied to 11 % of the observations. For the data, where the proposed method was utilized, the average relative error decreased from 109 % to 37 % for the simulated solar and from 18 % to 2.5 % for the simulated terrestrial downward radiative fluxes at the surface. The present study highlights the importance of jointly improving retrievals for low-level liquid-containing clouds which are frequently encountered in the high Arctic, together with observational capabilities both in terms of cloud remote sensing and radiative flux observations. Concrete suggestions for achieving these goals are provided.
For understanding Arctic climate change, it is critical to quantify and address uncertainties in climate data records on clouds and radiative fluxes derived from long-term passive satellite ...observations. A unique set of observations collected during the PS106 expedition of the research vessel Polarstern (28 May to 16 July 2017) by the OCEANET facility, is exploited here for this purpose and compared with the CERES SYN1deg ed. 4.1 satellite remote-sensing products. Mean cloud fraction (CF) of 86.7 % for CERES SYN1deg and 76.1 % for OCEANET were found for the entire cruise. The difference of CF between both data sets is due to different spatial resolution and momentary data gaps, which are a result of technical limitations of the set of shipborne instruments. A comparison of radiative fluxes during clear-sky (CS) conditions enables radiative closure (RC) for CERES SYN1deg products by means of independent radiative transfer simulations. Several challenges were encountered to accurately represent clouds in radiative transfer under cloudy conditions, especially for ice-containing clouds and low-level stratus (LLS) clouds. During LLS conditions, the OCEANET retrievals were particularly compromised by the altitude detection limit of 155 m of the cloud radar. Radiative fluxes from CERES SYN1deg show a good agreement with ship observations, having a bias (standard deviation) of −6.0 (14.6) and 23.1 (59.3) W m−2 for the downward longwave (LWD) and shortwave (SWD) fluxes, respectively. Based on CERES SYN1deg products, mean values of the radiation budget and the cloud radiative effect (CRE) were determined for the PS106 cruise track and the central Arctic region (70–90∘ N). For the period of study, the results indicate a strong influence of the SW flux in the radiation budget, which is reduced by clouds leading to a net surface CRE of −8.8 and −9.3 W m−2 along the PS106 cruise and for the entire Arctic, respectively. The similarity of local and regional CRE supports the consideration that the PS106 cloud observations can be representative of Arctic cloudiness during early summer.
Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)(3) project was established in 2016 (www.ac3-tr.de/). It comprises modeling and ...data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, 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. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric-ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
The modification of an existing cloud property retrieval scheme for
the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument
on board the geostationary Meteosat satellites is described ...to utilize
its high-resolution visible (HRV) channel for increasing the spatial
resolution of its physical outputs. This results in products with a
nadir spatial resolution of 1×1 km2 compared to
the standard 3×3 km2 resolution offered by the
narrowband channels. This improvement thus greatly reduces the
resolution gap between current geostationary and polar-orbiting
meteorological satellite imagers. In the first processing step,
cloudiness is determined from the HRV observations by a
threshold-based cloud masking algorithm. Subsequently, a linear model
that links the 0.6 µm, 0.8 µm, and HRV
reflectances provides a physical constraint to incorporate the spatial
high-frequency component of the HRV observations into the retrieval of
cloud optical depth. The implementation of the method is described,
including the ancillary datasets used. It is demonstrated that the
omission of high-frequency variations in the cloud-absorbing
1.6 µm channel results in comparatively large
uncertainties in the retrieved cloud effective radius, likely due to
the mismatch in channel resolutions. A newly developed downscaling
scheme for the 1.6 µm reflectance is therefore applied
to mitigate the effects of this scale mismatch. Benefits of the
increased spatial resolution of the resulting SEVIRI products are
demonstrated for three example applications: (i) for a convective
cloud field, it is shown that significantly better agreement between
the distributions of cloud optical depth retrieved from SEVIRI and
from collocated MODIS observations is achieved. (ii) The temporal
evolution of cloud properties for a growing convective storm at
standard and HRV spatial resolutions are compared, illustrating an
improved contrast in growth signatures resulting from the use of the
HRV channel. (iii) An example of surface solar irradiance, determined
from the retrieved cloud properties, is shown, for which the HRV channel
helps to better capture the large spatiotemporal variability induced
by convective clouds. These results suggest that incorporating the HRV
channel into the retrieval has potential for improving Meteosat-based
cloud products for several application domains.
Abstract Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC) 3 project was established in 2016 ( www.ac3-tr.de/ ). It comprises ...modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, 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. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
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