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, and 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) 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 (R/V) 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 the R/V 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.

Abstract. The French–German Arctic research base AWIPEV (the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research – AWI – and the French Polar Institute Paul Emile Victor – PEV) at Ny-Ålesund, Svalbard, is a unique station for monitoring cloud-related processes in the Arctic. For the first time, data from a set of ground-based instruments at the AWIPEV observatory are analyzed to characterize the vertical structure of clouds. For this study, a 14-month dataset from Cloudnet combining observations from a ceilometer, a 94 GHz cloud radar, and a microwave radiometer is used. A total cloud occurrence of ∼81 %, with 44.8 % multilayer and 36 % single-layer clouds, was found. Among single-layer clouds the occurrence of liquid, ice, and mixed-phase clouds was 6.4 %, 9 %, and 20.6 %, respectively. It was found that more than 90 % of single-layer liquid and mixed-phase clouds have liquid water path (LWP) values lower than 100 and 200 g m−2, respectively. Mean values of ice water path (IWP) for ice and mixed-phase clouds were found to be 273 and 164 g m−2, respectively. The different types of single-layer clouds are also related to in-cloud temperature and the relative humidity under which they occur. Statistics based on observations are compared to ICOsahedral Non-hydrostatic (ICON) model output. Distinct differences in liquid-phase occurrence in observations and the model at different environmental temperatures lead to higher occurrence of pure ice clouds. A lower occurrence of mixed-phase clouds in the model at temperatures between −20 and −5 ∘C becomes evident. The analyzed dataset is useful for satellite validation and model evaluation.

For the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016-September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m 22 ; LW: 24.9 W m 22 ) and all-sky (SW: 25.4 W m 22 ; LW: 20.2 W m 22 ) situations. For monthly averages, uncertainties in the CRE are estimated to be small (;2 W m 22 ). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m 22 . The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m 22 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP . 5 g m 22 ) clearly contribute most to the shortwave surface CRE (70%-98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP . 0 g m 22 ; LWP , 5 g m 22 ) equally important or even dominating the signal in the longwave surface CRE.

Previously developed regression formulae for estimating body mass in dogs and wolves based on cranial and mandibular dimensions are evaluated using modern canid specimens of known weight at death. Some of these equations proved reliable, but others have large standard errors of estimate and likely produce unreliable mass estimates. New sets of equations for estimating body mass in dogs and wolves are produced using our datasets, including a set of equations developed from combining the dog and wolf biometric data into a single population. The resulting regression equations allow body mass to be estimated from a series of cranial and mandibular dimensions with relatively low errors. Further, our datasets include larger numbers of specimens of larger ranges of body mass than in these previous studies. When the equations are applied to a suite of dogs and one wolf from Eastern Siberia, several patterns emerge. First, hunter–gatherers' dogs in this region vary widely in terms of body size, even within a limited geographic area and time period. Some were quite large, similar in size to modern Siberian huskies. Second, pastoralists' dogs are less variable in terms of body mass, but this may reflect the nature of our samples. In particular, pastoralists' dogs nearly all were sacrificed juvenile dogs, some of which appear to have been eaten. These dogs seem to have been approached adult body size when they were selected for sacrifice. Finally, our findings help to highlight the need for further refinement in methods used to study ancient canid remains. Copyright © 2014 John Wiley & Sons, Ltd.

Body mass is a key biometric that is useful in interpreting many aspects of an animal's life history. For many species, including dogs and wolves, methods for estimating body mass are not well developed. This paper assesses the utility of using limb dimensions to predict body mass in dogs and North American wolves. Regression analyses are utilized here to explore the correlations between limb dimensions and body masses of modern dogs and wolves, all of known body mass at death. These analyses reveal that a number of limb end dimensions are correlated with body mass in both dogs and wolves. Regression formulae generated through the analyses appear to allow body masses to be predicted with relatively small margins of error, often less than 10%. Formulae are calculated for groups with and without juveniles. In some cases, the dimensions of the juvenile specimens plot distinctly from those of adults, indicating that regression formulae specifically for juvenile canids may be needed. The strength of the limb dimension correlations is then compared with that of regression formulae for dog and wolf cranio-mandibular dimensions. For the dogs, the cranio-mandibular dimensions appear to slightly out-perform the limb element dimensions in predicting body mass. The wolf limb dimensions, however, always appear to provide better predictions of body mass than do the skull dimensions. The newly developed regression formulae are applied to several Middle Holocene dog skeletons from Siberia for which previous body mass estimates are available, the latter based on cranial dimensions. These two sets of estimates are then compared. The overall results of our study indicate the need for further research, particularly with larger sample sizes, including more juvenile specimens. We also argue that work on body size estimation in single dog breeds may be warranted in some cases.