Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field CampaignpublishedVersio

The Christmas Storm 2016: Comparing Snow Observations and the Operational Forecast Model MEPS

Previous studies showed the importance to have information about the vertical distribution of precipitation to simulate snow and related cyclone development correctly in regional, mesoscale models. During Christmas 2016, an extreme storm affected the local infrastructure of Eastern, Southern, and Western Norway. In this thesis, the Christmas storm 2016 is investigated for snow observations and the operational forecast model at Haukeliseter (991 m above sea level), Norway. The WMO measurement site Haukeliseter is equipped with conventional meteorological instru- ments and a double fence snow gauge instrument to reduce wind effects and increase catch-ratios for frozen precipitation. In winter 2016/2017, three additional instruments were installed for a US National Science Foundation funded field campaign, to estimate snow water content in the column with the help of the optimal estimation retrieval. In November 2016, the AROME-MetCoOp ensemble prediction system (MEPS) became operational at the Norwegian Meteorological Institute. In this thesis, the extreme weather event is studied using European Centre for Medium-Range Weather Forecasts weather analysis, meteorological measurements, including double fence gauge and radar observations, optimal estimation retrieval, and MEPS. During 21 and 26 December 2016, two cyclones as well as frontal passages affected Norway. Ob- served frozen and liquid precipitation is associated with the cyclones and the fronts. The met- eorological analysis of surface properties from observations and MEPS forecasts agree on the passages of occlusions and warm sector. Wind speeds and surface precipitation amount are pre- dicted too high by MEPS (mean absolute error: up to 10 ms−1 and 15 mm) during the entire event with westerlies revealing a better agreement with observations than south-easterlies. A sensitivity study of the optimal estimation retrieval shows the advantage of using the Multi-Angular Snow- fall Camera to choose the correct particle habit. During the Christmas 2016 storm, the average difference between the double fence gauge observations and the retrieved surface amount for assumed rimed aggregates is less than −5 % for 12 h and 24 h surface snow accumulation. With longer lead time the average difference decreases between double fence gauge observations and forecasted precipitation amount for 12 h and 24 h accumulation (+135 % and +33 %). However, for 24 and 26 December 2016, the surface precipitation amount is predicted too high compared to double fence gauge observations (+60 %). Liquid precipitation was observed at Haukeliseter in the afternoon on 25 December 2016. MEPS initialisations 24 h and 48 h prior successfully simulate the thickness and duration of the liquid layer in the lower most atmosphere, but it predicts less snow water content (≤ 1.2 gm−3 ) than the profiles of retrieved snow profiles (≤ 1.5 gm−3 ). Local topography effects by the surrounding mountains lead to continuous snow patterns during strong westerlies and weak south-easterlies, show high amount of snow water content with a pulsing pattern. Finally, orography impacts on snow observations and model forecast are discussed

Impact of associative word learning on phonotactic processing in 6-month-old infants: A combined EEG and fNIRS study

During early language development native phonotactics are acquired in a ‘bottom-up’ fashion, relying on exquisite auditory differentiation skills operational from birth. Since basic lexico-semantic abilities have been demonstrated from 6 months onwards, ‘top-down’ influences on phonotactic learning may complement the extraction of transitional probabilities in phonotactic learning. Such a bidirectional acquisition strategy predicts, that familiarization with (proto)words should affect processing of untrained word-forms of similar phonological structure. We investigated 6-month-old infants undergoing an associative training to establish a pseudoword-pseudoobject link. Comparison between pre- and post-training responses to trained and untrained items allowed investigating training effects. Additionally phonotactic status (50% legal, 50% illegal with regard to German) allowed investigating influences of previous language experience. EEG and functional near-infrared spectroscopy (fNIRS) provided measures of electrophysiological and hemodynamic responses. We find evidence for a robust effect of associative training on pseudoword processing when presented in isolation. This transferred to untrained items. Previous linguistic experience showed a much weaker effect. Taken together the results suggest that sensitivity to phonotactic contrasts is present at 6 months, but that acceptance as lexical candidates is rapidly modulated when word forms following non-native phonotactics become potentially meaningful due to repeated exposure in a semantic context. Keywords: fNIRS, Phonotactics, Associative training, Language developmen

Snowfall model validation using surface observations and an optimal estimation snowfall retrieval

In the winter, orographic precipitation falls as snow in the mid to high latitudes where it causes avalanches, affects local infrastructure, or leads to flooding during the spring thaw. We present a technique to validate operational numerical weather prediction model simulations in complex terrain. The presented verification technique uses a combined retrieval approach to obtain surface snowfall accumulation and vertical profiles of snow water at the Haukeliseter test site, Norway. Both surface observations and vertical profiles of snow are used to validate model simulations from the Norwegian Meteorological Institute’s operational forecast system and two simulations with adjusted cloud microphysics. Retrieved surface snowfall is validated against measurements conducted with a double-fence automated reference gauge (DFAR). In comparison, the optimal estimation snowfall retrieval produces + 10.9% more surface snowfall than the DFAR. The predicted surface snowfall from the operational forecast model and two additional simulations with microphysical adjustments (CTRL and ICE-T) are overestimated at the surface with +41.0 %, +43.8 %, and +59.2 %, respectively. Simultaneously, the CTRL and ICE-T simulations underestimate the mean snow water path by -1071.4% and -523.7 %, respectively. The study shows that we would reach false conclusions only using surface accumulation or vertical snow water content profiles. These results highlight the need to combine ground-based in-situ and vertically-profiling remote sensing instruments to identify biases in numerical weather prediction

Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies

Coordinated observations of the water cycle of marine cold-air outbreaks in the European Arctic during the ISLAS 2022 field campaign

International audienceMarine cold-air outbreaks (mCAOs) are a characteristic type of high-impact weather in the European Arctic and are characterized by an intense water cycle where polar cloud processes play an important role. Model simulations and weather forecasts of mCAO events are challenging and associated with poor predictability. One reason is that processes related to the water cycle interact with one another on a wide range of scales. In regional models, some of these processes are resolved and others are fully or partly parameterised. To test and improve numerical weather prediction models, additional observations and novel types of measurements of water vapour are highly demanded. Stable water isotopes are an increasingly available measurement, allowing to trace sub-grid scale processes, and providing the potential to constrain the mass budget of the atmospheric water cycle during mCAO events. During the ISLAS2022 field experiment (21 March to 10 April 2022), the stable isotope composition of water vapour and liquid samples, cloud structures, and other meteorological parameters were collected between Svalbard and Northern Scandinavia on various measurement platforms. Airborne survey flights to Svalbard provided the ocean evaporation signature and subsequent processing of water vapour during mCAO conditions. During a number of flights, mCAO airmasses were repeatedly sampled over a course of hours to days, allowing to characterize their thermodynamic evolution as clouds were first forming, then glaciating and precipitating. In addition, vapour isotope and sea water isotope measurements were taken continuously onboard R/V Helmer Hanssen between Tromsø and the Greenland west coast. Finally, coordinated land-based measurement activity over Northern Norway and Sweden allowed collection of precipitation samples, thus closing the mass budget of the mCAO events. Furthermore, using buoyancy-controlled meteorological balloons launched from Ny Ålesund, we additionally obtained continuous in-situ measurements of the boundary-layer evolution during the mCAO. We provide an overview over the airborne and ground-based measurement activities during the campaign and provide several examples to highlight the potential of the stable water isotope measurements to constrain the water budget of mCAOs in conjunction with traditional meteorological observations

Multicolor flourescence in situ hybridization studies in multiple myeloma and monoclonal gammopathy of undetermined significance

The aim of the study was to test the multicolor fluorescence in situ hybridization technique (M-FISH) in seven multiple myeloma (MM) and eight monoclonal gammopathy (MGUS) patients. None of the eight MGUS patients had chromosomal abnormalities by conventional cytogenetics. In two of these patients structural abnormalities of chromosomes 2, 11 and 19 were found by M-FISH. However, these findings were not confirmed by conventional in situ hybridization. M-FISH only showed numerical chromosomal abnormalities in one out of the three MM cases with a normal karyotype. In the two MM cases with complex karyotype, M-FISH demonstrated the origin of the marker chromosomes. M-FISH is a useful technique to identify the origin of the marker chromosomes in MM. In contrast, MM or MGUS patients with normal karyotypes by conventional cytogenetics did not show structural abnormalities by M-FISH.Partially supported by Grants from the Spanish FIS (98/1161 amp; 01/ 1161), Council of Castilla y León (Sa 113/01). NCG was supported by a Grant from the University of Salamanca. JC was supported by a Grant from the University Autónoma of Barcelona.Peer Reviewe