Browsing by Subject "snowfall"

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  • von Lerber, Annakaisa (Finnish Meteorological Institute, 2018)
    Finnish Meteorological Institute Contributions 143
    Globally, snow influences Earth and its ecosystems in several ways by having a significant impact on, e.g., climate and weather, Earth radiation balance, hydrology, and societal infrastructures. In mountainous regions and at high latitudes snowfall is vital in providing freshwater resources by accumulating water within the snowpack and releasing the water during the warm summer season. Snowfall also has an impact on transportation services, both in aviation and road maintenance. Remote sensing instrumentation, such as radars and radiometers, provide the needed temporal and spatial coverage for monitoring precipitation globally and on regional scales. In microwave remote sensing, the quantitative precipitation estimation is based on the assumed relations between the electromagnetic and physical properties of hydrometeors. To determine these relations for solid winter precipitation is challenging. Snow particles have an irregular structure, and their properties evolve continuously due to microphysical processes that take place aloft. Hence also the scattering properties, which are dependent on the size, shape, and dielectric permittivity of the hydrometeors, are changing. In this thesis, the microphysical properties of snowfall are studied with ground-based measurements, and the changes in prevailing snow particle characteristics are linked to remote sensing observations. Detailed ground observations from heavily rimed snow particles to openstructured low-density snowflakes are shown to be connected to collocated triple-frequency signatures. As a part of this work, two methods are implemented to retrieve mass estimates for an ensemble of snow particles combining observations of a video-disdrometer and a precipitation gauge. The changes in the retrieved mass-dimensional relations are shown to correspond to microphysical growth processes. The dependence of the C-band weather radar observations on the microphysical properties of snow is investigated and parametrized. The results apply to improve the accuracy of the radar-based snowfall estimation, and the developed methodology also provides uncertainties of the estimates. Furthermore, the created data set is utilized to validate space-borne snowfall measurements. This work demonstrates that the C-band weather radar signal propagating through a low melting layer can significantly be attenuated by the melting snow particles. The expected modeled attenuation is parametrized according to microphysical properties of snow at the top of the melting layer.
  • Li, Haoran; Moisseev, Dmitri; von Lerber, Annakaisa (2018)
    As an ice particle grows by riming its shape is expected to change, resulting in a more spherical particle at the later stages of riming. This conceptual model is at the core of the current ice microphysical schemes and used for dual-polarization radar observation based classification of hydrometeors. A quantitative relation between riming and shapes of snowflake aggregates, however, has not been established yet. This study aims to derive this relation by using surface-based precipitation and coinciding dual-polarization radar observations. The observations were collected during four winter seasons, 49 snowstorms, at University of Helsinki measurement station in Hyytiala, Finland. Results show that relation between the differential reflectivity and reflectivity-weighted rime mass fraction is not monotonic and depends on reflectivity-weighted mean diameter. This behavior can be explained by the opposing effects of riming on dual-polarization radar observations. Riming increases particle bulk density, which leads to more pronounced dual-polarization radar signatures. As riming progresses the aspect ratio of snowflake increases slowly until the rime mass fraction value reaches a certainty value after which the aspect ratio increases more rapidly. Finally, coutilization of Z(e), Z(dr), and K-dp for inferring riming fraction is analyzed.
  • Moiseev, Dmitry; Lautaportti, Susanna; Alku, Laura; Tabakova, Ksenia; O'Connor, Ewan; Leskinen, Matti; Kulmala, Markku (2019)
    Abstract: Eleven years of dual-polarization weather radar data, complemented by satellite and lidar observations, were used to investigate the origin of areas of localized intensification of precipitation spotted in the vicinity of Helsinki-Vantaa airport. It was observed that existing precipitation is enhanced locally on spatial scales from a few kilometers to several tens of kilometers. The precipitation intensity in these localized areas was 6-14 times higher than the background large-scale precipitation rate. Surface observations and dual-polarization radar data indicate that snowflakes within the ice portion of the falling precipitation in the intensification regions are larger and more isotropic than in the surrounding precipitation. There appears to be an increase in the ice particle number concentration within the intensification region. The observed events were linked to arriving or departing air traffic. We advocate that the mechanism responsible for intensification is aircraft-produced ice particles boosting the aggregation growth of snowflakes. Plain Language Summary: By analyzing 11 years of dual-polarization weather radar observations in the Helsinki region, we have discovered that airplanes landing in or departing from the Helsinki-Vantaa airport could locally increase precipitation rate by as much as 14 times. The observed phenomenon is related to the hole-punch clouds, which are also forming with the help of airplanes. The reported observations allow us to have a better understanding of precipitation formation processes that take place in ice and mixed phase clouds. They show that falling ice crystals from upper clouds could seed lower clouds and therefore increase rain or snowfall intensity through the process called snowflake aggregation. During snowflake aggregation bigger faster falling particles are formed by ice particles colliding and sticking together.
  • Moisseev, Dmitri; von Lerber, Annakaisa; Tiira, Jussi (2017)
    Ground-based observations of ice particle size distribution and ensemble mean density are used to quantify the effect of riming on snowfall. The rime mass fraction is derived from these measurements by following the approach that is used in a single ice-phase category microphysical scheme proposed for the use in numerical weather prediction models. One of the characteristics of the proposed scheme is that the prefactor of a power law relation that links mass and size of ice particles is determined by the rime mass fraction, while the exponent does not change. To derive the rime mass fraction, a mass-dimensional relation representative of unrimed snow is also determined. To check the validity of the proposed retrieval method, the derived rime mass fraction is converted to the effective liquid water path that is compared to microwave radiometer observations. Since dual-polarization radar observations are often used to detect riming, the impact of riming on dual-polarization radar variables is studied for differential reflectivity measurements. It is shown that the relation between rime mass fraction and differential reflectivity is ambiguous, other factors such as change in median volume diameter need also be considered. Given the current interest on sensitivity of precipitation to aerosol pollution, which could inhibit riming, the importance of riming for surface snow accumulation is investigated. It is found that riming is responsible for 5% to 40% of snowfall mass. The study is based on data collected at the University of Helsinki field station in Hyytiala during U.S. Department of Energy Biogenic Aerosols Effects on Clouds and Climate (BAECC) field campaign and the winter 2014/2015. In total 22 winter storms were analyzed, and detailed analysis of two events is presented to illustrate the study.
  • Luomaranta, Anna M; Aalto, Juha; Jylhä, Kirsti (2019)
    Snow conditions in high-latitude regions are changing in response to climate warming, and these changes are likely to accelerate as the warming proceeds. Here, we analyse daily gridded snow depth, temperature and precipitation data from Finland over the period 1961-2014 to discover the ongoing changes in monthly average snow depths (SN) and several snow-related indices. Our results indicate that regional differences of changes in snow conditions can be relatively large, even within such a small district as Finland. Moreover, the interannual variation of the various snow indices was found to be larger in southern Finland than in northern Finland. The largest decrease in snow depth occurred in the southern, western and central parts of Finland in late winter and early spring. This decrease was driven by increasing mixed and liquid precipitation and, especially in spring, increasing temperature. In northern Finland, the decreasing trend of snow depth was most evident in spring, but no change occurred during winter months, although the amount of solid precipitation was found to increase in December-February. In the same months, temperature and the amount of mixed and liquid precipitation increased, likely counteracting the effects of the increasing solid precipitation on snow depth. The annual maximum snow depth that typically occurs in March was found to decrease in over 85% of Finland's area, most strongly in western coastal areas. In almost half of Finland's area, this decrease occurred despite increasing solid precipitation. Our findings highlight the complexity of the responses of snow conditions to climatic variability in northern Europe.