The spatio-temporal distribution of mesoscale convective complexes over the Southeastern Western Siberia.pdf Introduction In the second half of the 20th century and the beginning of the 21st century, in the regions of Northern Eurasia, an increase in the proportion of convective clouds was noted [Chernokulsky et al., 2011]. The continuation of present trends could lead to an increase in frequency of associated hazardous phenomena such as hail, intense showers, squalls, etc. Mesoscale convective systems (MCS), and especially the subtype termed “mesoscale convective complexes” (MCCs) [Vel'tishchev, Stepanenko, 2006] are a severe manifestation of convective cloudiness. The MCC is a complex of cumulonimbus clouds united by a common quasi-oval anvil [Maddox, 1980; Houze, 2004, 2014]. Infrared images of MCCs have the following characteristics: the area of more or less continuous cloud cover with the upper boundary temperature below -32 °С is not less than 105 km2, and the area of the inner region with upper boundary temperature below -52 °С is not less than 5 x 104 km2. The specified dimensions are retained for 6 hours or more. The lifetime of the MCC is about 16 hours, but in some cases can last more than a day. Most MCCs exhibit a nocturnal life cycle that begins in mid to late midday, reaches its peak after midnight, and ends shortly after dawn [Laing, Fritsch, 1997]. Known for its production of severe weather and copious rainfall [Maddox, 1980; Fritsch et al., 1986; МеАта^, Cotton, 1989], a MCC typically forms in association with a weak mid-tropospheric short-wave trough and a weak surface front or outflow boundary. Its environment often exhibits pronounced low-level temperature and moisture advection in association with a well-defined low-level jet [Cotton, 1989; Augustine, Howard, 1991]. MCCs can be found in different geographic regions [Maddox, 1980; Velasco, Fritch, 1987; Augustine, Howard, 1991; Laing, Fritsch, 1997; Houze, 2004, 2014], including in Western Siberia [Kuzhevskaya et al., 2018; Zhukova et al., 2019]. However, in temperate latitudes, their sizes may be significantly smaller than those described for tropical regions. MCCs are known for generating hazardous weather conditions and heavy rainfall [Maddox, 1980; Fritsch et al., 1986; McAnelly, 1989]. It is widely known that MCCs significantly change the environment in which they develop [Fritsch, Maddox, 1981; Wetzel et al., 1983; Augustine, Zipser, 1987; Johnson, Bartels, 1992], and that they play an important role in initiating subsequent convective weather events [Fritsch et al., 1994]. MCC studies over the temperate latitudes of the United States [Maddox, 1980; Augustine, Howard, 1991; Houze, 2004] revealed a tendency for their formation from the anticyclonic side of a wide and relatively weak frontal zone. It is also known that the presence of synoptic heterogeneity is necessary to ensure the convergence of air flows and the inflow of a large amount of moisture into the lower atmosphere. For North America, such conditions are easily achievable due to the proximity of the Atlantic Ocean. The territory of the south of Western Siberia is characterized by a complex terrain, which influences the development and evolution of convective clouds, as well as the nature of the associated hazardous phenomena. However, this complexity makes it difficult to predict atmospheric convection. Earlier studies analyzed the temporal and spatial dynamics of atmospheric instability characteristics over the territory of Western Siberia in the presence of registered hazardous convective phenomena such as thunderstorms and hail [Gorbatenko et al., 2020; Gorbatenko, Konstantinova, 2011], and also for thunderstorms in the cold season [Zhokhova et al., 2018]. Studies of the height of cumulonimbus clouds were carried out in the presence of extensive thunderstorms, hail, and squalls [Gorbatenko et al., 2020; Ananova et al., 2007]. It has been noticed that over the last decade, the boundary of active convection, assessed by the temperature and humidity characteristics of the atmosphere, has shifted to the north. There has also been an increase in the duration of the thunderstorm season and the number of days with thunderstorms per year, as well as the number of days with prolonged hail and large diameter hail [Gorbatenko et al., 2020; Kuzhevskaia et al., 2019]. Using information from meteorological satellites, the cloudiness was measured diagnosed during the periods of heavy precipitation [Ku-zhevskaya et al., 2018] and approaches to the numerical modeling of the spatial localization of convective cells were developed [Nechepurenko et al., 2016]. The synoptic situations favorable to MCC formation and the production of hazardous phenomena were determined; the state of the atmosphere was assessed using the instability indices KIND and LIFT. It was noted that the MCC is formed during periods of both average and low degree of atmospheric instability [Zhukova et al., 2019]. In addition, estimates were obtained of the influence of powerful convective clouds, including MCC, as well as associated adverse and hazardous phenomena on the electrical state of the atmospheric surface layer in southern Western Siberia [Nagorskiy et al., 2014; Pustovalov, Nagorskiy, 2016, 2018a, 2018b; Nagorskiy et al., 2019]. The present study is aimed at assessing the spatiotemporal distribution and typical characteristics of the MCCs in southeastern Western Siberia. The assessment of the repeatability and characteristics of the MCCs was carried out for all recognized cases and also separately for the MCCs of frontal and air mass origin. This separate analysis is important because of significant differences in the conditions of formation, structure and form of MCCs of these two genetic types [Maddox, 1983; Houze, 2004; Zhukova et al., 2019]. Description of the study area The study was carried out for an area in southern Western Siberia, located in the central part of Eurasia, far from any oceanic coastline. The study area is mainly represented by flat terrain - the Vasyugan, Ket-Tymkaya, Ishim and Kulundinskaya plains and the Bar-abinskaya lowland (Fig. 1). The exception is the southeastern part of the territory, which is characterized by the mountainous Salair Ridge, Kuznetsk Alatau, as well as the northern part of the Altai Mountains and the western part of the Western Sayan. The northern part of the study area is heavily swampy and includes the largest swamp system in the northern hemisphere - the Vasyugan Swamp [Gorbatenko, Tunaev et al., 2020]. According to the authors [Tunaev, Gorbatenko, 2018], the Vasyugan Swamp plays a significant role in the formation and development of young cyclones, and the maximum contribution of swamps is noticeable in the summer. Above the Vasyugan Swamps, there is a so-called energy “recharge” and a significant increase in the moisture content and convective potential of the atmosphere. Russian Federation u Western Siberia u Tomsk Oblast, Omsk Oblast, Novosibirsk Oblast, Kemerovo Oblast, Altai Krai, Altai Republic 60 58 Ф KG ■a 56 □ -i 54 52 50 OTyumen rgan т t Krasnoyarsk О Ke t- Тут Tomsk о Plain Lowland Barnaul 4 ° Kemerovo Novosibisk О О Longitude Fig. 1. Location of the study area Рис. 1. Расположение территории исследования The main part of the study area is occupied by a unique landscape zone - the forest-bog zone of Western Siberia, with swamp systems covering about 40 %, and in some areas, up to 90 % of the area. To the south of the forest-bog zone, there is a forest-steppe zone, which is also characterized by high (up to 25 %) boggy terrain and a large number of lakes. The influx of a large amount of moisture into the atmosphere in this region occurs with the arrival of transformed air masses of southern Mediterranean cyclones, but could also be due to evaporation directly from the underlying boggy (water-rich) surface. Based on the classical ideas about the climate pattern in Southern Siberia in summer, cyclonic circulation should dominate here. Observations of the last two decades have revealed features in the summer circulation over the regions of Siberia. An increase in the frequency of occurrence of meridional southerly flows in summer over Western Siberia is noted [Kononova, 2015; Podne-besnykh, Ippolitov, 2019]. Such synoptic situations contribute to the formation of abnormally warm air over vast areas, which, given the existing synoptic heterogeneity, contribute to the development of powerful cumulonimbus clouds and even MCCs. Data used and research methodology RGB images of clouds [https://worldview. earthda-ta.nasa.gov/] and second-level processing products MODATML2 and MYDATML2 (resolution 5x5 km) [http://ladsweb.nascom.nasa.gov/], obtained from the MODIS spectroradiometer data, were selected. The MODIS spectroradiometer (Moderate Resolution Imaging Spectroradiometer) is one of the key instruments on the Terra and Aqua spacecraft [Qu et al., 2006]. Additionally, the synoptic charts with frontal analysis [https://meteoinfo.ru/mapsynop] were used. The first stage of the study was based on satellite images, and a visual interpretation of MCSs of an asymmetric type was carried out [Vel'tishchev, Stepanenko, 2006; Houze, 2014], these have a quasi-oval shape and a cross section of at least 50 km. Over the period from 2010 to 2019, more than 460 such cases were recorded. Based on synoptic maps [https://meteoinfo.ru/ mapsyn-op], the noted MCS cases were divided into air mass and frontal genetic types. A distinguishing characteristic of the frontal MCS is the entry into the cloudy band of a warm or cold front, which is detected near the occlusion point from the side of the warm air mass. Air mass MCSs are interpreted as single cloud structures, occurring in clusters of Cumulonimbus clouds, in the frontal zones of the cold front and zones of fully occluded cloud systems. The timing of selected MCSs was identified and the coordinates of their centers were determined. Comparison of selected cases of asymmetric MCS passage in the southeast of Western Siberia (Fig. 2, a) with MCC over different regions of the globe (Fig. 2, b, c) showed that despite the fact that the selected convective systems, as a rule, do not reach the threshold size established for the MCC [Vel'tishchev, Stepanenko, 2006; Houze, 2014], in terms of their other characteristics and characteristics of the accompanying atmospheric phenomena [Zhukova et al., 2019], they generally correspond to MCCs. Thus, the authors made the assumption that the selected MCS of an asymmetric type in the southeast of Western Siberia, in general, can be considered MCCs, however, due to regional features, their sizes are somewhat inferior to the MCCs in the tropical belt and the threshold sizes described in [Vel'tishchev, Stepanenko, 2006; Houze, 2014], are not fully applicable to the study area. Thus, it is necessary to develop new criteria for identifying MCC in the southeast of Western Siberia. The second stage of the study involved formalization of the recognized MCS cases and the calculation of their morphological and microphysical characteristics based on the data of MODIS cloud products and according to the methodology developed by the authors (see below). The MODATML2 / MYDATML2 [http://ladsweb. nas-com.nasa.gov/] files were selected for the transit date and coordinates of the selected MCS of the asymmetric type, containing two-dimensional data arrays (cells of which are 5 x 5 km in size) with cloud products, the following of which were used in this work: Cloud Optical Thickness (COT); Cloud Effective Radius (CER); Cloud Top Height (CTH); Cloud Water Path (CWP); Cloud Top Pressure (CTP); Cloud Top Temperature (CTT). Based on MODIS cloud products, a mask was constructed consisting of pixels of 5x5 km, with the following recognized conditions: СТТ < 200 K (-32 °С) [Maddox, 1980], СОТ > 30. For each case, the mask area was computed as the sum of all pixels within the mask multiplied by the area of one pixel (25 km2). The lengths of the mask chords along latitude (llat(i)) and longitude (llon(i)) were also calculated as the product of the sum of pixels along the meridian and parallel, respectively, multiplied by the pixel size (5 km). The values llat and llon corresponding to the 95th percentile were taken as the lengths of the entire convective complex along latitude and longitude - Llat and Llon. In addition, based on the values of the products CTH, CWP, CER, CTT, CTP in pixels falling inside the mask, the average values of the upper boundary height, integral moisture content, effective particle radius, temperature and pressure at the upper boundary of the MCC were calculated. The scheme for performing these calculations is shown in Figure 3. To exclude small convective complexes from further consideration, additional filtering of cases was carried out. We eliminated those convective complexes with a mask area less than a certain threshold area (SH). Two variants of SH were used: 1) 5,000 km2 (1/20 of the threshold area determined for tropical regions [Maddox, 1980]); 2) 10,000 km2 (1/10 of the threshold area determined for tropical regions [Maddox, 1980]). a b c 78 79 Longitude 11 12 13 Longitude Novosibirsk Oblast imena ♦ Kedro' Kolpashevo Tomsk Oblast • Barabinsk ф ■o 58

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