Life Cycle Characteristics of MCSs in Middle East China Tracked by Geostationary Satellite and Precipitation Estimates

Abstract

By combining high temporal and spatial resolution Multifunctional Transport Satellite-1R (MTSAT-1R) infrared (IR) images and precipitation data from the Climate Prediction Center morphing technique (CMORPH), this study tracked mesoscale convective systems (MCSs) from May to August in 2008 and 2009 in the middle of east China with an automatic tracking algorithm based on an areal overlapping methodology. This methodology is adjusted to include those MCSs with a relative weak intensity before formation. The unique advantage of combining high temporal and spatial resolution geostationary satellite brightness temperature images and the precipitation measurements for tracking MCSs is that the cloud-top height along with the coverage and the precipitation intensity can be well identified. Results showed that the MCSs formed most frequently in the southwest Henan Province and at the border of four provinces-Shandong, Henan, Anhui, and Jiangsu-which is east of the convergence zone near the terrain's edge. Locations of the highest cloud tops and of the heaviest precipitation rates did not always match. In addition, the MCSs in the study region tended to first reach the maximum precipitation rate, followed soon by the minimum brightness temperature, then the maximum associated precipitation area, and finally the maximum in system area.

Mesoscale Convective Systems in the Asian Monsoon Region From Advanced Himawari Imager: Algorithms and Preliminary Results

“…Due to the good correspondence between brightness temperature (BT) of infrared channel (at around 11 μm) from satellite and gauge-based rain rate (Vicente et al, 1998), the BT at this infrared channel has been widely used to identify pMCSs from satellite images in numerous previous works (e.g., Laing et al, 2008;Mathon et al, 2002;Mathon & Laurent, 2001). Interestingly, the BT threshold varies substantially, ranging from 208 to 258 K (Ai et al, 2016;Hodges & Thorncroft, 1997;Machado et al, 1998;Rafati & Karimi, 2017). As suggested by Arkin and Meisner (1987), cold cloud tops with BT lower than 235 K present the best correlations with tropical rainfall.…”

“…For instance, infrared data from the Geostationary Operational Environmental Satellite have been commonly applied to explore the initiation, propagation, and regional variations in South and North America (e.g., Anabor et al, ; Durkee & Mote, ; Mecikalski et al, ), and the Meteosat Second Generation (MSG) has been extensively used in characterizing the MCSs in Europe and Africa (e.g., Feidas, ; Klein et al, ; Senf et al, ). In the Asian monsoon region, the detailed survey with regard to spatial distributions and lifecycles of MCSs was mainly conducted by Fengyun‐2 geostationary meteorological satellite (e.g., Ai et al, ; J. Li et al, ; X. Yang et al, ). Besides, the polar‐orbiting satellites (e.g., Yuan & Houze, ), the Tropical Rainfall Measuring Mission (e.g., Choudhury et al, ; Jaramillo et al, ), and the active remote sensing satellites such as Cloudsat (e.g., Yuan et al, ) also provide extra sources to examine the MCSs.…”

“…For instance, infrared data from the Geostationary Operational Environmental Satellite have been commonly applied to explore the initiation, propagation, and regional variations in South and North America (e.g., Anabor et al, 2008;Durkee & Mote, 2010;Mecikalski et al, 2008), and the Meteosat Second Generation (MSG) has been extensively used in characterizing the MCSs in Europe and Africa (e.g., Feidas, 2017;Klein et al, 2018;Senf et al, 2015). In the Asian monsoon region, the detailed survey with regard to spatial distributions and lifecycles of MCSs was mainly conducted by Fengyun-2 geostationary meteorological satellite (e.g., Ai et al, 2016;J. Li et al, 2012;X.…”

Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery

“…The evolution of convective rainfall is of special interest in this context, since it is not only related to higher local rainfall intensities than stratiform rainfall but also has been found to be highly sensitive to atmospheric warming, significantly exceeding the Clausius‐Clapeyron scaling of 7% per degree temperature rise (Berg et al, ; Lenderink et al, ). Even though deep convection does not cause the majority of extreme rainfall events in all regions of the world, especially where orographic forcing or atmospheric rivers play a strong role for the atmospheric moisture content (e.g., Ai et al, ; Liu & Zipser, ; Sohn et al, ), more than 70% of the global rainfall over land originates from systems with deep convection (Xu & Zipser, ).…”

Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

“…One simple method is using a fixed brightness temperature (T b ) threshold for the IR window channel centered near 11 μm. The fixed T b is widely used in the life cycle study of weather systems containing DCCs [Machado et al, 1998;Mathon and Laurent, 2001;Ai et al, 2016]. However, the optimal threshold varies with the latitude, longitude, and the composition of the cloud top and should be determined from research based on different studying regions and periods [Mapes and Houze, 1993;Aumann et al, 2011].…”