The Spatial and Temporal Organization of Deep Convective Systems and Its Impacts on the Production of Anvil Clouds

Abstract. This paper presents a comparison of lidar ratios and volume extinction coefficients in tropical ice clouds, retrieved using observations from two instruments: the 532-nm Cloud Physics Lidar (CPL), and the in-situ Cloud Integrating Nephelometer (CIN) probe. Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements up to 17 km. Coincident observations from two cases of ice clouds located on top of deep convective systems are compared. First, lidar ratios are retrieved from CPL observations of attenuated backscatter, using a retrieval algorithm for opaque cloud similar to one used in the soon-to-be launched CALIPSO mission, and compared to results from the regular CPL algorithm. These lidar ratios are used to retrieve extinction coefficient profiles, which are compared to actual observations from the CIN in-situ probe, putting the emphasis on their vertical variability. When observations coincide, retrievals from both instruments are very similar. Differences are generally variations around the average profiles, and general trends on larger spatial scales are usually well reproduced. The two instruments agree well, with an average difference of less than 11% on optical depth retrievals. Results suggest the CALIPSO Deep Convection algorithm can be trusted to deliver realistic estimates of the lidar ratio, leading to good retrievals of extinction coefficients.

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Characteristics of Deep Convective Systems and Initiation during Warm Seasons over China and Its Vicinity

Remote Sensing ◽

10.3390/rs13214289 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4289

Author(s):

Yang Li ◽

Yubao Liu ◽

Yun Chen ◽

Baojun Chen ◽

Xin Zhang ◽

...

Keyword(s):

Tibetan Plateau ◽

South China ◽

Warm Season ◽

Statistical Characteristics ◽

The Tibetan Plateau ◽

Spatiotemporal Resolution ◽

Convective Systems ◽

Seasonal And Diurnal Variations ◽

Deep Convective Systems ◽

Guizhou Plateau

The spatiotemporal statistical characteristics of warm-season deep convective systems, particularly deep convective systems initiation (DCSI), over China and its vicinity are investigated using Himawari-8 geostationary satellite measurements collected during April-September from 2016 to 2020. Based on a satellite brightness temperature multiple-threshold convection identification and tracking method, a total of 47593 deep convective systems with lifetimes of at least 3 h were identified in the region. There are three outstanding local maxima in the region, located in the southwestern, central and eastern Tibetan Plateau and Yunnan-Guizhou Plateau, followed by a region of high convective activities in South China. Most convective systems are developed over the Tibetan Plateau, predominantly eastward-moving, while those developed in Yunnan-Guizhou Plateau and South China mostly move westward and southwestward. The DSCI occurrences become extremely active after the onset of the summer monsoon and tend to reach a maximum in July and August, with a diurnal peak at 11–13 LST in response to the enhanced solar heating and monsoon flows. Several DCSI hotspots are identified in the regions of inland mountains, tropical islands and coastal mountains during daytime, but in basins, plains and coastal areas during nighttime. DCSI over land and oceans exhibits significantly different sub-seasonal and diurnal variations. Oceanic DCSI has an ambiguous diurnal variation, although its sub-seasonal variation is similar to that over land. It is demonstrated that the high spatiotemporal resolution satellite dataset provides rich information for understanding the convective systems over China and vicinity, particularly the complex terrain and oceans where radar observations are sparse or none, which will help to improve the convective systems and initiation nowcasting.

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Deep Convective Systems Observed by A-Train in the Tropical Indo-Pacific Region Affected by the MJO

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-12-057.1 ◽

2013 ◽

Vol 70 (2) ◽

pp. 465-486 ◽

Cited By ~ 20

Author(s):

Jian Yuan ◽

Robert A. Houze

Keyword(s):

Large Scale ◽

Deep Convection ◽

Active Phase ◽

Maximum Height ◽

Pacific Region ◽

Convective Envelope ◽

Convective Systems ◽

Mesoscale Convective ◽

Deep Convective Systems ◽

Cloud Tops

Abstract In the Indo-Pacific region, mesoscale convective systems (MCSs) occur in a pattern consistent with the eastward propagation of the large-scale convective envelope of the Madden–Julian oscillation (MJO). MCSs are major contributors to the total precipitation. Over the open ocean they tend to be merged or connected systems, while over the Maritime Continent area they tend to be separated or discrete. Over all regions affected by the MJO, connected systems increase in frequency during the active phase of the MJO. Characteristics of each type of MCS (separated or connected) do not vary much over MJO-affected regions. However, separated and connected MCSs differ in structure from each other. Connected MCSs have a larger size and produce less but colder-topped anvil cloud. For both connected and separated MCSs, larger systems tend to have colder cloud tops and less warmer-topped anvil cloud. The maximum height of MCS precipitating cores varies only slightly, and the variation is related to sea surface temperature. Enhanced large-scale convection, greater frequency of occurrence of connected MCSs, and increased midtroposphere moisture coincide, regardless of the region, season, or large-scale conditions (such as the concurrent phase of the MJO), suggesting that the coexistence of these phenomena is likely the nature of deep convection in this region. The increase of midtroposphere moisture observed in all convective regimes during large-scale convectively active phases suggests that the source of midtroposphere moisture is not local or instantaneous and that the accumulation of midtroposphere moisture over MJO-affected regions needs to be better understood.

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Observations of tropical precipitating clouds ranging from shallow to deep convective systems

Geophysical Research Letters ◽

10.1029/2006gl026547 ◽

2006 ◽

Vol 33 (16) ◽

Cited By ~ 38

Author(s):

Hirohiko Masunaga ◽

Christian D. Kummerow

Keyword(s):

Convective Systems ◽

Deep Convective Systems ◽

Precipitating Clouds

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The airport-sCAle seveRe weather nowcastinG prOject (CARGO)

10.5194/egusphere-egu2020-15177 ◽

2020 ◽

Author(s):

Riccardo Biondi ◽

Pierre-Yves Tournigand ◽

Enrico Solazzo ◽

Eugenio Realini ◽

Corrado Cimarelli ◽

...

Keyword(s):

Water Vapour ◽

Heavy Rain ◽

Severe Weather ◽

Time Range ◽

Atmospheric Parameter ◽

Atmospheric Conditions ◽

Temporal Behaviour ◽

Convective Systems ◽

Integrated Water Vapour ◽

Deep Convective Systems

Monitoring and predicting extreme atmospheric events, such as deep convective systems, is very challenging especially when they develop locally in a short time range. Despite the great improvement in model parametrization and the use of satellite measurements, there are still large uncertainties on the knowledge of the dynamical processes of deep convective systems at local scale.We use an innovative approach integrating a dense network of in situ measurements and satellite-based observations/products for the improvement of meteorological nowcasting at airport spatial scale focusing on the Malpensa airport (Italy). We add to the standard atmospheric parameters analysis, the information of integrated water vapour and lightning spatio-temporal behaviour (potential heavy rain precursors) during heavy rain phenomena detected by meteorological radars. The study is based on the anomaly of each atmospheric parameter during a convective event in comparison to its climatology in non-pre-convective environment, so that we are able to detect the variation with respect to the &#8220;standard&#8221; conditions. The ground based GNSS receivers (allowing the determination of the integrated water vapour trend before and during the storm), together with the lightning detectors, the weather stations (providing the trend of temperature, humidity and wind fields), the radiosondes and the GNSS radio occultations (allowing the estimation of vertical profiles of temperature, pressure and humidity) provide information on the pre-convective and non-pre-convective environment as a 3D picture of the atmospheric conditions.The final goal is the test of a severe weather events nowcasting algorithm with high spatial resolution, and based on neural networks, for improving aviation safety. This is followed by the development of a user-friendly tailored final product, easily understandable by the Air Traffic Management stakeholder.We have collected more than 600 cases suitable to develop the neural network algorithm. We show here the algorithm implementation and the meteorological characterization of deep convection usually developing on the Malpensa airport area.

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