Cloud characteristics over the rain-shadow region of North Central peninsular India during monsoon withdrawal and post-withdrawal periods

Morwal, Savita B.; Narkhedkar, S. G.; Padmakumari, B.; Maheskumar, R. S.; Kothawale, D. R.; Dani, K. K.; Burger, Roelof; Bruintjes, Roelof; Kulkarni, J. R.

doi:10.1007/s00382-015-2595-0

Cited by 15 publications

(6 citation statements)

References 58 publications

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“…Such deviations were attributed to truncations caused by merging and splitting effects (Cetrone & Houze, 2006). In general, storms in the Western Ghats have shorter mean lifetimes of about 46 min compared to echo durations of 88 min over eastern tropical Atlantic during Global Atmospheric Research Program's Atlantic Tropical Experiment (GATE) experiment (Houze & Cheng, 1977) and 72 min over the tropical western Pacific during Kwajalein experiment (Cetrone & Houze, 2006) but are near comparable to observed durations of 55 min over the rain-shadow region of north central peninsular India (Morwal et al, 2016).…”

Section: Convective Cell Lifetime and Its Propagationmentioning

confidence: 82%

“…Cetrone and Houze () have discussed that the physical and dynamical limitations on storm area truncates their distribution, generally at larger values. Previous studies by Lopez (), Houze and Cheng (), Potts et al (), Cetrone and Houze (), Cifelli et al (), Peter et al (), and Morwal et al () have shown that frequency distribution of storm area can be represented by a lognormal distribution. This also applies to large‐scale cloud clusters of the tropics as seen through satellite imagery (e.g., Mapes & Houze, ; Williams & Houze, ).…”

Section: Resultsmentioning

confidence: 99%

“…The Lagrangian approach includes convective storm-tracking algorithms such as the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) (Dixon & Wiener, 1993) and Storm Cell Identification and Tracking (Johnson et al, 1998). In the past, several studies examined radar-derived statistics of convection properties using the Lagrangian or object-oriented approach over different geographical regions (e.g., Cetrone & Houze, 2006;Chen et al, 2012Chen et al, , 2014Davini et al, 2011;Gauthier et al, 2010;Goudenhoofdt & Delobbe, 2013;Karklinsky & Morin, 2006;Lang et al, 2007;Lopez, 1976;May & Ballinger, 2007;Peter et al, 2015;Potts et al, 2000;Rowe et al, 2011Rowe et al, , 2012Xu et al, 2012) with a very few studies over the Indian region (Morwal et al, 2016;Resmi et al, 2015).…”

Section: Data Set and Methods Of Analysismentioning

confidence: 99%

“…The observed and theoretical fits match over magnitudes of storm area through the range 10-150 km 2 . Cetrone and Houze (2006) have discussed that the physical and dynamical limitations on (1976), Houze and Cheng (1977), Potts et al (2000), Cetrone and Houze (2006), Cifelli et al (2007), Peter et al (2015), and Morwal et al (2016) have shown that frequency distribution of storm area can be represented by a lognormal distribution. This also applies to large-scale cloud clusters of the tropics as seen through satellite imagery (e.g., Mapes & Houze, 1993;Williams & Houze, 1987).…”

Section: Convective Cell Sizementioning

confidence: 99%

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Statistical Characteristics of Convective Clouds over the Western Ghats Derived from Weather Radar Observations

et al. 2017

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X‐band radar observations at Mandhardev (18.04°N, 73.85°E) are used to investigate statistics of convective clouds over the Western Ghats during monsoon season (June–September 2014). Convective storms (cells) are identified using an objective‐tracking method to examine their spatiotemporal variability, thus quantifying the time‐continuous aspects of convective cloud population over the region for the first time. An increased frequency of storm location and initiation along the windward mountains compared to coastal and lee side highlights orographic response to southwesterly flow, with superimposed diurnal cycle. An eastward progression of convective activity from upstream the barrier through windward slopes of mountains over to the lee side is observed. Storm area, height, and duration follow lognormal distributions; wherein, small‐sized storms contribute more to total population and unimodal distribution of 35 dBZ top heights (peaking at 5.5 km) depicts the dominance of shallow convection. Storms exhibit a pronounced diurnal cycle with a peak in afternoon hours, while the convective area maximum is delayed by several hours to that of precipitation flux. Cell lifetime and propagation show that cells move with slow speeds and have mean duration of 46 min. They align east‐west nearly parallel to mountain ridges, and their direction of movement is steered mostly by large‐scale winds at lower levels. Based on top heights, convective cells are further classified into cumulus, congestus, and deep clouds. In general, congestus (deep) cells are most abundant in the windward (leeward) side. A lead‐lag relationship between congestus and deep cells indicates midtroposphere moistening by congestus cells prior to deep convection.

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Section: Convective Cell Lifetime and Its Propagationmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

Section: Data Set and Methods Of Analysismentioning

confidence: 99%

Section: Convective Cell Sizementioning

confidence: 99%

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Statistical Characteristics of Convective Clouds over the Western Ghats Derived from Weather Radar Observations

et al. 2017

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“…Although these methods are relatively convenient, they lack objectivity and theoretical foundation. In order to compensate this limitation, a cumulative frequency method is introduced by calculating the cumulative frequency of excessive multiple of each water quality index [29].…”

Section: Eutrophication Condition Evaluation Based On Modified Fuzzy mentioning

confidence: 99%

A Fusion Water Quality Soft-Sensing Method Based on WASP Model and Its Application in Water Eutrophication Evaluation

Wang

Jia

et al. 2018

Journal of Chemistry

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Water environment protection is of great significance for both economic development and improvement of people's livelihood, where modeling of water environment evolution is indispensable in water quality analysis. However, many water quality indexes related to water quality model cannot be measured online, and some model parameters always vary among different water areas. Thus, this paper proposes a water quality soft-sensing method based on the water quality mechanism model to simulate evolution of water quality indexes online, where unscented Kalman filter is utilized to estimate model parameters. Furthermore, a modified fuzzy comprehensive evaluation method is presented to evaluate the level of water eutrophication condition. Finally, the water quality data collected from Taihu Lake and Beihai Lake are used to validate the effectiveness and generality of the proposed method. The results show that the proposed soft-sensing method is able to describe the variation of related water quality indexes, with better accuracy compared to nonlinear least squares based method and traditional trial-and-error based method. On this basis, the water eutrophication condition can be also accurately evaluated.

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Hydraulic jump: The cause of heavy rainfall on the immediate lee side of the Western Ghats in the Maharashtra state of India

Kulkarni¹,

Deshpande

Morwal³

et al. 2022

Intl Journal of Climatology

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North-South-oriented mountains (known as "The Western Ghats [WG]") running parallel to the west coast of peninsular India separate the Maharashtra state (lying on the northwest of peninsular India) into two meteorological subdivisions (a) Konkan lying on the windward side of WG receiving high monsoon rainfall (2,390 mm) and (b) Madhya Maharashtra (MM) lying on the leeward side receiving low monsoon rainfall (579 mm). The state of Maharashtra has two more subdivisions on the leeward side of WG, viz. Marathwada

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Cloud characteristics over the rain-shadow region of North Central peninsular India during monsoon withdrawal and post-withdrawal periods

Cited by 15 publications

References 58 publications

Statistical Characteristics of Convective Clouds over the Western Ghats Derived from Weather Radar Observations

Statistical Characteristics of Convective Clouds over the Western Ghats Derived from Weather Radar Observations

A Fusion Water Quality Soft-Sensing Method Based on WASP Model and Its Application in Water Eutrophication Evaluation

Hydraulic jump: The cause of heavy rainfall on the immediate lee side of the Western Ghats in the Maharashtra state of India

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