Changes in thunderstorm characteristics due to feeder cloud merging

Sin’kevich, A. А.; Krauss, T. W.

doi:10.1016/j.atmosres.2013.06.007

Cited by 11 publications

(6 citation statements)

References 30 publications

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“…The report of Byers and Braham [1949] described how "several small cumuli may unite to form a single cell" during the developing stage of a thunderstorm. More recent studies continue to show this, similarly defining merging as the joining of constant surfaces of rates of precipitation or radar echo [Tao and Simpson, 1989;Sinkevich and Krauss, 2014;Moseley et al, 2016]. More recent studies continue to show this, similarly defining merging as the joining of constant surfaces of rates of precipitation or radar echo [Tao and Simpson, 1989;Sinkevich and Krauss, 2014;Moseley et al, 2016].…”

Section: Introductionmentioning

confidence: 87%

“…In a radar study of convection in Florida, Simpson et al [1980] showed that rain cells produce an order of magnitude more rain after a merging event compared to those that do not merge. More recent studies continue to show this, similarly defining merging as the joining of constant surfaces of rates of precipitation or radar echo [Tao and Simpson, 1989;Sinkevich and Krauss, 2014;Moseley et al, 2016]. The simulations of Stalker and Knupp [2003] include a case of merging of two cloud boundaries, each containing interior updraft cores which do not merge.…”

Section: Introductionmentioning

confidence: 93%

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Connections matter: Updraft merging in organized tropical deep convection

Glenn

Krueger

2017

Geophysical Research Letters

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When tropical cumulus convection is organized, the spacing between updrafts is reduced, and deep convective cloud tops are higher. The relative importance of various processes through which organization increases cloud top heights is not well understood. It is likely that decreased spacing between updrafts in organized convection increases the frequency of convective updraft merging. What is the relative importance of merging in determining an updraft parcel's detrainment height? We investigated updraft parcel merging in organized deep convection using results from a large eddy simulation. We used Lagrangian parcel trajectories (LPTs) to locate merging events. LPTs that merge reach detrainment heights 1.5 km higher on average than LPTs which do not merge. Merged LPTs are more buoyant than nonmerged LPTs, implying less dilution due to entrainment. Using mutual information analysis, we found that merging, cloud base vertical velocity, and cloud base area are about equally important in determining parcel detrainment height.

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Section: Introductionmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 93%

Connections matter: Updraft merging in organized tropical deep convection

Glenn

Krueger

2017

Geophysical Research Letters

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“…The TRMM and Climate Prediction Centre MORPHing technique (CMORPH) rainfall estimates are available at 0.25°×0.25° resolutions. The PME thunderstorm identification, tracking, analysis and nowcasting (TITAN) radar technical details and precipitation algorithm are documented by Sinkevich and Krauss (). Since the TRMM rainfall estimates failed to detect the observed rainfall reported by weather stations, we have also compared the results with CMORPH rainfall estimates (Joyce et al , ), a multi‐satellite precipitation product from passive microwave and infrared data available at a resolution of 0.25°×0.25°.…”

Section: Methodsmentioning

confidence: 99%

Predicting extreme rainfall events over Jeddah, Saudi Arabia: impact of data assimilation with conventional and satellite observations

Viswanadhapalli

Srinivas

Langodan

et al. 2015

Quart J Royal Meteoro Soc

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The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes.Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations.Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model's thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with assimilation of all observational data provide best statistical scores.

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“…Much attention is paid to the calculation of energy costs for processing the supply air when designing buildings in different countries [1][2][3][4][5][6]. In the Russian Federation, the energy consumption by air conditioning systems is considered as a significant one, as well [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Influence of detailing the climate model on the calculation of energy consumption

2020

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The repeatability of outdoor air temperature and enthalpy combinations in a construction area is a necessary initial information for calculating the energy consumption of air conditioning systems. The most convenient form of presenting climatic data in such calculations is the probabilistic-statistical model, which constitutes a Table, the cells of which show the probabilistic repeatability of the outdoor air temperature and relative humidity. The parameter values given on the vertical and horizontal scales, that form the cell boundaries, can be taken with larger or smaller increments. The paper that served as the basis for this article, provides verification of the initial climatic model detailing experimentally under full-scale conditions in the city of Hanoi (Vietnam). The criterion for the appropriate model detailing was the deviation of the energy consumption estimates of the room cooling system, got experimentally and by calculation. Moreover, the calculations were performed not only on two climate probabilistic and statistical models, but also on the data of direct measurements of the outdoor air temperature and relative humidity with an accuracy of 0.1 for temperature and up to 2 % for relative humidity.

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Changes in thunderstorm characteristics due to feeder cloud merging

Cited by 11 publications

References 30 publications

Connections matter: Updraft merging in organized tropical deep convection

Connections matter: Updraft merging in organized tropical deep convection

Predicting extreme rainfall events over Jeddah, Saudi Arabia: impact of data assimilation with conventional and satellite observations

Influence of detailing the climate model on the calculation of energy consumption

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