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Observation- and Numerical-Analysis-Based Dynamics of the Uttarkashi Cloudburst

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Observation- and Numerical-Analysis-Based Dynamics of the Uttarkashi Cloudburst Ann. Geophys., 33, 671–686, 2015 www.ann-geophys.net/33/671/2015/ doi:10.5194/angeo-33-671-2015 © Author(s) 2015. CC Attribution 3.0 License. Observation- and numerical-analysis-based dynamics of the Uttarkashi cloudburst C. Chaudhuri1, S. Tripathi1,2, R. Srivastava1, and A. Misra1 1Department of Civil Engineering, Indian Institute of Technology, Kanpur, India 2Centre for Environmental Science and Engineering, Indian Institute of Technology, Kanpur, India Correspondence to: C. Chaudhuri ([email protected]) Received: 26 November 2014 – Revised: 9 March 2015 – Accepted: 5 May 2015 – Published: 3 June 2015 Abstract. A Himalayan cloudburst event, which occurred on 1 Introduction 3 August 2012 in the Uttarkashi (30.73◦ N, 78.45◦ E) region of Uttarakhand, India, was analyzed. The near-surface atmo- spheric variables were analyzed to study the formation, evo- The interactions between the synoptic-scale circulation and lution, and triggering mechanisms of this cloudburst. In or- hydrological cycle at mountains are highly complex and non- der to improve upon the understanding provided by the ob- linear in nature (Maraun et al., 2010). Even a moderate servations, numerical simulations were performed using the amount of rain may cause severe events in hills, e.g., flash Weather Research and Forecasting (WRF) model, configured floods and landslides (Borga et al., 2014). A cloudburst, also with a single domain at 18 km resolution. The model was known as rain gush or rain gust, is an extreme form of precip- tuned using variation of different parameterizations (convec- itation in which a high intensity of rain falls over a localized tive, microphysical, boundary layer, radiation, and land sur- area (Das et al., 2006). The India Meteorological Department face), and different model options (number of vertical levels, (IMD) defines cloudburst as a rainfall event with intensity of − and spin-up time), which resulted in a combination of pa- the order of 100 mm h 1, accompanied by strong winds and rameters and options that best reproduced the observed diur- lightning. It usually affects an area not exceeding 20–30 km2. nal characteristics of the near-surface atmospheric variables. The cloudbursts in India usually take place during the mon- Our study demonstrates the ability of WRF in forecasting soon season over regions with a steep orography, like the Hi- precipitation, and resolving synoptic-scale and mesoscale in- malayan region, the northeastern states, and Western Ghats. teractions. In order to better understand the cloudburst, we Cloudburst takes place when moist thermodynamically un- configured WRF with multiply nested two-way-interacting stable atmosphere faces a deep and rapid uplifting by a steep domains (18, 6, 2 km) centered on the location of interest, topography (Das et al., 2006). In cloudburst-like systems, the and simulated the event with the best configuration derived convective clouds may have a height of up to 15 km. The earlier. The results indicate that two mesoscale convective Himalayan cloudbursts result from low pressure area mon- systems originating from Madhya Pradesh and Tibet inter- soon clouds from the Bay of Bengal, carrying a huge amount acted over Uttarkashi and, under orographic uplifting and in of moisture over the Gangetic Plain to the Himalayas, and − the presence of favorable moisture condition, resulted in this “bursting” into a heavy downpour (75–100 mm h 1) under cloudburst event. the topographic influence. The cloudbursts generally occur in the remote hilly areas and are typically not noticed unless Keywords. Meteorology and atmospheric dynamics (con- the resulting flash floods and landslides cause a major so- vective processes; mesoscale meteorology; middle atmo- cioeconomic disruption. With an early prediction and warn- sphere dynamics) ing of these events, and an appropriate training of local ad- ministration, the socioeconomic impacts of cloudbursts may be reduced. The reliability of the predictions could be in- creased if high-resolution measurement data (∼ 10 km) of meteorological parameters are provided through meso-net Published by Copernicus Publications on behalf of the European Geosciences Union. 672 C. Chaudhuri et al.: Analysis-based dynamics of the Uttarkashi cloudburst observations such as automatic weather stations (AWSs), ra- 9 and 3 km nested domains. Ashrit(2010) observed move- diosonde/radiowind (RSRW), and Doppler weather radar. ment of instabilities from the Tibetan Plateau and interac- Numerical weather prediction (NWP) is useful for short- tion of these instabilities with the moisture-rich air from west or medium-range forecasting by downscaling either the and northwest. His finding is similar to that of Rasmussen large-scale observed field or the fields derived from a global and Houze(2012), which was derived based on available ob- circulation model (GCM). However, the highly nonlinear, servations. These studies suggest that numerical simulation and not yet fully understood, relationships between meteoro- can provide useful insight into the physical process of cloud- logical variables and topography imply that obtaining an ac- bursts. curate prediction is a difficult task. The nested regional circu- Mesoscale processes are influenced by surface inhomo- lation model (RCM) is initialized with the coarse-resolution geneities in elevation, snow cover, vegetation, and surface large-scale atmospheric fields from atmosphere–ocean gen- roughness (Giorgi and Avissar, 2010). The near-surface eral circulation models (AOGCMs) or from global reanaly- moisture and temperature also have a major impact on the sis. The continuous time integration is done with frequent up- mesoscale circulations (Stefanon et al., 2014). The mesoscale date of the lateral meteorological and surface boundary con- weather events can be separated into two general categories ditions (LBCs and SBCs). The RCM adds regional details on the basis of the triggering dynamics. First are the in- to account for the regional-scale forcing (e.g., topography, stabilities of the traveling system, which force some of the coastline, and land use/land cover). events like squall lines and mesoscale convective complexes. The resolution of the model is one of the most important Second are surface inhomogeneities, which trigger some of factors affecting the accuracy of the forecast. Wang et al. the events like mountain or valley circulations. Many at- (2004) showed that increasing the model resolution is im- tempts have been made to explain the orographic mecha- portant to improve the quality of forecasting the micro- and nisms. Smith(1979) explained two of them: (i) stable as- mesoscale systems. However, the availability of computer re- cent induces and enhances the stratiform precipitation, and sources and their capability greatly constrain the increment (ii) terrain triggers and enhances the convection. Bougeault of resolution, and it can only be increased at key regions. et al.(2001) studied the variety of conditions that can cause In this study, we have used the nested domain formulation to orographic rainfalls. Chen and Lin(2001) suggested that an overcome this problem, without a significant loss of accuracy impinging low-level jet can cause a large amount of rainfall (Cheng, 1994). over the upwind slope. Heavy rainfall events, like over Uttarkashi on 3 Au- Though cyclonic storms, thunderstorms, and squall lines, gust 2012, are documented for several mountain regions land/sea breezes have been widely simulated by mesoscale around the globe. One of the most devastating storms among models, the predictability of terrain-induced mesocircula- them was the one that caused the Big Thompson flood of tions and precipitation events is debatable. Pielke(1984) 1976 in Colorado. The Texas hill storm event (Caracena and pointed out that the terrain-induced mesoscale systems, be- Fritsch, 1983), near the town of Bluff, about 90 km north- ing generated by a geographically fixed feature, are eas- west of San Antonio, had an unofficial record of a 79 cm ier to predict than instabilities of the traveling system like accumulation of rain over 24 h. The meteorological condi- mesoscale convective complexes. The deterministic physical tions leading to the Big Thompson flood and the 1972 Black interactions between synoptic-scale motions and the underly- Hills flood near Rapid City, South Dakota, are documented ing local topography may increase the mesoscale predictabil- by Caracena et al.(1979) and Nair et al.(1997). Various ity over a region with a complex terrain (Mann and Kuo, types of storms with different structures and synoptic condi- 1998). However, the interactions between terrain and airflow, tions can originate from convective systems (Doswell, 1985; latent heating/cooling, and uncertainties in the cloud micro- Doswell et al., 1996; Maddox et al., 1978). Identifying and physics make the simulation of precipitation over mountain understanding the key meteorological conditions that caused areas a challenging task. The accuracy of the simulation the heavy rainfall events around the world can shed some quickly deteriorates as the integration time advances. light on the mechanism of such events and improve their pre- From an Indian perspective, the socioeconomic impor- diction over vulnerable regions like the Himalayas. tance of cloudburst-like systems is huge. However, few pre- A detailed understanding of the interaction between oro- vious studies have focused on understanding the dynamics graphic dynamics and cloud dynamics is still lacking. Das of such
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