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  • Author or Editor: Ravi S. Nanjundiah x
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Arindam Chakraborty and Ravi S. Nanjundiah

Abstract

This study uses precipitation estimates from the Tropical Rainfall Measuring Mission to quantify the spatial and temporal scales of northward propagation of convection over the Indian monsoon region during boreal summer. Propagating modes of convective systems in the intraseasonal time scales such as the Madden–Julian oscillation can interact with the intertropical convergence zone and bring active and break spells of the Indian summer monsoon. Wavelet analysis was used to quantify the spatial extent (scale) and center of these propagating convective bands, as well as the time period associated with different spatial scales. Results presented here suggest that during a good monsoon year the spatial scale of this oscillation is about 30° centered around 10°N. During weak monsoon years, the scale of propagation decreases and the center shifts farther south closer to the equator. A strong linear relationship is obtained between the center/scale of convective wave bands and intensity of monsoon precipitation over Indian land on the interannual time scale. Moreover, the spatial scale and its center during the break monsoon were found to be similar to an overall weak monsoon year. Based on this analysis, a new index is proposed to quantify the spatial scales associated with propagating convective bands. This automated wavelet-based technique developed here can be used to study meridional propagation of convection in a large volume of datasets from observations and model simulations. The information so obtained can be related to the interannual and intraseasonal variation of Indian monsoon precipitation.

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Nirupam Karmakar, Arindam Chakraborty, and Ravi S. Nanjundiah

Abstract

In this study, rainfall estimates by the Tropical Rainfall Measuring Mission are used to understand the spatiotemporal structures of convection in the intraseasonal time scale and their intensity during the boreal summer over South Asia. A quantitative analysis on how these intraseasonal modes modulate the central Indian rainfall is also provided.

Two dominant modes of variability with periodicities of 10–20 and 20–60 days are found, with the latter strongly modulated by sea surface temperature. The 20–60-day mode shows northward propagation from the equatorial Indian Ocean linked with eastward-propagating modes of convective systems over the tropics. The 10–20-day mode shows a complex space–time structure with a northwestward-propagating anomalous pattern emanating from the Indonesian coast. This pattern is found to be interacting with a structure emerging from higher latitudes propagating southeastward, the development of which is attributed to the vertical shear of the zonal wind. The two modes exhibit profound variability in their intensity on the interannual time scale and they contribute a comparable amount to the daily rainfall variability in a season. The intensity of the 20–60 and 10–20-day modes shows a significantly strong inverse and direct relationship with the all-India June–September rainfall, respectively.

This study establishes that the probability of the occurrence of substantial rainfall over central India increases significantly if the two intraseasonal modes simultaneously exhibit positive anomalies over the region. The results presented in this paper will provide a pathway to understand, using observations and numerical model simulations, intraseasonal variability and its relative contribution to the Indian summer monsoon. It can also be used for model evaluation.

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Saroj K. Mishra, J. Srinivasan, and Ravi S. Nanjundiah

Abstract

Several numerical experiments have been conducted using the NCAR Community Atmosphere Model, version 3 (CAM3) to examine the impact of the time step on rainfall in the intertropical convergence zone (ITCZ) in an aquaplanet. When the model time step was increased from 5 to 60 min the rainfall in the ITCZ decreased substantially. The impact of the time step on the ITCZ rainfall was assessed for a fixed spatial resolution (T63 with L26) for the semi-Lagrangian dynamical core (SLD). The increase in ITCZ rainfall at higher temporal resolution was primarily a result of the increase in large-scale precipitation. This increase in rainfall was caused by the positive feedback between surface evaporation, latent heating, and surface wind speed. Similar results were obtained when the semi-Lagrangian dynamical core was replaced by the Eulerian dynamical core. When the surface evaporation was specified, changes in rainfall were largely insensitive to temporal resolution. The impact of temporal resolution on rainfall was more sensitive to the latitudinal gradient of SST than to the magnitude of SST.

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Parthasarathi Mukhopadhyay, R. Krishnan, Ravi S. Nanjundiah, and M. Mohapatra
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Priyanka Banerjee, S. K. Satheesh, K. Krishna Moorthy, Ravi S. Nanjundiah, and Vijayakumar S. Nair

Abstract

Synergizing satellite remote sensing data with vertical profiles of atmospheric thermodynamics and regional climate model simulations, we investigate the relative importance, transport pathways, and seasonality of contribution of dust from regional (Thar Desert and adjoining arid regions) and remote (southwest Asia and northeast Africa) sources over the northeast Indian Ocean [i.e., the Bay of Bengal (BOB)]. We show that while over the northern BOB dust from the regional sources contribute more than 50% to the total dust load during the southwest monsoon period (June–September), interestingly; the remote dust sources dominate rest of the year. On the other hand, over the southern BOB, dust transported from the remote-source regions dominate throughout the year. During June, the dry elevated layer (at altitudes between 850 and 700 hPa) of dust, transported across the Indo-Gangetic Plain to the northern BOB, arises primarily from the Thar Desert. Dust from remote sources in the far west reaches the southern BOB after traversing over and around the southern Indian Peninsula. Since dust from these distinct source regions have different mineral composition (hence optical properties) and undergo distinct changes during atmospheric transport, it is important to understand source-specific dust contribution and transport pathways to address dust–climate feedback.

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Prakash Pithani, Sachin D. Ghude, R. K. Jenamani, Mrinal Biswas, C. V. Naidu, Sreyashi Debnath, Rachana Kulkarni, Narendra G. Dhangar, Chinmay Jena, Anupam Hazra, R. Phani, P. Mukhopadhyay, Thara Prabhakaran, Ravi S. Nanjundiah, and M. Rajeevan

Abstract

A Winter Fog Experiment (WiFEX) was conducted to study the genesis of fog formation between winters 2016–17 and 2017–18 at Indira Gandhi International Airport (IGIA), Delhi, India. To support the WiFEX field campaign, the Weather Research and Forecasting (WRF) Model was used to produce real-time forecasts at 2-km horizontal grid spacing. This paper summarizes the performance of the model forecasts for 43 very dense fog episodes (visibility < 200 m) and preliminary evaluation of the model against the observations. Similarly, near-surface liquid water content (LWC) from models and continuous visibility observations are used as a metric for model evaluation. Results show that the skill score is relatively promising for the hit rate with a value of 0.78, whereas the false alarm rate (0.19) and missing rate (0.32) are quite low. This indicates that the model has reasonable predictive accuracy, and the performance of the real-time forecast is better for both dense fog events and no-fog events. For success cases, the model accurately captured the near-surface meteorological conditions, particularly the low-level moisture, wind fields, and temperature inversion. In contrast, for failed cases, the WRF Model shows large error in near-surface relative humidity and temperature compared to the observations, although it captures temperature inversions reasonably well. Our results also suggest that the model is able to capture the variability in fog onset for consecutive fog events. Errors in near-surface variables during failed cases are found to be affected by the errors in the initial conditions taken from the Indian Institute of Tropical Meteorology Global Forecasting System (IITM-GFS) spectral model forecast. Further evaluation of the operational forecasts for dense fog cases indicates that the error in predicting fog onset stage is relatively large (mean error of 4 h) compared to the dissipation stage.

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