In the estimation of momentum fluxes over land surfaces by the bulk aerodynamic method, no unique value of the drag coefficient (C_D) is found in the literature. The drag coefficient is generally estimated from special observations at different parts of the world. In this study an attempt is made to estimate drag coefficient over the western desert sector of India using data sets of Monsoon Trough Boundary Layer Experiment (MONTBLEX) during the summer monsoon season of 1990. For this purpose, the fast and slow response data sets obtained simultaneously from a 30 m high micro-meteorological tower at Jodhpur are used. All the observations used in this study are confined to a wind speed regime of 2.5–9.0 ms⁻¹.

A comparison of momentum fluxes computed by eddy correlation (direct estimation) with profile and bulk aerodynamic (C_D = 3.9 × 10⁻³, Garratt, 1977) methods revealed that though the nature of variation of the fluxes by all these methods is almost similar, both the indirect methods give an under-estimated value of the fluxes. The drag coefficient is estimated as a function of wind speed and surface stability by a multiple regression approach. An average value of the estimated drag coefficient is found to be of the order of 5.43 × 10⁻³. The estimated value ofC_D is validated with a set of independent observations and found to be quite satisfactory. The recomputed momentum fluxes by bulk aerodynamic method using the estimated drag coefficient are in close agreement with the directly estimated fluxes.

Numerical experiment with improved boundary layer physics has been performed to study the Planetary Boundary Layer (PBL) characteristics over the monsoon trough region. Details of the evolution and structure of the associated boundary layer processes in the monsoon trough and adjoining oceanic regions are examined by integrating the model up to a period of 48 hours.

The model used for this study is a high resolution primitive equation, one with 0·5^o latitude/longitude horizontal resolution and 16 levels in the vertical (7 levels in the PBL). The boundary layer treatment in the model is based on the Monin-Obukhov similarity theory for the surface layer and Turbulent Kinetic Energy (TKE) formulation based onE-ε approach for the mixed layer. The model is integrated using the FGGE level IIIb analysis of European Centre for Medium Range Weather Forecasts (ECMWF), U.K.

The study shows that the diurnal variation of TKE over land is a dominant feature comparing with that over the ocean. Along the monsoon trough region, TKE increases from the eastern end to the western side which is mainly associated with the enhancement of sensible heat flux as we move from the eastern wet land to the western desert sector. It may be noted that the low level wind maximum, which is a characteristic feature over the monsoon region, is well simulated by this improved model physics.

The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa.

The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999

In 2013, Indian summer monsoon witnessed a very heavy rainfall event (>30 cm/day) over Uttarakhandin north India, claiming more than 5000 lives and property damage worth approximately 40 billionUSD. This event was associated with the interaction of two synoptic systems, i.e., intensified subtropicalwesterly trough over north India and north-westward moving monsoon depression formed over the Bayof Bengal. The event had occurred over highly variable terrain and land surface characteristics. Althoughglobal models predicted the large scale event, they failed to predict realistic location, timing, amount,intensity and distribution of rainfall over the region. The goal of this study is to assess the impactof land state conditions in simulating this severe event using a high resolution mesoscale model. Theland conditions such as multi-layer soil moisture and soil temperature fields were generated from HighResolution Land Data Assimilation (HRLDAS) modelling system. Two experiments were conductednamely, (1) CNTL (Control, without land data assimilation) and (2) LDAS, with land data assimilation(i.e., with HRLDAS-based soil moisture and temperature fields) using Weather Research and Forecasting(WRF) modelling system. Initial soil moisture correlation and root mean square error for LDAS is 0.73and 0.05, whereas for CNTL it is 0.63 and 0.053 respectively, with a stronger heat low in LDAS. Thedifferences in wind and moisture transport in LDAS favoured increased moisture transport from ArabianSea through a convectively unstable region embedded within two low pressure centers over Arabian Seaand Bay of Bengal. The improvement in rainfall is significantly correlated to the persistent generation ofpotential vorticity (PV) in LDAS. Further, PV tendency analysis confirmed that the increased generationof PV is due to the enhanced horizontal PV advection component rather than the diabatic heatingterms due to modified flow fields. These results suggest that, two different synoptic systems merged bythe strong interaction of moving PV columns resulted in the strengthening and further amplificationof the system over the region in LDAS. This study highlights the importance of better representation ofthe land surface fields for improved prediction of localized anomalous weather event over India.

The paper intends to present the development of the extended weather research forecasting data assimilation (WRFDA) system in the framework of the non-hydrostatic mesoscale model core of weather research forecasting system (WRF-NMM), as an imperative aspect of numerical modeling studies. Though originally the WRFDA provides improved initial conditions for advanced research WRF, wehave successfully developed a unified WRFDA utility that can be used by the WRF-NMM core, as well. After critical evaluation, it has been strategized to develop a code to merge WRFDA framework and WRF-NMM output. In this paper, we have provided a few selected implementations and initial results through single observation test, and background error statistics like eigenvalues, eigenvector and length scale among others, which showcase the successful development of extended WRFDA code for WRFNMM model. Furthermore, the extended WRFDA system is applied for the forecast of three severe cyclonic storms: Nargis (27 April–3 May 2008), Aila (23–26 May 2009) and Jal (4–8 November 2010)formed over the Bay of Bengal. Model results are compared and contrasted within the analysis fields and later on with high-resolution model forecasts. The mean initial position error is reduced by 33% with WRFDA as compared to GFS analysis. The vector displacement errors in track forecast are reduced by 33, 31, 30 and 20% to 24, 48, 72 and 96 hr forecasts respectively, in data assimilation experiments as compared to control run. The model diagnostics indicates successful implementation of WRFDA within the WRF-NMM system.