ORIGINAL ARTICLE Evaluation of the Weather Research and Forecasting Model Forecasts for Indian Summer Monsoon Rainfall of 2014 Using Ground Based Observations Swati Bhomia 1 & Prashant Kumar 1 & C. M. Kishtawal 1 Received: 4 September 2018 /Revised: 27 January 2019 /Accepted: 11 February 2019 # Korean Meteorological Society and Springer Nature B.V. 2019 Abstract The present study focuses on evaluating the ability of short-range rainfall forecasts from the Weather Research and Forecasting (WRF) model against observed gridded rainfall data from the India Meteorological Department (IMD) available over the Indian landmass during Indian summer monsoon (ISM) viz. June to September for the year 2014. The spatial distribution of the WRF predicted rainfall matches well with the IMD observed rainfall and indicates systematic rainfall biases over the Indian landmass. In general, precipitation is underestimated in dry, low elevation areas and overestimated in wet, high elevation areas by the WRF model. Based on rainfall verification scores, it was found that low and moderate rainfall was forecasted reasonably well by the WRF model compared to heavy rainfall. Moreover, extremal dependency score (EDS) has been used to verify heavy rainfall forecasts, as the traditional threat scores saturates towards high rainfall thresholds. Further, the separate analysis was carried out over five different homogeneous rainfall zones of India. Results show that the WRF model was able to predict rainfall reasonably well with higher correlation coefficient, lower bias and root mean square deviation in most of the zones. Moreover, the WRF rainfall forecasts at high spatial resolution (5 km) were also examined over Karnataka, India using dense rain gauge network. Keywords Forecast evaluation . WRF model . Monsoon rainfall 1 Introduction The primary source of water for agricultural production in India is the summer monsoon rainfall viz. June to September, as more than 80% of the annual total rainfall is received during this season (Rajeevan et al. 2013). Rainfall is probably the most important parameter that is predicted by numerical weather prediction (NWP) models. Predicting rainfall during monsoon season is the most difficult and challenging task due to its convective nature, large spatio- temporal variations, and orography dependence that makes it, the least accurate outputs available from the NWP models (Kumar et al. 2014). On the other hand, precise prediction of rainfall during monsoon season is considered highly essential bearing in mind its role in the sustenance of the agricultural systems and the economy of the country (Srinivas et al. 2013; Kumar et al. 2014). The accuracy of rainfall forecasts has improved steadily in the last three decades, and the systematic error with forecast length in the short-range has reduced significantly. However, compared to mid-latitudes, skill of rainfall prediction is still less over the tropical region (Webster et al. 1998; Gadgil 2003; Krishnamurti et al. 2006). In the last few decades, mesoscale modeling has become effortless to use and more readily avail- able (Mass and Kuo 1998). Continuous improvement in mod- el physics, implementation of numerical model at high reso- lution, availability of satellite, and conventional observations are major factors, which continuously improve the skill of the numerical models (Kumar et al. 2015a). The skill depends on various approximations, parameters, parameterization schemes as well as initial and boundary data (Jankov et al. 2007; Etherton and Santos 2008; Wen et al. 2012; Kumar and Shukla 2019). Raju et al. (2015) used the Weather Research and Forecasting (WRF) model to simulate summer monsoon characteristics during year 2001 to 2011 and found that the Responsible Editor: Ashok Karumuri. * Prashant Kumar kam3545@gmail.com 1 Atmospheric & Oceanic Sciences Group, Earth, Ocean, Atmosphere, Planetary Sciences and Applications Area (EPSA) Space Applications Centre (ISRO), Ahmedabad 380015, India Asia-Pacific Journal of Atmospheric Sciences https://doi.org/10.1007/s13143-019-00107-y Online ISSN 1976-7951 Print ISSN 1976-7633 Korean Meteorological Society