The operational medium range rainfall forecasts of the Met Office Unified Model (UM) are evaluated over India using the Contiguous Rainfall Area (CRA) verification technique. In the CRA method, forecast and observed weather systems (defined by a user-specified rain threshold) are objectively matched to estimate location, volume, and pattern errors. In this study, UM rainfall forecasts from nine (2007–2015) Indian monsoon seasons are evaluated against 0.5$^{\circ }\times$ 0.5$^{\circ }$ IMD–NCMRWF gridded observed rainfall over India (6.5$^{\circ }{-}$38.5$^{\circ }$N, 66.5$^{\circ }{-}$100.5$^{\circ }$E). The model forecasts show a wet bias due to excessive number of rainy days particularly of low amounts (<1 mm d$^{-1}$). Verification scores consistently suggest good skill the forecasts at threshold of 10 mm d$^{-1}$, while moderate (poor) skill at thresholds of <20 mm d$^{-1}$ (<40 mm d$^{-1}$). Spatial verification of rainfall forecasts is carried out for 10, 20, 40 and 80 mm d$^{-1}$ CRA thresholds for four sub-regions namely (i) northwest (NW), (ii) southwest (SW), (iii) eastern (E), and (iv) northeast (NE) sub-region. Over the SW sub-region, the forecasts tend to underestimate rain intensity. In the SW region, the forecast events tended to be displaced to the west and southwest of the observed position on an average by about 1$^{\circ }$ distance. Over eastern India (E) forecasts of light (heavy) rainfall events, like 10 mm d$^{-1}$ (20 and 40 mm d$^{-1}$) tend to be displaced to the south on an average by about 1$^{\circ }$ (southeast by 1$-2^{\circ }$). In all four regions, the relative contribution to total error due to displacement increases with increasing CRA threshold. These findings can be useful for forecasters and for model developers with regard to the model systematic errors associated with the monsoon rainfall over different parts of India.

In this study, real-time analysis of products and information dissemination (RAPID), a web-based quick visualisation and analysis tool for INSAT satellite data on a real-time basis has been introduced for identification of pre-monsoon severe weather events. The tool introduces the next generation weather data access and advanced visualisation. The combination of channels using red–green–blue (RGB) composites of INSAT-3D satellite and its physical significant value contents are presented. The solar reflectance and brightness temperatures (BTs) are the major components of the RGB composite. The solar reflectance component of the shortwave thermal infrared (IR) (1.6 $\mu$m), visible (0.5 $\mu$m) and thermal IR channels (10.8 $\mu$m) representing the cloud microstructure is known as Day Microphysics (DMP) RGB and the BT differences between 10.8, 12.0 and 3.9 $\mu$m is known as Night Microphysics (NMP) RGB. The threshold technique has been developed separately for both the RGB products of the year 2015–2016 and 2016–2017 of March–June, prior to the event (1–3 hr) for the detection of the thunderstorms. A validation analysis was conducted using the Forecast Demonstration Project of Storm Bulletins for pre-monsoon weather systems prepared by the India Meteorological Department and RADAR observations, demonstrating that this approach is extremely useful in recognising the area of convection prior to the occurrence of the events by the RGB thresholds. The validation of these thresholds has been carried out for March–June 2017. Both the RGBs i.e., DMP and NMP have a reasonable agreement with the ground-based observations and RADAR data. This threshold technique yields a very good probability of thunderstorm detection more than 94% and 93% with acceptable false alarm conditions, less than 3% and 5% for DMP and NMP, respectively. Furthermore, the limitations of these RGB products are additionally highlighted, and the future extent of refinement of these products in perspective of a rapid scan strategy is proposed. The threshold techniques are found to be useful for nowcasting application and are being used operationally using the RAPID tool.

The Madden Julian Oscillation (MJO) is the major fluctuation in tropical weather on weekly to monthly time scale and a major driver of Indian summer monsoon (ISM). In this study, using Indian Meteorological Department (IMD) high resolution daily gridded rainfall data and Wheeler-Hendon MJO indices, the daily rainfall distribution over India associated with various phases of eastward propagating MJO was examined to understand the MJO–monsoon rainfall relationship. The present study reveal that the onset of break and active events over India and the duration of these events are strongly related to the phase and strength of the MJO. The break events were relatively better associated with the strong MJO phases than the active events. About 80% of the break events were found to be set in during the phases 1, 2, 7 and 8 of MJO with maximum during phase 1 (34%). On the other hand, about 58% of the active events were set in during the MJO phases 3–6 with maximum during phase 6 (21%). The results of this study indicate an opportunity for using the real time information and skillful prediction of MJO phases for the extended range prediction of break and active conditions.

Due to climate variability and climate change there is an increase in magnitude and frequency of extreme precipitation events. During the last few decades these extreme rainfall events have been increased in global as well as on regional scale. Our climate is very much affected by the changes in frequency of extreme rainfall events. Particularly, variability of extreme rainfall events has been studied over one of the most valuable Indian region i.e. over Indo-Gangetic plain (IGP). Long term trend in extreme events has been analyzed with the help of IMD classification. The classification is considered for moderate rain (2.5–64.4 mm; category I), heavy rain (64.5–124.4 mm; category II) and very heavy rain (124.5 mm or more; category III) and the categorization of rainfall events is based on daily rainfall for the period 1901–2010 during Indian summer monsoon (JJAS). The significant long term trend in frequency of extreme rainfall events is analyzed using the statistical test. Long term trend analysis shows the significant decreasing trend for categories II and III. However, an increasing rainfall frequency is observed for moderate rainfall events (category I) during the considered period. A significant interannual and inter-decadal fluctuation in rainfall frequency and magnitude were observed over IGP. Events of moderate and heavy rainfall increases during the withdrawal period of Indian summer monsoon, which might contribute in several cases of flood in the region of IGP. In term of distribution and contribution of rainfall in agriculture area categories I and II, rainfall events are more important but changes in rainfall pattern may lead to flood and drought risk over IGP. The policy making decision for disaster risk and food security should be based on spatial as well as temporal variability of rainfall pattern over IGP region.

Since eternity, the Earth’s temperature has varied or fluctuated; it has its cooling and hot timing dependency on its orbital position as well as the isolation received from the Sun. The global climate continues to change rapidly compared to the speed of the natural variations in climate. Therefore, the spatially complete representations of surface climate are required for many purposes in applied sciences. But in recent centuries, the main matter of concern is that Earth’s normal temperature fluctuation is being influenced by some external factors such as enhanced greenhouse gases because of extreme uses of fossil fuels, severe industrialization, advance urbanization, etc. This study presents a comprehensive surface temperature dataset of Climatic Research Unit (CRU) available since 1901 for India, which is used to document significant changes in Indian temperature over ten decades, during winter season (January and February), pre-monsoon (March–May), monsoon (June–September) and post-monsoon (October–December) to examine the patterns and possible effects of global warming. A strong increasing pattern is observed with the fast growing of the development after 1950 which has shown nearly doubled in the last 50 yrs. The mean temperature during winter for the 2000s shows a consistent pattern of warming over the Himalayan region, northwestern and southern India, and a pattern of the warming observed over northeastern India and extending southwestward across central India during post-monsoon.