National Centre for Medium Range Weather Forecasting

About: National Centre for Medium Range Weather Forecasting is a government organization based out in Noida, India. It is known for research contribution in the topics: Monsoon & Weather Research and Forecasting Model. The organization has 176 authors who have published 368 publications receiving 4749 citations.

Global Retrospective Analysis Using NGFS for the Period 2000-2011

Abstract: The National Centre for Medium Range Weather Forecasting (NCMRWF) conducted its first global data retrospective analysis (reanalysis) for the period 1 January 2000-31 March 2011 using its GFS based system (NGFS). This reanalysis is called NGFS-R and the main objectives of this effort are to address issues for studying decadal variability of the Indian summer monsoon, high-resolution global analysis fields to study the Indian monsoon and to provide short-term mean fields for its seasonal/long-term forecasts by ensemble methods. NGFS-R has been conducted with the T574L64 version of the Global Data Assimilation and Forecasting System of NCMRWF that is operational as of May 2015, and using CFS-reanalysis data dump. With this effort, a high-resolution global data analysis at 6 h intervals is made available for about 16 years (2000-2015) for various uses and applications.

Intra‐annual variability of heat wave episodes over the east coast of India

Abstract: India is very prone to heat waves during April–June. The intra-annual variability of heat wave episodes over the east coast of India has been studied using 16-year NCMRWF global forecast system (NGFS) retrospective data. The objective of this study is threefold: (1) identification of heat wave episodes over the east coast of India, (2) intra-annual variability of heat wave episodes, and (3) which physical mechanism(s) is responsible for its occurrence and long-lasting? A total of ten heat wave episodes (100 hot days) were obtained for the period 2000–2015. The intensity of heat wave is found to be maximum (minimum) for 2015 (2007) episode. The average duration of heat wave episodes was 10 days, with the longest episode lasting for 20 days in the year 2003. Moreover, an average duration of severe heat wave is 3.5 days longer than that of a normal heat wave. The common feature observed in all heat wave cases is the presence of anticyclone in the upper troposphere and associated persistence high. This can cause sinking motion, which leads to surface warming due to adiabatic compression. The lack of soil moisture (SM) induces a positive feedback between the surface and the air above it, which amplifies the sensible heating and thereby increases surface temperature. The prevailed westerly anomalies over the study region which reduce the land–sea breeze result in heat wave. The heat wave episodes exhibit a significant intra-annual variability. Intensity of heat waves averaged over the east coast of India has shown an increase of 0.06 ∘C per heat wave. The geopotential height anomaly, vertical velocity, and SM exhibit significant intra-annual variability between the episodes and become decisive parameters for the maintenance and variability. The correlation coefficient between the maximum temperature and SM is found to be −0.56, indicating the importance of SM regulating the intensity of heat waves.

Rainfall Estimation from Kalpana-1 Satellite Data over Indian Land and Oceanic Regions

Abstract: Rainfall, an integral component of the global water and energy cycle, is one of the critical weather elements. Reliable information of rainfall over India is crucial for food security and sustainable economic growth. The first Indian dedicated meteorological geostationary satellite Kalpana-1 was launched by the Indian Space Research Organisation in late 2002 to study the synoptic weather systems, monsoons and extreme weather events. Various geophysical parameters derived from this satellite measurements are operational and used for a wide range of applications. Two rainfall products, based on distinct algorithms, from this satellite are also available to users. These two algorithms after certain refinements are also applied to the recently launched INSAT-3D satellite measurements to estimate rainfall. In this article, the algorithms used for the development of these Kalpana-1-based rainfall products are summarized. The assessment of these rainfall products against standard multisatellite datasets and in situ observations are also outlined. Both the rainfall products are comparable with independent multisatellite datasets and have reasonable agreement with ground-based observations over the Indian land and oceanic regions. Limitations of these rainfall products are also presented; and future scope for further refinement of these products in perspective of upcoming Indian geostationary satellite missions is proposed.

Distribution of lightning in relation to topography and vegetation cover over the dry and moist regions in the Himalayas

Abstract: The impacts of elevation, terrain slope and vegetation cover on lightning activity are investigated for contrasting environments in the north-east (NE) (21– $$29{^{\circ }}\hbox {N}$$ ; 86– $$94{^{\circ }}\hbox {E}$$ ) and the north-west (NW) (28– $$36{^{\circ }}\hbox {N}$$ ; 70– $$78{^{\circ }}\hbox {E}$$ ) regions of the Himalayan range. Lightning activity is more at a higher terrain slope/elevation in the dry NW region where vegetation cover is less, whereas it is more at a lower terrain slope/elevation in the moist NE region where vegetation cover is more. In the wet NE, 86% (84%) of the annual lightning flash rate density (LFRD) occurs at an elevation $${<} 500\ \hbox {m}$$ (terrain slope $${<} 2\%$$ ) and then sharply falls off at a higher elevation (terrain slope). However, only 49% (47%) of LFRD occurs at an elevation of $${<} 500\ \hbox {m}$$ (terrain slope $${<} 2\%$$ ) and then rather gradually falls off at a higher elevation (terrain slope) in the dry NW. The ratio of the percentages of LFRD and elevation points is much higher in the NW than in the NE above an elevation of $${\sim } 1000\ \hbox {m}$$ . The impacts of terrain slope and elevation in enhancing the lightning activity are stronger in the dry NW than in the moist NE. The correlation coefficient of the LFRD with the normalised difference vegetation index is higher in the NW than in the NE on both the regional and annual scales. Results are discussed as a caution in using any single climate variable as a proxy for projecting a change in the lightning–climate relationships in the scenario of global warming.

Sensitivity of the Himalayan orography representation in simulation of winter precipitation using Regional Climate Model (RegCM) nested in a GCM

Abstract: The role of the Himalayan orography representation in a Regional Climate Model (RegCM4) nested in NCMRWF global spectral model is examined in simulating the winter circulation and associated precipitation over the Northwest India (NWI; 23°–37.5°N and 69°–85°E) region. For this purpose, nine different set of orography representations for nine distinct precipitation years (three years each for wet, normal and dry) have been considered by increasing (decreasing) 5, 10, 15, and 20% from the mean height (CNTRL) of the Himalaya in RegCM4 model. Validation with various observations revealed a good improvement in reproducing the precipitation intensity and distribution with increased model height compared to the results obtained from CNTRL and reduced orography experiments. Further it has been found that, increase in height by 10% (P10) increases seasonal precipitation about 20%, while decrease in height by 10% (M10) results around 28% reduction in seasonal precipitation as compared to CNTRL experiment over NWI region. This improvement in precipitation simulation comes due to better representation of vertical pressure velocity and moisture transport as these factors play an important role in wintertime precipitation processes over NWI region. Furthermore, a comparison of model-simulated precipitation with observed precipitation at 17 station locations has been also carried out. Overall, the results suggest that when the orographic increment of 10% (P10) is applied on RegCM4 model, it has better skill in simulating the precipitation over the NWI region and this model is a useful tool for further regional downscaling studies.