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  • This dataset contains radar-derived measurements of cell-top height, size, 2 km reflectivity, and cell latitude and longitude from all convective cells between 14 May and 30 September 2016, where radar is available. The data was collected as part of the NERC/MoES Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign. The seven sites analysed here represent four different Indian climate regions, allowing the study of the spatiotemporal development of convection during the 2016 monsoon season at high (1 km) resolution. Variation in these different cell statistics are found over timescales of variability such as the diurnal cycle, active-break periods, and monsoon progression. The data were collected as part of the INCOMPASS field campaign May-July 2016, funded by Natural Environmental Research Council (NERC) (NE/L01386X/1). The aim of the project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales.

  • This dataset contains radar-derived measurements of cell-top height, size, 2 km reflectivity, and cell latitude and longitude from all convective cells between 14 May and 30 September 2016, where radar is available. The data was collected as part of the NERC/MoES Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign. The seven sites analysed here represent four different Indian climate regions, allowing the study of the spatiotemporal development of convection during the 2016 monsoon season at high (1 km) resolution. Variation in these different cell statistics are found over timescales of variability such as the diurnal cycle, active-break periods, and monsoon progression. The updated radar-derived cell statistics here have been corrected from the previous version by removing all convective cells that touch the outer edge of the radar domain. The data were collected as part of the INCOMPASS field campaign May-July 2016, funded by Natural Environmental Research Council (NERC) (NE/L01386X/1). The aim of the project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales.

  • This dataset contains temperature, humidity, wind and GPS location information recorded from 137 radiosondes launched during July 2016 as part of the NERC/MoES Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign. All radiosondes were launched from the airstrip of Indian Institute of Technology (IIT) Kanpur, Uttar Pradesh, northern India, from the location 26.519N, 80.233E, 126m above sea level. Launches took place between 5th July and 28th July at 00, 06, 12, 18UTC. The Vaisala RS41-SG radiosondes were fitted to Totex TA350 balloons. The data were collected as part of the INCOMPASS field campaign May-July 2016, funded by Natural Environmental Research Council (NERC) (NE/L01386X/1). The aim of the project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales.

  • Eddy covariance (EC) observations of surface-atmosphere exchanges of sensible heat and latent heat, momentum and net ecosystem carbon dioxide exchange were measured at thirty minute resolution at three Land Surface Stations in India. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. Meteorological observations include: the net radiation and its incoming and outgoing short- and long-wave components, air temperature, barometric pressure, relative humidity, wind speed and direction, and rainfall. Soil physics observations include: Soil heat fluxes, soil temperatures and soil volumetric water content. Observations were collected under the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) Project between January 2016 and January 2018. Full details about this dataset can be found at https://doi.org/10.5285/78c64025-1f8d-431c-bdeb-e69a5877d2ed

  • The dataset contains time series observations of meteorological and soil physics variables logged at one minute time resolution at three Land Surface Stations in India. The three INCOMPASS Land Surface Stations were located at: (1) agricultural land in Southern Karnataka (Berambadi); (2) the University of Agricultural Sciences in Dharwad in northern Karnataka; and (3) a semi-natural grassland at the Indian Institute of Technology in Kanpur (IITK), Uttar Pradesh. Observations were collected under the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) Project between January 2016 and January 2019. Full details about this dataset can be found at https://doi.org/10.5285/c5e72461-c61f-4800-8bbf-95c85f74c416