Modelling of Land Surface Net Radiation Under Different Sky Conditions using Satellite Data

Abstract

Essential climate variables (ECV) are a group of linked variables (physical, chemical, biological) which contribute to the understanding and critical characterization of the Earth climate. ECVs are adapted to provide empirical and statistical evidence required to understand, model and predict the earth's climate. The surface radiation (energy) budget, expressed in terms of energy exchange, is an ECV within the earth-atmosphere system. It is a fundamental quantity and component of the surface that modulates Earth surface processes within the climate system. The global mean uncertainty of net radiation is estimated to be around 1 Wm􀀀2 and a stability of 0.2 Wm􀀀2decade􀀀1. Net surface radiation (Rn) de nes the availability of radiation energy on and near the surface to drive many physical and physiological processes such as latent heat and sensible heat uxes, and evapotranspiration. Rn represents the sum of incoming and outgoing contributions of shortwave (0.3 to 3 m) and longwave radiation (4 { 100 m) uxes at the surface. It is the balance between the energy absorbed, re ected and emitted by the Earth's surface. It is the total energy that is available to in uence the climate and day to day weather. Accurate estimation of this is further helpful for understanding the shift within and their applicability in sustainable development, renewable energy, meteorological systems etc. Despite the well-known importance of all these quantities, it is still rare for Rn under di erent atmospheric compositions and related variables, to be measured in situ at meteorological stations partly because of instrumentation costs and di culty of access to many areas. There is an uncertainty of clouds and aerosols and their e ects which can lead to modelling and prediction errors. The in uencing factor which alters the balance of incoming and outgoing radiative uxes in the Earth-atmosphere system and is an index of the importance of the factor as a potential climate change mechanism, this mechanism is termed as Radiative forcing (RF). RF a ects strongly over vii viii the longwave region, where limited studies have been carried out for large regions. Most papers focus on a single component (either incoming or outgoing or direct Net). The proposed equations/formulas tend to be region speci c, functioning under speci c conditions, empirical or regression based and/or not applicable over a spatial resolution. Also, very limited studies have been carried over Indian landmass in the Longwave and Rn region. Estimation of Rn under di erent sky conditions over India is still an unexplored region speci cally on a spatial scale. Over the Indian landmass, with multisource information, empirical equations cannot incorporate the delicate microclimates, as well as large scale macroclimates easily. In recent times, the trend has shifted towards the development of machine learning techniques and usages of neural networks for radiation studies, as they outperform linear models especially for multilocation studies. With the era, and the development of high computation tools at researchers' disposal, more and more studies need to be carried out for multiple conditions. The lack of a generalized empirical equation becomes a hindrance. The study has developed development of a model based on scienti c and observational reasoning and analysis. It includes a physical and statistical approach, with an implementation for automatic map generation as outcome. The computations and satellite imagery focus in the visible and infrared region (0.25 to 100 m). The satellite imagery is in similar lines with the weather station datasets and same time period as well. The results and model can be useful in understanding the change in environmental and atmospheric conditions; identifying possible factors as a future prospect and reducing the climate change, if possible. Not to mention having possible applications in weather forecasting, data analysis, image processing, meteorological studies as well as construction of dam and building which can be properly insulated or built at a lower cost and more e ectively.