Tropical cyclone heat potential (TCHP) is an important ocean parameter influencing cyclones and hurricanes. The best approach for computing TCHP is to use in situ measurements. However, since in situ data have both spatial and temporal limitations, there is a need for satellite-based estimations. One potential solution is to use sea surface height anomalies (SSHAs) from altimeter observations. However, any estimation derived from satellite measurements requires extensive regional validation. In this letter, we compare satellite-derived TCHP values with those estimated using in situ measurements of the North Indian Ocean collected during 1993-2009. All the available measurements collected from the conductivity temperature and depth (CTD) profiler, expendable CTD profiler (XCTD), bathythermograph (BT), expendable BT (XBT) and Argo floats were used to estimate in situ derived TCHP values. TCHP estimations from satellite observations and in situ measurements are well correlated, with coefficient of determination R 2 of 0.65 (0.76) and a scatter index (SI) of 0.33 (0.25) on a daily (monthly) basis for the North Indian Ocean.
Agriculture is the backbone of the Indian economy and contributes ∼16% of gross domestic product and about 10% of total exports. Hence, accurate and timely forecasting of monthly Indian summer monsoon rainfall is very much in demand for economic planning and agricultural practices. Several methods and models, comprising dynamic and statistical models and combinations of the two, exist for monsoon forecasting. Here, a multi-model ensemble approach, combined with an artificial neural networking technique, was used to develop a soft-computing ensemble algorithm (SEA) to forecast the monthly and seasonal rainfall over the Indian subcontinent. Forecasts using January to May initial conditions along with observations during 1982-2014 were used to develop the model. The SEA compares well with observations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.