Meteorological data such as Sea Surface Temperature (SST), Wind direction and Wind speed are important parameters to determine the occurrence of upwelling. This study demonstrates some useful techniques that can be used to provide useful meteorological data, where these may be missing from conventional data sets that are provided by, for example, national meteorological authorities. The techniques used include: Plotting the daily temperature datasets in Lines on 2Axes using EXCEL,the nearest neighbour station using Principal Component Regression in Climate Predictability Tool (CPT), calculating the skills by comparing the two datasets using SYSTAT and using FERRET satellite derived data plots to determine the missing data for a particular time. Results showed that the www.windguru.cz dataset for Sagres (SW Portugal) proved to be more suitable for replacing the missing data of temperature on the Meteorological datasets because the skills were as high as 88%, comparing with in situ data. FERRET plots also indicated suitable substitutes for non availability of the Meteorological data such as wind direction and speed. In global scenario, upwelling involves the Physical, Chemical and Biological process. Physically-like cold water on the surface because of upwelling and this affects Sea surface temperature. Wind plays an important role in regulating the Sea Surface Temperature (SST) transporting heat through the surface water. Chemically - nutrients rich water brought to the surface and Biologically-production of phytoplankton bloom that results into chlorophyll increase and this gives the resulting color change in ocean color which can be detected by satellite images. Data from the Windguru website archive and the Ferret derived plots are suitable for replacing where they are missing data on the Meteorological datasets. Details and a short review of the oceanographic and meteorological conditions that are responsible for upwelling are presented in the text.