In Situ Sea Surface Temperature Observations and Their Errors: Student's Projects Based on ICOADS Data

Sea Surface temperature (SST) is a critical variable for analyses of climate variability and trends, as well as for seasonal climate prediction and extended weather forecasts. It is also a crucial parameter for understanding the impact of climate and environmental conditions on marine life, such as fish stock and movement and the health of coral reefs. We can monitor the SST from satellites but even with high quality remote sensing observations, it is important to validate observations with in situ temperature measurements taken directly in the water. There are various types of observational platforms providing in situ SST measurements: commercial, research, and government-operated ships (SH), drifting buoys (DB), also called floats or drifters, and also moored buoys (MB), which cannot move, fixed in place at a set of locations in the ocean. These types of observations are assembled in the International Comprehensive Ocean - Atmosphere Data Set (ICOADS). European Space Agency (ESA) through its Climate Change Initiative (CCI) has recently re-processed in a consistent way major global streams of satellite SST data, deliberately avoiding any dependencies of the product on concurrent in situ SST observations. Based on these data, daily globally-complete gridded fields of SST with 6 km spatial resolution were produced, using Ocean Sea Surface Temperature and Sea Ice Analysis (OSTIA) method for 1991-2010 period. The system was developed that extracts ICOADS data for individual SH, DB, and MB platforms, matches them by their times and locations with the OSTIA SST values and their uncertainties, and outputs the results in the form of a single CSV file per platform. Visualization, exploration, and statistical analyses of such files (one for each type of a platform), aimed at the analyses of the observed in situ SST variability and their error, constitute students' projects, which can be made suitable, depending on the depth of the expected statistical analysis, to a range of levels, from high school to master's programs. The projects were developed in collaboration with and for the use in class by colleagues from City College of City University of New York.