This special issue is focused on the assessment of algorithms for the observation of Earth's climate from environmental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth's climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temperature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as requiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observational contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust. (C) 2015 Elsevier Inc. All rights reserved.

来源平台：REMOTE SENSING OF ENVIRONMENT