The task of climate observation data processing is central to the quality of an assessment of future climate change impact. The current state-of-the-art is based on the long-running observation records of the meteorol...The task of climate observation data processing is central to the quality of an assessment of future climate change impact. The current state-of-the-art is based on the long-running observation records of the meteorological stations. However, it is common for the developing states to have only relatively short and/or intermittent record histories. The issue becomes even more aggravated under an effort to assess the climatic trends for specific territories with few meteorological stations. The paper offers a simple and effective technique to handle the climate observations; the technique makes the most complete use of an available data set by counting the data provided by all meteorological stations including those with short records and omissions. The method is based on numeric differentiation of source data samples.展开更多
文摘The task of climate observation data processing is central to the quality of an assessment of future climate change impact. The current state-of-the-art is based on the long-running observation records of the meteorological stations. However, it is common for the developing states to have only relatively short and/or intermittent record histories. The issue becomes even more aggravated under an effort to assess the climatic trends for specific territories with few meteorological stations. The paper offers a simple and effective technique to handle the climate observations; the technique makes the most complete use of an available data set by counting the data provided by all meteorological stations including those with short records and omissions. The method is based on numeric differentiation of source data samples.
