The quasi‐biennial oscillation (QBO) is important for understanding the dynamical and chemical variability of the global stratosphere. Currently available wind data from the equatorial stratosphere extend back to 1953. Here we present reconstructions of the QBO extending back to 1900 that can be used to constrain climate model simulations. The reconstructions are based on historical pilot balloon data as well as hourly sea‐level pressure (SLP) data from Jakarta, Indonesia. The latter were used to extract the signal of the solar semi‐diurnal tide in the middle atmosphere, which is modulated by the QBO. The reconstructions are in good agreement with the QBO signal extracted from historical total ozone data extending back to 1924. Further analyses suggest that the maximum phases of the QBO are captured relatively well after about 1910.
Abstract. Hand-written or printed manuscript data are an important source for paleo-climatological studies, but bringing them into a suitable format can be a time consuming adventure with uncertain success. Before starting the digitising work, it is worthwhile spending a few thoughts on the characteristics of the data, the scientific requirements with respect to quality and coverage, and on the different digitising techniques. Here we briefly discuss the most important considerations and report our own experience. We describe different methods for digitising numeric or text data, i.e., optical character recognition (OCR), speech recognition, and key entry. Each technique has its advantages and disadvantages that may become important for certain applications. It is therefore crucial to thoroughly investigate beforehand the characteristics of the manuscript data, define the quality targets and develop validation strategies.
Abstract. Hand-written or printed manuscript data are an important source for paleo-climatological studies, but bringing them into a suitable format can be a time consuming adventure with uncertain success. Before digitising such data (e.g., in the context a specific research project), it is worthwhile spending a few thoughts on the characteristics of the data, the scientific requirements with respect to quality and coverage, the metadata, and technical aspects such as reproduction techniques, digitising techniques, and quality control strategies. Here we briefly discuss the most important considerations according to our own experience and describe different methods for digitising numeric or text data (optical character recognition, speech recognition, and key entry). We present a tentative guide that is intended to help others compiling the necessary information and making the right decisions.
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