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ATMOSPHERIC OBSERVATIONS FORM the basis for weather prediction and analysis, for monitoring climate and climate change, and for atmospheric and climate research. Observations are carried out routinely and in a well-coordinated manner by weather services and individuals using a variety of platforms and instruments. The range of intentions behind observing the atmosphere leads to different types of data products. For climate trend applications, a number of errors need to be carefully addressed. Climate variables have been measured for centuries, but it has only been possible to construct a consistent global picture of climate trends from these data since the late 1900s.

Atmospheric observations are partial descriptions of the state of the atmosphere, the statistics of which determine the state of the climate system. If these observations are carried out over long time periods, changes in the climate system can be addressed. Most of the observations are measurements, for example, a property of the atmosphere is quantified using instruments.

The most important examples of atmospheric measurement are air temperature, pressure, humidity, wind speed and direction, radiation, and the composition of the atmosphere. However, visual observations of cloud type and fraction, precipitation type, or weather type are also important.

Atmospheric observations require a variety of instruments. In-situ instruments measure the physical or chemical properties of the surrounding air. Remote sensing systems indirectly derive these properties from perturbations of electromagnetic signals passing through the air. Platforms used for atmospheric observations include ground-based stations, ships, buoys, weather balloons, aircraft, or satellites. Sometimes the atmosphere is sampled a posteriori, for example, air samples in glass flasks are analyzed chemically in a laboratory, or the composition of air in bubbles trapped millennia ago in ice are analyzed.

Systematic atmospheric observations require a high degree of coordination, and can be of vital strategic interest. Therefore, they are mostly performed by large, national organizations such as weather services. Global cooperation is achieved through the World Meteorological Organization (WMO), which issues standards and recommendations concerning instruments, calibrations, measurement practices, reporting, and quality control/quality assurance. The WMO also regulates data exchange. Observations are also performed within large research programs.

Atmospheric observations are performed with different intentions. The most common ones are meteorological and climatological applications. Important considerations for meteorological applications are real-time availability, precision, and spatial resolution. These data are typically used for weather forecasting and analysis. Important considerations for climate data are accuracy, representativeness, and long-term stability. These data are used for climate research, planning and risk assessment, or similar applications.

The Uncertainties of Climatic Data

Long time-series of climatic data are subject to several types of uncertainties. Systematic or random errors in the measurement instruments make up only part of the total uncertainty. Changes in instrumentation, measurement practices, reporting, location, and station environments also contribute to the total uncertainty and inevitably lead to heterogeneous data sets. In order to assess long-term climate trends reliably, systematic errors must be corrected to make different parts of a series comparable, which is termed homogenization. For this process, sufficient background information on the measurements (often termed metadata) is necessary. Mostly, data are homogenized with respect to a time average such as monthly means. Additional efforts are necessary to address changes in climate extremes. With daily climate data, for instance, it is necessary to homogenize the shape of the distribution function, as negative extremes might be affected differently by an inhomogeneity (such as change in location) than positive extremes.

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