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Reconciling Observations of Global Temperature Change (2000) / Chapter Skim
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8 Radiosonde Observations
Pages 50-57

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From page 50...
... Exact trend values vary depending on the data source, treatment, and trend-fitting method (e.g., Angell, 1999; Parker et al., 1997; Santer et al., 1999; Santer et al., 20001. SOURCES OF UNCERTAINTY IN TREND ESTIMATES There are several unresolved challenges in determining reliable, global, radiosonde-based temperature trend estimates.
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From page 51...
... Measurements are made and transmitted with approximately 10-50 m resolution during ascent, but archived sounding data may contain only about 20 data levels per sounding. Radiosonde-based data sets for climate monitoring come from two basic data products: individual soundings containing all reported data (Angel!
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From page 52...
... Instrument Changes: There have been many and widespread changes of radiosonde sensors during the history of the global radiosonde network. These changes often brought useful improvements in precision and accuracy, essential for weather analysis and forecasting, but they also prejudiced the homogeneity of the records from the perspective of climate change analysis (Gaffer, 19944.
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From page 53...
... Changes in the rules by which stations compute their monthly averages, including which observing time to use and how many days of data must be available, can have large effects, which are revealed by comparisons with monthly averages computed using a consistent set of rules (Gaffer et al., 20001. Variety of Methods of Estimating Global Trends in Layer-Mean Temperatures Methods for Obtaining 1,ayer-Mean Temperatures: The MSU temperature product discussed in the previous chapter is a verticallybroad and non-uniform representation of tropospheric temperature.
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From page 54...
... An annual temperature anomaly of the selected stations may be calculated as the average of the available months, or as an average of the available seasons. If the record is incomplete in a systematic manner, the weighting implicitly applied to individual monthly data may introduce biases.
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From page 55...
... Because of the demonstrated sensitivity of trends to data adjustments, and the distinct possibility that some adjustments may introduce more error than they remove, it will be important to compare adjusted data sets and their effects on trends in the future. Parker et al.
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From page 56...
... A third approach utilizes statistical methods to objectively identify abrupt shifts, or change-points, in time series. Gaffen et al.
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From page 57...
... offer a further potential means of radiosonde temperature bias detection and removal through comparisons with firstguess fields. Each of these strategies for radiosonde data adjustment, except the last one, depends to some degree on metadata-information about the history of instruments and observing practices at each station.
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Key Terms

  • radiosonde data
  • global radiosonde
  • temperature trends
  • sounding data
  • monthly averages

  • temperature data
  • climat temp
  • lower stratosphere
  • radiosonde network
  • radiosonde temperature

  • data treatment
  • artificial changes
  • temperature anomaly
  • weather analysis
  • temp reports

  • lower troposphere
  • upper troposphere
  • australian bureau
  • radiosonde temperatures
  • introduce biases

  • pressure levels
  • soundings containing
  • excellent overview
  • individual sounding
  • lower altitude

  • consistent set
  • despite recent
  • adjust radiosonde
  • potentially biased
  • packages carried


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