TABLE 2.1 NPOESS Climate Environmental Data Record Threshold Requirements for Temperature and Moisture Soundings

System Capability

Temperature Threshold

Water Vapor Threshold (specific humidity)a

Horizontal Resolution


50 km



Clear, nadir

50 km


Clear, worst case

100 km


Cloudy, nadir

50 km


Cloudy, worst case

100 km


Stratosphere Clear

200 km


Vertical Resolution Clear

  1. Surface-300 millibars (mbar)

±1.0 K/1 km depth

20 mbar, surface-850 mbar

  1. 300-30 mbar

±1.0 K/3 km depth

50 mbar, 850-100 mbar

  1. 30-1 mbar

±1.0 K/5 km depth

  1. 1-0.01 mbar Cloudy (>80%)

±3.5 K/5 km depth

  1. Surface-700 mbar

±1.5 K/3 km depth

  1. 700-100 mbar

±1.5 K/3 km depth


Measurement Accuracy Clear

±0.5 K

  1. Surface-600 mbar



  1. 600-400 mbar



  1. 400-100 mbar Cloudy



  1. surface-600 mbar



  1. 600-400 mbar



  1. 400-100 mbar



Long-term Stability




±0.05 K/decade



±0.10 K/decade


aPrimarily clear-sky.

SOURCE: Adapted from NOAA (1997).


A detailed history of atmospheric sounding up to 1991 is summarized in the review article of Smith (1991). The basic physics involved in the design of temperature and moisture sounders from Earth orbit was published in the late 1950s (King, 1958; Kaplan, 1959), followed by a number of papers describing different methods of retrieval (e.g., Houghton et al., 1984; Smith, 1991). The early measurements that tested these concepts were based on measurements obtained from filter radiometers with a spectral resolution (λ/Δλ) typically on the order of 100. As noted below, the next step in sounding technology is toward sounders with a much higher spectral resolution (λ/Δλ ~ 1000).

The presence of clouds in the field of view of sounders has a detrimental effect on the quality of a retrieval. The absorption properties of cloud droplets and ice particles at infrared sounding wavelengths are so strong that even thin clouds contaminate the measurement of radiances. A number of techniques have been developed to minimize the effects of clouds on soundings. These usually require some way of identifying cloudy scenes to arrive at an equivalent clear-sky radiance quantity (such as the so-called “cloud-clearing” method of Smith, 1968). It is difficult to remove the effects of clouds entirely from the data, producing larger retrieval errors under these conditions (this is also reflected in Table 2.1). Methods accounting for the effects of clouds on the data are generally based on higher-resolution visible and infrared imaging data that are required to supplement the sounding channels.

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