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An algorithm for improving the retrieval of cloud liquid water and water vapor using effective radiating temperature of clouds

机译:利用云的有效辐射温度改善云中液态水和水蒸气的反演的算法

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An algorithm is discussed which can significantly lower the rms errors in integrated cloud liquid water and water vapor retrieval from radiometric brightness temperature. This algorithm makes use of the effective radiating temperature of the atmosphere which is estimated from surface temperature, cloud base temperature, and cloud base height. The surface temperature is easily measured, while the cloud base temperature and the cloud base height may be measured by use of a pyrometer and a ceilometer, respectively. The effective radiating temperature T/sub eff/ is estimated at two separate frequencies corresponding to the two frequencies used to measure radiometric brightness temperature, and these estimates are then used to modify the brightness temperatures. For a data base compiled at University Park, Pennsylvania, the estimates of effective radiating temperature reduced the rms error in retrieving cloud liquid water content from 37 to 21 /spl mu/m, and reduced the rms error in retrieving water vapor under cloudy conditions from 0.20 to 0.11 cm. The reduction in the uncertainty in retrieved liquid water content was consistent with that achieved by Han and Thomson (1) for tropical conditions. Han and Thomson used measurements of cloud base height and cloud base temperature, along with a climatological mean effective radiating temperature to improve their retrievals.
机译:讨论了一种算法,该算法可以显着降低从辐射亮度温度中检索到的集成云状液态水和水蒸气的均方根误差。该算法利用了从表面温度,云底温度和云底高度估算的大气有效辐射温度。表面温度容易测量,而云底温度和云底高度可以分别通过使用高温计和云高计来测量。在与用于测量辐射亮度温度的两个频率相对应的两个单独的频率处估计有效辐射温度T / sub eff /,然后将这些估计值用于修改亮度温度。对于宾夕法尼亚州大学公园市的数据库,有效辐射温度的估算将取回云层液态水含量时的均方根误差从37降低到21 / spl mu / m,并将在多云条件下取回水蒸气时的均方根误差减小了。 0.20至0.11厘米取回的液态水含量的不确定性降低与Han和Thomson(1)在热带条件下获得的降低一致。 Han和Thomson使用云底高度和云底温度以及气候平均有效辐射温度的测量值来改善其反演。

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