Assessments of cloud liquid water contributions to GPS radio occultation refractivity using measurements from COSMIC and CloudSat
Assessments of cloud liquid water contributions to GPS radio occultation refractivity using measurements from COSMIC and CloudSat
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DOI：
10.1029/2011jd016452
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发表时间：
2012-03
影响因子：
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通讯作者：
Suying Yang;X. Zou
中科院分区：
文献类型：
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作者：
Suying Yang;X. Zou
[1]利用CloudSat上的云廓线雷达观测了全球云参数，包括云液态水、云底高、云顶高和云类型。对2007 - 2009年3年期间全球气象、电离层和气候星座观测系统（COSMIC）的无线电掩星（RO）数据与CloudSat数据在空间和时间上进行了配置。并置的数据集，然后分为七组：一个晴朗的天空条件和六个不同的云类型与液态水含量（LWC）的测量。对于每一组，来自COSMIC GPS RO的大气中的二氧化碳的活动，温度和水汽进行了比较与欧洲中期天气预报中心（ECMWF）的分析。结果表明，COSMIC GPS观测到的RO_（10）活动比ECMWF计算的RO_（10）活动有系统地偏大，这被认为是云中的正N偏置。分数N偏差高达1.2%，这取决于云的类型。使用CloudSat LWC，它表明，LWC可以贡献0.8%的总活动的单个云和0.16%的正N偏置。0.16%的正N偏差在量级上与通过减去LWC贡献的观测到的CO2活动与使用GPS反演的温度、压力和湿度廓线计算的CO2活动之间的平均差（Δ NO-R）量化的反演不确定性相当。Δ NO-R值随LWC的增加而线性增加，与理论预测相符。正氮偏差与正水汽偏差、负温度偏差和大的液态水含量在空间上相关。
[1] Global cloud parameters including cloud liquid water, cloud base height, cloud top height, and cloud type are observed from the cloud profiling radar onboard CloudSat. Global Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) data during a 3 year period from 2007 to 2009 are collocated in space and time with CloudSat data. The collocated data set is then classified into seven groups: one clear-sky condition and six different cloud types with liquid water content (LWC) measurements. For each group, atmospheric refractivity, temperature, and water vapor derived from COSMIC GPS ROs are compared with those of the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. It is found that the COSMIC GPS RO refractivity observations are systematically greater than the refractivity calculated from ECMWF analyses, which is to be referred as a positive N bias in clouds. The fractional N bias is as high as 1.2% depending on cloud types. Using CloudSat LWC, it is demonstrated that LWC can contribute 0.8% of the total refractivity by individual clouds and 0.16% of the positive N bias. The 0.16% positive N bias is comparable in magnitude to the retrieval uncertainty quantified by the mean difference (ΔNO-R) between the observed refractivity with LWC contribution subtracted and the refractivity calculated using GPS retrieved profiles of temperature, pressure, and humidity. The values of ΔNO-R increase linearly with LWC as anticipated theoretically. Positive N biases are spatially correlated with positive water vapor biases, negative temperature biases, and large liquid water contents.