Advection‐condensation paradigm for stratospheric water vapor
Advection‐condensation paradigm for stratospheric water vapor
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DOI：
10.1029/2010jd014352
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发表时间：
2010-12
影响因子：
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通讯作者：
Y. S. Liu;S. Fueglistaler;P. Haynes
中科院分区：
文献类型：
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作者：
Y. S. Liu;S. Fueglistaler;P. Haynes
[1]对流-凝结(A-C)范例是分析气候变化中大气水汽分布及其变化的理论框架的起点。它假定水汽浓度受通过全四维温度(从而饱和混合比)场的传输控制。布鲁尔(1949)在水汽测量的基础上对平流层环流进行了定性推导，这是这一范例的第一次也是非常成功的应用。在这里，我们通过使用欧洲中期天气预报中心的数据，根据拉格朗日轨迹干点的饱和混合比来预测平流层水汽，检验了A-C范式的定量有效性。使用不同的数据集进行计算，我们表明，结果对温度和风场的看似微小的差异很敏感，并且对结果的解释(就识别被平流-凝结范例故意忽略的过程的影响而言)需要仔细的误差计算。我们介绍了一种半经验方法来分析水汽拉格朗日预测的误差。我们发现，温度场中的持续误差(在时间和空间上)会导致拉格朗日模型预测中的类似误差。相反，温度场方差的偏差在模型预测中引入了系统性偏差。此外，模式预测受到扩散和对流层到平流层输送的时间尺度的影响。我们的结论是，当考虑到欧洲中心再分析没有解决的小空间尺度和短时间尺度的温度波动时，基于A-C范式的平流层外世界水汽预报的干偏差为−40%±10%，−50%±10%。我们认为，对A-C范式最有可能消除这种干偏差的修正是包括云微物理过程(例如粒子的不完全沉积允许再蒸发)，这将瞬时脱水的假设放宽到饱和混合比。有趣的是，根据水蒸气浓度归因于A-C范式的偏差被发现与测量的水浓度成正比，而霜点温度的恒定偏移量可以解释大部分偏差及其在水蒸气混合比中的变异性。
[1] The advection-condensation (A-C) paradigm is a starting point for a theoretical framework for analysis of atmospheric water vapor distributions and changes therein in a changing climate. It postulates that water vapor concentrations are governed to leading order by the transport through the full four-dimensional temperature (and hence saturation mixing ratio) field. Brewer's (1949) qualitative deduction of the stratospheric circulation based on water vapor measurements was a first and prominently successful application of this paradigm. Here we examine the quantitative validity of the A-C paradigm by predicting stratospheric water vapor based on the saturation mixing ratio at the Lagrangian dry point of trajectories calculated using data from the European Centre for Medium-range Weather Forecasts. Using different data sets for the calculation, we show that results are sensitive to seemingly small differences in temperatures and wind fields and that interpretation of results (in terms of identification of effects of processes deliberately neglected by the advection-condensation paradigm) requires a careful error calculation. We introduce a semiempirical approach to analyze errors in the Lagrangian predictions of water vapor. We show that persistent (in time and space) errors in the temperature fields lead to similar errors in the Lagrangian model predictions. Conversely, biases in the variance of the temperature fields introduces a systematic bias in the model prediction. Further, model predictions are affected by dispersion and the time scale of troposphere-to-stratosphere transport. Our conclusion is that water vapor predictions for the stratospheric overworld based on the A-C paradigm have a dry bias of −40% ± 10% and −50% ± 10% when small-space-scale and short-time-scale temperature fluctuations not resolved by the ECMWF reanalyses are taken into account. We suggest that the correction to the A-C paradigm most likely to remove this dry bias is the inclusion of cloud microphysical processes (such as incomplete sedimentation of particles allowing reevaporation), which relax the assumption of instantaneous dehydration to the saturation mixing ratio. Interestingly, the bias attributed to the A-C paradigm in terms of water vapor concentration is found to be proportional to the measured water concentration, and a constant offset in terms of frost point temperature can account for much of the bias and its variability in water vapor mixing ratios.