Comparison of Conventional and Constrained Variational Methods for Computing Large‐Scale Budgets and Forcing Fields
Comparison of Conventional and Constrained Variational Methods for Computing Large‐Scale Budgets and Forcing Fields
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计算大规模预算和强制场的传统方法和约束变分方法的比较
DOI：
10.1029/2021jd035183
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Xie, Shaocheng
中科院分区：
文献类型：
--
作者：
Ciesielski, Paul E.;Johnson, Richard H.;Tang, Shuaiqi;Zhang, Yunyan;Xie, Shaocheng
大气热量和水分预算的分析是研究某个区域对流特征并为各种建模应用提供大规模强迫场的有效工具。本文研究了计算大规模大气预算的两种流行方法：传统预算方法（CBM），主要基于无线电探空仪数据使用客观网格分析，以及约束变分分析（CVA）方法，该方法通过在大气顶部和表面进行测量来补充大气场的垂直剖面，以保存质量、水、能量和动量。成功的预算计算取决于对大气热力学状态以及与对流和影响它的大规模环流相关的发散场的准确采样和分析。利用 2011 年 10 月至 12 月在印度洋中部进行的马登-朱利安振荡动力学 (DYNAMO) 现场活动期间获取的数据进行的分析，我们评估了这些预算方法的优点并检验了它们的局限性。虽然 CBM 的许多缺点，特别是探测数据中采样误差的影响，可以通过 CVA 有效地最小化，但 CVA 中准确的大规模诊断依赖于可靠的背景场和降雨限制。对于所检查的 DYNAMO 分析，用作 CVA 背景状态的运行模型场提供了准确解析甘岛附近对流垂直结构的风场。然而，模型热力学场的偏差在 CVA 中有所放大，导致对流环境比观察到的要弱得多。
Analyses of atmospheric heat and moisture budgets serve as an effective tool to study convective characteristics over a region and to provide large‐scale forcing fields for various modeling applications. This paper examines two popular methods for computing large‐scale atmospheric budgets: the conventional budget method (CBM) using objectively gridded analyses based primarily on radiosonde data and the constrained variational analysis (CVA) approach which supplements vertical profiles of atmospheric fields with measurements at the top of the atmosphere and at the surface to conserve mass, water, energy, and momentum. Successful budget computations are dependent on accurate sampling and analyses of the thermodynamic state of the atmosphere and the divergence field associated with convection and the large‐scale circulation that influences it. Utilizing analyses generated from data taken during Dynamics of the Madden‐Julian Oscillation (DYNAMO) field campaign conducted over the central Indian Ocean from October to December 2011, we evaluate the merits of these budget approaches and examine their limitations. While many of the shortcomings of the CBM, in particular effects of sampling errors in sounding data, are effectively minimized with CVA, accurate large‐scale diagnostics in CVA are dependent on reliable background fields and rainfall constraints. For the DYNAMO analyses examined, the operational model fields used as the CVA background state provided wind fields that accurately resolved the vertical structure of convection in the vicinity of Gan Island. However, biases in the model thermodynamic fields were somewhat amplified in CVA resulting in a convective environment much weaker than observed.
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