The distinct problems of physical inconsistency and of multivariate bias involved in the statistical adjustment of climate simulations,International Journal of Climatology

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The distinct problems of physical inconsistency and of multivariate bias involved in the statistical adjustment of climate simulations
International Journal of Climatology ( IF 3.5 ) Pub Date : 2022-09-21 , DOI: 10.1002/joc.7878
Mégane Alavoine ₁ , Patrick Grenier _{1,

2}

Affiliation

Bias adjustment of numerical climate model simulations involves several arguments wherein the notion of physical inconsistency is referred to, either for rejecting the legitimacy of bias adjustment in general or for justifying the necessity of sophisticated multivariate techniques. However, this notion is often mishandled, in part because the literature generally proceeds without defining it. In this context, the central objective of this study is to clarify and illustrate the distinction between physical inconsistency and multivariate bias, by investigating the effect of bias adjustment on two different kinds of intervariable relationships, namely a physical constraint expected to hold at every step of a time series and statistical properties that emerge with potential bias over a climatic timescale. To this end, 18 alternative bias adjustment techniques are applied on 10 climate simulations at 12 sites over North America. Adjusted variables are temperature, pressure, relative humidity and specific humidity, linked by a thermodynamic constraint. The analysis suggests on the one hand that a clear instance of potential physical inconsistency can be avoided with either a univariate or a multivariate technique, if and only if the bias adjustment strategy explicitly considers the physical constraint to be preserved. On the other hand, it also suggests that sophisticated multivariate techniques alone are not complete adjustment strategies in presence of a physical constraint, as they cannot replace its explicit consideration. By involving common bias adjustment procedures with likely effects on diverse basic statistical properties, this study may also help guide climate information users in the determination of adequate bias adjustment strategies for their research purposes.

中文翻译：

气候模拟的统计调整中涉及的物理不一致和多变量偏差的明显问题

数值气候模型模拟的偏差调整涉及几个论点，其中提到了物理不一致的概念，要么是为了拒绝一般偏差调整的合法性，要么是为了证明复杂的多元技术的必要性。然而，这个概念经常被错误地处理，部分原因是文献通常没有定义它。在这种情况下，本研究的中心目标是通过调查偏差调整对两种不同类型的变量间关系的影响，即预期在每时间序列的步骤和在气候时间尺度上具有潜在偏差的统计特性。为此，在北美 12 个地点的 10 个气候模拟中应用了 18 种替代偏差调整技术。调整后的变量是温度、压力、相对湿度和比湿度，它们通过热力学约束联系起来。分析表明，一方面，当且仅当偏差调整策略明确考虑保留物理约束时，可以使用单变量或多变量技术避免明显的潜在物理不一致实例。另一方面，它也表明，在存在物理约束的情况下，仅靠复杂的多变量技术并不是完整的调整策略，因为它们不能替代其明确的考虑。通过涉及可能对各种基本统计特性产生影响的常见偏差调整程序，

更新日期：2022-09-21

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