Abstract
As an intrinsic feature of daily surface air temperature (SAT) variability found in station measurements, temporal asymmetry (TA) can be taken as an evaluation metric to access the quality of SAT re-analysis product. In this study, TA calculated from four SAT variables, i.e., daily mean SAT (Tmean), daily maximum SAT (Tmax), daily minimum SAT (Tmin) and diurnal temperature range (TDTR = Tmax − Tmin), is applied to evaluate synoptic-scale performance of four reanalysis products (NCEP-2, JRA-55, ERA-I, and ERA-5) over China. The results show that four re-analyses overall overestimate the TA of daily Tmax and Tmin variability over China, but with a comparatively consistent estimated TA for Tmean. Moreover, the TA of Tmean variability for these four re-analyses shares high spatial consistency with those from the observation. However, four re-analyses own the similar region-dependent spatial patterns of overestimated TA for Tmax and Tmin variability, especially for Tmax. Since high TA is an indicator for strong nonlinear feature, only Tmean reanalysis is the most suitable to explore synoptic-scale extreme events, such as heat waves and cold waves, which are highly related to the strong nonlinear processes.
Highlights
The marked results are that most values of estimated temporal asymmetry (TA) in Tmax and Tmin from all four re-analyses are overestimated, especially in Tmax, only a few from National Centers for Environmental Prediction (NCEP)-2 reanalysis are comparable with or lower than those from observations
This finding is consistent with previous studies in NCEP-2 reanalysis compared with limited station observations (Xie et al 2019)
Different from the results given by only one specific reanalysis product (NCEP-2), the results given here indicate that the overestimated TA in Tmax and Tmin from re-analyses may be taken as a shared intrinsic feature to all analyzed reanalysis products
Summary
Asymmetric phenomena are ubiquitous in both natural and social sciences (Heinrich 2004; King 1996; Livina et al 2003; Ashkenazy and Tziperman 2004 ; Lisiecki and Raymo 2005; Bartos and Jánosi 2005; Gyure et al 2007; Ashkenazy et al 2008, 2016; Bisgaard and Kulahci 2011; Xie et al 2016, 2019), and it is an important indicator of nonlinear underlying processes (Schreiber and Schmitz 2000; Bartos and Jánosi 2005; Gyüre et al 2007; Ashkenazy et al 2008; Roldan and Parrondo 2010; Lacasa et al 2012).As a kind of asymmetry, the temporal asymmetry (TA) in time series, defined by different statistics between forward and backward (reversed) directed series, plays an important role in air temperature variability studies (Bartos and Jánosi 2005; Gyüre et al 2007; Ashkenazy et al 2008; Xie et al 2016, 2019). Previous studies found that there exists differential TA among different temperature variables' daily fluctuations over China from both station observations and NCEP-2 re-analyses (Xie et al 2019). Is it a universal feature to different kinds of re-analyses for the reported overestimated TA in Tmax and Tmin variability from NCEP-2 re-analyses over China (Xie et al 2019; Li et al 2021)? Is it a universal feature to different kinds of re-analyses for the reported overestimated TA in Tmax and Tmin variability from NCEP-2 re-analyses over China (Xie et al 2019; Li et al 2021)? If the answer is yes, is there any spatial consistency among different reanalysis products?
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