Differential temporal asymmetry among different temperature variables’ daily fluctuations

Xie, Fenghua; Nian, Da; Fu, Zuntao

doi:10.1007/s00382-018-04603-1

Cited by 13 publications

(17 citation statements)

References 75 publications

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“…Here we use high‐resolution regional climate model simulations and it has been shown that regional climate model simulations provide more realistic information of precipitation, with intensities and frequencies comparable to the recorded station data (Chan et al ., ), than global climate models. To make a direct comparison between station data and model simulations, some studies remap the gauge measurements onto a regular grid similar to the simulations (Diaconescu et al ., ), some interpolate the model grid points to the gauge locations (Xie et al ., ), and some directly choose the grid points closest to the stations (Diaconescu et al ., ; Pendergrass and Knutti, ). Here we choose the simplest way, in that we selected the closest grid point to compare with station observations.…”

Section: Methodsmentioning

confidence: 99%

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Yang

Franzke

2019

Intl Journal of Climatology

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Precipitation is an important meteorological variable which is critical for weather risk assessment. For instance, intense but short precipitation events can lead to flash floods and landslides. Most statistical modelling studies assume that the occurrence of precipitation events is based on a Poisson process with exponentially distributed waiting times while precipitation intensities are typically described by a gamma distribution or a mixture of two exponential distributions. Here, we show by using hourly precipitation data over the United Sates that the waiting time between precipitation events is non‐exponentially distributed and best described by a fractional Poisson process. A systematic model selection procedure reveals that the hourly precipitation intensities are best represented by a two‐distribution model for about 90% of all stations. The two‐distribution model consists of (a) a generalized Pareto distribution (GPD) model for bulk precipitation event sizes and (b) a power‐law distribution for large and extreme events. Finally, we analyse regional climate model output to evaluate how the climate models represent the high‐frequency temporal structure of U.S. precipitation. Our results reveal that these regional climate models fail to accurately reproduce the power‐law behaviour of intensities and severely underestimate the long durations between events.

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Section: Methodsmentioning

confidence: 99%

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Yang

Franzke

2019

Intl Journal of Climatology

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“…TA has been found to be an intrinsic feature in daily surface air temperature (SAT) variability in station measurements (Bartos and Jánosi 2005;Gyüre et al 2007;Xie et al 2016Xie et al , 2019Li et al 2021). Although similar TA behavior was also reported in re-analysis data (Ashkenazy et al 2008;Xie et al 2019;Li et al 2021), only a few studies (Xie et al 2019;Li et al 2021) compared TA difference between station measurement and re-analysis products, detailed and systematic comparative studies are still required. More specifically, 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)?…”

Section: Introductionmentioning

confidence: 85%

“…For commonly used temperature variables, daily mean temperature (Tmean), daily maximum SAT (Tmax), daily minimum SAT (Tmin) and diurnal temperature range (TDTR= Tmax-Tmin), TA strengths among these four temperature variables are markedly different with the weakest TA for DTR and the strongest TA for Tmean. Compared with the TA from station observations, TA from Tmax and Tmin in National Centers for Environmental Prediction (NCEP) AMIP-II Reanalysis (hereafter NCEP-2, Kanamitsu et al 2002) is highly overestimated for most regions over China (Xie et al 2019).…”

Section: Introductionmentioning

confidence: 90%

“…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 2008Ashkenazy et al , 2016Bisgaard and Kulahci 2011;Xie et al 2016Xie et al , 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).…”

Section: Introductionmentioning

confidence: 99%

“…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 2016Xie et al , 2019. Previous studies also 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). For commonly used temperature variables, daily mean temperature (Tmean), daily maximum SAT (Tmax), daily minimum SAT (Tmin) and diurnal temperature range (TDTR= Tmax-Tmin), TA strengths among these four temperature variables are markedly different with the weakest TA for DTR and the strongest TA for Tmean.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Re-analyses Over China based on the Temporal Asymmetry of Daily Temperature Variability

Chai

Huang

Yang

et al. 2021

Preprint

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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.

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Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China

Yan

2022

Intl Journal of Climatology

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The acceleration of global warming leads to frequent extreme weather events. The sensitivity of high-elevation regions to global warming makes their extremes more prominent. Based on the software Rclimdex1.0, 15 extreme climate indices from 120 meteorological stations in Yunnan from 1960 to 2019 were calculated. Trend analysis, correlation analysis, and cross-correlation analysis were used to investigate the spatiotemporal variation characteristics of these extreme climate indices. The results showed that, except CDD, other extreme precipitation indices were negatively correlated with the increase of elevation. The extreme warming indices (SU25, WSDI, TX90p, TN90p) showed an increasing trend with the increase of elevation, while the extreme cold indices (CSDI, FD0, TX10p, TN10p) showed a decreasing trend with the increase of elevation. The rate of nocturnal warming at high elevations is higher than that at low elevations. The change rate of extreme warmth indices (SU25, WSDI, TX90p, TN90p) and extreme cold indices (FD0, CSDI, TX10p, TN10p) was negatively correlated (p < .05) in all elevation ranges, and this correlation was most significant in the elevation range of 1,500-2,000 m. These results highlight that the rate of drying and warming at higher elevations is higher than that at lower elevations, providing case support and scientific basis for sensitivity of high-altitude regions to extreme climate.

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Differential temporal asymmetry among different temperature variables’ daily fluctuations

Cited by 13 publications

References 75 publications

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Evaluation of Re-analyses Over China based on the Temporal Asymmetry of Daily Temperature Variability

Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China

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