CCHZ‐DISO: A Timely New Assessment System for Data Quality or Model Performance From Da Dao Zhi Jian

Hu, Zengyun; Chen, Deliang; Chen, Xi; Zhou, Qiming; Peng, Yuzhou; Li, Jianfeng; Sang, Yan‐Fang

doi:10.1029/2022gl100681

Cited by 40 publications

(28 citation statements)

References 17 publications

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“…The correlation coefficient (CC), absolute error (AE), and root-mean-square error (RMSE) were employed to quantify the accuracy. Previously, we proposed a novel comprehensive index, Distance between Indices of Simulation and Observation (DISO) (Hu et al, 2019c;Zhou et al, 2021;Hu et al, 2022b), which has been widely used (Cui et al, 2020;Hu et al, 2020;. Therefore, in this study, DISO was employed to describe the comprehensive performance of the GPM.…”

Section: Datasets and Methodsmentioning

confidence: 99%

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Characteristics and physical mechanisms of a rainstorm in Hotan, Xinjiang, China

Yin

Zhang

Zhu³

et al. 2022

Front. Environ. Sci.

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Owing to global warming, extreme precipitation events in the arid regions of Central Asia have increased, resulting in significant consequences for water resources and ecosystems. Hence, to address the features and corresponding physical mechanisms of these rainstorms, we examined the rainstorm that occurred in Hotan, Xinjiang in June 2021 as a case study. We employed multiple datasets, including meteorological stations, sounding observations, satellite precipitation data, and reanalysis datasets. The results indicate that the Global Precipitation Measurement satellite precipitation product accurately captured the temporal and spatial variations in this rainstorm, as verified against hourly in situ observation data. Some meteorological stations recorded values greater than twice their historical records, such as Luopu, Pishan, Moyu, and Hotan. Moreover, the duration of the precipitation was longer than 2 days. For the physical mechanisms of this rainstorm, the water vapor in this rainstorm is sourced from the 45°–65°N region of the North Atlantic Ocean crosses the Ural Mountains and the West Siberian Plain to southern Xinjiang. The low-pressure levels (e.g., 700 hPa and 850 hPa) have the more water vapor flux and specific humidity than the high-pressure levels. Our findings can aid the understanding of extreme precipitation events in Central Asia and provide a reference for dealing with meteorological disasters, including extreme precipitation, in the context of global climate change.

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Section: Datasets and Methodsmentioning

confidence: 99%

“…In the DISO equation, RB is the relative bias, and NRMSE is the normalized RMSE. The details of DISO can be founded in Hu et al (2022b).…”

Section: Datasets and Methodsmentioning

confidence: 99%

Characteristics and physical mechanisms of a rainstorm in Hotan, Xinjiang, China

Yin

Zhang

Zhu³

et al. 2022

Front. Environ. Sci.

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“…In this study, we used DISO (the distance between indices of simulation and observation) indicator combined with correlation coefficient (r) and mean absolute error (MAE) to assess the reliability of ERA5-Land in capturing daily temperature data and 11 extreme temperature indices in the QLM (Hu et al, 2019;Zhou et al, 2021;Hu et al, 2022;Xu et al, 2022). The equation of DISO is shown in Table 3.…”

Section: Evaluation Methodsmentioning

confidence: 99%

Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China

Zhao

He²,

Ma³

et al. 2023

Front. Ecol. Evol.

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An increase in extreme temperature events could have a significant impact on terrestrial ecosystems. Reanalysis temperature data are an important data set for extreme temperature estimation in mountainous areas with few meteorological stations. The ability of ERA5-Land reanalysis data to capture the extreme temperature index published by the Expert Team on Climate Change Detection and Indices (ETCCDI) was evaluated by using the observational data from 17 meteorological stations in the Qilian Mountains (QLM) during 1979–2017. The results show that the ERA5-Land reanalysis temperature data can capture well for the daily maximum temperature, two warm extremes (TXx and TX90p) and one cold extreme (FD0) in the QLM. ERA5-Land’s ability to capture temperature extremes is best in summer and worst in spring and winter. In addition, ERA5-Land can capture trends in all extreme temperature indices except the daily temperature range (DTR). The main bias of ERA5-Land is due to the difference in elevation between the ground observation station and the ERA5-Land grid point. The simulation accuracy of ERA5-Land increases with the decrease of elevation difference. The results can provide a reference for the study of local extreme temperature by using reanalysis data.

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“…The actual values of R act are calculated using observed data from ground stations. Three evaluation indices, Nash-Sutcliffe efficiency coefficient (NSE), distance of indices between simulation and observation (DISO) (Zhou et al, 2021;Hu et al, 2022), and percentage deviation (P bias ), were selected to assess the precision of R act estimated by the three methods. The three evaluation indices are expressed as follows:…”

Section: The Precision Calculation Of R Actmentioning

confidence: 99%

The index of clothing for assessing tourism climate comfort: Development and application

Liu²,

Deng³

et al. 2023

Front. Environ. Sci.

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Climate comfort is a significant factor in analyzing the effects of climate change on tourism, and considerable research has used multidimensional climate indices to evaluate climate comfort. In particular, the index of clothing (ICL) is recognized as one of the most popular climate indices and has been widely applied in many studies. While few studies focused on the calculation method of the index of clothing model’s surface solar radiation (Ract), the computed value was greater than that observed at ground stations. Thus, this study tried to improve solar radiation energy calculation on the Earth’s surface in the index of clothing model with the method recommended by the International Food and Agriculture Organization (FAO), and then validated the new model based on the meteorological data of 31 provincial capitals in mainland China during 1980–2019. Results showed that: 1) The value of Ract calculated by the International Food and Agriculture Organization (FAO) method was close to the site observations (Pbais < 15%), and was suggested to be used in enhancing the estimate approach for Ract in the index of clothing; 2) Different from the original index of clothing, ICL-new is significantly more effective in evaluating climate comfort in middle and low latitude regions; 3) Climate change had a considerable influence on the climate comfort of cities in mainland China. Since 1980, the climate comfort of cities in eastern China had increased in spring, while that of cities in western China had declined, and most cities had a decreasing trend in summer. Finally, our findings revealed that ICL-new can realistically and precisely depicts the actual scenario than the original index of clothing, and it is more suitable to provide scientific impact assessment and tourism management for government agencies and destination management.

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CCHZ‐DISO: A Timely New Assessment System for Data Quality or Model Performance From Da Dao Zhi Jian

Cited by 40 publications

References 17 publications

Characteristics and physical mechanisms of a rainstorm in Hotan, Xinjiang, China

Characteristics and physical mechanisms of a rainstorm in Hotan, Xinjiang, China

Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China

The index of clothing for assessing tourism climate comfort: Development and application

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