Assessment of air temperatures from different meteorological reanalyses for the East Antarctic region between Zhonshan and Dome A

Xie, Aihong; Allison, Ian; Xiao, Cunde; Shimeng, Wang; Ren, Jiawen; Qin, Dahe

doi:10.1007/s11430-013-4684-4

Cited by 8 publications

(19 citation statements)

References 33 publications

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“…In general, the monthly RMSE for ERA Interim T max is large at Dome A, but smaller at the other three sites. The performance of T max at the three sites is similar to that of T mean (Xie et al, 2014). Figure 5 presents Taylor diagrams summarizing the performance of ERA Interim reanalysis for the austral seasons of spring, summer, autumn, and winter.…”

Section: Assessment Of the Monthly And Seasonal Performance Of Era Inmentioning

confidence: 74%

“…(4) The in situ stations lie in different grid points for each reanalysis. Hence, we focused on the basic evaluation of reanalysis, and the observed data were directly compared with those from the grid cell covering the site, with neither elevation correlation nor interpolation (Xie et al, 2014). Surface daily T min and T max statistics for the reanalysis and observational data were examined to assess the daily, annual, and seasonal performance.…”

Section: Methodsmentioning

confidence: 99%

“…Xie et al (2014) and Ma et al (2008) have given details for this correction. We also filtered the height-corrected data to eliminate outliers that are more than three standard deviations outside the average daily value for the study period covering [2005][2006][2007][2008].…”

Section: Observational Meteorological Datamentioning

confidence: 99%

“…Previous research in Antarctica has emphasized mean temperature (T mean ) from reanalysis and observations, showing that reanalysis data are useful for monitoring changes in data-sparse regions (Boccara et al, 2008;Bromwich et al, 2007;Genthon et al, 2010;Gobiet, 2005;Xie et al, 2014). Few studies in Antarctica have focused on maximum temperatures (T max ) or minimum temperatures (T min ), which are more sensitive to climate change than their mean values (IPCC, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, given the limited coverage of purely in situ observations, it is necessary to determine whether reanalysis can fill the gaps in these databases (Donat et al, 2014). Xie et al (2014) suggested that ERA Interim performs best in East Antarctica, after comparing these data with the other reanalysis for T mean . Hence, we selected ERA Interim to evaluate extracted daily T min and T max , to determine whether ERA Interim could replicate temperature extremes in East Ant-arctica during [2005][2006][2007][2008].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Can Temperature Extremes in East Antarctica be Replicated from ERA Interim Reanalysis?

Xie

Wang

Xiao

et al. 2016

Arctic, Antarctic, and Alpine Research

Self Cite

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Section: Assessment Of the Monthly And Seasonal Performance Of Era Inmentioning

confidence: 74%

Section: Methodsmentioning

confidence: 99%

Section: Observational Meteorological Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Can Temperature Extremes in East Antarctica be Replicated from ERA Interim Reanalysis?

Xie

Wang

Xiao

et al. 2016

Arctic, Antarctic, and Alpine Research

Self Cite

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Water vapor‐weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend

et al. 2016

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Water vapor‐weighted mean temperature, Tm, is a vital parameter for retrieving precipitable water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems (GNSS) signal propagation. In this study, the Tm at 368 GNSS stations for 2000–2012 were calculated using three methods: (1) temperature and humidity profiles from ERA‐Interim, (2) the Bevis Tm–Ts relationship, and (3) the Global Pressure and Temperature 2 wet model. Tm derived from the first method was used as a reference to assess the errors of the other two methods. Comparisons show that the relative errors of the Tm derived from these two methods are in the range of 1–3% across more than 95% of all the stations. The PWVs were calculated using the aforementioned three types of Tm and the GNSS‐derived ZWD at 107 stations. Again, the PWVs calculated using Tm from the first method were used as the reference of the other two PWVs. The root‐mean‐square errors of these two PWVs are both in the range of 0.1–0.7 mm. The second method is recommended in real‐time applications, since its performance is slightly better than the third method. In addition, the linear trends of the PWV time series from the first method were also used as the reference to evaluate the trends from the other two methods. Results show that 13% and 23% of the PWV trends from the respective second and third methods have a relative error of larger than 10%. For climate change studies, the first method, if available, is always recommended.

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Temperature variability over the past three centuries in the coastal region of Princess Elizabeth Land, Antarctica, reconstructed from ice core stable isotope records

Huang,

Qian,

Yan

et al. 2023

Quaternary International

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Assessment of air temperatures from different meteorological reanalyses for the East Antarctic region between Zhonshan and Dome A

Cited by 8 publications

References 33 publications

Can Temperature Extremes in East Antarctica be Replicated from ERA Interim Reanalysis?

Can Temperature Extremes in East Antarctica be Replicated from ERA Interim Reanalysis?

Water vapor‐weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend

Temperature variability over the past three centuries in the coastal region of Princess Elizabeth Land, Antarctica, reconstructed from ice core stable isotope records

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