Intramonthly Variability of Daily Surface Air Temperature in Russia in 1970–2015

Babina, E. D.; Семенов, В. А.

doi:10.3103/s1068373919080028

Cited by 11 publications

(2 citation statements)

References 22 publications

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“…The minimum RMSE values were observed in the tropical zone (as expected, due to the lower temperature variations). Canada, Alaska, Greenland, and Russia showed the worst RMSE, possibly due to the high surface air temperature variability at several temporal scales; furthermore, the air temperature has significantly increased in those regions in the last few decades in comparison to other regions [50][51][52]. Figure 7c shows the temperature bias spatial distribution, with a mean global value of 0.0 ± 0.6 K and a maximum absolute value of 2.8 K. Positive values indicate an HGPT model overestimation (e.g., northern of Canada and western Russia) and negative values indicate an underestimation (e.g., Antarctic regions).…”

Section: Resultsmentioning

confidence: 99%

An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

et al. 2020

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The Global Navigation Satellite System (GNSS) meteorology contribution to the comprehension of the Earth’s atmosphere’s global and regional variations is essential. In GNSS processing, the zenith wet delay is obtained using the difference between the zenith total delay and the zenith hydrostatic delay. The zenith wet delay can also be converted into precipitable water vapor by knowing the atmospheric weighted mean temperature profiles. Improving the accuracy of the zenith hydrostatic delay and the weighted mean temperature, normally obtained using modeled surface meteorological parameters at coarse scales, leads to a more accurate and precise zenith wet delay estimation, and consequently, to a better precipitable water vapor estimation. In this study, we developed an hourly global pressure and temperature (HGPT) model based on the full spatial and temporal resolution of the new ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The HGPT model provides information regarding the surface pressure, surface air temperature, zenith hydrostatic delay, and weighted mean temperature. It is based on the time-segmentation concept and uses the annual and semi-annual periodicities for surface pressure, and annual, semi-annual, and quarterly periodicities for surface air temperature. The amplitudes and initial phase variations are estimated as a periodic function. The weighted mean temperature is determined using a 20-year time series of monthly data to understand its seasonality and geographic variability. We also introduced a linear trend to account for a global climate change scenario. Data from the year 2018 acquired from 510 radiosonde stations downloaded from the National Oceanic and Atmospheric Administration (NOAA) Integrated Global Radiosonde Archive were used to assess the model coefficients. Results show that the GNSS meteorology, hydrological models, Interferometric Synthetic Aperture Radar (InSAR) meteorology, climate studies, and other topics can significantly benefit from an ERA5 full-resolution model.

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Section: Resultsmentioning

confidence: 99%

An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

et al. 2020

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“…On the other hand, a decrease in the meridional temperature gradient in the NH mid-and high latitudes due to accelerated warming of the Arctic weakens cold (and warm) intrusions and, hence, the variability of temperature anomalies in general [108]. This is supported by the analysis of daily temperature variations in different spectral ranges using data from Russian stations [109]. It is still an open question of whether the mid-and high-latitude weather becomes more extreme with global warming.…”

Section: Problems To Solve and Urgent Tasksmentioning

confidence: 78%

Modern Arctic Climate Research: Progress, Change of Concepts, and Urgent Problems

Семенов

2021

Izv. Atmos. Ocean. Phys.

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A review of some major advances in studies of Arctic climate change in the last decade is presented. Mechanisms of positive feedbacks leading to accelerated climate changes in the northern high latitudes are considered. Some recently popular hypotheses of the rapid Arctic climate change that failed when confronted with observed climate changes are exemplified. Urgent problems regarding Arctic climate change are formulated.

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Daily temperature variation in March in East Asia from 1979 to 2020

Kim,

Ahn

2024

Clim Dyn

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Intramonthly Variability of Daily Surface Air Temperature in Russia in 1970–2015

Cited by 11 publications

References 22 publications

An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

Modern Arctic Climate Research: Progress, Change of Concepts, and Urgent Problems

Daily temperature variation in March in East Asia from 1979 to 2020

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