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Quantitative assessment of urbanization effect on surface air temperature (SAT) change provides crucial basis for formal detection and attribution analyses of climate change. However, debates about urbanization‐related warming bias in documented regional SAT trend still persist, mainly due to different determination of rural stations. Here the urbanization effect on SAT change over the Beijing–Tianjin–Hebei region in China during 1980–2019 is estimated through three kinds of ways (i.e., comparisons between urban and rural stations [arithmetically station‐averaged], urban‐dominated and rural‐dominated patches [patch‐weighted mean], and realistic urban and rural areas [area‐weighted mean]). The last method explicitly takes urban and rural land cover fractions into account when calculating urban/rural and regional mean SAT trends. Urbanization‐induced warming in the annual mean SAT change of urban stations (areas) through the three ways are estimated as 0.159°C, 0.195°C, and 0.138°C per decade, respectively. And urbanization effect on regional averaged annual mean SAT calculated by patch‐weighted and area‐weighted methods are 0.113°C and 0.050°C per decade, respectively, which account for 33.8% and 14.8% of the total regional warming. The urbanization effect on observed SAT change estimated by considering realistic urban/rural land cover proportions is much lower than traditional station‐unweighted way. [ABSTRACT FROM AUTHOR]

Using the daily 2 m maximum temperature (Tmax), 2 m minimum temperature (Tmin) and cloud cover data measured at ground sites of the China Meteorological Administration in North China from 2000 to 2017, this study investigates the influence of clouds on the daily temperature range (DTR) defined as the difference between Tmax and Tmin. As expected, the cloud cover shows the similar averaged spatial distribution and monthly variation with Tmin. Surprisingly, it also shows the similar average spatial distribution and monthly variation with Tmax, suggesting the more important roles of regions (latitude) and seasons associated with the variations of land surface temperature, which is further related to solar radiation absorbed and surface heat capacity. By comparing monthly variations of temperature between cloudy and clear skies, we find that clouds can weaken Tmax and increase Tmin, and thus decrease DTR. As a result, the spatial distribution of DTR is opposite to the cloud cover. The clouds have relatively stronger impact on Tmin and DTR over mountain region, which is most likely caused by the stronger longwave cloud radiative forcing associated with higher cloud tops over the mountain region. [ABSTRACT FROM AUTHOR]

We investigated interdecadal relationship changes between the Arctic oscillation (AO) and Aleutian low (AL) for the period 1980–2021 along with the linkage on surface air temperature (SAT) over Eastern Eurasia during the boreal winter (December–January–February). The AO–AL relationship has weakened since the mid‐1990s. To explore a possible explanation, we compared atmospheric fields for two contrasting periods, one when the AO–AL relationship is the strongest (1986–2006) and one when it is the weakest (2000–2020). In both periods, atmospheric circulation over the Arctic region for the two AO–AL in‐phase relationships (i.e., either +AO/+AL or –AO/−AL) evolves with negative AO‐like patterns, contributing to a weakening AO–AL relationship in concurrent with a cool SAT in Eastern Eurasia. We found that the correlation between AL and SAT over Eastern Eurasia decreases, while the AO and SAT correlation remains unchanged. This implies that low‐frequency atmospheric circulation changes such as those of the AO and AL should be considered when studying SAT changes in Eastern Eurasia. [ABSTRACT FROM AUTHOR]

Observational studies indicated that the East Asian winter monsoon (EAWM) showed significant decadal variations and experienced an interdecadal weakening in the mid‐1980s. How did the EAWM evolve thereafter? In this study, we investigate the decadal variations of the EAWM in the past three decades using five reanalysis datasets and one observational dataset. In total, five members of EAWM system are examined. In the lower troposphere, the Siberian high intensity becomes stronger around 2005 in all five reanalysis datasets, whereas the Aleutian low strengthens in the mid‐1990s and weakens in the mid‐2000s. The two subsystems show opposing changes in the past two decades. In the middle troposphere, the intensity of the East Asian trough remains weakening in recent decades only with some short‐time strengthening around the years of 1995 and 2010. In the upper troposphere, the EAWM index based on the meridional shear of the East Asian jet stream at the 300‐hPa level shows a weak positive trend since the 1990s. It has decadal variations similar to those of the East Asian trough. In the context of these members' changes, the low‐level northerly wind index exhibits two cycles since the year 1980. This index increases in the mid‐1980s, then decreases since the mid‐1990s, and finally increases in the mid‐2000s. Further analysis on the East Asian surface air temperature also reflects similar decadal variations. In summary, unlike the interdecadal shift in the mid‐1980s, the EAWM members (i.e., the Siberian high, the Aleutian low, the low‐level northwesterly wind, the East Asian trough and the East Asian jet stream) do not show consistent decadal variations over the past 30 years. The low‐level members show more significant changes. [ABSTRACT FROM AUTHOR]