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Vegetation activity and phenology are significantly affected by climate change, and changes in vegetation activity and phenology can in turn affect regional or global climate patterns. As one of the world’s great biomes, temperate grasslands have undergone remarkable changes in recent decades, but the connections between vegetation activity and phenology changes and regional climate there have remained unclear. Using the observation minus reanalysis (OMR) method, this study investigated the possible effects of vegetation activity and vegetation growing season changes on air temperatures in temperate grasslands of China. The results showed that average NDVI of the temperate grassland significantly increased by 0.011 decade21 for the growing season during 1982–2015. The growing season started earlier and ended later, resulting in an extension. Increased vegetation activity during spring and autumn significantly warmed spring and autumn air temperatures by reducing albedo. By contrast, summer greening had no significant effect on summer temperature, due to the opposing effects of decreased albedo and enhanced evapotranspiration on temperature. The earlier start and later end of the growing season contributed to warmer spring and autumn air temperatures. As phenological changes had no significant effect on summer temperature, the extended growing season warmed air temperature. Our results suggest that the climate change–induced increasing vegetation activity and extended growing seasons can further aggravate regional warming in temperate grasslands of China, implying that the effects of vegetation activity and phenology changes on regional climate should be considered in climate models for accurately simulating climate change in temperate grasslands. [ABSTRACT FROM AUTHOR]

A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the early-twentieth-century Arctic warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and subdaily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from 10 individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days, day-to-day temperature variability, and the onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the contemporary Arctic warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7°C) and Canadian Arctic (1.9°C) regions. A shortening of winter and lengthening of summer were noted. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW. Significance Statement: It is well established that human activity (particularly increased greenhouse gas emissions) is the primary driving mechanism of the recent dramatic warming in the Arctic. However, the causes of a similar warming here in the first half of the twentieth century remain uncertain. The limited knowledge about the climate of that period—which mainly results from the low resolution of data—is a significant obstacle to a definitive determination of the forcing mechanisms. Therefore, the main aim of our paper is to improve our understanding of specific aspects of weather and climate (including extremes) using long-term series of daily and subdaily data that have rarely been applied for this purpose. This new, more comprehensive knowledge about the historical Arctic climate should allow the scientific community (particularly climate modelers) to better validate both climate models and reanalysis products and, consequently, to more precisely identify the causes of the early-twentieth-century Arctic warming. [ABSTRACT FROM AUTHOR]

Based on observational data from 1961 to 2014, the ability of 20 global climate models (GCMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate surface air temperature climatology and variability over the Tibetan Plateau (TP) is evaluated. The possible difference between the simulations of CMIP6 models and temperature simulations by models participating in the fifth phase of the CMIP (CMIP5) over the TP is also examined. The results reveal that most GCMs have the ability to reproduce climatological patterns and seasonal spatial variations in the surface air temperature. However, most GCMs have a cold bias, with a mean underestimation of 0.05–8.28 °C, and the multimodel ensemble means (MME) and medians of 20 GCMs underestimate the climatological mean over the TP by approximately 2.51 °C and 2.22 °C for 1961–2014. Regarding annual temperature, the top five GCMs with the least amount of bias for both the spatial distribution and regional-averaged temperature are NESM3, UKESM1.0-LL, CESM2, HadGEM3-GC3.1-LL, and GISS-ES.1-G. The cold bias of GCMs over the eastern TP is smaller than that over the TP, and the cold bias is more serious over the western TP. The MME and multimodel median values of 20 GCMs are − 2.00 °C and − 1.94 °C over the eastern TP, respectively, while they are − 3.00 °C and − 2.35 °C over the western TP. Regarding seasonal temperature, outputs from CMIP6 GCMs also reveal a significant cold bias over the western TP that is particularly prominent in spring and winter. Compared with CIMP5 simulations, the CIMP6 models seem to show very limited improvement over the TP. Cold bias is more serious for annual, spring, summer, and winter simulations in CMIP6 than in CMIP5, especially over the western TP. Nevertheless, the simulations of the geographical distribution of annual and seasonal temperatures are further improved in CMIP6. Moreover, over the northeastern TP, such as Tsaidam Basin and Qilian Mountain, GCMs from CMIP6 show slight improvement. [ABSTRACT FROM AUTHOR]

The decadal surface air temperature (SAT) variation over East Asia (EA) is characterized by an opposite pattern, warming over the northern EA along with cooling over the southern EA, and vice versa, fluctuating on decadal time scale. We found that Pacific Decadal Oscillation (PDO) has been largely responsible for the opposite decadal SAT variation. Positive (negative) phase of the PDO is related to the northern warming (cooling) and southern cooling (warming) over EA, and the decadal variation of the opposite SAT pattern is highly correlated with the PDO decadal variability, implying a decadal modulation of SAT by PDO. We investigated the influence of PDO on the opposite decadal SAT pattern by employing a dynamical adjustment method based on constructed circulation analogues. The results showed that the PDO associated variability in the large-scale atmospheric circulation over Eurasia, characterized by a dipole structure with cyclonic circulation occupying the northern Eurasia but anticyclonic circulation over the southern Eurasia when in positive PDO phase, is responsible for the opposite decadal SAT pattern. Further analysis on the origin of the anomalous atmospheric circulation was performed by combining observations and climate model simulations. Based on observations and the multi-model simulations of Atmospheric Model Intercomparison Project (AMIP) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we found a contribution of intrinsic atmospheric dynamics, which was further suggested by the results using the Community Atmosphere Model simulations. • Decadal temperature variation over East Asia is characterized by dipole pattern. • Pacific Decadal Oscillation is responsible for the decadal temperature variation. • Pacific Decadal Oscillation modulates temperature via atmospheric circulation anomaly. [ABSTRACT FROM AUTHOR]

The effect of Eurasian spring snowmelt on surface air temperature (SAT) in late spring (April-May) and early summer (June-July) and the relevant physical mechanisms during 1981-2016 are investigated. Results show that the first mode of the interannual Eurasian spring snowmelt represents an east-west dipole anomaly pattern, with an intense center over Siberia and another moderate center around eastern Europe. The European spring snowmelt shows an insignificant relation to the local SAT, whereas the Siberian spring snowmelt has a significant impact on the SAT in late spring and early summer. More Siberian spring snowmelt contributes to higher SAT in late spring and lower SAT in early summer via different mechanisms. In late spring, increased Siberian spring snowmelt corresponds to less local surface albedo and cloud cover, leading to the surface absorbing more shortwave radiation and thereby higher SAT. The subsurface and deep soil moisture anomalies generated from Siberian spring snowmelt can persist into early summer. Excessive Siberian spring snowmelt corresponds to positive soil moisture anomalies, contributing to decreased sensible heat and increased cloud cover in early summer. Increased cloud cover leads to the surface receiving less shortwave radiation. Thus, lower SAT appears over Siberia in early summer due to reduced sensible heat and shortwave radiation. However, the simulation of Eurasian spring snowmelt variability and its influences on SAT via the snow hydrological effect is still a challenge for the climate models that participated in phase 6 of the Coupled Model Intercomparison Project. [ABSTRACT FROM AUTHOR]