Attributing the surface air temperature (SAT) trends at regional scale to internally generated and externally forced components is a major challenge. Based on the observations and ensemble simulations of climate models, we apply a “dynamical adjustment” methodology to estimate quantitatively the contribution of the internal and forced dynamic and thermodynamic components to the East Asian winter SAT trends during 1979–2018. The observed winter SAT trends are strongly influenced by internal variability, especially in the northern East Asia (NEA). The internal component of observed SAT trends is largely dynamically induced, whereas the forced component is controlled by thermodynamics. The internally generated variability offsets the forced warming by more than 70% in the NEA, leading to a weak observed warming in the NEA. In contrast, internal contributions are small in the southern East Asia. The internally generated SAT changes in the NEA are closely tied to the multidecadal changes of Arctic Oscillation.

The present study applies the empirical orthogonal function (EOF) method to investigate the large-scale pattern and the plausible dynamic processes of the boreal winter diurnal temperature range (DTR) changes in the East Asia (EA)–Australia (AUS) region based on the CRU Time Series version 4.00 (TS4.00) and NCEP–NCAR reanalysis datasets. Results show that the DTR changes during 1948–2015 are dominated by two distinct modes. The first mode, characterized by a same-sign variation over most regions of EA–AUS, represents a declining trend of DTR. The second mode, featuring an opposite-sign variation, represents the interannual variations in DTR. The two modes are both closely associated with the changes in cloud cover (CLT) caused by atmospheric circulation anomalies in EA–AUS. For the trend mode, anomalous southerly and northerly winds over EA and AUS, respectively, bring warm and wet air from low latitudes to EA–AUS, inducing an increase in CLT and thereby reducing DTR in most areas of EA–AUS. The changes of circulation are mainly due to the thermodynamic responses of atmosphere to the nonuniform warming in EA–AUS. In addition, the second mode of DTR is largely forced by the ENSO variability. The weakened Walker circulation associated with warm ENSO events triggers a pair of anomalous low-level anticyclones (south and north of the equator) over the western Pacific. The AUS region is under control of the southern anticyclone, thereby reducing the CLT and increasing the DTR in AUS as a result of anomalous descending motion. In contrast, the EA region is controlled by anomalous southerlies to the west of the northern anticyclone. The northward transports of moistures from the warm ocean increase the CLT, reducing DTR in EA.

Whether the rapid warming of the Arctic, particularly the Barents-Kara Sea (BKS), substantially affects the Eurasian winter climate has been debated for over a decade. Here, we use an extended dynamical adjustment method to separate the effects of internal dynamics and thermodynamically forced BKS warming on atmospheric circulation, relying solely on observations. Evidence shows that the observed link between BKS warming and Eurasian cooling is influenced by both atmospheric internal variability and forced BKS warming. Internal variability, particularly the Arctic Oscillation, predominantly contributed to the observed Eurasian cooling from 1991 to 2012. While BKS warming has a weaker impact on Eurasian cooling on interannual to interdecadal timescales, it notably affects multidecadal scales, contributing to the observed “warming hole” in central Eurasia during 1980–2022. Our findings suggest a weak but non-negligible Eurasian cooling response to BKS warming on multidecadal timescales. These findings advance the understanding of the complex causal relationships between Arctic and mid-latitude climates.

Detecting the contributions of internal variability and external forcing to the evolution of surface air temperature (SAT) trend at regional scales is a challenge. Based on the observations and large-ensemble simulations of climate models, we estimate the contribution of the internal and forced components to the evolution of East Asian winter land SAT (EAWT) during 1961–2018. Although the external forcing induced EAWT trends show a slow increase, both the total and internally generated EAWT trends exhibit a decrease with the extension of the time period, suggesting a critical role of internal variability in the evolution of the EAWT trends. The internal variability contributes to about 70% of total EAWT trends during 1961–1995. With the extension of the time period, the contribution of internal variability decreases, whereas the contribution of external forcing gradually grows to dominate the EAWT trends. Based on the dynamical adjustment method, we identify that the internal dynamics and forced thermodynamics account for a majority of internal and forced EAWT variations, respectively. We further identify that the multidecadal fluctuation of internal component of autumn Arctic sea ice is a critical precursor of the internal variability, especially the internal dynamically induced EAWT variations, through triggering a meridional stationary Rossby wave response in the following boreal winter. Our findings provide an insight into the understanding of the present and future climate change over East Asia.

Since 1960s, India experiences a series of extreme drought and flood events during the summer months. The Humid Subtropical Climatic Zone (HSTC), which comprises the Indo‐Gangetic Plain region of India, is highly vulnerable to the climatic extremities. This region is the home for approximately 40% of total population and yields approximately 50% of total agricultural production of India. We investigate the historical variation in dry/wet conditions and project the future changes in extreme events under two different scenarios of the Coupled Model Inter‐comparison Project 5 models. First, the model parameters, that is, precipitation (P) and temperature (T) are bias corrected with respect to observation data and finally six models are selected, which are in right phase with the observation for composite analysis. Next, we calculate the potential evapotranspiration (PET) and the Standardized Potential Evapotranspiration Index to characterize the extreme events. BothPand PET are projected to increase in theHSTCzone; however, both the wet and dry conditions demonstrate a persistent increase in future. In relative terms,Pincreases faster thanPETalong the Gangetic Plain region (wet condition) and decreases in the southern and eastern part of the region (dry condition). The mitigating effect (RCP4.5 scenario) of precipitation increase will be overridden by strengthenedPETand extreme dry condition project markedly underRCP8.5 scenario. The features are consistent with the increase/ decrease in multimodel meanSPEI, consistent with the spatial pattern ofP−PET. The area affected due to wet and dry events will be relatively higher under theRCP4.5 andRCP8.5 scenario, respectively.