Geophysical Fluid Dynamics Laboratory Research Articles

The lagged connection of the positive NAO with the MJO phase 3 in a simplified atmospheric model

Based on a simplified nonlinear model and reanalysis data, the lagged connection of the North Atlantic Oscillation (NAO) with the Madden–Julian Oscillation (MJO) in boreal winters is investigated. The positive NAO is observed to occur more frequently about 8–20 days after the onset of the MJO phase 3. A series of heating forcing experiments and initial-value experiments are conducted by utilizing the Geophysical Fluid Dynamics Laboratory (GFDL) dynamical core atmospheric model. The extratropical responses to the tropical heating associated with the MJO phase 3 are characterized by a wave train over the Pacific–North American region with an anticyclone anomaly over the northeastern Pacific and then followed by a positive-NAO-like pattern over the North Atlantic sector. These circulation anomalies generally match the observed lagged-connection well. At the earlier stage, the Rossby wave train excited by the MJO convection propagates into the North Atlantic, leading to a planetary wave anomaly with a low-over-high dipole prior to the positive NAO. At the later stage, the anomalous synoptic eddy vorticity forcing (EVF) streamfunction tendency has a negative-over-positive dipole, which plays a key role in the development of the positive NAO. Further analysis of the initial-value experiments indicates that, for the subsequent formation of the positive NAO, the anomalous circulation over the Indian Ocean aroused by the MJO phase 3 is more crucial than that over the northeastern Pacific.

The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs

AbstractIn this two‐part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea‐ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top‐of‐atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.

The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies

AbstractIn Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

Equilibrium Climate Sensitivity Obtained From Multimillennial Runs of Two GFDL Climate Models

AbstractEquilibrium climate sensitivity (ECS), defined as the long‐term change in global mean surface air temperature in response to doubling atmospheric CO2, is usually computed from short atmospheric simulations over a mixed layer ocean, or inferred using a linear regression over a short‐time period of adjustment. We report the actual ECS from multimillenial simulations of two Geophysical Fluid Dynamics Laboratory (GFDL) general circulation models (GCMs), ESM2M, and CM3 of 3.3 K and 4.8 K, respectively. Both values are ~1 K higher than estimates for the same models reported in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change obtained by regressing the Earth's energy imbalance against temperature. This underestimate is mainly due to changes in the climate feedback parameter (−α) within the first century after atmospheric CO2 has stabilized. For both GCMs it is possible to estimate ECS with linear regression to within 0.3 K by increasing CO2 at 1% per year to doubling and using years 51–350 after CO2 is constant. We show that changes in −α differ between the two GCMs and are strongly tied to the changes in both vertical velocity at 500 hPa (ω500) and estimated inversion strength that the GCMs experience during the progression toward the equilibrium. This suggests that while cloud physics parametrizations are important for determining the strength of −α, the substantially different atmospheric state resulting from a changed sea surface temperature pattern may be of equal importance.

Modelling the effects of climate and land-use change on the hydrochemistry and ecology of the River Wye (Wales)

Interactions between climate change and land use change might have substantial effects on aquatic ecosystems, but are still poorly understood. Using the Welsh River Wye as a case study, we linked models of water quality (Integrated Catchment - INCA) and climate (GFDL - Geophysical Fluid Dynamics Laboratory and IPSL - Institut Pierre Simon Laplace) under greenhouse gas scenarios (RCP4.5 and RCP8.5) to drive a bespoke ecosystem model that simulated the responses of aquatic organisms. The potential effects of economic and social development were also investigated using scenarios from the EU MARS project (Managing Aquatic Ecosystems and Water Resources under Multiple Stress). Longitudinal position along the river mediated response to increasing anthropogenic pressures. Upland locations appeared particularly sensitive to nutrient enrichment or potential re-acidification compared to lowland environments which are already eutrophic. These results can guide attempts to mitigate future impacts and reiterate the need for sensitive land management in upland, temperate environments which are likely to become increasingly important to water supply and biodiversity conservation as the effects of climate change intensify.

Dominant Role of Atlantic Multidecadal Oscillation in the Recent Decadal Changes in Western North Pacific Tropical Cyclone Activity

AbstractOver the 1997–2014 period, the mean frequency of western North Pacific (WNP) tropical cyclones (TCs) was markedly lower (~18%) than the period 1980–1996. Here we show that these changes were driven by an intensification of the vertical wind shear in the southeastern/eastern WNP tied to the changes in the Walker circulation, which arose primarily in response to the enhanced sea surface temperature (SST) warming in the North Atlantic, while the SST anomalies associated with the negative phase of the Pacific Decadal Oscillation in the tropical Pacific and the anthropogenic forcing play only secondary roles. These results are based on observations and experiments using the Geophysical Fluid Dynamics Laboratory Forecast‐oriented Low‐ocean Resolution Coupled Climate Model coupled climate model. The present study suggests a crucial role of the North Atlantic SST in causing decadal changes to WNP TC frequency.

Index-Based Study of Future Precipitation Changes over Subansiri River Catchment under Changing Climate

This study focuses on the long-term (2011-2100) changes in precipitation indices under different climate change scenarios in Subansiri river basin, a tributary of Brahmaputra River in Northeast India. The fifth phase coupled model intercomparison project (CMIP5) data for different representative concentration pathways (RCPs) scenarios as suggested by Intergovernmental Panel on Climate Change (IPCC) is used for the study. Statistical downscaling model (SDSM) is used to downscale the precipitation. Three global climate model (GCM) datasets from earth system model and geophysical fluid dynamics laboratory (namely ESM2G, ESM2M, and GFDL-CM3) with four RCP scenarios (namely RCP2.6, RCP4.5, RCP6.0, and RCP8.5) were used for generating daily precipitation time series for a time period of 2011 to 2100. Precipitation based indices were computed on a multi-decadal time scale to detect the changes in precipitation pattern and its distribution. Total five precipitation stations were selected for downscaling and precipitation indices analysis. The non-parametric Mann-Kendall test method was used for the trend analysis of the precipitation indices. Indices based analysis of the precipitation shows an increase in the intensity of precipitation whereas a decrease in number of precipitation days on the lower part of the basin. The increase in number of rainy days followed by a decrease in intensity in the upper station was observed. Long-term (2011-2100) future projection of precipitation for annual precipitation shows statistically significant increase of minimum 1.8% at station 1 (for RCP2.6) to maximum 11% in station 3 (for RCP8.5) as compared to observed period annual precipitation.

Estimation of Drought Change Trends in Northeast China in 2020-2050 and Its Impact on Maize Yield

Based on the results of nine Coupled Model Intercomparison Project Phase 5 (CMIP5) coupling models, the temperature and precipitation data of 114 stations in Northeast China were compared and analyzed. The simulation effect of CMIP5 model on precipitation and temperature in Northeast China was evaluated. The research shows that the Geophysical Fluid Dynamics Laboratory Earth System Models (GGFDL-ESM2G) have the best simulation effect on precipitation and temperature in Northeast China. Based on the SPEI index, the relationship between the drought trend of maize growing season and the yield change rate of maize in Northeast China was analyzed, and the future drought (2020-2050) and corn yield in Northeast China were estimated. The cumulative Standardized Precipitation Evapotranspiration Index (SPEI) analysis of the northeast maize growing season (May-September) shows that the drought in the northeastern region showed an intensifying trend from 1980 to 2010, especially in the first ten years of the 21st century. The cumulative SPEI index has a significant positive correlation with the yield of maize in Northeast China, and has a certain indicator effect on the yield of maize in Northeast China. The three scenarios of GFDL-ESM2G model show that under the three scenarios of Representative Concentration Pathways (RCP), the warming in Northeast China is significant; under the RCP4.5 scenario, the precipitation in Northeast China is increasing; in the RCP2.6 and RCP8.5 climate scenarios, precipitation is presented and reduces the trend of drought. Estimates of drought trends in Northeast China show that under the RCP4.5 climate scenario, the drought in Northeast China showed a slowing trend from 2020 to 2050. Under the RCP2.6 and RCP8.5 climate scenarios, the drought in Northeast China showed an increasing trend. Under the RCP2.6 and RCP8.5 climate scenarios, the yield change rate of maize in Northeast China showed a downward trend, indicating that climate warming caused the drought in Northeast China to increase, which had a negative impact on corn yield increase. In severe drought years, drought may cause northeast corn production seriously reduced. However, under the RCP4.5 scenario, drought has little effect on corn yield.

Response of the Tropical Indian Ocean to Greenhouse Gases and Aerosol Forcing in the GFDL CM3 Coupled Climate Model

ABSTRACTThe response of the tropical Indian Ocean (TIO) to greenhouse gases (GHGs) and aerosols are investigated based on historical single-forcing and all-forcing simulations using the Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3). Results reveal a positive Indian Ocean Dipole (pIOD)-like pattern in GHG forcing but a negative Indian Ocean Dipole (nIOD)-like pattern in aerosol forcing. The GHG-induced pIOD-like pattern features less (more) sea surface temperature (SST) warming over the southeastern (western) TIO, accompanied by equatorial easterly anomalies, as well as a shallower thermocline off Sumatra. The aerosol-induced nIOD-like pattern displays the reverse features, characterized by less (more) SST cooling over the southeastern (western) TIO, anomalous equatorial westerlies, and a deeper thermocline off Sumatra. Although the aerosol-induced pattern appears to resemble a reversal of the GHG-induced pattern, there is a strong asymmetry in the SST changes over the southeastern TIO, where the cooling responding to aerosol forcing exceeds the warming in response to GHG forcing, and a negative SST residual is thus produced. A mixed-layer heat budget analysis suggests that the negative SST residual results mainly from asymmetric responses of shortwave radiation, zonal advection, and diffusion to GHGs and aerosols. For comparison, the formation processes for the negative SST skewness over the southeastern TIO between the internal pIOD and nIOD are also discussed.

Impact of Intraseasonal Oscillations on the Tropical Cyclone Activity Over the Gulf of Mexico and Western Caribbean Sea in GFDL HiRAM

AbstractThe tropical cyclones (TCs) that form over the warm waters in the Gulf of Mexico region pose a major threat to the surrounding coastal communities. Skillful subseasonal prediction of TC activity is important for early preparedness and reducing the TC damage in this region. In this study, we evaluate the performance of a 25 km resolution Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) in simulating the modulation of the TC activity in the Gulf of Mexico and western Caribbean Sea by the intraseasonal oscillation (ISO) based on multiyear retrospective seasonal predictions. We demonstrate that the HiRAM faithfully captures the observed influence of ISO on TC activity over the region of interest, including the formation of tropical storms and (major) hurricanes, as well as the landfalling storms. This is likely because of the realistic representation of the large‐scale anomalies associated with boreal summer ISO over Northeast Pacific in HiRAM, especially the enhanced (reduced) moisture throughout the troposphere during the convectively enhanced (suppressed) phase of ISO. The reasonable performance of HiRAM suggests its potential for the subseasonal prediction of regional TC risk.

A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error

AbstractA new paradigm in benchmark absorption‐scattering radiative transfer is presented that enables both the globally averaged and spatially resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol instantaneous radiative effect (IRE). A proof of concept is demonstrated with the Geophysical Fluid Dynamics Laboratory AM4 and Community Earth System Model 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model‐relevant biases. These diagnostic results show that the models' aerosol IRE bias is of the same magnitude as the persistent range cited (~1 W/m2) and also varies spatially and with intrinsic aerosol optical properties. The findings underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.

Improved Seasonal Prediction of Rainfall over East Africa for Application in Agriculture: Statistical Downscaling of CFSv2 and GFDL-FLOR

AbstractStatistically downscaled forecasts of October–December (OND) rainfall are evaluated over East Africa from two general circulation model (GCM) seasonal prediction systems. The method uses canonical correlation analysis to relate variability in predicted large-scale rainfall (characterizing, e.g., predicted ENSO and Indian Ocean dipole variability) to observed local variability over Kenya and Tanzania. Evaluation is performed for the period 1982–2011 and for the real-time forecast for OND 2015, a season when a strong El Niño was active. The seasonal forecast systems used are the National Centers for Environmental Prediction Climate Forecast System, version 2 (CFSv2), and the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution (GFDL-FLOR) version of CM2.5. The Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) rainfall dataset—a blend of in situ station observations and satellite estimates—was used at 5 km × 5 km resolution over Kenya and Tanzania as benchmark data for the downscaling. Results for the case-study forecast for OND 2015 show that downscaled output from both models adds realistic spatial detail relative to the coarser raw model output—albeit with some overestimation of rainfall that may have been derived from the downscaling procedure introducing a wet response to El Niño more typical of historical cases. Assessment of the downscaled forecasts over the 1982–2011 period shows positive long-term skill better than that documented in previous studies of unprocessed GCM forecasts for the region. Climate forecast downscaling is thus a key undertaking worldwide in the generation of more reliable products for sector specific application including agricultural planning and decision-making.

Weddell Polynya Transport Mechanisms in the Abyssal Ocean

AbstractWeddell Polynya transport mechanisms in the deep and abyssal oceans are examined in the NOAA Geophysical Fluid Dynamics Laboratory’s (GFDL) coupled climate model CM2G. During an 1820-yr-long integration of the model, polynyas are forced every 29 years in the Weddell Sea via an increase in the diapycnal diffusivity. Composites of the events are used to examine the mechanisms responsible for transporting polynya signals away from the Weddell Sea. Polynya signal transport is governed by two dynamical mechanisms that act on different time scales and spread at different rates. Large-scale waves, such as Kelvin and planetary and topographic Rossby waves, propagate the polynya signal rapidly, on interannual-to-decadal time scales, while advection transports the signal more slowly, on decadal-to-centennial time scales. Despite their different spreading rates, these mechanisms can act contemporaneously, and it is often their combined effect that governs the property changes in the global deep and abyssal oceans. Both waves and advection cause temperature changes on isobaths. In the deep Atlantic, advection accounts for <15% of the total temperature change in the model, indicating that waves are strongly dominant there. Elsewhere, waves are still the stronger contributor, but advection accounts for 20%–40% of the total temperature change.

The Impact of Climate Change on Hazardous Convective Weather in the United States: Insight from High-Resolution Dynamical Downscaling

This study explores the potential impact anthropogenic climate change may have upon hazardous convective weather (HCW; i.e., tornadoes, large hail, and damaging wind gusts) in the United States. Utilizing the Weather Research and Forecasting (WRF) Model, high-resolution (4 km) dynamically downscaled simulations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), are produced for a historical (1971–2000) and future (2071–2100) period. Synthetic HCW day climatologies are created using upward vertical velocity (UVV) exceeding 22 m s−1 as a proxy for HCW occurrence and subsequently compared to the environmental approach of estimating changes in daily frequency of convective environments favorable for HCW (NDSEV) from the driving climate model. Results from the WRF simulations demonstrate that the proxy for HCW becomes more frequent by the end of the twenty-first century, with the greatest absolute increases in daily frequency occurring during the spring and summer. Compared to NDSEV from GFDL CM3, both approaches suggest a longer HCW season, perhaps lengthening by more than a month. The change in environmental estimates are 2–4 times larger than that gauged from WRF; further analyses show that the conditional probability of HCW given NDSEV declines during summer for much of the central United States, a result that may be attributed to both an increase in the magnitude of convective inhibition (CIN) and decreased forcing for ascent, hindering convective initiation. Such an outcome supports the motivation for continued use of dynamical downscaling to overcome the limitations of the GCM-based environmental analysis.

Process-Oriented Diagnosis of Tropical Cyclones in High-Resolution GCMs

This study proposes a set of process-oriented diagnostics with the aim of understanding how model physics and numerics control the representation of tropical cyclones (TCs), especially their intensity distribution, in GCMs. Three simulations are made using two 50-km GCMs developed at NOAA’s Geophysical Fluid Dynamics Laboratory. The two models are forced with the observed sea surface temperature [Atmospheric Model version 2.5 (AM2.5) and High Resolution Atmospheric Model (HiRAM)], and in the third simulation, the AM2.5 model is coupled to an ocean GCM [Forecast-Oriented Low Ocean Resolution (FLOR)]. The frequency distributions of maximum near-surface wind near TC centers show that HiRAM tends to develop stronger TCs than the other models do. Large-scale environmental parameters, such as potential intensity, do not explain the differences between HiRAM and the other models. It is found that HiRAM produces a greater amount of precipitation near the TC center, suggesting that associated greater diabatic heating enables TCs to become stronger in HiRAM. HiRAM also shows a greater contrast in relative humidity and surface latent heat flux between the inner and outer regions of TCs. Various fields are composited on precipitation percentiles to reveal the essential character of the interaction among convection, moisture, and surface heat flux. Results show that the moisture sensitivity of convection is higher in HiRAM than in the other model simulations. HiRAM also exhibits a stronger feedback from surface latent heat flux to convection via near-surface wind speed in heavy rain-rate regimes. The results emphasize that the moisture–convection coupling and the surface heat flux feedback are critical processes that affect the intensity of TCs in GCMs.

Colliding Modons: A Nonlinear Test for the Evaluation of Global Dynamical Cores

AbstractThe modon, a pair of counter‐rotating vortices propelling one another along a straight line, is an idealization of some observed large‐scale and small‐scale atmospheric and oceanic processes (e.g., twin cyclones), providing a challenging nonlinear test for fluid‐dynamics solvers (known as “dynamical cores”). We present an easy‐to‐setup test of colliding modons suitable for both shallow‐water and three‐dimensional dynamical cores on the sphere. Two pairs of idealized modons are configured to collide, exchange vortices, and depart in opposite directions, repeating indefinitely in the absence of ambient rotation. This test is applicable to both hydrostatic and nonhydrostatic dynamical cores and is particularly challenging for refined grids on the sphere, regardless of solution methodology, or vertical coordinate. We applied this test to three popular dynamical cores, used by three different general circulation models: the Spectral‐Element (SE) core of the Community Atmosphere Model, the Geophysical Fluid Dynamics Laboratory (GFDL) spectral core, and the GFDL Finite‐Volume Cubed‐Sphere dynamical core (FV3). Tests with a locally refined grid and nonhydrostatic dynamics were also performed with FV3. All cores tested were able to capture the propagation, collision, and exchange of the modons, albeit the rate at which the modon was diffused varied between the three cores and showed a strong dependence on the strength of hyperdiffusion.

Drivers of Continued Surface Warming After Cessation of Carbon Emissions

AbstractThe climate response after cessation of carbon emissions is examined here, exploiting a single equation connecting surface warming to cumulative carbon emissions. The multicentennial response to an idealized pulse of carbon is considered by diagnosing a 1,000 year integration of an Earth system model (Geophysical Fluid Dynamics Laboratory ESM2M) and an ensemble of efficient Earth system model simulations. After emissions cease, surface temperature evolves according to (i) how much of the emitted carbon remains in the atmosphere and (ii) how much of the additional radiative forcing warms the surface rather than the ocean interior. The peak in surface temperature is delayed in time after carbon emissions cease through the decline in ocean heat uptake, which in turn increases the proportion of radiative forcing warming the surface. Eventually, after many centuries, surface temperature declines as the radiative forcing decreases through the excess atmospheric CO2 being taken up by the ocean and land.

The impact of anthropogenic land use and land cover change on regional climate extremes

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model’s near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2–3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model’s novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

A Weather-Type-Based Cross-Time-Scale Diagnostic Framework for Coupled Circulation Models

Abstract This study proposes an integrated diagnostic framework based on atmospheric circulation regime spatial patterns and frequencies of occurrence to facilitate the identification of model systematic errors across multiple time scales. To illustrate the approach, three sets of 32-yr-long simulations are analyzed for northeastern North America and for the March–May season using the Geophysical Fluid Dynamics Laboratory’s Low Ocean–Atmosphere Resolution (LOAR) and Forecast-Oriented Low Ocean Resolution (FLOR) coupled models; the main difference between these two models is the horizontal resolution of the atmospheric model used. Regime-dependent biases are explored in the light of different atmospheric horizontal resolutions and under different nudging approaches. It is found that both models exhibit a fair representation of the observed circulation regime spatial patterns and frequencies of occurrence, although some biases are present independently of the horizontal resolution or the nudging approach and are associated with a misrepresentation of troughs centered north of the Great Lakes and deep coastal troughs. Moreover, the intraseasonal occurrence of certain model regimes is delayed with respect to observations. On the other hand, interexperiment differences in the mean frequencies of occurrence of the simulated weather types, and their variability across multiple time scales, tend to be negligible. This result suggests that low-resolution models could be of potential use to diagnose and predict physical variables via their simulated weather type characteristics.

Land surface air temperature variations over Eurasia and possible causes in the past century

ABSTRACTIn this study, the variations of annual land surface air temperature (SAT) over Eurasia and the northern part of Africa (0°–180°E, 0°–90°N) were investigated using monthly SAT data from the Climatic Research Unit, University of East Anglia for 1901–2014 and the simulations from the Geophysical Fluid Dynamics Laboratory coupled model. The observed results suggested that the SAT variations exhibited robust non‐uniform spatial features at multi‐time scales. For the variations in inter‐annual to decadal time scales (IDV), the intensity generally increased from south to north, with the strongest intensity being around Siberia and four times that of the weakest intensity found around China. The IDV leading pattern showed a north–south dipole across 40°N. The simulated results suggested that the north–south dipole and the northwards increase of the IDV were due to internal interactions within the complex nonlinear climate system, but the natural and greenhouse gas forcings could intensify the IDV.The warming trend of the SAT was generally homogeneous, but it showed distinctive multi‐decadal fluctuations in different regions. The linear secular trends and robust multi‐decadal variation around Siberia and China corresponded to the considerable acceleration and deceleration in the warming over the two regions, respectively. The warming around Siberia was mainly caused by greenhouse gases but its modulation due to natural forcing was also considerable because of the robust multi‐decadal variations. Around China, the multi‐decadal variation, contributed by the natural forcing, can explain more than half the variances in the warming. The warming trend around central Asia was intense and parabolic, and the multi‐decadal variation over there was weak and showed few modulating effects.