Based on time series and linear trend analysis, the authors evaluated the performance of the fourth generation atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP AGCM4.0), in simulating surface air temperature (SAT) during the twentieth century over China and the globe. The numerical experiment is conducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major warming regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the Southern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model under-estimates the observed trend over the continents. More-over, the model simulates the spatial distribution of SAT in China, with a bias of approximately-2°C in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.
Based on four sets of numerical simulations prescribed with atmospheric radiative forcing and sea surface temperature(SST) forcing in the Community Atmospheric Model version 3(CAM3), the interannual and interdecadal variabilities of the Antarctic oscillation(AAO) during austral summer were studied. It was found that the interannual variability is mainly driven by SST forcing. On the other hand, atmospheric radiative forcing plays a major role in the interdecadal variability. A cooling trend was found in the high latitudes of the Southern Hemisphere(SH) when atmospheric radiative forcing was specified in the model. This cooling trend tended to enhance the temperature gradient between the mid and high latitudes in the SH, inducing a transition of the AAO from a negative to a positive phase on the interdecadal timescale. The cooling trend was also partly weakened by the SST forcing, leading to a better simulation compared with the purely atmospheric radiative forcing run. Therefore, SST forcing cannot be ignored, although it is not as important as atmospheric radiative forcing.
In this study,the authors investigated changes in Last Glacial Maximum(LGM)sea surface temperature(SST)simulated by the Paleoclimate Modelling Intercomparison Project(PMIP)multimodels and reconstructed by the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface(MARGO)project,focusing on model-data comparison.The results showed that the PMIP models produced greater ocean cooling in the North Pacific and Tropical Ocean than the MARGO,particularly in the northwestern Pacific,where the modeldata mismatch was larger.All the models failed to capture the anomalous east-west SST gradient in the North Atlantic.In addition,large discrepancies among the models were observed in the mid-latitude ocean,particularly with models in the second phase of the PMIP.Although these models showed better agreement with the MARGO,the latest models in the third phase of the PMIP did not show substantial progresses in simulating LGM ocean surface conditions.That is,improvements in the modeling community are still needed to describe SST for a better understanding of climate during the LGM.
Based on NCEP/NCAR(National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data from 1979 to 2010, the impacts of two types of El Nio on atmospheric circulation in the Southern Hemisphere(SH) are analyzed. It is shown that, when a warming event occurs in the equatorial eastern Pacific(EP El Nio), there is a negative sea level pressure(SLP) anomaly in the eastern Pacific and a positive one in the western Pacific. Besides, there exists a negative anomaly between 40°S and 60°S and a positive anomaly to the south of 60°S. When a warming event in the central Pacific(CP El Nio) occurs, there appears a negative SLP anomaly in the central Pacific and a positive SLP anomaly in the eastern and western Pacific, but the SLP anomalies are not so evident in the SH extratropics. In particular, the Pacific–South America(PSA) pattern induced by the CP El Nio is located more northwestward, with a weaker anomaly compared with the EP El Nio. This diference is directly related with the diferent position of heating centers associated with the two types of El Nio events. Because the SST anomaly associated with CP El Nio is located more westward than that associated with EP El Nio, the related heating center tends to move westward and the response of SH atmospheric circulation to the tropical heating changes accordingly, thus exciting a diferent position of the PSA pattern. It is also noted that the local meridional cell plays a role in the SH high latitudes during EP El Nio. The anomalous ascending motion due to the enhancement of convection over the eastern Pacific leads to an enhancement of the local Hadley cell and the meridional cell in the middle and high latitudes, which in turn induces an anomalous descending motion and the related positive anomaly of geopotential height over the Amundsen-Bellingshausen Sea.
The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly.
Based on a simulation using a newly developed climate system model(Chinese Academy of Sciences-Earth System Model-Climate system component, CAS-ESM-C), the author investigated the Aleutian Low- Icelandic Low Seesaw(AIS) and its decadal variation. Results showed that the CAS-ESM-C can reasonably reproduce not only the spatial distribution of the climatology of sea level pressure(SLP) in winter, but also the AIS and its decadal variation. The period 496–535 of the integration by this model was divided into two sub-periods: 496–515(P1) and 516–535(P2) to further investigate the decadal weakening of the AIS. It was shown that this decadal variation of the AIS is mainly due to the phase transition of the Pacific Decadal Oscillation(PDO), from its positive phase to its negative phase. This transition of the PDO causes the sea surface temperature(SST) in the equatorial eastern(northern) Pacific to cool(warm), resulting in the decadal weakening of mid-latitude westerlies over the North Pacific and North Atlantic. This may be responsible for the weakening of the inverse relation between the Aleutian Low(AL) and the Icelandic Low(IL).
This study focuses on the intraseasonal variation of the East Asian summer monsoon(EASM) simulated by IAP AGCM4.0, the fourth-generation atmospheric general circulation model recently developed at the Institute of Atmospheric Physics,Chinese Academy of Sciences. In general, the model simulates the intraseasonal evolution of the EASM and the related rain belt. Besides, the model also simulates the two northward jumps of the western Pacific subtropical high(WPSH), which are closely related to the convective activities in the warm pool region and Rossby wave activities in high latitudes. Nevertheless,some evident biases in the model were found to exist. Due to a stronger WPSH, the model fails to simulate the rain belt in southern China during May and June. Besides, the model simulates a later retreat of the EASM, which is attributed to the overestimated land–sea thermal contrast in August. In particular, the timing of the two northward jumps of the WPSH in the model is not coincident with the observation, with a later jump by two pentads for the first jump and an earlier jump by one pentad for the second, i.e., the interval between the two jumps is shorter than the observation. This bias is mainly ascribed to a shorter oscillating periodicity of convection in the tropical northwestern Pacific.
