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It remains a challenge for climate models to correctly capture the relationship between precipitation and ENSO. This study examines the linkage between the simulated precipitation climatology and ENSO-related precipitation anomaly during boreal winter based on the multi-model ensemble from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) and perturbed parameter ensemble (PPE) with the Beijing Climate Center (BCC) atmospheric model. The AMIP5 models have large biases in simulating the tropical precipitation anomaly during El Nino, such as the shifts of the Inter-Tropical Convergence Zone (ITCZ) and South Pacific Convergence Zone (SPCZ). The inter-model differences show that the precipitation change in response to sea surface temperature (SST) change increases with enhanced precipitation climatology. The ENSO-related precipitation anomaly can also be related to the spatial distribution of the mean-state precipitation. The simulated ITCZ/SPCZ displacements are significantly correlated with the spatial precipitation-SST relationship in the mean state. Models with stronger mean-state precipitation-SST relationship also produce stronger SPCZ/ITCZ displacements. The mean-state tropical precipitation also has strong impacts on the ENSO-related precipitation anomalies over East Asia. In the BCC PPE, the connection between the mean-state precipitation and ENSO-related precipitation anomaly is overall consistent with that in AMIP5. Parameters associated with the low-cloud and deep convection processes are the most influential ones for the precipitation simulations in BCC. Compared with the version in AMIP5, the new BCC model can better simulate the precipitation climatology and the relationship between ENSO and precipitation over southern China. These results have important implications for model development and model-based climate predictions.

Cluster extreme event (CEE), which is characterized by large affected area and long duration of extreme weather, has been arousing the worldwide serious concerns due to its severe impact on society. The winter cluster extreme events of low temperature (LT_CEEs) in the northern hemisphere from 1979 to 2013 are identified with a simplified objective method based on ERA-Interim and JRA-25 daily minimum surface air temperature. The probability density function (PDF) distributions of most indices in the winter LT_CEEs derived from the two datasets are well consistent with each other, especially in the occurrence frequency, duration, and affected area. As expected, the downward trend of all indices in recent 35 years under global warming is congruously revealed from both reanalysis. Nevertheless, the various indices of the winter LT_CEEs after 1998 are generally stable accompanied with slight upward trend, which might be closely related to the speed slowdown of global warming but require further investigation. Similar analysis was carried out with the simulated results of BCC_CSM1.1 model under four scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. The occurrence frequency of the winter LT_CEEs under RCP2.6 remains stable after 2050, but significantly decreases under RCP4.5 and RCP6.0, and disappears under RCP8.5 scenario. Overall, the descent rate of the winter LT_CEEs accelerates with the emission rise.

The uncertainty of global summer precipitation simulated by the 23 CMIP5 CGCMs and the possible impacts of model resolutions are investigated in this study. Large uncertainties exist over the tropical and subtropical regions, which can be mainly attributed to convective precipitation simulation. High-resolution models (HRMs) and low-resolution models (LRMs) are further investigated to demonstrate their different contributions to the uncertainties of the ensemble mean. It shows that the high-resolution model ensemble means (HMME) and low-resolution model ensemble mean (LMME) mitigate the biases between the MME and observation over most continents and oceans, respectively. The HMME simulates more precipitation than the LMME over most oceans, but less precipitation over some continents. The dominant precipitation category in the HRMs (LRMs) is the heavy precipitation (moderate precipitation) over the tropic regions. The combinations of convective and stratiform precipitation are also quite different: the HMME has much higher ratio of stratiform precipitation while the LMME has more convective precipitation. Finally, differences in precipitation between the HMME and LMME can be traced to their differences in the SST simulations via the local and remote air-sea interaction.

In this paper, the performance of the regional climate model (RegCM4) in simulating the interannual and interdecadal variation of Meiyu rainfall over lower and middle reaches of Yangtze River (LMRYR) in China is evaluated. The results show that the bias of the simulated Meiyu rainfall exhibits some uncertainties and obvious interdecadal variation similar with that of Meiyu rainfall itself. The rainfall bias and its interdecadal variation have little impact on the simulation of the interannual variation of the Meiyu rainfall. Not only the amplitude but also the phase of the interannual variation of the Meiyu rainfall can be reproduced by the RegCM4. However, the interdecadal variation of the rainfall bias has large impacts on the model’s performance in simulating the interdecadal component of the Meiyu rainfall, leading to lower skill of RegCM4 in simulating the interdecadal variation of the Meiyu rainfall than that in simulating the interannual variation. In addition, the interannual signals of the temperature, humidity, and vorticity in the lower troposphere in the large-scale NCEP lateral boundary force are stronger than the interdecadal signals, and the model can respond well to these interannual signals. Therefore, the RegCM4 has better performance in simulating the interannual variation of water vapor budget than the interdecadal variation, which further favors the simulation of the Meiyu rainfall at interannual time scale.

Based on the output data of Beijing Climate Center Atmospheric General Circulation Model version 2.0.1 (BCC_AGCM2.0.1), this study evaluates the simulated precipitation and associated circulation during the Meiyu period over the Yangtze-Huaihe River Basin (YHRB). The results show that BCC_AGCM2.0.1 can reasonably reproduce the spatial pattern of Meiyu over the YHRB. However, compared to the observation, the model underestimated (overestimated) the torrential and heavy (moderate and light) rainy days, indicating that the more (less) simulated light (torrential) rainy days result in more (less) modeled total rainy days (Meiyu precipitation amount). The simulated Meiyu onset begins in early June, earlier about 20 days than the climatological observation. For duration, Meiyu persists for 15 days, about 5 days shorter than the observation, which may be due to the simulated land-sea thermal contrast is earlier in early June. During the Meiyu period, the distribution patterns of the upper troposphere atmospheric circulation can be well simulated by BCC_AGCM2.0.1, but the obvious deficiency lies in the lower-troposphere air temperature and wind field, especially over Tibetan Plateau area.

NCEP/NCAR reanalysis daily data from 1951 to 2008 are used in this study to reveal the spatial-asymmetric features in the seasonal variation of the upper-tropospheric jet stream (UTJS) and its thermal dynamic forcing mechanism. The jet occurrence percentage distribution of the UTJS demonstrates a spiral-like pattern in winter, but it is quasi-annular in summer. The jet occurrence percentage in the Eastern Hemisphere is larger than that in the Western Hemisphere, and its maximum area is located further south. The polar front jet stream (PJS) and subtropical jet stream (SJS) can be distinguished over the Northern Africa and Asian regions, whereas only one jet stream can be observed over the Western Pacific and Atlantic Ocean. Furthermore, a single peak pattern is found in the seasonal variation of the SJS occurrence frequency with the highest jet occurrence appearing in winter and the lowest in summer, while a double peak pattern is observed in the seasonal variation of the PJS occurrence, i.e., the jet occurrence reaches its peaks in autumn and spring for the PJS. Based on the thermal wind theory, air temperature gradient and atmospheric baroclinicity are calculated and compared with the jet occurrence variation to explore the thermal dynamic forcing mechanism for the UTJS variation. In addition, synoptic-scale transports of eddy heat and momentum are also calculated. The results indicate that the SJS variation is primarily determined by the air temperature gradient and atmospheric baroclinicity, while the PJS variation is under great influence of the transport of eddy heat and momentum over Northern Africa and East Asia. The UTJS variation over the area from 140E to 70W cannot be well individually explained by the air temperature gradient and atmospheric baroclinicity. Further analysis indicates that UTJS variation over this area is largely under control of combined effect of the transport of eddy heat and momentum as well as the atmospheric baroclinicity.

A parameterization scheme for the thermal effects of subgrid scale orography is incorporated into a regional climate model (developed at Nanjing University) and its impact on modeling of the surface energy budget over East Asia is evaluated. This scheme includes the effect of terrain slope and orientation on the computation of solar and infrared radiation fluxes at the surface, as well as the surface sensible and latent heat fluxes. Calculations show that subgrid terrain parameters alter the diurnal cycle and horizontal distributions of surface energy budget components. This effect becomes more significant with increased terrain slope, especially in winter. Due to the inclusion of the subgrid topography, the surface area of a model grid box changes over complex terrain areas. Numerical experiments, with and without the subgrid scale topography scheme, show that the parameterization scheme of subgrid scale topography modifies the distribution of the surface energy budget and surface temperature around the Tibetan Plateau. Comparisons with observations indicate that the subgrid topography scheme, implemented in the climate model, reproduces the observed detailed spatial temperature structures at the eastern edge of the Tibetan Plateau and reduces the tendency to overestimate precipitation along the southern coastal areas of China in summer.

¶One of the most pronounced features of the land surface is its heterogeneity. In order to further understand land-atmosphere interactions and improve climate modeling it is very important to investigate effects of subgrid scale heterogeneities, especially hydrological-process heterogeneities. In this paper, after the construction and sensitivity tests of a hydrological model (VXM), which accounts for precipitation heterogeneity (PH) and infiltration heterogeneity (IH), we incorporated VXM into the NCAR (National Center for Atmospheric Research) regional climate model RegCM2 and thus obtained the augmented regional climate model (hereafter, ARCM). By using 3-month (May–July) observational data of 1991 Meiyu season, we conducted numerical experiments with ARCM, analyzed the sensitivities, and found that: (1) The regional climate and surface hydrology are very sensitive to IH as well as PH, i.e., the simulations for the surface fluxes, soil temperature, soil moisture, precipitation and surface runoff can be greatly affected by those heterogeneities. (2) ARCM can effectively improve the simulation of hydrological processes, i.e., it can greatly enhance the surface runoff ratio (i.e., the ratio of surface runoff to precipitation), which is consistent with observations over humid areas in China. (3) It seems that the IH influence on the surface climate is larger than the PH influence. (4) The modeled climate is sensitive to the VXM parameters. For example, it is significantly modified after the surface impermeable fraction has been accounted for, suggesting some features of aridification.