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An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Plain Language Summary: China is a vulnerable country to climate change due to its dense population, unbalanced social and economic development, shortage of water resources, and fragile ecosystems. How future precipitation will change over the region is of great concern for the general public and decision makers. This paper presents a first analysis of precipitation simulations from a set of five RCM (RegCM4) 21st century climate change projections, driven by coarse resolution general circulation models (GCMs) over China. We find that the spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by a precipitation underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in north China by both the GCMs and RegCM4 in all seasons except summer, when, weak correlations of the projected change patterns are found between the GCMs and nested RegCM4, indicating the greater role of the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Key Points: The spatial patterns of bias show common features between the GCMs and RegCM4RegCM4 provides greater spatial detail of present day precipitation simulation compared to the GCMs and finer structures of future changesThe change patterns across the RegCM4 projections show a high correlation, but not always between each pair of driving GCM and RegCM4 [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are developed to simulate the past climate and generate future climate predictions. In the context of global warming, their important roles in identifying possible solutions to water resources planning/management are recognized by the world. However, in actual and regional implementation, due to many factors like initial and boundary conditions, parameters and model structures and so forth, there are great variabilities and uncertainties across the future climate projections of GCMs outputs, which has attracted criticism from water resources planners. Thus, the GCMs usually must be evaluated for assessing their performances in simulating the historical observations. Currently, there are many different conclusions and opinions as to whether the optimal individual model is more advantageous or whether the combined consideration of MME works better. The purpose of this paper is to compare the advantages and disadvantages between the selection of the optimal single GCM and multi‐model ensemble (MME) based on one of the more objective selection methods called TOPSIS. The results show that the performances of GCMs in simulating precipitation and temperature in different climate subregions over China are not identical. For CMIP6 GCMs simulations, the optimal precipitation GCM is CMCC‐CM2‐SR5 for EC, MIROC6 for SC, SWC and NWC, CESM2‐WACCM for NC and NEC, and FGOALS‐g3 for QTP. As for temperature, only NESM3 and BCC‐ESM1 are the optimal GCM for QTP and NWC, respectively; in other subregions, MME is better than single GCM. In general, a simple arithmetic averaging approach employed to generate the MME model is not superior to the optimal GCM, although the error metric with the observed data is reduced, at the cost of a severe compression of the interannual variability. [ABSTRACT FROM AUTHOR]

Global circulation models (GCMs) are routinely used to project future climate conditions worldwide, such as temperature and precipitation. However, inputs with a finer resolution are required to drive impact‐related models at local scales. The non‐homogeneous hidden Markov model (NHMM) is a widely used algorithm for the precipitation statistical downscaling for GCMs. To improve the accuracy of the traditional NHMM in reproducing spatiotemporal precipitation features of specific geographic sites, especially extreme precipitation, we developed a new precipitation downscaling framework. This hierarchical model includes two levels: (1) establishing an ensemble learning model to predict the occurrence probabilities for different levels of daily precipitation aggregated at multiple sites and (2) constructing a NHMM downscaling scheme of daily amount at the scale of a single rain gauge using the outputs of ensemble learning model as predictors. As the results obtained for the case study in the central‐eastern China (CEC), show that our downscaling model is highly efficient and performs better than the NHMM in simulating precipitation variability and extreme precipitation. Finally, our projections indicate that CEC may experience increased precipitation in the future. Compared with ~26 years (1990–2015), the extreme precipitation frequency and amount would significantly increase by 21.9%–48.1% and 12.3%–38.3%, respectively, by the late century (2075–2100) under the Shared Socioeconomic Pathway 585 climate scenario. [ABSTRACT FROM AUTHOR]

A global model formulation for unified weather‐climate forecast is evaluated, with emphasis on the climate simulations at typical hydrostatic resolutions. The internal sensitivity is explored by considering different dynamical configurations (resolution, solver type, transport scheme). After a basic assessment of the global mean climate, a detailed analysis of precipitation characteristics is extended to East Asia. The model shows a reasonable mean state, seasonal variation, frequency–intensity structure, and diurnal phase time. The artificial rainfall around the steep slopes of the Tibetan Plateau can be improved through choices in the dynamical configuration. The regional features characterized by "afternoon versus nocturnal‐to‐early‐morning peaks" are properly distinguished. The hourly climatic features are comparable to super‐parameterized CAM5. Different dynamical configurations demonstrate unique sensitivities related to underling physical mechanisms, which are studied from the perspective of the diurnal cycle for three representative regions. Over South China, the higher‐resolution models decrease the weak‐precipitation while increase intense rainfall, thus reducing the dry biases. This is contributed by enhanced grid and sub‐grid scale motions associated with daytime convection progression. Over central western China, the variable‐resolution model better simulates the eastward propagating episodes characterized by a transition from convective to stratiform rainfall along the eastern slope of the Plateau. This reduces the positive biases at the high topography of the Plateau and alleviates the negative biases at the lower foot. Over central eastern China, the model replicates the dominant role of large‐scale governing factors in regulating the early morning rainfall peaks, and produces stratiform heating patterns. Plain Language Summary: We examine the statistical simulation of a model developed within the Global‐to‐Regional Integrated forecast SysTem, using Atmospheric Model Intercomparison Project style integration. This is among an effort in exploring a unified system for weather and climate modeling. Because of the evolutionary nature of model development, the absolute model performance can change. Thus, special attention is paid to the model sensitivity related to dynamical configurations, which helps to gain understanding that can support continuous research and development. Precipitation is one of the most important variables in a general circulation model as it encapsulates the synergistic effects of resolvable and non‐resolvable processes, the hydrological cycle, and radiative balance. Simulating precipitation faces the challenges in representing the moist physics and its interaction with dynamics. We use precipitation as performance metrics for a better understanding of the model behavior, focusing on a unique region–East Asia. The diurnal cycle is given particular emphasis because it reveals the direct physical mechanism of precipitation, and can help to disentangle the interactions between model dynamics and physics. We show that the models produce hourly rainfall features that are comparable to a global multiscale modeling framework that has two interactive dynamical solvers, and support some beneficial sensitivity. Key Points: To evaluate a model formulation for unified weather‐climate forecast using the Atmospheric Model Intercomparison Project‐style experimentTo understand model precipitation characteristics over East Asia by analyzing hourly scale apparent sources/sinks and grid‐scale tendenciesTo understand model sensitivity related to dynamical configurations, including grid resolution, moisture transport scheme and solver type [ABSTRACT FROM AUTHOR]