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--> --> -->Moreover, convective and large-scale precipitation components are closely associated with the vertical distribution of moisture (Bretherton et al., 2004) and cloud fractions (Zhao, 2014; Wang and Zhang, 2016). Because the radiative effects of low and high clouds differ (Wetherald and Manabe, 1988), the different components of convective and large-scale precipitation may closely correspond to different climate feedbacks (Zelinka et al., 2013, Stephens et al., 2019), eventually driving uncertainties in climate change projection (Andrews et al., 2012; Kauppinen and Malmi, 2018). Distinguishing the differences in convective and large-scale precipitation among climate models is helpful in understanding the uncertainties of future projection.
The outputs of the new-generation phase 6 of the Coupled Model Intercomparison Project (CMIP6) models were recently released, providing a new opportunity to revisit the aforementioned dilemmas. Are there any distinct features of the convective/large-scale (C/L) precipitation partitions among these CMIP6 models, particularly in terms of heavy rainfall? To what extent does model resolution influence C/L rainfall components in heavy rainfall? And what are the associated moisture/cloud vertical distributions? The following sections will answer the above questions in sequence.
To identify the effect of horizontal resolution on C/L components, several pairs of models which released both high- and low-resolution versions were obtained (see section 3.2). To identify the climate feedback, the surface air temperature outputs are also applied in the simulations forced by an abrupt quadrupling of CO2 (abrupt-4xCO2) experiment of CMIP6 models, which covers the years 2000–14. The observed RH is derived from ECMWF Reanalysis v5 (ERA5) (Copernicus Climate Change Service, 2017), which has a horizontal resolution of 0.25° × 0.25° and 37 pressure levels. To avoid the effect of resolution on results, all model datasets were interpolated onto a 1° × 1° grid using the nearest-neighbor interpolation method (Accadia et al., 2003).
To describe the frequency/percentage distribution of precipitation as a function of intensity, the daily precipitation rate was divided into a 1 mm d?1 interval, starting from 0.5 mm d?1 (He et al., 2019). Following the definition of different precipitation intensities by the China Meteorological Administration and previous studies (e.g., Matsumoto and Takahashi, 1999; He et al., 2019), this study focuses on features above 50 mm d?1, which is the usual threshold selection for heavy precipitation.
A 1 mm d?1 interval composite of rainfall intensity for the whole tropical domain was made in order to investigate the behaviors of moisture and cloud fraction vertical profiles against different rainfall intensities. Here, the tropical region covers the area between 20°S and 20°N. To discuss the effect of climate feedback, the surface temperature anomaly of the period 1850–2000 was obtained by removing the air temperature of the year 1850.
3.1. Classification of C/L rainfall partitions for tropical heavy rainfall in CMIP6
To recognize the current status of tropical C/L rainfall partitions associated with heavy rainfall in CMIP6, the frequency distributions and percentage contributions of the C/L component against rainfall intensity in 16 CMIP6 model outputs focusing on heavy rainfall were investigated, as shown in Fig. 1. As a result, only four models in CMIP6 (EC-Earth3, UKESM1-0-LL, HadGEM3-GC31-HM, and SAM0-UNICON) have the feature that convective rainfall exceeds large-scale rainfall in heavy rainfall, as shown in Fig. 1(I). In contrast, in the other 12 models, large-scale rainfall is equal to or exceeds convective rainfall in the heavy rainfall partition as show in Fig. 1(II, III, IV), and those models were further categorized into three major types according to different percentage contributions of C/L rainfall. The first type includes BCC-CSM2-MR, CESM2, NESM3, GFDL-CM4, MIROC6, FGOALS-g3, and MRI-AGCM3-2-H [see Fig. 1(II)]. For these models, the convective rainfall exceeds the large-scale rainfall in intensity at approximately less than 50 mm d?1 while it becomes less than the large-scale component at greater than 50 mm d?1, except for MIROC6 which has more convective rainfall until 170 mm d?1. The percentage of the large-scale rainfall is gradually increasing with the intensity increase and reaches approximately 70%–80% in extreme heavy rainfall. The second type includes CNRM-ESM2-1, CNRM-CM6-1, and ECMWF-IFS-HR [see Fig. 1(III)]. For these models, the convective rainfall exceeds the large-scale rainfall at less than 50 mm d?1 while the large-scale and convective rainfall nearly account for a similar percentage (50%) for extreme rainfall greater than 50 mm d?1. The third type includes CanESM5 and IPSL-CM6A-LR [see Fig. 1(IV)]. For these models, the convective component is greater than the large-scale rainfall for a precipitation intensity less than 50 mm d?1 but sharply decreases at greater than 50 mm d?1. The large-scale precipitation falsely increases with increased intensity and contributes nearly 100% for a heavy extreme rainfall greater than 150 mm d?1. In other words, the category I models have much more convective rainfall than large-scale rainfall in heavy rainfall; the category II models have more large-scale precipitation than convective precipitation in heavy rainfall; the category III models have similar percentages of large-scale and convective rainfalls in heavy rainfall; and the category IV models almost only include the large-scale precipitation component in extreme heavy rainfall.
Figure1. Frequency–intensity distribution of total (black), convective (red), and large-scale (blue) rainfall (a) and percentage–intensity distribution of large-scale and convective rainfall (b) in CMIP6. I?IV denotes four categories of convective and large-scale precipitation partitions.2
3.2. How do horizontal resolutions influence C/L partition in CMIP6?
As previous studies have reported, the partitions of convective and large-scale rainfall may be associated with horizontal spatial resolution (Weisman et al., 1997, Pieri et al., 2015; He et al., 2019). Here, the effect that model horizontal resolution has on the C/L component in CMIP6 is examined through the following two approaches. First, the convective rainfall components between higher and lower versions of some given models are compared. For example, HadGEM-GC3 and IPSL-CM6A are shown in Fig. 2a. In HadGEM-GC3, which features convective rainfall exceeding large-scale rainfall in heavy rainfall, the convective rainfall percentage in its higher resolution (0.23° × 0.35°) is slightly less than that in its lower resolution (1.25° × 1.875°) at intensities between 50 mm d?1 and 300 mm d?1 but becomes more than that in its lower resolution at intensities greater than 400 mm d?1. However, differing results are found for IPSL-CM6A, which has more large-scale rainfall than convective rainfall in heavy rainfall. Compared with the IPSL-CM6A lower resolution (1.26° × 2.5°) version, the convective percentage in the higher resolution (0.5° × 0.7°) version is greater at intensities less than 300 mm d?1 but lower for heavy extreme rainfall greater than 400 mm d?1. In both lower and higher resolution versions of IPSL-CM6A, the first-order feature remains that large-scale rainfall significantly exceeds convective rainfall, which is not influenced by difference in horizontal resolution.
Figure2. (a) Convective rainfall percentage of higher (red) and lower (blue) resolution versions in given models and (b) convective rainfall percentage (right panel) and C/L percentage ratio (left panel), respectively in HRM (red) and LRM (blue).Second, a comparison between two groups of models with relatively lower and higher resolutions (see the model descriptions in Table S2 in ESM) is made, shown in Fig. 2b. The results show that averaged convective rainfall accounts for a larger percentage in the high-resolution group than in the low-resolution group of CMIP6. Meanwhile, the multi-model ensemble convective rainfall percentage exceeds large-scale rainfall in the high-resolution group while large-scale rainfall exceeds convective rainfall in the low-resolution group of CMIP6 at intensities between 50–300 mm d?1. Accordingly, the models with higher resolution generally produce more convective rainfall partition than those with lower resolution. However, not all models follow this trend. Higher resolution does not always lead to higher convective rainfall percentage.
Figure3. Composite vertical profiles of RH against different precipitation intensities (contour on the left) and the normalized vertical profile of RH at greater than 50 mm d?1 (XY plot on the right) based on GPM/ERA5 and four categories of C/L component in CMIP6.However, in the other three categories of models, those that have more large-scale than convective precipitation in the extreme rainfall partition, the aforementioned two remarkable peaks of RH vertical distribution under observation are not reproduced well, particularly the upper-level peak. In terms of the three categories based on the different categories of convective/large-scale components mentioned in section 3.1, the associated RH distributions primarily show common biases for each category, as shown in Fig. 3. In category II, the observed RH upper-level peak disappears and the whole middle-lower tropospheric atmosphere is wet below 300 hPa, which corresponds to the large-scale rainfall (the maximum is nearly 80%) exceeding convective rainfall for extreme partition greater than 50 mm d?1, except for MRI-AGCM3-2-H and GFDL-CM4. In category III, the RH upper-level peak is significant but lower and located at over 500 hPa, which corresponds to the comparable C/L rainfall in the rainfall extreme partition. In category IV, in which 100% of the extreme portion precipitation comes from large-scale rainfall and 0% comes from convective rainfall, the observed RH upper-level peak also disappears, and the simulated RH has only a single vertical peak with a large amount of moisture trapped in the lower troposphere, which accordingly causes heavy large-scale rainfall.
In observation, heavy rainfall is typically caused by deep convection in tropical regions, which usually corresponds to cloud tops higher than 15 km (Sekaranom et al., 2018, Fig. 3). Considering the accessible daily cloud vertical distribution output, one model in each category was purposely chosen to examine its cloud vertical distribution as shown in Fig. 4. In category I, the extreme rainfall partition features a large mid-to-high cloud fraction, which is consistent with deep convection. In category II, the cloud fraction between 200 hPa and 700 hPa significantly increases during extreme rainfall, which corresponds to lower cloud tops, an increased middle-to-lower cloud fraction, and increased cloud thickness between 200 hPa and 700 hPa. Therefore, the large-scale rainfall overcomes the convective rainfall in the simulation of this condition. In category III, high clouds at approximately 100–150 hPa and middle clouds at approximately 500 hPa are distinguishable, which corresponds to comparable convective and large-scale rainfalls in the simulation. In category IV, low clouds are dominant, which is consistent with the 100% large-scale rainfall in the extreme rainfall simulation. Because different cloud types have different contributions to climate adjustments in coupled models under global warming (Zelinka et al., 2013), the distinct vertical distributions of the cloud fraction provide the greatest source of intermodal spread in climate response to greenhouse warming, which can be somewhat detected, as shown in Fig. S4 (Soden and Held, 2006; Po-Chedley et al., 2019).
Figure4. Composite vertical profiles of cloud fraction based on different precipitation intensities in four CMIP6 models.Note that it is challenging to find appropriate observations to make an apples-to-apples comparison with a GCM. On one hand, in satellite observations, most stratiform precipitation in the tropics is a precipitation from anvil clouds of a convective system (Tao et al., 2006) and characterized by a “bright band (melting layer)” (Awaka et al., 2007). In GCMs, convective and large-scale precipitations are calculated by a convection scheme and a large-scale condensation scheme, respectively. Therefore, large-scale precipitation in the model is not the same as stratiform precipitation in the satellite observations. On the other hand, the rain intensity in satellite observations is the instantaneous intensity (mm h?1), which may pass through a particular grid point only once in about five days. As the daily average of the rain intensity is a conditional average (average over the rainy area and rainy time only), it does not represent the daily accumulated rain amount (mm d?1) for the grid cell in a GCM. However, the convective rain intensity should be larger than large-scale rain intensity in the tropics (Tao et al., 2010). Heavier large-scale precipitation in the tropics in GCMs may be due to some deficiency of the cumulus parameterization scheme in most models, so that the tropical convective precipitation may be represented by unrealistically heavy large- scale precipitation.
Acknowledgements. This study was supported by funding from the National Natural Science Foundation of China (Grant 42022034, 91737306, 41675100), and National Key Research and development Program of China (Grant No. 2017YFA0604004). We would like to thank Professor Letu HUSI from the Institute of Remote Sensing and Digital Earth of CAS and Professor Qi Liu from the University of Science and Technology of China (USTC) for their useful comments on satellite datasets. We would also like to acknowledge the high-performance computing support from the Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University (
Electronic supplementary material: Supplementary material is available in the online version of this article at
