Dataset to reproduce the figures of "Observational constraint on a feedback from supercooled clouds reduces projected warming uncertainty"

These files, further described below, contain the necessary variables to reproduce the figures of Cesana et al. (2024), which are not publically available. LPR_observations.zip: This file contains the liquid phase ratio of all the observational datasets used in Fig. 1b of the manuscript. All the information about these datasets can be found in Supplementary Note 1 of their paper. LPR_CMIP5_CMIP6.zip: This file contains the liquid phase ratio frequency (using a lidar simulator) and mass (raw output of the model from the ESGF website) of all the 10 CMIP6 and 10 CMIP5 models used in Fig. 1a and Fig. 2. All the information is included in the Methods. MIROC6 data were provided by Takuro Michibata (Okayama University) and Tomoo Ogura (National Institute for Environmental Studies). LPR_NASA-GISS-ModelE3.zip: This file contains the liquid phase ratio frequency (using a lidar simulator) and mass (raw output of the model) of all the six ModelE3 configurations used in Fig. 3 and 4. All the information is included in the Methods and in Cesana et al. (2021). CESM2bugfix_lidar_outputs.zip: This file contains the liquid and ice cloud fractions using the lidar simulator for an AMIP simulation of CESM2, used in Fig. 2 and 3. Compared to the official output, a bugfix in the lidar simulator has been fixed to avoid snow particles to be accounted as liquid particles. These outputs have been provided by Jennifer Kay from University of Colorado Boulder. NASA-GISS-ModelE3_Cloud_Feedbacks.zip: This file contains the cloud feedbacks derived from AMIP and AMIP-p4K runs (2007-2012) using the Zelinka et al. (2016) cloud radiative kernels method, which is used in Fig. 4. The full description can be found in the Methods. CMIP6_Temperature_Profiles.zip: This file contains the temperature profiles of six CMIP6 models (CanESM5, CESM2, CNRM-CM6-1, GFDL-CM4, IPSL-CM6A-LR, MRI-ESM2-0) for AMIP and AMIP-p4K runs (2007-2014), which are used in Fig. 5 of the paper. The full description can be found in the Methods. The CNRM-CM6-1 outputs have been provided by Romain Roehrig from CNRM. The IPSL-CM6A-LR outputs have been provided by Artem Feolilov and Helene Chepfer from LMD. NASA-GISS-ModelE3_Temperature_Profiles.zip: This file contains the temperature profiles of each of the six ModelE3 configurations (Tun2, Tun1, Tun3, Tun4, Tun5 and Phys) for AMIP and AMIP-p4K runs (2007-2012), which are used in Fig. 5 of the paper. The full description can be found in the Methods and in Cesana et al. (2021). References Cesana, G.V., A.S. Ackerman, A.M. Fridlind, I. Silber, and M. Kelley, 2021: Snow reconciles observed and simulated phase partitioning and doubles cloud feedback. Geophys. Res. Lett., 48, no. 20, e2021GL094876, doi:10.1029/2021GL094876. Cesana, G.V. et al., 2024: Observational constraint on a feedback from supercooled clouds reduces projected warming uncertainty. Commun Earth Environ, accepted.

下述文件包含复现Cesana等(2024)论文附图所需的全部变量，该论文相关数据尚未公开发布。

LPR_observations.zip：本压缩包包含手稿图1b中使用的全部观测数据集的液相比率（liquid phase ratio），相关数据集的详细信息可参见该论文的补充说明1。

LPR_CMIP5_CMIP6.zip：本压缩包包含手稿图1a与图2中使用的10个CMIP6模式与10个CMIP5模式的液相比率频率（采用激光雷达模拟器（lidar simulator）计算）与模型原始输出的质量数据（来自ESGF网站），全部相关信息已收录于方法部分。MIROC6模式数据由冈山大学的Takuro Michibata与日本国立环境研究所的Tomoo Ogura提供。

LPR_NASA-GISS-ModelE3.zip：本压缩包包含手稿图3与图4中使用的全部6个ModelE3配置的液相比率频率（采用激光雷达模拟器计算）与模型原始输出的质量数据，相关详细信息可参见方法部分与Cesana等(2021)的研究。

CESM2bugfix_lidar_outputs.zip：本压缩包包含针对CESM2的AMIP模拟实验、采用激光雷达模拟器计算得到的液相与冰云分数，该数据用于图2与图3。相较于官方输出结果，本数据集修复了激光雷达模拟器中将雪粒子误判为液相粒子的问题。该数据集由科罗拉多大学博尔德分校的Jennifer Kay提供。

NASA-GISS-ModelE3_Cloud_Feedbacks.zip：本压缩包包含采用Zelinka等(2016)的云辐射核方法（cloud radiative kernels method），基于AMIP与AMIP-p4K实验（2007-2012年）推导得到的云反馈数据，该数据用于图4，完整说明可参见方法部分。

CMIP6_Temperature_Profiles.zip：本压缩包包含6个CMIP6模式（CanESM5、CESM2、CNRM-CM6-1、GFDL-CM4、IPSL-CM6A-LR、MRI-ESM2-0）在AMIP与AMIP-p4K实验（2007-2014年）中的温度廓线（temperature profiles）数据，该数据用于论文图5，完整说明可参见方法部分。其中CNRM-CM6-1模式输出由法国国家气象研究中心（CNRM）的Romain Roehrig提供；IPSL-CM6A-LR模式输出由LMD实验室的Artem Feolilov与Helene Chepfer提供。

NASA-GISS-ModelE3_Temperature_Profiles.zip：本压缩包包含6个ModelE3配置（Tun2、Tun1、Tun3、Tun4、Tun5与Phys）在AMIP与AMIP-p4K实验（2007-2012年）中的温度廓线数据，该数据用于论文图5，完整说明可参见方法部分与Cesana等(2021)的研究。

### 参考文献
Cesana, G.V., A.S. Ackerman, A.M. Fridlind, I. Silber, 及 M. Kelley, 2021: 雪粒子调和观测与模拟的相态分配并使云反馈翻倍。《地球物理研究快报》(Geophys. Res. Lett.), 第48卷第20期, e2021GL094876, doi:10.1029/2021GL094876。
Cesana, G.V. 等, 2024: 基于过冷云反馈的观测约束降低预估增暖不确定性。《通讯-地球与环境》(Commun Earth Environ), 已录用。