Evaluation of GCM Precipitation Processes Using Metrics from Ground-based Measurements at the Azores

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Description

Recent studies show that the warm rain in GCMs is too frequent but too light compared to observations. Warm rain process in GCMs is parameterized as functions of grid-mean cloud water mixing ratio (qc), cloud particle size (re), cloud droplet number concentration (Nt), and rain water mixing ratio (qr). The so-called autoconversion (Eauto) and accretion (Eaccr) enhancement factors are introduced to account for the sub-grid variance of cloud properties from their means in a grid box. However, only a few studies have assessed the dependence of enhancement factors on sub-grid scale microphysical variabilities and none of them used ground-based observations in the evaluations. In this study, we use ground-based observations and retrievals over the ARM Azores site to estimate the Eauto and Eaccr with different temporal variations (0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 3.5h, 4h, 4.5h, and 5h) that correspond to different model spatial scales. Compared to the constant value in GCMs, the calculated Eauto values in this study increase from 1.79 (0.5h) to 3.15 (3.5h) and remain relatively stable afterwards, which is close to the assumed value of 3.2 in GCMs. On the other hand, the calculated Eaccr values increase from 1.25 (0.5h) to 1.6 (5h), which is about 17% and 50% greater than the assumed value (1.07) in GCMs. The overestimated Eauto value used in GCMs could be one of the reasons why most of the GCMs can produce too frequent precipitation events, while the small Eaccr value could be used to explains why most of the GCMs can produce more light precipitation amounts. To further investigate these two enhancement factors, we classified the MBL clouds into different boundary layer conditions using lower tropospheric stability (LTS): stable (LTS > 18K), mid-stable (13.5K ≤ LTS ≤ 18K), and unstable (LTS < 13.5K). Both Eauto and Eaccr increase with decreased boundary layer stability. This study also finds that both Eauto and Eaccr are larger for drizzling clouds than for non-drizzling clouds. Using constant values of Eauto and Eaccr in GCMs cannot reveal the variability of cloud properties in different grid sizes and under different boundary layer conditions. Therefore, it is necessary to implement the results found in this study into GCMs simulations in the future.