Investigation of the Convection‐Allowing Prediction Error of an Extreme Precipitation Event of China Using CRTM‐Simulated Brightness Temperature

Abstract

An extreme rainfall case occurred on 20 July 2016 in northern China, producing over 600 mm of maximum 24 hr accumulated rainfall. The case is characterized by low‐echo centroid (LEC) based on radar observations. It is simulated by Weather Research and Forecasting model at 4 km grid spacing using the Morrison two‐moment microphysics scheme. Infrared brightness temperature (BT) simulated using a radiative transfer model together with simulated reflectivity are used to evaluate the simulated cloud structures. In general, the model predicts the rainfall amount, location, and propagation well. However, it fails to accurately predict the three‐dimensional cloud structures. The predicted convective cores (>35 dBZ) are higher than the freezing level, suggesting the presence of active cold‐cloud processes while the observed LEC suggests that warm‐cloud processes dominate. The simulation also produces too many upper level clouds and over‐predicts the fractions of overshooting clouds, resulting great over‐prediction of cloud top height (CTH). Additionally, the sensitivity of simulated BT to predicted cloud properties including CTH, cloud species and hydrometeor effective radii are examined to better understand the sources of error in simulated BT. Among those factors, CTH is found to be most critical to BT simulation. For every kilometer of CTH over‐prediction, there is about 6.431 K of negative BT bias owing to the lapse rate and the absorption and scattering effects of cloud particles. For most cloudy regions, cloud ice dominates the effect on simulated BT. Using diagnosed effective radii of simulated hydrometeors within the radiative transfer model results in small improvement to the BT simulation.

How Well Does 4‐km WRF Model Predict Three‐Dimensional Reflectivity Structure Over China as Compared to Radar Observations?

“…A similar result was found by Yang et al. (2022) in a low‐echo‐centroid (LEC) extreme rainfall case. Moreover, all microphysics schemes significantly overestimated the cloud top height, suggesting overestimation of cloud ice in the upper level.…”

“…Specifically, the Lin microphysics scheme tended to overestimate the high cloud, while the other schemes underestimated the mid-level cloud. A similar result was found by Yang et al (2022) in a low-echo-centroid (LEC) extreme rainfall case. Moreover, all microphysics schemes significantly overestimated the cloud top height, suggesting overestimation of cloud ice in the upper level.…”

“…In a study by Yang et al. (2022), the forecast demonstrated almost the same height for LEC and subsequent deep convection on the following day. The development of a microphysics scheme is usually based on a single type of precipitation system and typically represents the mean distribution of convection.…”

“…Besides, a legitimate question to ask is if the cloud height prediction problem we are seeing with the Morrison scheme is unique to this scheme, and if other schemes share the same problem. Limited case studies we have conducted as well as in Yang et al (2022) with different microphysical schemes do not show significant differences in the predicted cloud height, which suggests that the problem is not specific to particular microphysics schemes. Further studies with more cases using additional microphysics schemes are needed to robustly answer this question.…”

“…For example, the height of LEC (Vitale & Ryan, 2013) convection is significantly lower than that of deep convection, although the rainfall amount generated by these two systems may almost be the same. In a study by Yang et al (2022), the forecast demonstrated almost the same height for LEC and subsequent deep convection on the following day. The development of a microphysics scheme is usually based on a single type of precipitation system and typically represents the mean distribution of convection.…”