Impact of Different Cloud Microphysics Parameterization Schemes on Typhoon Intensity and Structure

The impact of different cloud microphysics parameterization schemes on the intensity and structure of the Super-strong Typhoon Rammasun(1409)in 2014 is investigated using the Weather Research and Forecasting model version 3.4 with eight cloud microphysics parameterization schemes.Results indicate that the uncertainty of cloud microphysics schemes results in typhoon forecast uncertainties,which increase with forecast time.Typhoon forecast uncertainty primarily affects intensity predictions,with significant differences in predicted typhoon intensity using various cloud microphysics schemes.Typhoon forecast uncertainty also affects the predicted typhoon structure.Greater typhoon intensity is accompanied by smaller vortex width,tighter vortex structure,stronger wind in the middle and lower troposphere,greater height of the strong wind region,smaller thickness of the eyewall and the outward extension of the eyewall,and a warmer warm core at upper levels of the eye.The differences among the various cloud microphysics schemes lead to different amounts and distributions of water vapor and hydrometeors in clouds.Different hydrometeors have different vertical distributions.In the radial direction,the maxima for the various hydrometeors forecast by a single cloud microphysics scheme are collocated with each other and with the center of maximum precipitation.When the hydrometeor concentration is high and hydrometeors exist at lower altitudes,more precipitation often occurs.Both the vertical and horizontal winds are the strongest at the location of maximum precipitation.Results also indicate that typhoon intensities forecast by cloud microphysics schemes containing graupel processes are noticeably greater than those forecast by schemes without graupel processes.Among the eight cloud microphysics schemes investigated,typhoon intensity forecasts using the WRF Single-Moment 6-class and Thompson schemes are the most accurate.

Evaluating the Impacts of Cloud Microphysical and Overlap Parameters on Simulated Clouds in Global Climate Models

The improvement of the accuracy of simulated cloud-related variables,such as the cloud fraction,in global climate models(GCMs)is still a challenging problem in climate modeling.In this study,the influence of cloud microphysics schemes(one-moment versus two-moment schemes)and cloud overlap methods(observation-based versus a fixed vertical decorrelation length)on the simulated cloud fraction was assessed in the BCC_AGCM2.0_CUACE/Aero.Compared with the fixed decorrelation length method,the observation-based approach produced a significantly improved cloud fraction both globally and for four representative regions.The utilization of a two-moment cloud microphysics scheme,on the other hand,notably improved the simulated cloud fraction compared with the one-moment scheme;specifically,the relative bias in the global mean total cloud fraction decreased by 42.9%–84.8%.Furthermore,the total cloud fraction bias decreased by 6.6%in the boreal winter(DJF)and 1.64%in the boreal summer(JJA).Cloud radiative forcing globally and in the four regions improved by 0.3%−1.2% and 0.2%−2.0%,respectively.Thus,our results showed that the interaction between clouds and climate through microphysical and radiation processes is a key contributor to simulation uncertainty.

Two-moment Bulk Stratiform Cloud Microphysics in the Grid-point Atmospheric Model of IAP LASG (GAMIL)

A two-moment bulk stratiform microphysics scheme, including recently developed physically-based droplet activation/ice nucleation parameterizations has been implemented into the Grid-point Atmospheric Model of IAP LASG （GAMIL） as an effort to enhance the model＇s capability to simulate aerosol indirect effects. Unlike the previous one-moment cloud microphysics scheme, the new scheme produces a reasonable rep- resentation of cloud particle size and number concentration. This scheme captures the observed spatial variations in cloud droplet number concentrations. Simulated ice crystal number concentrations in cirrus clouds qualitatively agree with in situ observations. The longwave and shortwave cloud forcings are in better agreement with observations. Sensitivity tests show that the column cloud droplet number concentrations calculated from two different droplet activation parameterizations are similar. However, ice crystal number concentration in mixed-phased clouds is sensitive to different heterogeneous ice nucleation formulations. The simulation with high ice crystal number concentration in mixed-phase clouds has less liquid water path and weaker cloud forcing. ~rthermore, ice crystal number concentration in cirrus clouds is sensitive to different ice nucleation parameterizations. Sensitivity tests also suggest that the impact of pre-existing ice crystals on homogeneous freezing in old clouds should be taken into account.

Influences of Graupel Microphysics on CMA-GFS Simulation of Summer Regional Precipitation

The horizontal resolution of global numerical weather prediction models is continuously developing. However, due to the imperfect precipitation simulation/forecast of these models, the demand for considering riming particles in cloud microphysical schemes in these models is increasing. This study employed the latest versions of global atmospheric reanalysis data (ERA5), the satellite retrieval data of the Global Precipitation Observation Program (GPM),and station precipitation observations to explore the impacts of adding graupel to the cloud microphysical scheme in the China Meteorological Administration-Global Forecast System (CMA-GFS) on summer regional precipitation simulations in four Chinese climate zones. The results verify that the new graupel scheme can enable CMA-GFS to decently predict global graupel distribution, especially in tropical and midlatitude regions. The addition of graupel in the cloud microphysics increases the precipitation simulation in North China, while that in Southwest China is weakened and dispersed. Moreover, graupel scheme increases the precipitation simulations of almost all magnitudes.The increase in light rain is obvious, and the absolute value of heavy rain is strengthened. This may be because graupel quickly melts into rain after falling out of the zero-temperature layer due to its large mass and fast falling speed, increasing surface precipitation. In summary, the addition of graupel in the cloud microphysical scheme can improve CMA-GFS’s underestimation of strong precipitation.

Simulation of FY-2D infrared brightness temperature and sensitivity analysis to the errors of WRF simulated cloud variables

This study simulated FY-2 D satellite infrared brightness images based on the WRF and RTTOV models. The effects of prediction errors in WRF micro-and macroscale cloud variables on FY-2 D infrared brightness temperature accuracy were analyzed. The principle findings were as follows. In the T+0–48 h simulation time, the root mean square errors of the simulated brightness temperatures were within the range 10–27 K, i.e., better than the range of 20–40 K achieved previously. In the T+0–24 h simulation time, the correlation coefficients between the simulated and measured brightness temperatures for all four channels were >0.5. The simulation performance of water channel IR3 was stable and the best. The four types of cloud microphysical scheme considered all showed that the simulated values of brightness temperature in clouds were too high and that the distributions of cloud systems were incomplete, especially in typhoon areas. The performance of the THOM scheme was considered best, followed in descending order by the WSM6, WDM6, and LIN schemes. Compared with observed values, the maximum deviation appeared in the range 253–273 K for all schemes. On the microscale, the snow water mixing ratio of the THOM scheme was much bigger than that of the other schemes. Improving the production efficiency or increasing the availability of solid water in the cloud microphysical scheme would provide slight benefit for brightness temperature simulations. On the macroscale, the cloud amount obtained by the scheme used in this study was small. Improving the diagnostic scheme for cloud amount, especially high-level cloud, could improve the accuracy of brightness temperature simulations. These results could provide an intuitive reference for forecasters and constitute technical support for the creation of simulated brightness temperature images for the FY-4 satellite.