Zoning Evaluation of Hourly Precipitation in High-resolution Regional Numerical Models over Hainan Island

This study assesses the performance of three high-resolution regional numerical models in predicting hourly rainfall over Hainan Island from April to October for the years from 2020 to 2022.The rainfall amount,frequency,intensity,duration,and diurnal cycle are examined through zoning evaluation.The results show that the China Meteor-ological Administration Guangdong Rapid Update Assimilation Numerical Forecast System(CMA-GD)tends to forecast a higher occurrence of light precipitation.It underestimates the late afternoon precipitation and the occurrence of short-duration events.The China Meteorological Administration Shanghai Numerical Forecast Model System(CMA-SH9)reproduces excessive precipitation at a higher frequency and intensity throughout the island.It overestimates rainfall during the late afternoon and midnight periods.The simulated most frequent peak times of rainfall in CMA-SH9 are 0-1 hour deviations from the observed data.The China Meteorological Administration Mesoscale Weather Numerical Forecasting System(CMA-MESO)displays a similar pattern to rainfall observations but fails to replicate reasonable structure and diurnal variation of frequency-intensity.It underestimates the occurrence of long-duration events and overestimates related rainfall amounts from midnight to early morning.Notably,significant discrepancies are observed in the predictions of the three models for areas with complex terrain,such as the central,southeastern,and southwestern regions of Hainan Island.

Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System

MetCoOp is a Nordic collaboration on operational Numerical Weather Prediction based on a common limited-area km-scale ensemble system. The initial states are produced using a 3-dimensional variational data assimilation scheme utilizing a large amount of observations from conventional in-situ measurements, weather radars, global navigation satellite system, advanced scatterometer data and satellite radiances from various satellite platforms. A version of the forecasting system which is aimed for future operations has been prepared for an enhanced assimilation of microwave radiances. This enhanced data assimilation system will use radiances from the Microwave Humidity Sounder, the Advanced Microwave Sounding Unit-A and the Micro-Wave Humidity Sounder-2 instruments on-board the Metop-C and Fengyun-3 C/D polar orbiting satellites. The implementation process includes channel selection, set-up of an adaptive bias correction procedure, and careful monitoring of data usage and quality control of observations. The benefit of the additional microwave observations in terms of data coverage and impact on analyses, as derived using the degree of freedom of signal approach, is demonstrated. A positive impact on forecast quality is shown, and the effect on the precipitation for a case study is examined. Finally, the role of enhanced data assimilation techniques and adaptions towards nowcasting are discussed.