Isolated convective cloud system is one of the important convective cloud forms in Hainan Island, it’s significant to study the evolution characteristics for identifying, tracking convective clouds and improving the efficiency of weather modification. Based on the S-band dual-polarization Doppler weather radar (CINRAD/SA-D) data of Hainan Island from 2015 to 2020, the dual-polarization characteristic of typical isolated convective clouds case and the evolution of isolated convective clouds over the island are analyzed. The results show that the radar data of the typical case of isolated convective clouds in Hainan Island (July 26, 2020) present obvious differential reflectivity (Z_DR) and specific differential phase shift (K_DP) column phenomena during the development phase, which means the convective motion in the clouds was strong. The total number of isolated convective clouds case in Hainan Island from 2015 to 2020 is 495 times, accounting for 11.82% of the total convective cloud cases (4 017 times). The southwest low pressure trough, the warming high pressure ridge and the southward cold front are three weather systems triggering isolated convective clouds easily. The isolated convective clouds from March to June are more, accounting for 76.84% of the total cases. It is significantly higher than that of other months. March is a high-incidence month for isolated convective clouds, in which isolated convective clouds account for 47.78% of the total cases. In one day, the period from 14:00 to 17:00 is the period of high occurrence of isolated convective clouds in Hainan Island, accounting for 72.84% of the total cases (475 times). The frequency of isolated convective clouds in southwestern and central mountainous areas in Hainan Island is higher, accounting for about 88.84% of the total cases (475 times). The movement direction of isolated convective clouds is mainly northeast and southeast, which is mainly affected by westerly and southerly winds. In addition, the movement speed of isolated convective clouds is mainly concentrated between 6 and 20 km·h^-1 and the movement distance of isolated convective clouds is mainly distributed between 6 and 20 km. More than half of isolated convective clouds in movement distance are less than 20 km.

Based on the observation data such as radar, rainfall and radiosonde, the precipitation enhancement effect of the warm cloud-seeding experiments using hygroscopic flares at Bawangling, Changjiang and Maoyang, Wuzhishan in Hainan Island from 2015 to 2020 in different months and weather systems is conducted.On this basis, the physical response characteristics of the catalysis process are analyzed through typical cases. The results show that positive effect of seeding experiments under the influence of the low pressure trough in the South China Sea and the South China coast is relatively obvious, and the average absolute precipitation increment of cloud seeded experiments is 2.00 mm higher than that of cloud unseeded experiments. The warm cloud-seeding experiments in July, August, and September all showed different level positive effect of precipitation enhancement. The warm cloud-seeding experiments in August had the highest average absolute increment of precipitation, which is 4.71 mm. For the total warm cloud-seeding experiments of the two sites in Hainan Island, the average absolute precipitation increment is 0.73 mm, the average relative precipitation increase and average water increment is 13.52% and 39.73×10⁴ m³ respectively. From the physical evaluation of typical case, 0.5 h after catalysis is critical moment, after which the gap of almost all physical parameters between seeded cloud and contrast cloud is widened.

Weighted mean temperature (T_m) is a key parameter in the retrieval of atmospheric precipitable water (PW) from ground-based Global Positioning System (GPS). In order to improve the accuracy and reliability of the retrieval of PW in Hainan Island, temporal variation characteristics of T_m calculated based on Haikou radiosonde data during 2008-2010 and the relation with meteorological factors at Haikou station are analyzed. On this basis, based on radiosonde and surface observation data during 2008-2012, single-factor and multi-factor T_m regression equations and T_m regression models with day of year factor are established at Haikou, and the models are validated by using radiosonde and surface observation data during 2013-2014. Based on the local T_m regression models, the ground-based GPS PW retrieval of Haikou is performed from May to October 2012, and the retrieval accuracy is verified. The results show that: by comparison of the true T_m, the RMSE of single-factor and two-factor local T_m models are 2.000 and 1.978 K, superior to Bevis and constant model. The local model of T_m has good consistency with T_m calculated by radiosonde data. The GPS PW from single-factor T_m model exhibits much stronger correlations with radiosonde PW than GPS PW based on Bevis model, and the RMSE of GPS PW by single-factor T_m model is lower than that based on Bevis model. Compared with the multi-factor linear T_m model, GPS PW based on the T_m model with day of year factor has significantly improved accuracy. The local models could meet the accuracy requirements of the PW from ground-based GPS data of Haikou.