The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model

被引:4
|
作者
Torcasio, Rosa Claudia [1 ]
Mascitelli, Alessandra [1 ,2 ]
Realini, Eugenio [3 ]
Barindelli, Stefano [3 ]
Tagliaferro, Giulio [4 ]
Puca, Silvia [5 ]
Dietrich, Stefano [1 ]
Federico, Stefano [1 ]
机构
[1] Inst Atmospher Sci & Climate CNR ISAC, Natl Res Council Italy, Via Fosso del Cavaliere 100, I-00133 Rome, Italy
[2] Univ Gabriele dAnnunzio Chieti Pescara, Ctr Adv Studies & Technol CAST, Dept Adv Technol Med & Dent DTM&O, Via Vestini 31, I-66100 Chieti, Italy
[3] Geomat Res & Dev srl GReD, via Cavour 2, I-22074 Lomazzo, Italy
[4] BIPM Time Dept, Sevres, France
[5] USSN, Via Vitorchiano 4, I-00189 Rome, Italy
关键词
GPS DATA; CONVECTION; COMMUNITY;
D O I
10.5194/nhess-23-3319-2023
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The impact of assimilating GNSS-ZTD (global navigation satellite system-zenith total delay) on the precipitable water vapor and precipitation forecast over Italy is studied for the month of October 2019, which was characterized by several moderate to intense precipitation events, especially over northwestern Italy. The WRF (Weather Research and Forecasting) model, version 4.1.3, is used with its 3D-Var data assimilation system to assimilate ZTD observations from 388 GNSS receivers distributed over the country. The dataset was built collecting data from all the major national and regional GNSS permanent networks, achieving dense coverage over the whole area. The water vapor forecast is verified for the forecast hours of 1-6 h after the last data assimilation time. Results show that WRF underestimates the atmospheric water vapor content for the period, and GNSS-ZTD data assimilation improves this underestimation. The precipitation forecast is verified in the phases of 0-3 and 3-6 h after the last data assimilation time using more than 3000 rain gauges spread over Italy. The application of GNSS-ZTD data assimilation to a case study improved the precipitation forecast by increasing the rainfall maximum and by better focusing the precipitation pattern over northeastern Italy, with the main drawback being the prediction of false alarms. Considering the study over the whole period, GNSS-ZTD data assimilation had a positive impact on rainfall forecast, with an improvement in the performance up to 6 h and with statistically significant results for moderate to intense rainfall thresholds (25-30 mm (3 h) - 1 ).
引用
收藏
页码:3319 / 3336
页数:18
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