中国气象局气象探测中心 CMA Meteorological Observation Centre Meteorological Applications of Precipitable Water Vapor Measurements Retrieved by the National GNSS Networks in China Hong Liang, Yuncang Cao, Wan Xiaomin, Xu Zhifang, Wang Haishen, Hu Heng With slices from (Jiqin Zhong, IUM) CMA Meteorological Observation Centre

中国气象局气象探测中心 CMA Meteorological Observation Centre Outline  Introduction of national ground-based GNSS networks in China.  Methods to data processing and quality control (QC) procedure.  Validation of near real-time zenith tropospheric delay (ZTD) and precipitable water vapor (PWV) estimates.  Meteorological Applications of ZTD and PWV Measurements.  Conclusions and perspectives

中国气象局气象探测中心 CMA Meteorological Observation Centre Ground-based GNSS Observations in Meteorology One of the most valuable attributes of GNSS is its ability to provide accurate signal delay estimates under all weather conditions, including thick cloud cover and precipitation. PWV is retrieved from GNSS signal delays caused by the refractivity of the troposphere. ~5km ~22 km Mapping Function ~1/sin(a) a a sisi FOV h sjsj szsz the fundamental measurement is N(s) the refractivity of the atmosphere along the path of the radio signal N(s) = 10 6 (n(s)-1).

中国气象局气象探测中心 CMA Meteorological Observation Centre Main objectives  Assess the ground-based GNSS observations quality and try to find out the solutions to improve the in-situ observation quality in China.  Provide weather forecasters and NWP data assimilation system with PWV estimates which have accuracies better than 2 mm of PWV and can be available within 1h of the data collection.

中国气象局气象探测中心 CMA Meteorological Observation Centre National GNSS Networks in China Crustal Movement Observation Network (CMONC)CMA GB GNSS network (CGGN) CORS: 260 sites Main Purpose: monitor crustal movement Manager: China Earthquake Administration Observation: from Equipment manufacturer: Trimble CORS: 820 sites Main Purpose: measure precipitable water vapor Manager: China Meteorological Administration Observation: from Equipment manufacturers: Trimble, Leica, and TPS et al.

中国气象局气象探测中心 CMA Meteorological Observation Centre Crustal Movement Observation Network Observation room Meteorological instrument GNSS antenna Observation facilities and equipments Trimble Vaisala ptu300 Met. data collector Trimble NETR8 Receiver NAS Router UPS Anti-surge system Structure of observation stand Observation stand 3.2m >4m Bedrock Surface

中国气象局气象探测中心 CMA Meteorological Observation Centre CMA GNSS NETWORK Anqing in Anhui Structure of observation stand 3.2 m >4 m Tough soil Observation site Observation room Receiver, Router, and Battery, et al. Receiver, Router, and Battery, et al. Surface

中国气象局气象探测中心 CMA Meteorological Observation Centre Observation data quality analysis for CMONC Monthly mean values of daily epoch, MP1, MP2 and o/s of CMON sites Dec Daily epochs MP2 MP1 Obs./cycle slips

中国气象局气象探测中心 CMA Meteorological Observation Centre Observation data quality analysis for CGGN Monthly mean values of daily epochs, MP1, MP2 and o/s of CGN sites Dec Daily epochsMP1 MP2 Obs./cycle slips

中国气象局气象探测中心 CMA Meteorological Observation Centre qf MOIST system for data processing and quality assessment (MOIST: MOCC Integrated water vapor Sensing Tech.) Local GNSS Obs. Rinex2.11 format hourly 、 daily file Qualified obs. Quality assessment report GAMIT/ GLOBK (10.50) Tracking site obs. Ephemeris/tables ZTD ZHD ： SAS model Tm: linear model Qualified ZTD and PWV products Decompress Data merge QC ZWD Radiosondes EC/NCEP reanalysis GFS analysis PWV Quality assessment report High-accurate prior coordinates of local GNSS sites QC

中国气象局气象探测中心 CMA Meteorological Observation Centre Methodology of data processing and QC No.ItemAcronymThreshold valueDefinition 1Data integrity rateNN≥0.8 Ratio of number of Obs. epochs to that of Possible epochs 2Data availabilityVV≥0.8 Ratio of number of complete Obs. ( including L1, L2, et al.) to that of possible Obs. 3L1 MultipathMP1MP1≤1.0 mMultipath in L1 carrier phase measurements 4L2 MultipathMP2MP2≤1.0 mMultipath in L2 carrier phase measurements 5o/sOSOS>100Ratio of number of Obs. to that of cycle slips Table 1: threshold values of QC for carrier phases observation (o-files) Step1 : QC for carrier phases observation and meteorological data ElementThreshold valeChange within 24 hours Surface pressure （ hPa ） 400 ～ 1080 <50 Surface air temperature （℃） -75 ～ 80<50 Table 2: threshold values of QC for meteorological data (m-files)

中国气象局气象探测中心 CMA Meteorological Observation Centre Methodology of data processing and QC Step 2: Observation data processing  Hourly Navigation message files collected real-time will be merged into a single n-file.  The 8-h sliding-window technique described by ( Foster and Bevis, 2005; ) is applied to estimate the zenith tropospheric delay (ZTD) and cycle hourly and hourly. Foster J., M. Bevis and S. Businger Journal of Atmospheric and Oceanic Technology. 22:

中国气象局气象探测中心 CMA Meteorological Observation Centre Methodology of data processing and QC Step 3: estimate mean temperature Yao Y B, Zhang B, Xu C Q, et al. Chin Sci Bull, 2014, 59, doi: /s Latitudeab 90~ ~ ~ ~ ~ ~ Table 3 the values of coefficients a and b  Compute weighted mean temperature of atmosphere from a latitude-related linear model as described in Yao et al. (2014).  The error of mean temperature estimate is about 2~3 Kelvin.

中国气象局气象探测中心 CMA Meteorological Observation Centre Methodology of data processing and QC Step 4: QC for ZTD and PWV If there is a sufficient number of epochs observed in the current session, the validity of ZTD and PWV estimates are based on three following factors.  Is the ZTD or PWV estimate physically realistic;  Is the estimate consistent with prior estimates;  Is the RMS scatter in the estimates lower than the minimum acceptable retrieval error. ItemThreshold valueDefinition Data integrity rate≥0.5 Ratio of Obs. epochs to that of Possible epochs during the current session RMS≤25 mm“Formal error” value of ZTD estimate ElementThreshold valueVariation within 1 hour ZTD （ mm ） 1000 ≤ ZTD ≤ 3500<100 PWV （ mm ） 0< PWV ≤ 100<15 Table 3 Threshold values of data integrity rate and RMS of ZTD estimate Table 4 Threshold values of ZTD and PWV

中国气象局气象探测中心 CMA Meteorological Observation Centre Validation of ZTD and PWV estimates Comparison of ZTD values estimated by GIPSY from IGS website and MOIST Formal error of ZTD estimates May 8, 2016

中国气象局气象探测中心 CMA Meteorological Observation Centre Validation of ZTD and PWV estimates Comparison of PWV determined by GPS and Radiosonde in 2013 Xichang Weining Shantou Tengchong

中国气象局气象探测中心 CMA Meteorological Observation Centre Validation of ZTD and PWV estimates : samples: mean=0.00 stdv=2.76 skew= kurt= samples: 6621 Mean=0.00 stdv=1.2 skew= kurt= : Samples:56151 mean=0.000 stdv= skew= kurt= : Samples=50114 mean=0.000 stdv= skew= kurt= : samples=51764 mean=0.000 stdv= skew= kurt= : samples:=39718 mean=0.000 stdv= skew= kurt= (Provided by JiQin Zhong, IUM) Comparison of ZTD values estimated by GFS analysis and GNSS Probability density distribution of the ZTD difference between GFS and MOIST

中国气象局气象探测中心 CMA Meteorological Observation Centre PWV application for radiation simulations Radiation simulation using SES2 radiative transfer model under clear sky conditions at Naqu over the Tibetan Plateau from 25 Feb. to 16 Mar in 2008 (1)Technique in Kuo et al. (1993) is applied to scale NCEP specific humidity profile by GPS. (2)SES2 radiative transfer model. (3) RS Specific humidity as reference measurements. Location

中国气象局气象探测中心 CMA Meteorological Observation Centre Assimilation of PWV into NWP digest system Histogram of difference in 3 hour Ts forecast scores between assimilation with GNSS PW data and without GNSS PWV data in GRAPES model Differences in PWV between GNSS and GRAPES background output during the period from 21 to 31 July 2013, unit: cm After assimilating PWV data into regional model GRAPES, the 3 hours precipitation forecast skill has improved significantly. Assimilate PWV observations into GRAPSE_RAFS assimilation system

中国气象局气象探测中心 CMA Meteorological Observation Centre Conclusions and perspectives Conclusions:  Currently, the ground-based GNSS network which used to monitor atmospheric precipitable water vapor (PWV) over China consists of two sub-netwoks and totally 1080 sites.  Most of the ground-based GNSS observations are in good quality in China, but some sites have serious problems such as large multipath effect and cycle slips problems. To update the receivers and antennas at these sites is one of the effective ways to solve the issues.  The operational system MOIST is a very useful tool to assess data quality and process data in real time. The near real-time ZTD and PWV are comparable with those determined by radiosondes and GFS analysis.  The assimilation of PWV into regional NWP model (GRAPES) is helpful to improve the 3h precipitation forecast skill.

中国气象局气象探测中心 CMA Meteorological Observation Centre Conclusions and perspectives Perspectives:  To continuously improve the methodology to process ground-based GNSS observations to produce more accurate near real-time ZTD and PWV data, thus to make our operational system MOIST more powerful.  To strengthen cooperation with NWP data assimilation group to maximize impact of GB GNSS observations to weather forecast in China.