scholarly journals A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

2018 ◽  
Author(s):  
Zhaohui Xiong ◽  
Bao Zhang ◽  
Yibin Yao
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Weather Prediction ◽  
Wrf Model ◽  
Vertical Direction ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Rainy Period ◽  
Lower Accuracy

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

scholarly journals Comparisons between the WRF data assimilation and the GNSS tomography technique in retrieving 3-D wet refractivity fields in Hong Kong

2019 ◽  
Vol 37 (1) ◽  
pp. 25-36 ◽  
Author(s):  
Zhaohui Xiong ◽  
Bao Zhang ◽  
Yibin Yao
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Data Assimilation ◽  
Vertical Direction ◽  
Lower Troposphere ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
Dry Period ◽  
Lower Accuracy ◽  
Background Data

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to accurately describe its three-dimensional (3-D) dynamical changes. The data assimilation technique and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting Data Assimilation (WRFDA) model (a representative of the data assimilation models) in retrieving wet refractivity (WR) in the Hong Kong area during a wet period and a dry period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delays. The WRFDA is used to assimilate the zenith tropospheric delay to improve the background data. The radiosonde data are used to validate the WR derived from the GNSS tomography, the WRFDA output, and the background data. The root mean square (rms) of the WR derived from the tomography results, the WRFDA output, and the background data are 6.50, 4.31, and 4.15 mm km−1 in the wet period. The rms becomes 7.02, 7.26, and 6.35 mm km−1 in the dry period. The lower accuracy in the dry period is mainly due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA only slightly improves the accuracy of the WR and that the WRFDA WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the WRFDA WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA, the retrieved WR is improved.

scholarly journals Near real-time water vapor tomography using ground-based GPS and meteorological data: long-term experiment in Hong Kong

2014 ◽  
Vol 32 (8) ◽  
pp. 911-923 ◽  
Author(s):  
P. Jiang ◽  
S. R. Ye ◽  
Y. Y. Liu ◽  
J. J. Zhang ◽  
P. F. Xia
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Real Time ◽  
Time Window ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Double Difference ◽  
Statistical Measures ◽  
Term Experiment

Abstract. Water vapor tomography is a promising technique for reconstructing the 4-D moisture field, which is important to the weather forecasting and nowcasting as well as to the numerical weather prediction. A near real-time 4-D water vapor tomographic system is developed in this study. GPS slant water vapor (SWV) observations are derived by a sliding time window strategy using double-difference model and predicted orbits. Besides GPS SWV, surface water vapor measurements are also assimilated as real time observations into the tomographic system in order to improve the distribution of observations in the lowest layers of tomographic grid. A 1-year term experiment in Hong Kong was carried out. The feasibility of the GPS data processing strategy is demonstrated by the good agreement between the time series of GPS-derived Precipitable Water Vapor (PWV) and radio-sounding-derived PWV with a bias of 0.04 mm and a root-mean-square error (RMSE) of 1.75 mm. Using surface humidity observations in the tomographic system, the bias and RMSE between tomography and radiosonde data are decreased by half in the ground level, but such improved effects weaken gradually with the rise of altitude until becoming adverse above 4000 m. The overall bias is decreased from 0.17 to 0.13 g m−3 and RMSE is reduced from 1.43 to 1.28 g m−3. By taking the correlation coefficient and RMSE between tomography and radiosonde individual profile as the statistical measures, quality of individual profile is also improved as the success rate of tomographic solution is increased from 44.44 to 63.82% while the failure rate is reduced from 55.56 to 36.18%.

Real-time and near real-time ZTD from a local network of low-cost dual-frequency GNSS receivers.

2021 ◽  
Author(s):  
Tomasz Hadas ◽  
Grzegorz Marut ◽  
Jan Kapłon ◽  
Witold Rohm
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Low Cost ◽  
Weather Prediction ◽  
Local Network ◽  
System Component ◽  
Dual Frequency ◽  
Lower Accuracy ◽  
Gnss Receivers ◽  
The Impact

<p>The dynamics of water vapor distribution in the troposphere, measured with Global Navigation Satellite Systems (GNSS), is a subject of weather research and climate studies. With GNSS, remote sensing of the troposphere in Europe is performed continuously and operationally under the E-GVAP (http://egvap.dmi.dk/) program with more than 2000 permanent stations. These data are one of the assimilation system component of mesoscale weather prediction models (10 km scale) for many nations across Europe. However, advancing precise local forecasts for severe weather requires high resolution models and observing system.   Further densification of the tracking network, e.g. in urban or mountain areas, will be costly when considering geodetic-grade equipment. However, the rapid development of GNSS-based applications results in a dynamic release of mass-market GNSS receivers. It has been demonstrated that post-processing of GPS-data from a dual-frequency low-cost receiver allows retrieving ZTD with high accuracy. Although low-cost receivers are a promising solution to the problem of densifying GNSS networks for water vapor monitoring, there are still some technological limitations and they require further development and calibration.</p><p>We have developed a low-cost GNSS station, dedicated to real-time GNSS meteorology, which provides GPS, GLONASS and Galileo dual-frequency observations either in RINEX v3.04 format or via RTCM v3.3 stream, with either Ethernet or GSM data transmission. The first two units are deployed in a close vicinity of permanent station WROC, which belongs to the International GNSS Service (IGS) network. Therefore, we compare results from real-time and near real-time processing of GNSS observations from a low-cost unit with IGS Final products. We also investigate the impact of replacing a standard patch antenna with an inexpensive survey-grade antenna. Finally, we deploy a local network of low-cost receivers in and around the city of Wroclaw, Poland, in order to analyze the dynamics of troposphere delay at a very high spatial resolution.</p><p>As a measure of accuracy, we use the standard deviation of ZTD differences between estimated ZTD and IGS Final product. For the near real-time mode, that accuracy is 5 mm and 6 mm, for single- (L1) and dual-frequency (L1/L5,E5b) solution, respectively. Lower accuracy of the dual-frequency relative solution we justify by the missing antenna phase center correction model for L5 and E5b frequencies. With the real-time Precise Point Positioning technique, we estimate ZTD with the accuracy of 7.5 – 8.6 mm. After antenna replacement, the accuracy is improved almost by a factor of 2 (to 4.1 mm), which is close to the 3.1 mm accuracy which we obtain in real-time using data from the WROC station.</p>

scholarly journals Asian water tower evinced in total column water vapor: a comparison among multiple satellite and reanalysis data sets

2019 ◽  
Vol 54 (1-2) ◽  
pp. 231-245 ◽  
Author(s):  
Yin Zhao ◽  
Tianjun Zhou
Keyword(s):  
Water Vapor ◽  
Satellite Data ◽  
Annual Cycle ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Data Sets ◽  
Important Indicator ◽  
Ensemble Mean ◽  
Asian Water ◽  
Total Column

Abstract The total column water vapor (TCWV) over the Tibetan Plateau (TP) is one important indicator of the Asian water tower, and the changes in the TCWV are vital to the climate and ecosystem in downstream regions. However, the observational data is insufficient to understand the changes in the TCWV due to the high elevation of the TP. Satellite and reanalysis data can be used as substitutes, but their quality needs to be evaluated. In this study, based on a homogenized radiosonde data set, a comprehensive evaluation of the TCWV over the TP derived from two satellite data sets (AIRS-only and AIRS/AMSU) and seven existing reanalysis data sets (MERRA, MERRA2, NCEP1, NCEP2, CFSR, ERA-I, JRA55) is performed in the context of the climatology, annual cycle and interannual variability. Both satellite data sets reasonably reproduce the characteristics of the TCWV over the TP. All reanalysis data sets perform well in reproducing the annual mean climatology of the TCWV over the TP (R = 0.99), except for NCEP1 (R = 0.96) and NCEP2 (R = 0.92). ERA-I is more reliable in capturing the spatial pattern of the annual cycle (R = 0.94), while NCEP1 shows the lowest skill (R = 0.72). JRA55 performs best in capturing the features of the interannual coherent variation (EOF1, R = 0.97). The skill-weighted ensemble mean of the reanalysis data performs better than the unweighted ensemble mean and most of the single reanalysis data sets. The evaluation provides essential information on both the strengths and weaknesses of the major satellite and reanalysis data sets in measuring the total column water vapor over the TP.

scholarly journals Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Qin Zhang ◽  
Junhua Ye ◽  
Shuangcheng Zhang ◽  
Fei Han
Keyword(s):  
Water Vapor ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Reanalysis Data ◽  
Precipitable Water Vapor ◽  
Reanalysis Dataset ◽  
High Positive Correlation ◽  
Advantages And Disadvantages ◽  
Ecmwf Reanalysis

Precipitable water vapor (PWV) content detection is vital to heavy rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV. In general, these methods can be divided into two categories, ground-based or space-based. In this study, we analyze the advantages and disadvantages of these technologies, compare retrieved atmosphere parameters by different RO (radio occultation) observations, like FORMOSAT-3/COSMIC (Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate) and FY3C (China Feng Yun 3C), and assess retrieved PWV precision with a radiosonde. Besides, we interpolate PWV from NWP (numerical weather prediction) reanalysis data for more comparison and analysis with RO. Specifically, ground-based GNSS is of high precision and continuous availability to monitor PWV distribution; in our paper, we show cases to validate and compare GNSS retrieving PWV with a radiosonde. Except GNSS PWV, we give two different radio occultation sounding results, COSMIC and FY3C, to validate the precision to monitor PWV from space in a global area. FY3C results containing Beidou (China Beidou Global Satellite Navigation System) radio occultation events need to be emphasized. So, in our study, we get the retrieved atmospheric profiles from GPS and Beidou radio occultation observations and derive atmosphere PWV by a variational retrieval method based on these data over a global area. Besides, other space-based methods, such as microwave satellite, are also useful in detecting PWV distribution situations in a global area from space; in this study, we present a case of retrieved PWV using microwave satellite observation. NWP reanalysis data ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim and the new-generation reanalysis data ERA5 provide global grid atmosphere parameters, like surface temperature, different-level pressures, and precipitable water. We show cases of retrieved PWV and validate the precision with radiosonde results and compare new reanalysis dataset ERA5 with ERA-Interim, finding that ERA5 can get higher precision-retrieved atmosphere parameters and PWV. In the end, from our comparison, we find that the retrieved PWV from RO (FY3C and COSMIC) and ECMWF reanalysis data (ERA-Interim and ERA5) have a high positive correlation and that almost all R2 values exceed 0.9, compare retrieved PWV with a radiosonde, and find that whether it is RO and ECMWF reanalysis data, ground-based GNSS, or microwave satellite, they all show small biases.

scholarly journals Evaluating Multiple WRF Configurations and Forcing over the Northern Patagonian Icecap (NPI) and Baker River Basin

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 815
Author(s):  
Marcelo Somos-Valenzuela ◽  
Francisco Manquehual-Cheuque
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Weather Prediction ◽  
Wrf Model ◽  
Land Surface Model ◽  
Short Wave ◽  
Reanalysis Data ◽  
Wave Radiation ◽  
Surface Model ◽  
Nwp Model

The use of numerical weather prediction (NWP) model to dynamically downscale coarse climate reanalysis data allows for the capture of processes that are influenced by land cover and topographic features. Climate reanalysis downscaling is useful for hydrology modeling, where catchment processes happen on a spatial scale that is not represented in reanalysis models. Selecting proper parameterization in the NWP for downscaling is crucial to downscale the climate variables of interest. In this work, we are interested in identifying at least one combination of physics in the Weather Research Forecast (WRF) model that performs well in our area of study that covers the Baker River Basin and the Northern Patagonian Icecap (NPI) in the south of Chile. We used ERA-Interim reanalysis data to run WRF in twenty-four different combinations of physics for three years in a nested domain of 22.5 and 4.5 km with 34 vertical levels. From more to less confident, we found that, for the planetary boundary layer (PBL), the best option is to use YSU; for the land surface model (LSM), the best option is the five-Layer Thermal, RRTM for longwave, Dudhia for short wave radiation, and Thompson for the microphysics. In general, the model did well for temperature (average, minimum, maximum) for most of the observation points and configurations. Precipitation was good, but just a few configurations stood out (i.e., conf-9 and conf-10). Surface pressure and Relative Humidity results were not good or bad, and it depends on the statistics with which we evaluate the time series (i.e., KGE or NSE). The results for wind speed were inferior; there was a warm bias in all of the stations. Once we identify the best configuration in our experiment, we run WRF for one year using ERA5 and FNL0832 climate reanalysis. Our results indicate that Era-interim provided better results for precipitation. In the case of temperature, FNL0832 gave better results; however, all of the models’ performances were good. Therefore, working with ERA-Interim seems the best option in this region with the physics selected. We did not experiment with changes in resolution, which may have improved results with ERA5 that has a better spatial and temporal resolution.

scholarly journals Antarctic Low-Tropospheric Humidity Inversions: 10-Yr Climatology

2013 ◽  
Vol 26 (14) ◽  
pp. 5205-5219 ◽  
Author(s):  
Tiina Nygård ◽  
Teresa Valkonen ◽  
Timo Vihma
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Weather Prediction ◽  
Temperature Inversion ◽  
Statistical Characteristics ◽  
The Arctic ◽  
Radiosonde Data ◽  
Atmospheric Moisture Budget ◽  
Temperature Inversions ◽  
The Antarctic

Abstract Humidity inversions are nearly permanently present in the coastal Antarctic atmosphere. This is shown based on an investigation of statistical characteristics of humidity inversions at 11 Antarctic coastal stations using radiosonde data from the Integrated Global Radiosonde Archive (IGRA) from 2000 to 2009. The humidity inversion occurrence was highest in winter and spring, and high atmospheric pressure and cloud-free conditions generally increased the occurrence. A typical humidity inversion was less than 200 m deep and 0.2 g kg−1 strong, and a typical humidity profile contained several separate inversion layers. The inversion base height had notable seasonal variations, but generally the humidity inversions were located at higher altitudes than temperature inversions. Roughly half of the humidity inversions were associated with temperature inversions, especially near the surface, and humidity and temperature inversion strengths as well as depths correlated at several stations. On the other hand, approximately 60% of the humidity inversions were accompanied by horizontal advection of water vapor increasing with height, which is also a probable factor supporting humidity inversions. The spatial variability of humidity inversions was linked to the topography and the water vapor content of the air. Compared to previous results for the Arctic, the most striking differences in humidity inversions in the Antarctic were a much higher frequency of occurrence in summer, at least under clear skies, and a reverse seasonal cycle of the inversion height. The results can be used as a baseline for validation of weather prediction and climate models and for studies addressing changes in atmospheric moisture budget in the Antarctic.

Variations of Water Vapor Transports in Three Rivers’ Headstream during 1971-2010

2014 ◽  
Vol 1073-1076 ◽  
pp. 1760-1763
Author(s):  
Bi Tao Fu ◽  
Xiao Fan Zeng
Keyword(s):  
Water Vapor ◽  
Reanalysis Data ◽  
Specific Humidity ◽  
Water Vapor Transport ◽  
Radiosonde Data ◽  
Adverse Impacts ◽  
Decadal Variations ◽  
Three Rivers ◽  
Precipitation Formation ◽  
Water Vapor Budget

Trend of water vapor transports in the Three Rivers’ Headstream region (China) during 1971-2010 was analyzed based on the applicability analysis of the NCEP/NCAR I reanalysis data in contrast to two kind of data: the daily wind and specific humidity of the R1 data, and the radiosonde data in and around the region. The results show that the meridional water vapor fluxes in the region decreased significantly, causing the net water vapor budget decreasing. The decadal variations of water vapor fluxes in the 1970s and 1980s are relatively smaller than those in the 1990s and 2000s. During 1971-2010, the water vapor budget showed an obvious decreasing trend in spring, summer and autumn, while no significant trend in winter. Overall, the water vapor transport into the region decreased significantly, especially in July and September, which had adverse impacts on precipitation formation.

scholarly journals Detecting Water Vapor Variability during Heavy Precipitation Events in Hong Kong Using the GPS Tomographic Technique

2017 ◽  
Vol 34 (5) ◽  
pp. 1001-1019 ◽  
Author(s):  
Biyan Chen ◽  
Zhizhao Liu ◽  
Wai-Kin Wong ◽  
Wang-Chun Woo
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Heavy Rain ◽  
Heavy Precipitation ◽  
Radiosonde Data ◽  
Weather Forecasts ◽  
Moisture Variation ◽  
Tomographic Technique ◽  
Rain Events ◽  
Precipitation Events

AbstractWater vapor has a strong influence on the evolution of heavy precipitation events due to the huge latent heat associated with the phase change process of water. Accurate monitoring of atmospheric water vapor distribution is thus essential in predicting the severity and life cycle of heavy rain. This paper presents a systematic study on the application of tomographic solutions to investigate water vapor variations during heavy precipitation events. Using global positioning system (GPS) observations, the wet refractivity field was constructed at a temporal resolution of 30 min for three heavy precipitation events occurring in Hong Kong, China, in 2010–14. The zenith wet delay (ZWD) is shown to be a good indicator in observing the water vapor evolution in heavy rain events. The variabilities of water vapor at five altitude layers (<1000, 1000–2000, 2000–3000, 3000–5000, and >5000 m) were examined. It revealed that water vapor above 3000 m has larger fluctuation than that under 3000 m, though it accounts for only 10%–25% of the total amount of water vapor. The relative humidity fields derived from tomographic results revealed moisture variation, accumulation, saturation, and condensation during the heavy rain events. The water vapor variabilities observed by tomography have been validated using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and radiosonde data. The results positively demonstrated the potential of using water vapor tomographic technique for detecting and monitoring the evolution of heavy rain events.

Data Fusion of GEO FY4A GIIRS and LEO Hyperspectral Infrared Sounders with Surface Observations: A Hong Kong Case Study

2021 ◽  
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Weather Prediction ◽  
Coastal Region ◽  
Sampling Interval ◽  
Surface Data ◽  
Accurate Temperature ◽  
Rapid Transition ◽  
Surface Observations

Abstract Hyperspectral infrared satellite observations from geostationary platforms allow for the retrieval of temperature and water vapor measurements with higher temporal and vertical resolution than was previously available. The Chinese satellite, FY-4A includes the Geostationary Interferometric Infrared Sounder (GIIRS) which has the ability to measure vertical profiles of temperature and water vapor from space at times when ground-based upper air soundings are not available and can fill an important need in short-range weather prediction. In this study, CAPE and LI, which are used for forecasting atmospheric instability, were computed using the SHARPpy algorithm used by the NWS Storm Prediction Center. However, remote infrared and microwave sensing is lacking detailed information in the boundary layer, so the addition of the NOAA MADIS surface data may be necessary in order to get accurate temperature and moisture measurement near the surface. This study uses May 10-16, 2019 in the coastal region near Hong Kong for evaluating the use of hourly surface observations combined with satellite soundings from FY4A GIIRS at two hour intervals. The GIIRS plus MADIS surface-based CAPE and LI estimates are compared to estimates derived from low earth orbiting (LEO) SNPP and NOAA20 from NOAA, METOP from EUMETSAT, NWP reanalysis, and local radiosondes. In the case study, the two-hour sampling interval of the GIIRS geostationary sounder was able to capture the rapid transition (16 hours) from stable to unstable atmosphere in both CAPE and LI. The use of surface observations with satellite soundings gave mixed results, possibly due to the complex terrain near Hong Kong.

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