Determination of Weighted Mean Temperature (Tm) Lapse Rate and Assessment of Its Impact on Tm Calculation

Yang, Fei; Guo, Jiming; Meng, Xiaolin; Shi, Junbo; Xu, Yi; Zhang, Di

doi:10.1109/access.2019.2946916

Cited by 12 publications

(5 citation statements)

References 44 publications

(35 reference statements)

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“…This requires the lapse rate of Tm. Therefore, the lapse rate of Tm affects the precision of the final estimation of Tm [16][17][18]21]:…”

Section: Research Datamentioning

confidence: 99%

“…However, of the above models, the vertical adjustment of Tm is not involved, which restricts the precision of the estimated value of Tm. Therefore, some scholars studied the calculation and modeling lapse rate of Tm [16,17]. Huang et al [18] constructed a Tm lapse rate function model for estimating seasonal fine changes given the large fluctuations in China, which improved the precision of Tm estimation.…”

Section: Introductionmentioning

confidence: 99%

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A Weighted Mean Temperature Model with Nonlinear Elevation Correction Using China as an Example

2021

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The weighted mean temperature (Tm) is a crucial parameter for determining the tropospheric delay in transforming precipitable water vapor. We used the reanalysis data provided by European Centre for Medium-Range Weather Forecasts (ECMWF) to analyze the distribution characteristics of Tm in the vertical direction in China. To address the problem that the precision of the traditional linear function model is limited in fitting the Tm profile, a scheme using the linear and Fourier functions to fit the Tm profile was constructed. Based on the least squares principle (LSQ) to fit the change in its coefficients over time, a Tm model for China with nonlinear elevation correction (CTm-h) was constructed. The experimental results show that, using ECMWF and radiosonde data to evaluate the precision of the CTm-h model, the RMS is 3.43 K and 4.64 K, respectively. Compared to GPT2w, the precision of the CTm-h model in China is increased by about 26.8%. The CTm-h model provides a significant improvement in the correction effect of Tm in the vertical direction, and the Tm profile calculated by the model is closer to the reference value.

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“…This requires the lapse rate of Tm. Therefore, the lapse rate of Tm affects the precision of the final estimation of Tm [16][17][18]21]:…”

Section: Research Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Weighted Mean Temperature Model with Nonlinear Elevation Correction Using China as an Example

2021

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“…Using (4) to obtain T m requires water vapor pressure and temperature profiles. Temperature profiles can be obtained from RS data (note that the location of the RS station is usually not the same as any GNSS stations); e i requires a conversion [33], [34]:…”

Section: B Pwv Derived From Gnss and Era-5 Datasetmentioning

confidence: 99%

Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

Shen

Wan

et al. 2020

IEEE Access

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Tropical cyclones (TCs) are intense rotating storm systems, characterized by strong winds, heavy humidity and storm surges, and usually cause an abnormal increase in regional water vapor during the period of their occurrence. Global navigation satellite system (GNSS) is well-established and initially mainly for positioning, navigation and timing. However, due to their global coverage and 24/7 operability under all weather conditions, GNSS has been widely used in meteorology such as the retrieval of precipitable water vapor (PWV). Since PWV time series obtained from a regional ground GNSS tracking stations network has high temporal and spatial resolutions, in this research, the temporal and spatial variation trends of regional PWVs during several TCs' periods in Hong Kong were investigated, and a new method using high-resolution GNSS-PWV time series to estimate a TC's movement was proposed. Test data were from 15 GNSS tracking stations equipped with meteorological sensors, and three GNSS stations without meteorological sensors but using meteorological data interpolated from ERA5 (fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting) dataset, and six TC events occurred in 2017 were selected for cases studies. Moreover, for a better accuracy of GNSS-PWV, which is converted from the zenith wet delay of the GNSS signal multiplying a conversion factor that uses a weighted mean temperature (T m), a seasonal multi-factor T m model was established and tested. Results showed that the new T m model outperformed the previous regional T m model used in Hong Kong. In addition, based on the temporal variation trend and spatial distribution of the regional PWV, one can determine if a TC approaches the region. A geometric approach to estimating a TC's movement was developed and its test results agreed well with the truth. These results suggest the potential of using GNSS signals to monitor the movements of TCs for short-time TC forecasting due to their high temporal resolution. INDEX TERMS Tropical cyclone, global navigation satellite system, precipitable water vapor, weighted mean temperature, ERA5. I. INTRODUCTION Over recent years, increasing tropical cyclone (TC) events occurred frequently in the North Pacific, Indian Ocean, Southwest Pacific and North Atlantic, causing considerable damage in nearby cities [1]-[5]. Many countries, provinces and cities have set up meteorological departments, which take the early warning and forecasting of TCs as a key task. Water vapor, as a main component of the atmosphere, is a key factor The associate editor coordinating the review of this manuscript and approving it for publication was Gerardo Di Martino. influencing TCs' development [6], [7]. The monitoring of regional water vapor variation is critical for the forecasting of the movement, intensity and rainfall of TCs [8]-[10]. Traditional techniques for the acquisition of atmospheric water vapor, such as infrared satellite remote sensing, radiosondes (RS) and microwave radiometers, have the disa...

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“…After the height system conversion, the ZTD can be determined at different pressure levels with the meteorological parameters at and above this level [31][32][33][34]. As suggested by previous studies [12,21], the ZTD decreases exponentially with the altitude, which has been adopted in many ZTD models [13,21,22].…”

Section: Calculation Of Inverse Scale Heightmentioning

confidence: 99%

A New Four-Layer Inverse Scale Height Grid Model of China for Zenith Tropospheric Delay Correction

Zhang

Wang

et al. 2020

IEEE Access

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To reduce the convergence time in the real-time precise point positioning (PPP), the zenith tropospheric delay (ZTD) needs to be modeled with high accuracy and sent to the users to be introduced as a priori value. Because of the height difference between the model height and user's location, the ZTD at the model height must be converted to that at the user's height. Therefore, it is crucial to investigate an optimal method for this height correction of ZTD. It is normally assumed that the ZTD decreases exponentially with the altitude and an empirical decrease factor is adopted for depicting the ZTD variation with altitude. In this study, the performance of the commonly used single-layer model of the decrease factor was investigated. Based on the investigation of the single-layer model, a new four-layer grid model (0.25°×0.25°) over China was constructed with 10-year (from 2009 to 2018) ERA5 data, and its performance was validated. The results indicate that the newly constructed four-layer model has a better performance than the single-layer model with the bias and root mean square (RMS) of the determined ZTD reduced by 54.4% and 27.6%, respectively. With the four-and single-layer grid model and GNSS-derived ZTD, two ZTD models i.e. four-layer ZTD and single-layer ZTD were constructed over China. The experiment shows that the convergence time of PPP can be obviously reduced when introducing these two ZTD models and the four-layer ZTD model has a much better performance than the single-layer ZTD, especially at stations with a high altitude. INDEX TERMS ZTD vertical reduction, height correction, inverse scale height, four-layer model

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Determination of Weighted Mean Temperature (Tm) Lapse Rate and Assessment of Its Impact on Tm Calculation

Cited by 12 publications

References 44 publications

A Weighted Mean Temperature Model with Nonlinear Elevation Correction Using China as an Example

A Weighted Mean Temperature Model with Nonlinear Elevation Correction Using China as an Example

Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

A New Four-Layer Inverse Scale Height Grid Model of China for Zenith Tropospheric Delay Correction

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