Comparison of the grid-wise VMF3 and GPT3 troposphere models derived from the VMF data server: A study for the European region

Öz

The Zenith Total Delay (ZTD) must be determined for applications requiring high accuracy, such as Global Navigation Satellite Systems (GNSS), geodesy and cartography, weather forecasting, and astronomical observations, as it is a significant factor affecting the accuracy of electromagnetic signals. The delay effect can be predicted with traditional troposphere models based on surface meteorological parameters. Due to certain environmental and economic factors, meteorological data cannot always be obtained from in-situ observations. Furthermore, considering the inherent modeling errors in these approaches, it becomes challenging to obtain accurate results in data processing procedures. As a solution, the Vienna Mapping Functions (VMF) data server, based on continuously updated Numerical Weather Prediction (NWP) data from the European Centre for Medium-Range Weather Forecasts (ECMWF), provides tropospheric products from two different models: discrete and empirical. Additionally, this server offers site-wise ZTDs directly derived from in-situ observations at reference stations, as well as gridded data for predicting ZTDs at random locations where stations are not present. This study focuses on comparative analysis of the performance of grid-wise Vienna Mapping Function-3 (VMF3) and Global Pressure and Temperature-3 (GPT3) tropospheric models in predicting ZTDs derived from the VMF data server. The application was conducted over randomly selected reference points in the European region, and the daily ZTDs obtained from the models were evaluated. The study results have shown that the VMF3 model predicts ZTD with Root Mean Square Error (RMSE) values ranging from 0.7 to 1.1 cm, while these error values range from 3.2 to 5.0 cm for the GPT3 model. Generally, it can be said that VMF3 exhibits higher capability in predicting ZTD compared to the GPT3 model. It can be concluded that grid-wise VMF3 can be used as a supportive model for determining ZTD in locations where in-situ observations are not possible or where there is no data archive for site-wise products.

Anahtar Kelimeler

• GNSS
• Zenith Total Delay (ZTD)
• Vienna Mapping Function-3 (VMF3)
• Global Pressure and Temperature-3 (GPT3)
• Tropospheric Models

VMF veri sunucusundan türetilen grid bazlı VMF3 ve GPT3 troposfer modellerinin karşılaştırılması: Avrupa bölgesi için bir çalışma

Öz

Toplam Zenit Gecikmesi (ZTD), elektromanyetik sinyallerin doğruluğunu etkileyen önemli bir faktör olduğundan Küresel Navigasyon Uydu Sistemleri (Global Navigation Satellite Systems, GNSS), jeodezi ve haritacılık, hava durumu tahminleri ve astronomik gözlemler gibi yüksek doğruluk gerektiren uygulamalar için belirlenmesi gerekir. Gecikme etkisi, yüzey meteorolojik parametrelerine dayanan geleneksel troposfer modelleriyle tahmin edilebilir. Meteorolojik verilerin birtakım çevresel ve ekonomik hususlar nedeniyle yerinde gözlemlerden elde edilememesi ve ilgili modellerdeki içsel modelleme hataları dikkate alındığında, bu yaklaşımların veri işleme süreçlerinde doğru sonuçları sağlaması zorlaşmaktadır. Bir çözüm olarak, Avrupa Orta Vadeli Hava Tahminleri Merkezi'nden (ECMWF) sürekli güncellenen Sayısal Hava Tahminleri (NWP) verilerine dayalı Vienna İz Düşüm Fonksiyonu (VMF) veri sunucusu; ayrık ve ampirik olmak üzere iki farklı modelden troposferik ürünler sağlamaktadır. Ayrıca, bu sunucuda, referans istasyonlarındaki yerinde gözlemlerle elde edilen saha bazlı (site-wise) ZTD’ler doğrudan, istasyonların bulunmadığı rastgele konumlardaki ZTD’lerin kestirimi için grid bazlı (grid-wise) veriler kullanıcılara sunulmaktadır. Bu çalışma, VMF veri sunucusu tarafından türetilmiş grid Viyana İz Düşüm Fonksiyonu-3 (VMF3) ve Global Basınç ve Sıcaklık-3 (GPT3)troposfer modellerinin ZTD kestirimindeki performansının karşılaştırmalı analizine odaklanmıştır. Avrupa Bölgesi’nden seçilmiş rastgele konumlardaki referans noktaları üzerinden uygulama gerçekleştirilmiş olup modellerden elde edilen günlük ZTD’ler değerlendirilmiştir. Çalışma sonuçları, VMF3 modelinin 0.7-1.1 cm arasında değişen Karesel Ortalama Hata (KOH) değerleri ile ZTD’yi kestirdiğini, bu hata değerlerinin GPT3 modeli için 3.2-5.0 cm arasında olduğunu göstermiştir. Genel olarak, VMF3’ün GPT3 modeline kıyasla ZTD kestirimindeki yeteneğinin daha yüksek olduğu söylenebilir. Yerinde gözlemlerin mümkün olmadığı ya da saha bazlı ürünlere ait veri arşivinin olmadığı konumlar için ZTD’nin belirlenmesinde grid bazlı VMF3’ün destekleyici bir model olarak kullanılabileceği sonucuna varılabilir.

Anahtar Kelimeler

• GNSS
• Toplam Zenit Gecikmesi (ZTD)
• Viyana İz Düşüm Fonksiyonu-3(VMF3)
• Global Basınç ve Sıcaklık-3(GPT3)
• Troposferik Modeller

Teşekkür

Bu çalışma, ilk yazarın Konya Teknik Üniversitesi Lisansüstü Eğitim Enstitüsü Harita Mühendisliği Anabilim Dalında hazırlanan doktora tezinin bir parçasıdır.

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