Performance Comparison of Geoid Refinement between XGM2016 and EGM2008 Based on the KTH and RCR Methods: Jilin Province, China

Abstract

The selection of an appropriate global gravity field model and refinement method can effectively improve the accuracy of the refined regional geoid model in a certain research area. We analyzed the accuracy of Experimental Geopotential Model (XGM2016) based on the GPS-leveling data and the modification parameters of the global mean square errors in the KTH geoid refinement in Jilin Province, China. The regional geoid was refined based on Earth Gravitational Model (EGM2008) and XGM2016 using both the Helmert condensation method with an RCR procedure and the KTH method. A comparison of the original two gravity field models to the GPS-leveling benchmarks showed that the accuracies of XGM2016 and EGM2008 in the plain area of Jilin Province are similar with a standard deviation (STD) of 5.8 cm, whereas the accuracy of EGM2008 in the high mountainous area is 1.4 cm better than that of XGM2016, which may be attributed to its low resolution. The modification parameters between the two gravity field models showed that the coefficient error of XGM2016 model was lower than that of EGM2008 for the same degree of expansion. The different modification limits and integral radii may produce a centimeter level difference in global mean square error, while the influence of the truncation error caused by the integral was at the millimeter level. The terrestrial gravity data error accounted for the majority of the global mean square error. The optimal least squares modification obtained the minimum global mean square error, and the global mean square error calculated based on XGM2016 model was reduced by about 1~3 cm compared with EGM2008. The refined geoid based on the two gravity field models indicated that both KTH and RCR method can effectively improve the STD of the geoid model from about six to three centimeters. The refined accuracy of EGM2008 model using RCR and KTH methods is slightly better than that of XGM2016 model in the plain and high mountain areas after seven-parameter fitting. EGM2008 based on the KTH method was the most precise at ± 2.0 cm in the plain area and ± 2.4 cm in the mountainous area. Generally, for the refined geoid based on the two Earth gravity models, KTH produced results similar to RCR in the plain area, and had relatively better performance for the mountainous area where terrestrial gravity data is sparse and unevenly distributed.

Evaluating the Impact of the Recent Combined and Satellite-Only Global Geopotential Model on the Gravimetric Geoid Model

“…Within the framework of the KTH method, four additive corrections are calculated, which include the combined topographic correction 𝛿𝑁̃𝑐𝑜𝑚𝑏 𝑇𝑜𝑝 , the downward continuation correction 𝛿𝑁̃𝐷𝑊𝐶, the total atmospheric correction 𝛿𝑁̃𝑎𝑡𝑚, and the total ellipsoidal correction 𝛿𝑁̃𝑒𝑙𝑙. These corrections are subsequently combined with the approximate gravimetric geoid in the following manner: 𝑁 = 𝑁 ̃+ 𝛿𝑁 𝑇𝑜𝑝𝑐𝑜𝑚𝑏 + 𝛿𝑁 𝐷𝑊𝐶 + 𝛿𝑁 𝑎𝑡𝑚 + 𝛿𝑁 𝑒𝑙𝑙 (12) The initial additive correction, referred to as the combined topographic correction, is calculated using the formula presented in reference [36].…”

“…Several studies by Doganalp [7], Nicacio et al [8], Goyal et al [9], Lee and Kwon [10], and Nyoka et al [11], have conducted evaluations in their respective fields to identify the most suitable model. Recent research by Wu et al [12] compared two gravity field models, XGM2016 and EGM2008, and found that the selection of the gravity field model significantly affects the accuracy of the geoid model within the study area. This finding is consistent with the results of a study conducted by Isik et al [13], which involved the construction of a gravimetric geoid model for the Turkey region using several satellite-only models.…”

Empirical comparison between stochastic and deterministic modifiers over the French Auvergne geoid computation test-bed

“…The KTH method has been used to compute the Swedish national quasigeoid (Ågren et al 2009b), the Nordic Geodetic Commission 2015 quasigeoid (Ågren et al 2016). The KTH approach has received much wider application than the CUT approach, with quasi/geoid models for the Baltic countries (Ellmann 2004), Iran (Kiamehr 2006), Tanzania (Ulotu 2009), Greece (Daras et al 2010), Kazakhstan (Inerbayeva 2010), Sudan (Abdalla and Fairhead 2011),New Zealand (Abdalla and Tenzer 2011), central Turkey (Abbak et al 2012), Moldova (Danila 2012), Saudia Arabia (Abdalla and Mogren 2015), Uganda (Ssengendo 2015), Poland (Kuczynska-Siehien et al 2016), peninsular Malaysia (Pa'suya et al 2019, Estonia (Ellmann et al 2019) and Jilin province in China (Wu et al 2020).…”