###### Abstract
The GNSS height values showed that the monthly averages of July values were higher than the interval values, and the difference reached 2 cm. The difference reached 6 cm for the daily average. [PERSON] et al. [29] conducted a study using 3-day datasets for each month of 2009 from the GPS stations of the Marmaa Continuous GPS Network. Their objective was to examine how seasonal changes affect GPS location accuracy. They evaluated 24-h GPS measurements in the dataset with various base lengths, including 4-, 6-, 8-, and 12-h datasets. The study revealed that the accuracy of the observed stations' positions could vary each month in the north-south, east-west, and height directions. Notably, the GPS location accuracy was lowest during the summer (July) and highest in the winter (January and December). The author of [30] analyzed one-year datasets from a mid-latitude GPS station to examine the impact of seasons. The RMS values of the coordinate components were calculated, and then the researcher explored their relationship with meteorological parameters, including temperature, pressure, and humidity. The findings revealed significant correlations between the northern and eastern components of the coordinates and the temperature data. Moreover, it was observed that the RMS values were consistently higher during the spring and summer months, indicating a potential seasonal influence on the GPS station's accuracy. The authors of [31] used time series analysis to examine the relationship between GPS coordinate changes and seasonal variation. The researchers analyzed the changes in the coordinate components of multiple GPS stations between 1996 and 2016 and studied their amplitude and RMS values. The findings revealed that the amplitude of the time series of a station exhibited a vertical increase towards the end of winter and a vertical collapse towards the end of summer. This observation was attributed to groundwater or uplift following winter snowmelt. Furthermore, the study determined that the horizontal coordinate amplitudes were 2-3 times smaller than the vertical ones. The researchers explained this difference by stating that GPS vertical position accuracy was three times lower than horizontal position accuracy and that vertical component crustal deformations exhibitedlarger amplitudes. The authors of [32] analyzed crustal deformations by comparing data from eight GPS stations spanning a range of 2.5 to 13 years. The analysis included time series, gravity recovery, and climate test data. The results revealed that no significant seasonal effect was observed in the horizontal component of the GPS stations. However, in the height component, it was determined that the water storage cycle in the climate zone played a significant role. The study found that when more water is stored in the spring, the crust experiences a greater load, resulting in minimal heights. Conversely, when less water is stored in late summer or early autumn, the load on the crust decreases, leading to maximum heights. This seasonal variation in height reached up to 10 mm. Therefore, seasonal variation was the primary cause of fluctuations in the height component. The main purpose of our study was to present an analysis of the vertical velocity field within the Eastern Anatolia region of Turkey, focusing on its correlation with seasonal variations. This investigation utilizes data from a continuous GNSS network, which has been operating for approximately six years. In order to ensure reliable uncertainties, we took the noise characteristics into account. We recognize that we cannot achieve this objective by only examining seasonal changes. Our research aimed to enhance the accuracy of the vertical component by incorporating meteorological parameters. Therefore, we employed two approaches to evaluate the influence of meteorological parameters on the vertical component. The first approach is simple linear regression analysis, while the second is the ARMA model.