Akademik Veri Yönetim Sistemi
2. ICCC Workshop 2023: Geodesy for Climate Research, Berlin, Almanya, 28 - 29 Mart 2023, ss.1, (Özet Bildiri)
Total Water Storage (TWS) has been monitored by the Gravity Recovery and Climate Experiment (GRACE) mission and its successor, the GRACE Follow-On mission. Groundwater, surface water, and water from snow and glaciers are all included in the TWS description of the hydrosphere's natural variability. Harmonic regression functions are used to estimate monthly variations in global TWS values, assuming a linear trend and seasonal signals. However, climate change, floods, or droughts, as well as increased human water withdrawals as a potential cause of the nonlinearity in the actual long-term variations of the TWS time series may be mentioned. For the purpose of quantifying and explaining this nonlinearity, we present a novel approach to a deterministic model of TWS time series derived from the Goddard Space Flight Center (GSFC) global mascon solution. The redefined deterministic model incorporates a polynomial function along with the seasonal components. These polynomial functions have a third, fourth, or fifth degree; the optimal degree is chosen independently for each mascon. We showed that the form of a polynomial function is physically reasonable and spatially consistent. Greenland, Antarctica, Alaska, the Great Lakes of North America, the Mississippi River Basin, the eastern part of South America, the Tigris and Euphrates River Basins, southern Africa, and the Caspian Sea region are mostly affected by long-term changes other than linear ones. The proposed model can determine nonlinearity in the long-term changes caused by dry and wet periods, which are captured by the climate index. This aids in the comprehension of GRACE signal complexity. Overall, the results indicate that polynomial functions improve TWS time series modeling. We note that the RMS values improved by up to 50% in the areas with the largest nonlinearities. This model also allows the mapping of extreme dry and wet periods that result in nonlinearity.