Abstarct: Global climate change is a subject that has captivated the attention of numerous researchers worldwide over the past few decades. Conducting research pertaining to climate change is imperative for enhancing preparedness to mitigate its effects and reduce the associated costs of damages. In this study, the impact of large-scale climate signals on the variations in both the quality and level of groundwater in 28 piezometric wells in Isfahan Province and the groundwater level in the Lake Urmia basin was investigated. All relevant data concerning the large-scale climate signals were sourced from the NOAA website. Monthly data pertaining to groundwater quality and levels were collected for the statistical period from 2003 to 2019. Subsequently, using MATLAB software, correlations between the indices and variations in groundwater quality and levels were calculated. Two indices, Nino 1+2 and TNI, as well as two indices, Nino 4 and TNI, were identified as the most influential factors affecting variations in groundwater level and quality within the wells studied in Isfahan Province. Additionally, within the context of the Lake Urmia basin, the key indices exerting the most significant impact on groundwater level fluctuations were TNI, Nino1+2, and Nino4. Furthermore, employing the Pearson correlation coefficient, it was determined that the TNI index stands as the paramount influencer of changes in groundwater quality and levels within both Isfahan Province and the Lake Urmia basin. Notably, this influential effect was most pronounced at time lags of 20 and 8 months, demonstrating the highest correlations with changes in groundwater levels in Isfahan Province and the Urmia basin, respectively. Therefore, it can be concluded that the effects of large-scale climate signals, albeit with a multi-month delay, extend their influence to Iran, affecting various regions of the country, including Isfahan Province. Notably, the correlation patterns between groundwater quality and levels with the TNI index predominantly displayed both negative and positive associations. Specifically, a decrease in the TNI index corresponded to a reduction in groundwater levels and an increase in groundwater salinity.