## 1 Introduction
They reported that the GSMaP precipitation products outperformed other GPPs, followed by the Integrated Multi-satellite Retrieval for Global Precipitation Measurement (IMERG). Moreover, [PERSON] [6] assessed the performance of four GPPs using in situ observations from the Trans-African Hydro-Meteorological Observatory (TAHMO) over the eastern (i.e., Uganda) and western (i.e., Ghana) parts of Africa. The evaluations were conducted in various time scales, revealing weak performances of all examined GPPs in capturing daily precipitation patterns, but better performances on monthly and seasonal scales. Moreover, [PERSON] et al. [40] compared the accuracy of four Global Precipitation Measurement (GPM)-based GPPs over the southern slopes of the central Himalayas between March 2014 and December 2016. The statistical analyses indicated that the GSMaP gauge-adjusted GPP obtained higher accuracy, and the gauge-adjusted GPPs in general performed consistently well at representing seasonal dynamics. As in other parts of the world, GPPs have been employed for different purposes in Iran [24; 43; 44; 45; 46]. Consequently, several studies were devoted to comparing and evaluating the accuracy of different GPPs in Iran [43; 45; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58]. For example, [PERSON] et al. [57]investigated the performance of four high-resolution GPPs over six regions in Iran during a 5-year period (2003-2008). Overall, they discovered that the TRMM Multi-sensor Precipitation Analysis (TMPA) 3B42V7 led to better performance over three other GPPs (i.e., PERSIANN, TMPA-3B42 RT, and the Climate Prediction Center Morphing technique (CMORPH)). In another study, [PERSON] et al. [55] conducted a thorough accuracy analysis of different IMERG GPPs over Iran between 2014 and 2017. The intercomparison with in situ precipitation observations suggested a discrepant performance of IMERG products. In particular, they reported that, on average, the performances improved from IMERG-early to IMERG-final products, while it was recommended not to rely on IMERG-final products for extreme precipitations. Likewise, [PERSON] et al. [58] explored the capability of six GPPs, namely, Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), CMORPH, PERSIANN, PERSIANN Climate Data Record (PERSIANN-CDR), TRMM 3B42V7, and Soil Moisture inversion to RAIN (SM2 RAIN) in Karkheh Basin between 2003 and 2014. They incorporated in situ precipitation observations from 28 stations, and both continuous and categorical analyses specified low variation in the performance of all GPPs. However, considering all investigations, it was stated that the PERSIANN-CDR and SM2 RAIN showed the best performance as post-satellite precipitation estimates. Furthermore, [51] employed in situ observations from 344 stations to assess the capability of three GSMaP GPPs in Iran between 2014 and 2018. It was stated that all three versions of GSMaP were capable of displaying the spatial pattern of precipitation. However, findings demonstrated the higher accuracy of the GSMaP gauge-adjusted type at daily and monthly time scales. Although different studies were carried out to evaluate the performance of GPPs in Iran, each focused on a relatively small area (i.e., province or basin) or investigated one or two different GPPs. The other studies incorporated a small number of stations or considered a short period for comparisons and performance evaluation. These factors make it impractical to compare GPPs when considering the entirety of Iran, necessitating a consistent intercomparison of different well-known and recent GPPs. In light of the preceding, the aim of this paper is to evaluate the performance and capability of six satellite and reanalysis GPPs throughout Iran using in situ observations.