*4.1. Elevation*

Since Austria characterized by complex terrain and big difference in altitude over the country, annual mean precipitation range significantly varies with elevation and climate conditions. The microclimate can be created due to rapid changes in elevation which cause the obstruct the air mass movement or this rapid changes in elevation can cause the updraft of the air mass over the mountains to create orographic rainfall. Hence, for more deep analysis, the evaluation of the precipitation products was conducted by classifying the stations' elevation equal or less than 1000 m the stations located in greater than 1000 m altitudes (1000 m ≥ stations' Elevation > 1000 m) over the whole country in order to account for the effect of topography.

For the first category (1000 m ≥ Elevation), the performance of gridded precipitation products was evaluated by comparing daily data for 642 stations which fell into 502 pixels, while the second category contains 140 stations which fell into 125 pixels. Figures 6 and 7 show the spatial distribution of the

statistical indices for all products against in situ observations values for different elevation categories. MAE and RMSE evaluation metrics showed similar spatial patterns, while a sharp contrast from east to west of Austria for both elevation categories is observed, except for MSWEP, which indicated gradual variation. According to CC, MSWEP performed well, followed by IMERG-V05B and -V06A over the whole region, while ERA5, SM2RAIN, and IMERG-V05-RT showed weak CC, respectively, particularly over the alpine valleys.

With the increase of elevation, the mean RMSE, MAE, and bias increase and CC decreases, whereas the bias of IMERG-V05B and -V06A show a decreasing trend with increasing elevation/rainfall. The reason for this difference may be attributed to the cancellation of positive and negative biases, while logically due to high precipitation amounts the error should be higher. In other words, MAE and RMSE measure the absolute error magnitude and bias measure the relative error. The MAE, which evaluates the average magnitude error between precipitation products and in situ observations, were 2.26 mm, 2.2 mm, 2.21 mm, 1.44 mm, 2.59 mm, and 2.57 mm for IMERG-V05B, -V06A, -V05-RT, MSWEP, ERA5, and SM2RAIN, respectively, for the elevation category of less than 1000 m.

**Figure 6.** Spatial distributions and box plots of the statistical indices for the precipitation products and stations with the elevation equal or less than 1000 m. The center-line of each boxplot depicts the median value (50th percentile) and the box encompasses the 25th and 75th percentiles of the sample data, while the whiskers represent the extreme values, respectively.

Similarly, CC value of the aforementioned products was ≥ 0.5 in the majority of stations with an average value of 0.69, 0.70, 0.64, 0.86, 0.55, and 0.59, respectively, for the stations with less than 1000 m in altitude, while the average CC value of 0.64, 0.66, 0.55, and 0.85 obtained for the IMERG-V05B, -V06A, -V05-RT, and MSWEP, respectively, for the stations located in the high altitudes. The ERA5 and SM2RAIN products failed to capture the observed daily precipitation with CC < 0.5 in most stations over the high altitudes and complex terrains. In general, one can say all products performed better in the low altitudes compared to the high altitudes.

**Figure 7.** Spatial distributions and box plots of the statistical indices for the precipitation products and stations with the elevation greater than 1000 m. The center-line of each boxplot depicts the median value (50th percentile) and the box encompasses the 25th and 75th percentiles of the sample data, while the whiskers represent the extreme values, respectively.

It is notable to mention that inconsistent estimation of the precipitation products (except MSWEP) is possibly due to the rough terrains effect. The overall performance of the precipitation products is lower in the peripheries of the study area where most stations are situated in the mountainous area [26].
