*4.2. Extreme Events*

In this part, R90th index using daily precipitation were examined to characterize the spatial distribution of daily precipitation and its extremes in order to cover the associated uncertainties. The 90% percentile level of wet days (P ≥ 0.1 mm) as the R90th threshold has been used. The resulting threshold for each station and precipitation products are shown in Figure 8. As can be seen, the lengths of extremes are double over the Alpine area in compare to low altitude regions (eastern part of the country). The stations' R90th showed the maximum values at high-elevation areas and in the west and northwest of the country. This region is considered the Alpine mountains with high mean annual precipitation amounts and has complex precipitation systems. The spatial distribution of the R90th for MSWEP, IMERG-V05B, and –V06a were rather similar with higher number of days for the precipitation threshold above 90th percentile over the south part of the region, which showed the reliability of the estimations of this index. However, the spatial mean value of R90th for MSWEP was more close to the stations. In contrast, ERA5 underestimated extreme events over the big part of the south region, while showed higher number of extreme days over north Austria. Moreover, SM2RAIN, displayed underestimation of the R90th, almost over the whole country, except for some parts over the western region.

**Figure 8.** Distribution of daily R90th percentile of precipitation.

Figure 9 illustrates the spatial distributions of aggregated precipitation for stations (through bilinear interpolation), IMERG-V05B, -V06A, -V05-RT, MSWEP, ERA5, and SM2RAIN across Austria during the study period. The high precipitation areas extended from east to west along with alpine mountains. Although there are differences in magnitudes of precipitation among the products, in general, all products reasonably captured the precipitation distribution for most parts of the domain. The remarkable precipitation gradients are well-captured by MSWEP, possibly due to using daily in situ observation for bias correction in its algorithms when compared to IMERG, which uses monthly in situ observations for its bias correction. Another cause might be the native higher spatial resolutions of MSWEP (0.1◦ × 0.1◦) than for example ERA5 product (~0.28◦ × ~0.28◦). Nevertheless, ERA5 only poorly agrees with the gauge-based data at daily and monthly time scales, while patterns of accumulated precipitation agree well.

Moreover, IMERG indicates smoother precipitation trend from the west to the eastern part of the study area. The other reason for less comparable of IMERG products with MSWEP might be due to the limited temporal sampling of observations through active and passive microwave satellite sensors in comparison to MSWEP [27,28]. The station observation shows mean precipitation of 2.78 mm, whereas IMERG-V05B, -V06A, MSWEP, and ERA5 overestimate and IMERG-V05-RT underestimates over the whole domain with the mean precipitation values of 3.08 mm, 3.11 mm, 3.11 mm, 3.36 mm, and 2.41 mm, respectively.

**Figure 9.** Spatial distribution of accumulated precipitation (mm) from June 2014 to December 2015 by stations, IMERG-V05B, IMERG-V06A, IMERG-V05-RT, MSWEP, and ERA5.

Figure 9 indicates that the total annual precipitation increases with elevation in the center of the country and extended to the west and south parts of the domain. In contrast, it reduces with elevation over the east parts. Stations located in the low altitudes of the eastern and northern parts of the basin receive less precipitation compared to the associated high altitudes.

#### *4.3. Precipitation Detection Capability*

The spatial distributions and box-plots of POD and FAR for the light-moderate precipitation range (0.1 mm ≤ P < 10 mm) and heavy precipitation (P > 10 mm) over Austria are shown in Figure 10. As can be seen, all products indicated acceptable skill scores in detecting light-moderate precipitation events. These results underscore the substantial advances in earth system modeling and SPE over the last decade. However, the POD of IMERG-05B has a mean areal value of 0.88, while that of IMERG-V06A has a mean value of 0.90, which shows an improvement of IMERG-V-06A over IMERG-V05B in detecting light-moderate precipitation events. Moreover, ERA5, MSWEP, and SM2RAIN indicated higher average POD with 0.94, 0.93, and 0.93, respectively, than all IMERG products. However, looking at the spatial distribution of POD indicating that the ECMWF's fourth-generation reanalysis (ERA5) and MSWEP have obvious advantages in detecting light-moderate precipitation events. In general, each value of POD of ERA5 and MSWEP is significantly better than other products, particularly IMERG products, at most of the stations, which might be due to the tendency of reanalysis data to overestimate light-moderate precipitation frequency [18,24]. In contrast, MSWEP is superior to other products to correctly detect precipitation and no-precipitation events.

The FAR for light-moderate precipitation range of all IMERG and MSWEP products presents almost similar spatial distribution pattern with better performance of MSWEP, particularly over the west part of the country. Figure 10 also shows that MSWEP has the lowest average FAR value (0.11) than other products over the area, while SM2RAIN and ERA5 reveal the highest FAR values (0.33 and 0.25).

**Figure 10.** Spatial distributions and box-plots of POD and FAR at daily scale with respect to precipitation range of light-moderate (0.1 mm ≤ P < 10 mm) and heavy (P > 10 mm) events over Austria. The red-line in the middle of the box-plots represent the median value, the lines above and below the box represent the 25th and 75th percentile values, respectively, while the whiskers represent the extreme values.

As can be seen, the FAR values of IMERG products gradually rising from east to west, which indicates that it is more likely to appear false alarm in areas with higher precipitation. In addition, higher FAR might be due to the high amount of moisture in the atmosphere in this area that the satellites observed, although precipitation did not occur because of the evaporation of raindrops before reaching the ground [29].

For the heavy precipitation category (P > 10 mm), MSWEP and SM2RAIN products were found as the most and least powerful products to detect precipitation with the average value of 0.74 and 0.28 for MSWEP and 0.35 and 0.41 for SM2RAIN with respect to POD and FAR values over the area. Compared with MSWEP, IMERG-V05B, and -V06A, the ERA5 product has more complex spatial non-uniformity of POD and FAR. The MSWEP was found to dominate in the east and north, while the ERA5 dominated in the west in detecting the events. Despite this, a low POD and a high FAR of IMERG products for heavy precipitation mean that they are not able to properly detect precipitation in their exact precipitation categories (P ≥ 10 mm), but they might be able to detect the amount of precipitation somewhat lower than the specified intensities [3].

Lower POD for IMERG-V05-RT, particularly over the high altitudes in the west part of the country may be associated with missed precipitation over this region. The missed precipitation may be caused not only by snow cover on the ground at higher altitudes but also precipitation originates from small-scale and short-lived convective systems.

Notice that in the northern region of the study areas the value of FAR for precipitation above 10 mm/day from all IMERG products was rather high, which could be due not only to evaporation and not falling the small and tiny raindrops of the observed liquid water in the atmosphere profiles during the warm seasons, but also short-term precipitation events are highly variable in space and time and might not be detected by rain gauges, while being detected by other gridded products.
