Performance Assessment of CHIRPSv2.0 and MERRA-2 Gridded Precipitation Datasets over Complex Topography of Turkey †

: Precipitation is a major component of the global water cycle, and its accurate measure-ment, especially over complex topography, requires a dense gauge network, which is often limited for many parts of the world. In recent decades, Gridded Precipitation Datasets (GPDs) that merge information from satellites, numerical weather prediction models, and available ground data could be a potential alternative source for many hydro-climatic studies. However, their validation is a prerequisite task before utilizing them for different applications. This study aims to evaluate the spatio-temporal consistency of CHIRPSv2.0 and MERRA-2 datasets over different elevation ranges in Turkey based on five hydrological years (2015 – 2019) under Kling-Gupta Efficiency (KGE) metric for daily and monthly time steps. Moreover, three categorical indicators, including Threat Score (TS), Pierce Skill Score (PSS), and Gilbert Skill Score (GSS), are employed to address GPD detectability strength for various precipitation intensities. In general, GPDs show high performance for monthly (median KGE of; 0.62 – 0.76) time step than daily (median KGE of; 0.19 – 0.28), and MERRA-2 outperforms CHIRPSv2.0 considering daily precipitation, while CHIRPSv2.0 shows higher performance

Why Gridded Precipitation Datasets (GPDs) are Important ??!! Why? v Accurate precipitation estimates with high spatio-temporal resolution are essential for many studies related to water resources on regional and global scales [1,2].
Precipitation monitoring over highly elevated regions and complex topography has been a great challenge in recent years [3,4] , and the lack of precipitation observation usually limits hydro-climatic studies, especially for data-scare regions [5].
v Alternatively, Gridded Precipitation Datasets (GPDs), which take advantage of satellite sensor information and numerical weather prediction model output data, present high spatio-temporal resolution and long-term precipitation estimates [1,6].
However, the validation of GPDs over a particular area may not be applicable for other regions, and a detailed assessment is required to address GPDs performance over time and space.
v According to the previously described context, this study aims to evaluate the spatio-temporal consistency of two multi-source Gridded Precipitation Datasets (CHIRPSv2.0 and MERRA-2) over complex topography (distinct elevation ranges) of Turkey considering the daily and monthly precipitation.    v Based on observed precipitation, the entire region receives precipitation of around 1.80 mm and 56.25 mm for daily and monthly time steps and Areas with an elevation of less than 500 m, which mostly represent coastal regions, experience higher precipitation amounts (2.37 mm/day and 73.2 mm/month).

Evaluation of mean daily and monthly precipitation
v CHIRPSv2.0 shows close precipitation estimates to observed and its perfect records is obtained over areas with elevation more than 1500 m and MERRA-2 only underestimates daily and monthly precipitation in the coastal areas (area with elevation less than 500 m).

Performance accuracy of GPDs at the station location
v Overall, both CHIRPSv2.0 and MERRA-2 show higher performance for the monthly precipitation than the daily time step.
v Considering daily precipitation, MERRA-2 shows higher performance compared to CHIRPSv2.0 at the gridpoint level, which is relatively indicated by higher KGE and correlation coefficient (r) values. Performance accuracy of GPDs at the regional scale v Considering daily precipitation, MERRA-2 shows higher performance over the entire region (median KGE of; 0.28).
v In general, MERRA-2 displays lower performance compared to CHIRPSv2.0 when the elevation is increased.
v Both CHIRPSv2.0 and MERRA-2 show significantly higher performance for monthly precipitation estimates.

Detection ability of GPDs for daily precipitation
v The GPD's ability to detect daily precipitation events for five intensities is expressed in the form of Threat Score (TS), Pierce Skill Score (PSS), and Gilbert Skill Score (GSS) .
v MERRA-2 shows higher detectability strength compared to CHIRPSv2.0 over different elevation ranges, and CHIRPSv2.0 shows slightly higher detection ability only for extreme (> 40 mm/day) precipitation over areas with an elevation of less than 500 m, which mostly presents coastal regions in the country. Conclusions v MERRA-2 shows a higher mean precipitation for areas over 500 m elevation and becomes more observable over areas with an elevation of more than 1500 m, while CHIRPSv2.0 produces effective daily and monthly mean precipitation and it has a perfect match with observed precipitation over areas having an elevation of more than 1500 m.
v Overall, MERRA-2 exhibits higher performance compared to CHIRPSv2.0 for the daily time step, where CHIRPSv2.0 outperforms MERRA-2 considering the monthly time window.
v Considering the performance of GPDs over different elevation ranges, CHIRPSv2.0 presents a relatively stable performance compared to MERRA-2 for both daily and monthly precipitation.
v Overall, MERRA-2 displays relatively higher detectability strength compared to CHIRPSv2.0 for different precipitation intensities, while CHIRPSv2.0 shows detection ability higher than MERRA-2 only for extreme precipitation over areas with less than 500 m. Moreover, both the CHIRPSv2.0 and MERRA-2 detection abilities decrease as the intensity and elevation increase.