GM R
Shiraz University, Civil and Environmental Engineering, Faculty Member
This study provides a comprehensive evaluation of a great variety of state-ofthe- art precipitation datasets against gauge observations over the Karun basin in southwestern Iran. In particular, we consider (a) gauge-interpolated datasets... more
This study provides a comprehensive evaluation of a great variety of state-ofthe-
art precipitation datasets against gauge observations over the Karun basin in
southwestern Iran. In particular, we consider (a) gauge-interpolated datasets
(GPCCv8, CRU TS4.01, PREC/L, and CPC-Unified), (b) multi-source products
(PERSIANN-CDR, CHIRPS2.0, MSWEP V2, HydroGFD2.0, and SM2RAIN-CCI),
and (c) reanalyses (ERA-Interim, ERA5, CFSR, and JRA-55). The spatiotemporal
performance of each product is evaluated against monthly precipitation observations
from 155 gauges distributed across the basin during the period
2000–2015. This way, we find that overall the GPCCv8 dataset agrees best with
the measurements. Most datasets show significant underestimations, which are
largest for the interpolated datasets. These underestimations are usually
smallest at low altitudes and increase towards more mountainous areas,
although there is large spread across the products. Interestingly, no overall performance
difference can be found between precipitation datasets for which
gauge observations from Karun basin were used, versus products that were
derived without these measurements, except in the case of GPCCv8. In general,
our findings highlight remarkable differences between state-of-the-art precipitation
products over regions with comparatively sparse gauge density, such as
Iran. Revealing the best-performing datasets and their remaining weaknesses,
we provide guidance for monitoring and modelling applications which rely on
high-quality precipitation input.
art precipitation datasets against gauge observations over the Karun basin in
southwestern Iran. In particular, we consider (a) gauge-interpolated datasets
(GPCCv8, CRU TS4.01, PREC/L, and CPC-Unified), (b) multi-source products
(PERSIANN-CDR, CHIRPS2.0, MSWEP V2, HydroGFD2.0, and SM2RAIN-CCI),
and (c) reanalyses (ERA-Interim, ERA5, CFSR, and JRA-55). The spatiotemporal
performance of each product is evaluated against monthly precipitation observations
from 155 gauges distributed across the basin during the period
2000–2015. This way, we find that overall the GPCCv8 dataset agrees best with
the measurements. Most datasets show significant underestimations, which are
largest for the interpolated datasets. These underestimations are usually
smallest at low altitudes and increase towards more mountainous areas,
although there is large spread across the products. Interestingly, no overall performance
difference can be found between precipitation datasets for which
gauge observations from Karun basin were used, versus products that were
derived without these measurements, except in the case of GPCCv8. In general,
our findings highlight remarkable differences between state-of-the-art precipitation
products over regions with comparatively sparse gauge density, such as
Iran. Revealing the best-performing datasets and their remaining weaknesses,
we provide guidance for monitoring and modelling applications which rely on
high-quality precipitation input.
