Evaluation of different gridded precipitation products in trend analysis of precipitation features over Iran

Shobeiri, Shahin; Sharafati, Ahmad; Neshat, Aminreza

doi:10.1007/s11600-021-00595-5

Cited by 13 publications

(3 citation statements)

References 33 publications

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“…Nevertheless, for the long‐term assessment of drought conditions, further research is required. Some studies have found divergent trends in annual precipitation between ERA5 data and observational datasets (Shobeiri et al, 2021; Tarek et al, 2020). In particular, Nogueira (2020) compared the annual precipitation trends from the GPCC and ERA5 datasets and found that ERA5 shows ample precipitation declining trends in several regions of Africa and South America that are not observed with the GPCC.…”

Section: Comparison With the Speibasementioning

confidence: 99%

A global drought monitoring system and dataset based on ERA5 reanalysis: A focus on crop‐growing regions

Vicente‐Serrano

Domínguez‐Castro

Reig

et al. 2022

Geoscience Data Journal

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Drought monitoring systems are real‐time information systems focused on drought severity data. They are useful for determining the drought onset and development and defining the spatial extent of drought at any time. Effective drought monitoring requires databases with high spatial and temporal resolution and large spatial and temporal coverage. Recent reanalysis datasets meet these requirements and offer an excellent alternative to observational data. In addition, reanalysis data allow better quantification of some variables that affect drought severity and are more seldom observed. This study presents a global drought dataset and a monitoring system based on the Standardized Precipitation Evapotranspiration Index (SPEI) and ERA5 reanalysis data. Computation of the atmospheric evaporative demand for the SPEI follows the FAO‐56 Penman‐Monteith equation. The system is updated weekly, providing near real‐time information at a 0.5° spatial resolution and global coverage. It also contains a historical dataset with the values of the SPEI at different time scales since January 1979. The drought monitoring system includes the assessment of drought severity for dominant crop‐growing areas. A comparison between SPEI computed from the ERA5 and CRU datasets shows generally good spatial and temporal agreement, albeit with some important differences originating mainly from the different spatial patterns of SPEI anomalies, as well as from employing long‐term climate trends for different regions worldwide. The results show that the ERA5 dataset offers robust results and supports its use for drought monitoring. The new system and dataset are publicly available at the link https://global‐drought‐crops.csic.es/.

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Section: Comparison With the Speibasementioning

confidence: 99%

A global drought monitoring system and dataset based on ERA5 reanalysis: A focus on crop‐growing regions

Vicente‐Serrano

Domínguez‐Castro

Reig

et al. 2022

Geoscience Data Journal

View full text Add to dashboard Cite

show abstract

“…A few studies have evaluated the performance of ERA‐Interim or ERA5 precipitation products for Iran (Darand & Khandu, 2020; Fallah et al., 2020; Khoshchehreh et al., 2021; Shayeghi et al., 2020; Shobeiri et al., 2021; Taghizadeh et al., 2021). However, none of them has focused on a comprehensive comparison of different successive ERA precipitation products to demonstrate their evolution over time.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

Ghajarnia

Akbari

Saemian

et al. 2022

Earth and Space Science

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Precipitation is one of the most important components of the hydrological cycle (Eltahir & Bras, 1996;Oki & Kanae, 2006) and great efforts have been invested in monitoring its spatiotemporal variability (Arabzadeh et al., 2020;Koohi et al., 2021;Teague & Gallicchio, 2017). Multiple methods have been developed to measure and monitor precipitation in the field, but accurate estimation of precipitation is still challenging (Adhikari et al., 2020;Foufoula-Georgiou et al., 2020). For example, this difficulty is due to, high spatiotemporal variability in complex topographical regions (Beck et al., 2019) and different sources of uncertainty associated with different measurement methods and scales (Behrangi & Wen, 2017). These uncertainties impede the study of climate and interconnections of hydroclimatic variables, water resources management, and hydrological forecasts (Foufoula-Georgiou et al., 2020;Sun et al., 2018).There are three main sources of precipitation data: (a) ground-based data (mainly from precipitation gauge networks), (b) satellite remote sensing (RS) data, and (c) reanalysis data sets (Hosseini-Moghari et al., 2018;Shayeghi et al., 2020;Sun et al., 2018). Each of these has its strengths and weaknesses. Gauges provide the most accurate measurements, but they are geographically sparse, especially in remote areas, inaccessible topographies, and harsh climates (

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“…A few studies have evaluated the performance of ERA-Interim or ERA5 precipitation products for Iran (Darand and Khandu, 2020;Fallah et al, 2020;Khoshchehreh et al, 2021;Shayeghi et al, 2020;Shobeiri et al, 2021;Taghizadeh et al, 2021). However, none of them has focused on a comprehensive comparison of different successive ERA precipitation products to demonstrate their evolution over time.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

Ghajarnia¹,

Akbari²,

Saemian³

et al. 2022

Preprint

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ECMWF Reanalysis (ERA), one of the most widely used precipitation products evolved over time from ERA-40 to ERA-20CM, ERA-20C, ERA-Interim, and ERA5. Studies evaluating the performance of individual ERA products cannot adequately assess the evolution in the products. We compared the performance of all ERA precipitation products using daily, monthly, and annual data (1980-2018) from more than 2100 Iran precipitation gauges. Results indicated that ERA-40 performed worst, followed by ERA-20CM, which showed only minor improvements over ERA-40. ERA-20C considerably outperformed its predecessors, benefiting from assimilation of observational data. Although several previous studies have reported full superiority of ERA5 over ERA-Interim, our results revealed several shortcomings compared with ERA-Interim in ERA5 estimates. Both ERA-Interim and ERA5 performed best overall, with ERA-Interim showing better statistical and categorical skill scores, and ERA5 performing better in estimating extreme precipitations. These results suggest that the accuracy of ERA precipitation products improved from ERA-40 to ERA-Interim, but not consistently from ERA-Interim to ERA5. This study employed a grid-grid comparison approach by firstly creating a gridded reference dataset through spatial aggregation of point source observations, however, the results from a point-grid approach show no change in the overall ranking of products (despite the existence of slight changes in the error index values). These findings are useful for model development at global scale and for hydrological applications in Iran.

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Evaluation of different gridded precipitation products in trend analysis of precipitation features over Iran

Cited by 13 publications

References 33 publications

A global drought monitoring system and dataset based on ERA5 reanalysis: A focus on crop‐growing regions

A global drought monitoring system and dataset based on ERA5 reanalysis: A focus on crop‐growing regions

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

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