HydroGFD3.0 (Hydrological Global Forcing Data): a 25 km global precipitation and temperature data set updated in near-real time
-
Published:2021-04-13
Issue:4
Volume:13
Page:1531-1545
-
ISSN:1866-3516
-
Container-title:Earth System Science Data
-
language:en
-
Short-container-title:Earth Syst. Sci. Data
Author:
Berg PeterORCID, Almén Fredrik, Bozhinova DenicaORCID
Abstract
Abstract. HydroGFD3 (Hydrological Global Forcing Data) is a data set of bias-adjusted reanalysis data for daily precipitation and minimum, mean, and maximum temperature. It is mainly intended for large-scale hydrological modelling but is also suitable for other impact modelling.
The data set has an almost global land area coverage, excluding the Antarctic continent and small islands, at a horizontal resolution of 0.25∘, i.e. about 25 km.
It is available for the complete ERA5 reanalysis time period, currently 1979 until 5 d ago.
This period will be extended back to 1950 once the back catalogue of ERA5 is available.
The historical period is adjusted using global gridded observational data sets, and to acquire real-time data, a collection of several reference data sets is used.
Consistency in time is attempted by relying on a background climatology and only making use of anomalies from the different data sets.
Precipitation is adjusted for mean bias as well as the number of wet days in a month.
The latter is relying on a calibrated statistical method with input only of the monthly precipitation anomaly such that no additional input data about the number of wet days are necessary.
The daily mean temperature is adjusted toward the monthly mean of the observations and applied to 1 h time steps of the ERA5 reanalysis.
Daily mean, minimum, and maximum temperature are then calculated.
The performance of the HydroGFD3 data set is on par with other similar products, although there are significant differences in different parts of the globe, especially where observations are uncertain.
Further, HydroGFD3 tends to have higher precipitation extremes, partly due to its higher spatial resolution.
In this paper, we present the methodology, evaluation results, and how to access the data set at https://doi.org/10.5281/zenodo.3871707 (Berg et al., 2020).
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
Reference34 articles.
1. Andersson, J. C., Ali, A., Arheimer, B., Gustafsson, D., and Minoungou, B.:
Providing peak river flow statistics and forecasting in the Niger River
basin, Phys. Chem. Earth, 100, 3–12, https://doi.org/10.1016/j.pce.2017.02.010,
2017. a 2. Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation, Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, 2020. a 3. Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R.,
Cecil, L. D., Nelson, B. R., and Prat, O. P.: PERSIANN-CDR: Daily
Precipitation Climate Data Record from Multisatellite Observations for
Hydrological and Climate Studies, B. Am. Meteorol. Soc., 96, 69–83,
https://doi.org/10.1175/bams-d-13-00068.1, 2015. a 4. Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017. a, b, c 5. Berg, P., Donnelly, C., and Gustafsson, D.: Near-real-time adjusted reanalysis forcing data for hydrology, Hydrol. Earth Syst. Sci., 22, 989–1000, https://doi.org/10.5194/hess-22-989-2018, 2018. a, b, c
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|