the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An intercomparison of four gridded precipitation products over Europe using the three-cornered-hat method
Abstract. Precipitation is arguably one of the most relevant surface variables impacting human lives on the planet, but global-coverage, high-resolution and good-quality observations are not readily available. In particular, gridded observational datasets are much needed for model development and forecast quality assessment. Here we compare the quality of four types of gridded precipitation products over Europe, namely: a rain-gauge interpolation; a satellite-derived product; a radar composite; and a reanalysis. Each product has its own strengths and weaknesses, and since each precipitation estimate uses different measuring techniques, we can employ a triangulation method to estimate the error variance of each product with respect to the unknown true values. Results show that: a) the satellite product has limited quality over Europe and may be problematic to use in quantitative forecast evaluation and diagnostics; b) the radar composite has spurious features that need to be considered when used in verification; c) all products struggle in topographically complex areas; d) the rain-gauge interpolation is not free of errors, despite rain gauges being often treated as ground truth in the literature; and e) the reanalysis dataset produces in some cases the best available estimates, in particular over the European near-coastal waters.
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Status: closed
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RC1: 'Comment on egusphere-2024-807', Richard Anthes, 03 Apr 2024
This is an excellent paper that applies the three-cornered hat (3CH) and four-cornered hat (4CH) methods to estimate the uncertainties (random error variances) of four precipitation datasets. It is acceptable for publication after the authors consider some relatively minor changes that would improve the clarity of the paper. My full review with suggested edits is included as a Supplement.
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AC1: 'Reply on RC1', Llorenç Lledó, 21 Jun 2024
We want to thank the reviewer for the positive appreciation of this manuscript, and for taking the time to read it and suggest specific improvements. We have made several changes in the manuscript that we believe improved its clarity and quality.
We attach the responses as a pdf document. The responses are in blue following each reviewer's comment.
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AC1: 'Reply on RC1', Llorenç Lledó, 21 Jun 2024
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RC2: 'Comment on egusphere-2024-807', Anonymous Referee #2, 24 Apr 2024
This study explores the estimation of random error variance in four gridded precipitation datasets sourced from various natural sources using the triangulation method called the Four Cornered Hat (4CH). In my assessment, the paper falls short of the standard expected by the Journal of HESS and would benefit significantly from a major revision. My main concern is the ambiguity regarding whether the variant of the 3CH, the 4CH, is an innovative aspect of this study. My full review is included as a Supplement.
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AC2: 'Reply on RC2', Llorenç Lledó, 21 Jun 2024
We want to thank the reviewer for taking the time to read the manuscript and suggesting several aspects that required improvement. In the revised manuscript we have clarified the novelty of our method by putting it in context with existing multiple-collocation techniques. We have also made several changes in the manuscript that we believe improved its clarity and quality.
We attach the responses as a pdf document. The responses are in blue following each reviewer's comment.
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AC2: 'Reply on RC2', Llorenç Lledó, 21 Jun 2024
Status: closed
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RC1: 'Comment on egusphere-2024-807', Richard Anthes, 03 Apr 2024
This is an excellent paper that applies the three-cornered hat (3CH) and four-cornered hat (4CH) methods to estimate the uncertainties (random error variances) of four precipitation datasets. It is acceptable for publication after the authors consider some relatively minor changes that would improve the clarity of the paper. My full review with suggested edits is included as a Supplement.
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AC1: 'Reply on RC1', Llorenç Lledó, 21 Jun 2024
We want to thank the reviewer for the positive appreciation of this manuscript, and for taking the time to read it and suggest specific improvements. We have made several changes in the manuscript that we believe improved its clarity and quality.
We attach the responses as a pdf document. The responses are in blue following each reviewer's comment.
-
AC1: 'Reply on RC1', Llorenç Lledó, 21 Jun 2024
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RC2: 'Comment on egusphere-2024-807', Anonymous Referee #2, 24 Apr 2024
This study explores the estimation of random error variance in four gridded precipitation datasets sourced from various natural sources using the triangulation method called the Four Cornered Hat (4CH). In my assessment, the paper falls short of the standard expected by the Journal of HESS and would benefit significantly from a major revision. My main concern is the ambiguity regarding whether the variant of the 3CH, the 4CH, is an innovative aspect of this study. My full review is included as a Supplement.
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AC2: 'Reply on RC2', Llorenç Lledó, 21 Jun 2024
We want to thank the reviewer for taking the time to read the manuscript and suggesting several aspects that required improvement. In the revised manuscript we have clarified the novelty of our method by putting it in context with existing multiple-collocation techniques. We have also made several changes in the manuscript that we believe improved its clarity and quality.
We attach the responses as a pdf document. The responses are in blue following each reviewer's comment.
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AC2: 'Reply on RC2', Llorenç Lledó, 21 Jun 2024
Interactive computing environment
Jupyter notebook containing all the analyses Llorenç Lledó https://github.com/lluritu/4CH_precip_comparison/
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