Intercomparison of annual precipitation indices and extremes over global land areas from in situ, space-based and reanalysis products

Alexander, Lisa V.; Bador, Margot; Roca, Rémy; Contractor, Steefan; Donat, Markus G.; Nguyen, Phuong‐Loan

doi:10.1088/1748-9326/ab79e2

Cited by 109 publications

(101 citation statements)

References 40 publications

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“…Compared to annual total daily precipitation, annual extreme precipitation shows higher interproduct spread. This is not sensitive to the use of Rx1day as Alexander et al (2020) find that other extreme precipitation indices (e.g. R99p) show similar levels of interproduct spread (see also Herold et al 2017 andMasunaga et al 2019).…”

Section: Resultsmentioning

confidence: 86%

Diverse estimates of annual maxima daily precipitation in 22 state-of-the-art quasi-global land observation datasets

Bador

Alexander

Contractor

et al. 2020

Environ. Res. Lett.

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Observational evidence of precipitation extremes is vital to better understand how these events might change in a future warmer climate. Over the terrestrial regions of a quasi-global domain, we assess the representation of annual maxima of daily precipitation (Rx1day) in 22 observational products gridded at 1°×1°resolution and clustered into four categories: station-based in situ, satellite observations with or without a correction to rain gauges, and reanalyses (5, 8, 4 and 5 datasets, respectively). We also evaluate the interproduct spread across the ensemble and within the four clusters, as a measure of observational uncertainty. We find that reanalyses present a heterogeneous representation of Rx1day in particular over the tropics, and their interproduct spread is the highest compared to any other cluster. Extreme precipitation in satellite data broadly compares well with in situ-based data. We find a general better agreement with in situ-based observations and less interproduct spread for the satellite products with a correction to rain gauges compared to the uncorrected products. Given the level of uncertainties associated with the estimation of Rx1day in the observations, none of the datasets can be thought of as the best estimate. Our recommendation is to avoid using reanalyses as observational evidence and to consider in situ and satellite data (the corrected version preferably) in an ensemble of products for a better estimation of precipitation extremes and their observational uncertainties. Based on this we choose a subsample of 10 datasets to reduce the interproduct spread in both the representation of Rx1day and its timing throughout the year, compared to all 22 datasets. We emphasize that the recommendations and selection of datasets given here may not be relevant for different precipitation indices, and other grid resolutions and time scales.

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Section: Resultsmentioning

confidence: 86%

Diverse estimates of annual maxima daily precipitation in 22 state-of-the-art quasi-global land observation datasets

Bador

Alexander

Contractor

et al. 2020

Environ. Res. Lett.

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“…The more recent generation of satellite-based gridded precipitation products 31 exhibits a robust thermodynamic scaling with surface temperature over tropical land, at a rate of change consistent with the theory 9 . This consistency suggests that these precipitation estimates are well-suited to document the complex, yet remarkably organized, nature of extreme precipitation in the tropics 32 . We therefore investigate here the statistical relationship between morphology of convective systems and extreme precipitation by pooling data from all over the tropics.…”

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confidence: 63%

“…This version indeed proposes quite a different representation of the tropical precipitation from earlier versions of this product. This is likely an artifact of the update of the Kriging algorithm used 42 . Note that the land sub-ensemble product agrees well with GPCC v1 distribution.…”

Section: Methodsmentioning

confidence: 99%

Extreme precipitation in the tropics is closely associated with long-lived convective systems

Roca

Fiolleau

2020

Commun Earth Environ

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Water and energy cycles are linked to global warming through the water vapor feedback and heavy precipitation events are expected to intensify as the climate warms. For the mid-latitudes, extreme precipitation theory has been successful in explaining the observations, however, studies of responses in the tropics have diverged. Here we present an analysis of satellite-derived observations of daily accumulated precipitation and of the characteristics of convective systems throughout the tropics to investigate the relationship between the organization of mesoscale convective systems and extreme precipitation in the tropics. We find that 40% of the days with more than 250 mm precipitation over land are associated with convective systems that last more than 24 hours, although those systems only represent 5% of mesoscale convective systems overall. We conclude that long-lived mesoscale convective systems that are well organized contribute disproportionally to extreme tropical precipitation.

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“…As well as daily gridded rainfall, we use 6-hourly rainfall observations from two sources: the new 12 km Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA; Su et al 2019) over 1990-2015 as well as that from all Bureau of Meteorology gauges with hourly rainfall data for at least 10 years between 1979 and 2015. While reanalyses offer the advantage of gridded rainfall that is more spatially and temporally consistent than the more sporadic gauge datasets, the reliance on model-generated rainfall can result in a range of errors including an overestimation of wet days and an underestimation of extreme rainfall (Alexander et al 2020). However, BARRA has been found to compare well with the AWAP reanalysis on a daily basis, particularly for extreme rainfall (Acharya et al 2019), and provides an additional source of subdaily information to supplement the gauge data.…”

Section: Rainfallmentioning

confidence: 99%

The contributions of fronts, lows and thunderstorms to southern Australian rainfall

et al. 2020

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A systematic analysis of the main weather types influencing southern Australian rainfall is presented for the period 1979–2015. This incorporates two multi-method datasets of cold fronts and low pressure systems, which indicate the more robust fronts and lows as distinguished from the weaker and less impactful events that are often indicated only by a single method. The front and low pressure system datasets are then combined with a dataset of environmental conditions associated with thunderstorms, as well as datasets of warm fronts and high pressure systems. The results demonstrate that these weather types collectively account for about 86% of days and more than 98% of rainfall in Australia south of 25° S. We also show how the key rain-bearing weather systems vary throughout the year and for different regions, with the co-occurrence of simultaneous lows, fronts and thunderstorm conditions particularly important during the spring and summer months in southeast Australia.

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Intercomparison of annual precipitation indices and extremes over global land areas from in situ, space-based and reanalysis products

Cited by 109 publications

References 40 publications

Diverse estimates of annual maxima daily precipitation in 22 state-of-the-art quasi-global land observation datasets

Diverse estimates of annual maxima daily precipitation in 22 state-of-the-art quasi-global land observation datasets

Extreme precipitation in the tropics is closely associated with long-lived convective systems

The contributions of fronts, lows and thunderstorms to southern Australian rainfall

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