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  • 1
    In: Environmental Research Letters, IOP Publishing, Vol. 14, No. 12 ( 2019-12-06), p. 125008-
    Type of Medium: Online Resource
    ISSN: 1748-9326
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2019
    detail.hit.zdb_id: 2255379-4
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  • 2
    Online Resource
    Online Resource
    IOP Publishing ; 2017
    In:  Environmental Research Letters Vol. 12, No. 7 ( 2017-07-01), p. 074025-
    In: Environmental Research Letters, IOP Publishing, Vol. 12, No. 7 ( 2017-07-01), p. 074025-
    Type of Medium: Online Resource
    ISSN: 1748-9326
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2017
    detail.hit.zdb_id: 2255379-4
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2021
    In:  International Journal of Climatology Vol. 41, No. 15 ( 2021-12), p. 6654-6673
    In: International Journal of Climatology, Wiley, Vol. 41, No. 15 ( 2021-12), p. 6654-6673
    Abstract: Australia experiences some of the world's most variable rainfall. Previous studies have mostly focused on understanding rainfall variability in terms of frequency and intensity. However, understanding the timing of when extreme rainfall occurs is crucial for seasonal prediction, although it largely remains unexplored. Here we investigate the timing of extreme rainfall in Australia and the spatial variability of this timing. This study examines how some of the large‐scale drivers, such as the El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO), determine the timing and interannual variability of the timing of extreme rainfall in Australia. Our results show that there is a clear spatial north–south delineation in the season when extreme rainfall occurs in Australia, shown by a contour diagonally extending roughly from 21°S in the west of Australia to 33°S in the east. North of this contour, extreme rainfall usually occurs in austral summer, with the smallest interannual variability in the timing of extreme rainfall in this region. In the south, extreme rainfall usually occurs in autumn/winter months; however, the timing is highly variable. In southeast Australia (SEA), extreme rainfall can fall at any time of the year, which makes seasonal prediction extremely challenging for this region. Both observation and reanalysis data show that the area where extreme rainfall occurs in summer extends further south during negative IPO years. We also find that IPO and ENSO phases, and the interaction between them, play significant roles in both determining the timing of extreme rainfall and constraining the interannual variability, especially in SEA. We focus on SEA for further analysis as this region shows the greatest shift in seasonality of extremes in response to large‐scale variability. We conclude that studying the relationship between rainfall and large‐scale drivers is important for verification and improvement of the seasonal prediction of extreme rainfall.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 4
    In: International Journal of Climatology, Wiley, Vol. 42, No. 12 ( 2022-10), p. 6537-6561
    Abstract: The ability of regional climate models (RCMs) to accurately simulate the current climate is increasingly important for impact assessments over Southeast Asia (SEA), identified as one of the world's most vulnerable regions to climate change. In this study, we evaluate the performance of a set of regional high‐resolution simulations from the Coordinated Regional Climate Downscaling Experiment‐SEA (CORDEX‐SEA) in simulating rainfall over the region. Simulations of the 1982–2005 seasonal mean climatology of daily precipitation and precipitation distribution over land are compared to observations from different sources (i.e., in situ‐based and satellite‐based). We also evaluate to what extent the precipitation distribution in RCMs is closer to observations than their associated forcing global climate models (GCMs). Observational estimates of precipitation over SEA have large uncertainties, making the model evaluations complicated. Despite these difficulties, our results highlight that RCMs can reproduce some complexities in the spatial distribution of seasonal rainfall but generally have a larger wet bias than GCMs. This is particularly true for the extremes in which RCMs show a large overestimation of rainfall intensity. There are some precipitation quantiles and grid points in which RCMs show limited reductions in biases compared to observations, but there is no consistency across all simulations and RCMs are generally further away from observations than their forcing GCMs. We find that greater intensity in RCMs over CORDEX‐SEA compared to their associated forcing GCMs is firstly associated with the increased supply of moisture from both local and large‐scale sources. Second, a widespread increase in convective precipitation is found across the region in RCMs. Our findings suggest that a model's ability to simulate precipitation over the region relies more on the RCM setup itself (e.g., parameterization scheme), rather than its forcing GCM. This should be considered when assessing the reliability of RCM precipitation simulations for future projections.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 5
    In: Earth System Science Data, Copernicus GmbH, Vol. 11, No. 3 ( 2019-07-10), p. 1017-1035
    Abstract: Abstract. We introduce the Frequent Rainfall Observations on GridS (FROGS) database (Roca et al., 2019). It is composed of gridded daily-precipitation products on a common 1∘×1∘ grid to ease intercomparison and assessment exercises. The database includes satellite, ground-based and reanalysis products. As most of the satellite products rely on rain gauges for calibration, unadjusted versions of satellite products are also provided where available. Each product is provided over its length of record and up to 2017 if available. Quasi-global, quasi-global land-only, ocean-only and tropical-only as well as regional products (over continental Africa and South America) are included. All products are provided on a common netCDF format that is compliant with Climate and Forecast (CF) Convention and Attribute Convention for Dataset Discovery (ACDD) standards. Preliminary investigations of this large ensemble indicate that while many features appear robust across the products, the characterization of precipitation extremes exhibits a large spread calling for careful selection of the products used for scientific applications. All datasets are freely available via an FTP server and identified thanks to the DOI: https://doi.org/10.14768/06337394-73A9-407C-9997-0E380DAC5598.
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2475469-9
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  • 6
    Online Resource
    Online Resource
    American Meteorological Society ; 2024
    In:  Journal of Climate Vol. 37, No. 4 ( 2024-02-15), p. 1089-1110
    In: Journal of Climate, American Meteorological Society, Vol. 37, No. 4 ( 2024-02-15), p. 1089-1110
    Abstract: Presently, there is no standardized framework or metrics identified to assess regional climate model precipitation output. Because of this, it can be difficult to make a one-to-one comparison of their performance between regions or studies, or against coarser-resolution global climate models. To address this, we introduce the first steps toward establishing a dynamic, yet standardized, benchmarking framework that can be used to assess model skill in simulating various characteristics of rainfall. Benchmarking differs from typical model evaluation in that it requires that performance expectations are set a priori. This framework has innumerable applications to underpin scientific studies that assess model performance, inform model development priorities, and aid stakeholder decision-making by providing a structured methodology to identify fit-for-purpose model simulations for climate risk assessments and adaptation strategies. While this framework can be applied to regional climate model simulations at any spatial domain, we demonstrate its effectiveness over Australia using high-resolution, 0.5° × 0.5° simulations from the CORDEX-Australasia ensemble. We provide recommendations for selecting metrics and pragmatic benchmarking thresholds depending on the application of the framework. This includes a top tier of minimum standard metrics to establish a minimum benchmarking standard for ongoing climate model assessment. We present multiple applications of the framework using feedback received from potential user communities and encourage the scientific and user community to build on this framework by tailoring benchmarks and incorporating additional metrics specific to their application. Significance Statement We introduce a standardized benchmarking framework for assessing the skill of regional climate models in simulating precipitation. This framework addresses the lack of a uniform approach in the scientific community and has diverse applications in scientific research, model development, and societal decision-making. We define a set of minimum standard metrics to underpin ongoing climate model assessments that quantify model skill in simulating fundamental characteristics of rainfall. We provide guidance for selecting metrics and defining benchmarking thresholds, demonstrated using multiple case studies over Australia. This framework has broad applications for numerous user communities and provides a structured methodology for the assessment of model performance.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2024
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 7
    Online Resource
    Online Resource
    American Meteorological Society ; 2018
    In:  Journal of Climate Vol. 31, No. 16 ( 2018-08-15), p. 6505-6525
    In: Journal of Climate, American Meteorological Society, Vol. 31, No. 16 ( 2018-08-15), p. 6505-6525
    Abstract: A warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2018
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 8
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2022
    In:  Earth's Future Vol. 10, No. 12 ( 2022-12)
    In: Earth's Future, American Geophysical Union (AGU), Vol. 10, No. 12 ( 2022-12)
    Abstract: We present projected seasonal changes in Coupled Model Intercomparison Project (CMIP6) total and extreme precipitation and show that they scale into the future CMIP6 multi‐model mean seasonal change is of same sign for total and extreme precipitation when there is high agreement between models This is found locally (at the grid cell scale) and regionally and is generally supported by the 29 individual models
    Type of Medium: Online Resource
    ISSN: 2328-4277 , 2328-4277
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2022
    detail.hit.zdb_id: 2746403-9
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  • 9
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2023
    In:  Climate Dynamics Vol. 61, No. 7-8 ( 2023-10), p. 3431-3452
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 61, No. 7-8 ( 2023-10), p. 3431-3452
    Abstract: This study focuses on future seasonal changes in daily precipitation using Regional Climate Models (RCMs) from the Coordinated Regional Climate Downscaling Experiments-Southeast Asia ensemble (CORDEX-SEA). Projections using this RCM ensemble generally show a larger inter-model spread in winter than in summer, with higher significance and model agreement in summer over most land areas. We evaluate how well the RCMs simulate climatological precipitation using two skill metrics. To extract reliable projections, two sub-ensembles of ‘better’ and ‘worse’ performing models are selected and their respective projections compared. We find projected intensification of summer precipitation over northern SEA, which is robust across RCMs. On the contrary, in the southern part of SEA, the ‘worse’ ensemble projects a significant and widespread decrease in summer rainfall intensity whereas a slight intensification is projected by the ‘better’ ensemble. Further exploration of inter-model differences in future changes reveals that these are mainly explained by changes in moisture supply from large-scale sources (i.e., moisture convergence) with enhanced effects from local sources (i.e., evapotranspiration). The ‘worse’ models project greater changes in atmospheric circulation compared with the ‘better’ models, which can explain part of the uncertainty in projections for daily precipitation over the CORDEX-SEA domain. Hence, our findings might help assess more reliable projections over the SEA region by selecting models based on a two-step model evaluation: the ability of models to simulate historical daily precipitation and their performance in reproducing key physical processes of the regional climate.
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 382992-3
    detail.hit.zdb_id: 1471747-5
    SSG: 16,13
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  • 10
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 125, No. 13 ( 2020-07-16)
    Abstract: Models generally agree on an intensification of precipitation extremes at higher spatial atmospheric resolution Observational uncertainties are substantial for precipitation extremes, which makes the evaluation of the models difficult Increasing spatial resolution alone is not sufficient to obtain a systematic improvement in the simulation of precipitation extremes
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2020
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
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