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  • 1
    Online Resource
    Online Resource
    IWA Publishing ; 2015
    In:  Journal of Hydroinformatics Vol. 17, No. 3 ( 2015-05-01), p. 422-445
    In: Journal of Hydroinformatics, IWA Publishing, Vol. 17, No. 3 ( 2015-05-01), p. 422-445
    Abstract: The improvement of precipitation estimation with the use of radar-raingauge rainfall merging techniques is influenced by several factors, such as topography, storm types, raingauge network density for adjustment, data quality and the rainfall accumulation time. However, the influence of the raingauge network configuration on the performance of radar-raingauge merging methods is often ignored. The aim of this study is to compare and evaluate the performance of different radar-raingauge merging methods on various densities of raingauge network and raingauge network configurations. The analysis of the effect of the raingauge network density shows that the performance of Kriging merging methods increases with the increase of raingauge network density. The results also showed that the influence of raingauge network configuration on the spatial distribution of precipitation of the merged products is relatively smaller for the Kriging with radar-based error correction (KRE) and Kriging with external drift (KED) methods than for the ordinary Kriging method. This indicates that the inclusion of radar data in the KRE and KED methods helps to maintain the spatial distribution of precipitation on an hourly timescale. According to the statistical performance indicators and visual inspection of the merged rainfall fields, the KED outperforms the other radar-raingauge merging techniques, regardless of raingauge network density and configuration.
    Type of Medium: Online Resource
    ISSN: 1464-7141 , 1465-1734
    Language: English
    Publisher: IWA Publishing
    Publication Date: 2015
    detail.hit.zdb_id: 2020923-X
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  • 2
    Online Resource
    Online Resource
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 8 ( 2022-04-18), p. 1945-
    In: Remote Sensing, MDPI AG, Vol. 14, No. 8 ( 2022-04-18), p. 1945-
    Abstract: The spatial and temporal characteristics of precipitation and floods during typhoons in Guangdong province were examined by using TRMM TMPA 3B42 precipitation data and the Dominant River Routing Integrated with VIC Environment (DRIVE) model outputs for the period 1998–2019. The evaluations based on gauge-measured and model-simulated streamflow show the reliability of the DRIVE model. The typhoon tracks are divided into five categories for those that landed on or influenced Guangdong province. Generally, the spatial distribution of precipitation and floods differ for different typhoon tracks. Precipitation has a similar spatial distribution to flood duration (FD) but is substantially different from flood intensity (FI). The average precipitation over Guangdong province usually reaches its peak at the landing time of typhoons, while the average FD and FI reach their peaks several hours later than precipitation peak. The lagged correlations between precipitation and FD/FI are hence always higher than their simultaneous correlations.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2015
    In:  Hydrological Processes Vol. 29, No. 7 ( 2015-03-30), p. 1704-1716
    In: Hydrological Processes, Wiley, Vol. 29, No. 7 ( 2015-03-30), p. 1704-1716
    Abstract: Radar‐based estimates of rainfall are affected by many sources of uncertainties, which would propagate through the hydrological model when radar rainfall estimates are used as input or initial conditions. An elegant solution to quantify these uncertainties is to model the empirical relationship between radar measurements and rain gauge observations (as the ‘ground reference’). However, most current studies only use a fixed and uniform model to represent the uncertainty of radar rainfall, without consideration of its variation under different synoptic regimes. Wind is such a typical weather factor, as it not only induces error in rain gauge measurements but also causes the raindrops observed by weather radar to drift when they reach the ground. For this reason, as a first attempt, this study introduces the wind field into the uncertainty model and designs the radar rainfall uncertainty model under different wind conditions. We separate the original dataset into three subsamples according to wind speed, which are named as WDI (0–2 m/s), WDII (2–4 m/s) and WDIII ( 〉 4 m/s). The multivariate distributed ensemble generator is introduced and established for each subsample. Thirty typical events (10 at each wind range) are selected to explore the behaviours of uncertainty under different wind ranges. In each time step, 500 ensemble members are generated, and the values of 5th to 95th percentile values are used to produce the uncertainty bands. Two basic features of uncertainty bands, namely dispersion and ensemble bias, increase significantly with the growth of wind speed, demonstrating that wind speed plays a considerable role in influencing the behaviour of the uncertainty band. On the basis of these pieces of evidence, we conclude that the radar rainfall uncertainty model established under different wind conditions should be more realistic in representing the radar rainfall uncertainty. This study is only a start in incorporating synoptic regimes into rainfall uncertainty analysis, and a great deal of more effort is still needed to build a realistic and comprehensive uncertainty model for radar rainfall data. Copyright © 2014 John Wiley & Sons, Ltd.
    Type of Medium: Online Resource
    ISSN: 0885-6087 , 1099-1085
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 1479953-4
    SSG: 14
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  • 4
    Online Resource
    Online Resource
    American Meteorological Society ; 2020
    In:  Journal of Climate Vol. 33, No. 8 ( 2020-04-15), p. 3289-3305
    In: Journal of Climate, American Meteorological Society, Vol. 33, No. 8 ( 2020-04-15), p. 3289-3305
    Abstract: Spatial and temporal variations of global floods during the TRMM period (1998–2013) are explored by means of the outputs of the Dominant River Routing Integrated with VIC Environment model (DRIVE) driven by the precipitation rates from the TRMM Multisatellite Precipitation Analysis (TMPA). Climatological and seasonal mean features of floods including frequency (FF), duration (FD), and mean and total intensity (FI and FTI) are examined and further compared to those for a variety of precipitation indices derived from the daily TMPA rain rates. In general, floods and precipitation manifest similar spatial distributions, confirming that more precipitation (both amount and frequency) often indicates higher probability of floods. However, different flood indices can be associated with different precipitation characteristics with a highly region-dependent distribution. FF and FD tend to be more related to daily precipitation frequency globally, especially the mid- to high-end precipitation frequencies (F10, F25, F50). However, FI and FTI tend to be more associated with the mean volume/magnitude of those (extreme) daily precipitation events (Pr10 and Pr25). Nonetheless, daily precipitation intensity except the very high end one (R50) generally has a relatively weak effect on floods. The precipitation–flood relations at the 10 large regions are further examined, providing an improved understanding of precipitation-related flood-generating mechanisms in different locations. On the interannual time scale, El Niño–Southern Oscillation (ENSO) can significantly affect floods in many flood-prone zones. However, it is noted that even though the ENSO effect on floods is mostly through modulating various aspects of precipitation events, significant ENSO signals in precipitation cannot always translate to an effective, simultaneous impact on floods.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 5
    Online Resource
    Online Resource
    American Meteorological Society ; 2023
    In:  Journal of Hydrometeorology Vol. 24, No. 12 ( 2023-12), p. 2191-2205
    In: Journal of Hydrometeorology, American Meteorological Society, Vol. 24, No. 12 ( 2023-12), p. 2191-2205
    Abstract: Precipitation data are known to be the key driver of hydrological simulations. Hence, reliable quantitative precipitation estimates and forecasts are vital for accurate hydrological forecasting. Satellite-based precipitation estimates from Integrated Multi-satellitE Retrievals for GPM Early Run (IMERG-E) and forecasted precipitation from NASA’s Goddard Earth Observing System Forward Processing (GEOS-FP) have shown values in global flood nowcasting and forecasting. However, few studies have comprehensively evaluated their hydrological performance let alone explored the potential value of combining them. Therefore, this study undertakes a quasi-global evaluation of their utility in real-time hydrological monitoring and 1–5-day forecasting with the Dominant River Tracing-Routing Integrated with Variable Infiltration Capacity (VIC) Environment (DRIVE) model. The gauge-corrected IMERG Final Run precipitation estimates and corresponding hydrological simulation are used as the references. Results showed that the hit bias is the dominant error source of IMERG-E, while the false precipitation is more noticeable in GEOS-FP. In terms of hydrological performance, the GEOS-FP-driven model (DRIVE-FP) performance is close to the IMERG-E-driven model (DRIVE-E) performance on day 1, indicating that GEOS-FP could nicely fill the gap of nowcasting caused by the IMERG-E time latency. For longer lead-time forecasts, the bias tends to diminish in most regions, likely because the under- or overestimation in IMERG-E is generally offset by the distinct types of misestimation in GEOS-FP. The skillful initial hydrological conditions present outperformed forecasts in most regions, except for tropical areas where the accuracy of GEOS-FP prevails. Overall, this study provides a valuable view of the combined use of IMERG-E and GEOS-FP precipitation in the context of hydrological nowcasts and forecasts.
    Type of Medium: Online Resource
    ISSN: 1525-755X , 1525-7541
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2023
    detail.hit.zdb_id: 2042176-X
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  • 6
    In: Frontiers in Environmental Science, Frontiers Media SA, Vol. 8 ( 2020-11-25)
    Abstract: Understanding the driving factors for precipitation extremes matters for adaptation and mitigation measures against the changing hydrometeorological hazards in Yangtze River basin, a habitable area that provides water resources for domestic, farming, and industrial needs. However, the region is naturally subject to major floods linked to monsoonal heavy precipitation during May–September. This study aims to quantify anthropogenic influences on the changing risk of 2-week-long precipitation extremes such as the July 2019 extreme cases, as well as events of shorter durations, over the middle and lower reaches of Yangtze River basin (MLYRB). Precipitation extremes with different durations ranging from 1-day to 14-days maximum precipitation accumulations are investigated. Gridded daily precipitations based on nearly 2,400 meteorological stations across China are used to define maximum accumulated precipitation extremes over the MLYRB in July during 1961–2019. Attribution analysis is conducted by using the Met Office HadGEM3-GA6 modeling system, which comprises two sets of 525-member ensembles for 2019. One is forced with observed sea-surface temperatures (SSTs), sea-ice and all forcings, and the other is forced with preindustrialized SSTs and natural forcings only. The risk ratio between the exceedance probabilities estimated from all-forcing and natural-forcing simulations is calculated to quantify the anthropogenic contribution to the changing risks of the July 2019–like precipitation extremes. The results reveal that anthropogenic warming has reduced the likelihood of 2019-like 14-days heavy precipitation over the mid–lower reaches of the Yangtze River by 20%, but increased that of 2-days extremes by 30%.
    Type of Medium: Online Resource
    ISSN: 2296-665X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
    detail.hit.zdb_id: 2741535-1
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  • 7
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Bulletin of the American Meteorological Society Vol. 102, No. 6 ( 2021-06), p. E1133-E1149
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 102, No. 6 ( 2021-06), p. E1133-E1149
    Abstract: A reliable flood event inventory that reflects the occurrence and evolution of past floods is important for studies of flood hazards and risks, hydroclimatic extremes, and future flood projections. However, currently available flood inventories are based on single-sourced data and often neglect underreported or less impactful flood events. Furthermore, traditional archives store flood events only at sparse geographic points, which significantly limits their further applicability. Also, few publicly available archives contain all-inclusive records of potential natural flooded area over time. To tackle these challenges, we construct two types of multisourced flood event inventories (MFI) for all river basins across the contiguous United States covering the period 1998–2013 on daily and subcatchment scales, which is publicly available at http://flood.umd.edu/download/CONUS/ . These archives integrate flood information from in situ observations, remote sensing observations, hydrological model simulations, and five high-quality precipitation products. The first inventory (MFI-Actual) includes all actual floods that occurred in the presence of flood protection infrastructures, while the second, “natural (undefended)” inventory (MFI-Natural) reconstructs the possible “historical” floods without flood protection, which could be more directly influenced by climate variation. In the proposed two inventories, 2,755 and 4,661 flood events were estimated, respectively. MFI-Natural reconstructed 1,597 floods in ungauged basins, and recovered 608 extreme streamflow events in gauged subcatchments where floods would have happened if there were no flood protection. There is an average of four upstream dams located in these flood-recovered subcatchments, which indicates that modern flood defenses efficiently prevent significant flooding from extreme precipitation in many catchments over the country.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 8
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 103, No. 3 ( 2022-03), p. S83-S89
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 9
    Online Resource
    Online Resource
    American Meteorological Society ; 2022
    In:  Bulletin of the American Meteorological Society Vol. 103, No. 3 ( 2022-03), p. S61-S67
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 103, No. 3 ( 2022-03), p. S61-S67
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 10
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Bulletin of the American Meteorological Society Vol. 102, No. 1 ( 2021-01), p. S103-S109
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 102, No. 1 ( 2021-01), p. S103-S109
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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