Yiwen Mei

Error Analysis of Satellite Precipitation Products in Mountainous Basins

Accuratequantitative precipitationestimationover mountainous basins is of great importancebecause of their susceptibility to hazards such as flash floods, shallow landslides, and debris flows, triggered by heavy precipitation events (HPEs). In situ observations over mountainous areas are limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for hydrological applications. In this study, four widely used satellite-based precipitation products [Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42, version 7 (3B42V7), and in near‐real time (3B42-RT); Climate Prediction Center (CPC) morphing technique (CMORPH); and PrecipitationEstimationfromRemotelySensedImagery UsingArtificialNeural Networks(PERSIANN)] are evaluated with respect to their performance in capturing the properties of HPEs over different basin scales. Evaluation is carried out over the upper Adige River basin (eastern Italian Alps) for an 8-yr period (2003‐10). Basin-averaged rainfall derived from a dense rain gauge network in the region is used as a reference. Satellite precipitation error analysis is performed for warm (May‐August) and cold (September‐December) season months as well as for different quantile ranges of basin-averaged precipitation accumulations. Three error metrics and a score system are introduced to quantify the performances of the various satellite products. Overall, no single precipitation product can be considered ideal for detecting and quantifying HPE. Results show better consistency between gauges and the two 3B42 products, particularly during warm season months that are associated with high-intensity convective events. All satellite products are shown to have a magnitude-dependent error ranging from overestimation at low precipitation regimes to underestimation at high precipitation accumulations; this effect is more pronounced in the CMORPH and PERSIANN products.

Evaluating Satellite Precipitation Error Propagation in Runoff Simulations of Mountainous Basins

AbstractThis study investigates the error characteristics of six quasi-global satellite precipitation products and their error propagation in flow simulations for a range of mountainous basin scales (255–6967 km2) and two different periods (May–August and September–November) in northeast Italy. Statistics describing the systematic and random error, the temporal similarity, and error ratios between precipitation and runoff are presented. Overall, strong over-/underestimation associated with the near-real-time 3B42/Climate Prediction Center morphing technique (CMORPH) products is shown. Results suggest positive correlation between the systematic error and basin elevation. Performance evaluation of flow simulations yields a higher degree of consistency for the moderate to large basin scales and the May–August period. Gauge adjustment for the different satellite products is shown to moderate their error magnitude and increase their correlation with reference precipitation and streamflow simulations. Moreover,...

Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape). Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

A global distributed basin morphometric dataset

Basin morphometry is vital information for relating storms to hydrologic hazards, such as landslides and floods. In this paper we present the first comprehensive global dataset of distributed basin morphometry at 30 arc seconds resolution. The dataset includes nine prime morphometric variables; in addition we present formulas for generating twenty-one additional morphometric variables based on combination of the prime variables. The dataset can aid different applications including studies of land-atmosphere interaction, and modelling of floods and droughts for sustainable water management. The validity of the dataset has been consolidated by successfully repeating the Hack’s law.

Using high-resolution satellite precipitation for flood frequency analysis: case study over the Connecticut River Basin

This study evaluates the feasibility of using satellite precipitation datasets in flood frequency analysis based on the accuracy of different return period flows derived using a hydrological model driven with satellite and ground-based reference rainfall fields over the Connecticut River Basin. Four quasi-global satellite products (TRMM-3B42V7, TRMM-3B42RT, CMORPH, and PERSIANN) at 3-h/0.25° resolution and the National Weather Service (Stage IV) gauge-adjusted radar rainfall dataset (representing the reference rainfall) are integrated in this study, with the Coupled Routing and Excess Storage distributed hydrological model to simulate annual peak flows during warm season (May–November) months. The log-Pearson type III frequency distribution applied to an 11-year record of annual peak flow data is used to derive different return period flows. Evaluation against the Stage IV-driven simulations shows that the TRMM-3B42V7 product has the highest correlation and lowest bias in terms of the derived annual maxima flows compared to the other satellite products. In terms of the different return period flood frequency curves, the various satellite product-based results well-represent the variability across the different basins depicted in the reference precipitation-driven simulations. With the increasing record length of high-resolution satellite products, results from this paper can motivate future studies over basins lacking adequate ground-based records to support flood frequency analyses.

Reply to “Comments on ‘Error Analysis of Satellite Precipitation Products in Mountainous Basins’”

Evaluation on the accuracy of global satellite precipitation products is of great interest to the hydrologic community. Recently, Mei et al. (2014) evaluated the performance of four widely used satellite precipitation products over an Alpine basin in northeastern Italy. Yong (2015) commented on the representativeness of these results by comparing their findings to other studies, giving particular emphasis on a similar evaluation study over mainland China. The four quasi-global satellite products involved in Mei et al. (2014) are the TMPA 3B42 in real time [3B42-RT; calibrated according to the climatology of TMPA 3B42, version 6 (3B42V6); hereafter named 3B42-RT-CCA]; TMPA 3B42, version 7 (3B42-V7); Climate Prediction Center (CPC) morphing technique (CMORPH); and PERSIANN [see section 2b in Mei et al. (2014) for descriptions]. Yong (2015) states that selection of real-time products [e.g., QMORPH (a variation on CMORPH), Global Satellite Mapping of Precipitation in near–real time (GSMaP_ NRT), and the uncalibrated 3B42-RT (hereafter named 3B42-RT-UC)] would have been more appropriate for evaluating the potential of satellite precipitation estimation in real-time hydrological applications. We agree that the near-real-time satellite datasets can be of great interest to the hydrologic community focusing on flood hazard warnings. However, we believe that evaluation of post-real-time satellite precipitation products provides evidence on their potential use for a number of water resource applications (e.g., water budget calculations, derivation of precipitation intensity–frequency–duration curves, and derivation of rainfall thresholds for hydrologic hazard warning systems), which is of interest to the hydrologic community as well. Moreover, Mei et al. (2014) presented a comparison of a near-real-time (i.e., the 3B42-RT-CCA) product with the corresponding gauge-adjusted (3B42-V7) product, which provides an assessment on the effectiveness of current climatological and post-real-time adjustment techniques in satellite precipitation estimation. The comments in Yong (2015) focused particularly on the results reported in Table 4 of Mei et al. (2014) and specifically regarding the effect that climatological gauge adjustment may have on the random error of satellite estimates for moderate to high rainfall rates. Yong (2015) states that ‘‘[b]ecause of the dynamic balance between systematic and random errors caused by the CCA, we speculate that the RMSE values of uncalibrated 3B42-RT might also be lower than 3B42-RT in this Italian basin.’’ To address this point, we have expanded the analysis presented in Table 4 of Mei et al. (2014) to include the 3B42-RT-UC product and contrasted its error characteristics to the corresponding error properties of the climatological-mean-adjusted (3B42-RT-CCA) and postreal-time (3B42-V7) products. Results shown in Table 1 confirm the quoted statement by Yong (2015); namely, 3B42-RT-UC is characterized with a lower degree of random error than that of the 3B42-RT-CCA at event scale. Moreover, the cold season error statistics [RMSE and correlation coefficient (CC)] of 3B42-RT-UC exhibit improvements over both 3B42-V7 and 3B42-RT-CCA. Yong (2015) further commented on the results and justification we gave regarding the higher cold season correlation coefficient values in 3B42-RT-CCA relative to 3B42-V7.Mei et al. (2014) stated that this is due to the Corresponding author address: Emmanouil N. Anagnostou, CEE, University of Connecticut, 261 Glenbrook Rd., Unit 3037, Storrs, CT 06269. E-mail: manos@engr.uconn.edu JUNE 2015 CORRES PONDENCE 1445

A Comprehensive Database of Flood Events in the Contiguous United States from 2002 to 2013

AbstractNotwithstanding the rich record of hydrometric observations compiled by the U.S. Geological Survey (USGS) across the contiguous United States (CONUS), flood event catalogs are sparse and incomplete. Available databases or inventories are mostly survey- or report-based, impact oriented, or limited to flash floods. These data do not represent the full range of flood events occurring in CONUS in terms of geographical locations, severity, triggering weather, or basin morphometry. This study describes a comprehensive dataset consisting of more than half a million flood events extracted from 6,301 USGS flow records and radar-rainfall fields from 2002 to 2013, using the characteristic point method. The database features event duration; first- (mass center) and second- (spreading) order moments of both precipitation and flow, flow peak and percentile, event runoff coefficient, base flow, and information on the basin geomorphology. It can support flood modeling, geomorphological and geophysical impact stud...