Mapping the world's tropical cyclone rainfall contribution over land using the TRMM Multi‐satellite Precipitation Analysis

Prat, Olivier P.; Nelson, Brian R.

doi:10.1002/wrcr.20527

Cited by 81 publications

(45 citation statements)

References 66 publications

(117 reference statements)

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“…Additionally, compared with the contributions between monthly and extreme rainfall, the contributions in extreme rainfall in inland are much lower than that in monthly rainfall at the same regions, suggesting impacts of TCs on extreme rainfall are greatly weakened in inland regions. Nevertheless, TCR amounts in our results are higher than those in other global studies (e.g., Prat & Nelson, 2013;Skok et al, 2013), possibly because of the differences between data types (satellite versus observations here), spatial resolution (more dense stations here), and record length (much longer here).…”

Section: Journal Of Geophysical Research: Atmospherescontrasting

confidence: 87%

Tropical Cyclonic Rainfall in China: Changing Properties, Seasonality, and Causes

Zhang

Lai

et al. 2018

JGR Atmospheres

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Using daily rainfall data from 1936 stations across China, this study investigated tropical cyclonic rainfall (TCR) changes during 1960–2014. The possible reasons behind TCR changes were examined using tracks and frequency of tropical cyclones (TCs) in both space and time. The highest annual TCR occur in coastal regions of east and southeast China (>500 mm/year). At monthly scale, August TCR can reach 150–250 mm in coastal regions. From the contribution viewpoint, TCR accounts for more than 40% of the monthly total rainfall and extreme rainfall events along the southeast coast of China. The contributions of TCR to the monthly rainfall amount decrease rapidly from coast to inland and are even faster for contributions of TCR to extreme rainfall. The distance inland from the shoreline with 250 km has been identified as the threshold, within that these contributions abruptly increase with decreasing distance from shoreline, and vice versa. In terms of extreme rainfall regimes, logistic and Poisson regressive techniques were used to identify the connections between TC‐induced extreme rainfall and El Niño–Southern Oscillation. Both these two regressions reveal that TC‐induced extreme rainfall tends to occur with higher frequency and magnitude in southeastern China (east and northeast coast of China) during La Niña (El Niño) years (El Niño). These consistent relations and remarkable spatial patterns can help to predict the occurrence of TC‐induced extreme rainfall events across eastern China.

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Section: Journal Of Geophysical Research: Atmospherescontrasting

confidence: 87%

Tropical Cyclonic Rainfall in China: Changing Properties, Seasonality, and Causes

Zhang

Lai

et al. 2018

JGR Atmospheres

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“…The contributions of TC precipitation to annual mean precipitation in most regions established in this study are comparable to those of Prat and Nelson [], a study which focused on TC precipitation. However, the signal in the North Indian Ocean looks weaker in this study (Figure ).…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have tried to estimate the relative amounts of precipitation contributed by each type of weather system. For example, the distributions of precipitation by TCs have been studied for various spatial scales: global [Jiang and Zipser, 2010;Jiang et al, 2011;Prat and Nelson, 2013], North Pacific [Rodgers et al, 2000;Kubota and Wang, 2009], North Atlantic [Rodgers et al, 2001], and smaller regions [Englehart and Douglas, 2001;Larson et al, 2005;Chen et al, 2010]. The distributions of extreme precipitation by TCs have also been assessed in some regions [e.g., Knight and Davis, 2009].…”

Section: Introductionmentioning

confidence: 99%

Relative contributions of weather systems to mean and extreme global precipitation

et al. 2017

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This study presents the first global estimates of the relative contributions of different weather systems, i.e., tropical cyclone, center and front of extratropical cyclone, and others, to mean and extreme precipitation. An objective method of classification of the precipitating weather systems was used with a reanalysis data set and a satellite‐based precipitation product for 2001–2010. Tropical cyclones, extratropical cyclones with associated fronts, and other weather systems contribute about 4%, 37%, and 59%, respectively, of the global (60°S–60°N) mean precipitation. The relative contributions of the weather systems were found to be different both in terms of the different classes of precipitation intensity and in terms of the different temporal scales of precipitation. Tropical cyclones and extratropical cyclones produced greater contributions to extreme hourly precipitation than to annual precipitation in most of the oceanic regions of their activity. The contributions of tropical cyclones to extreme precipitation showed clear peaks on temporal scales of 24–72 h. The contributions of extratropical cyclones showed less dependence on the temporal scale than tropical cyclones. Consideration of combinations of multiple weather systems revealed that in eastern North America and East Asia, substantial portions (22% and 19%, respectively) of the extreme 24 h precipitation related to tropical cyclones are contributed by the coexistence of tropical cyclones and fronts. However, such contributions were found rarely in other land regions. On most temporal scales, fronts at locations remote from the centers of extratropical cyclones were found to contribute to extreme precipitation as much as the centers of extratropical cyclones.

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“…It is worth noting that the T/W contribution is much higher than its occurrence in the coastal area of Texas (TX), North Carolina (NC), South Carolina (SC), Georgia (GA), and central/southern FL. This is likely due to large volume of precipitation associated with tropical cyclone activity [26].…”

Section: Methodsmentioning

confidence: 99%

Mapping the Precipitation Type Distribution Over the Contiguous United States Using NOAA/NSSL National Multi-Sensor Mosaic QPE

Chen

Zhang

Mullens

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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Understanding the Earth's energy cycle and water balance requires an understanding of the distribution of precipitation types and their total equivalent water budget estimation. The fine distribution of precipitation types over the contiguous United States (CONUS) is not yet well understood due to either unavailability or coarse resolution of previous satellite-and ground radar-based precipitation products that have difficulty in classifying precipitation. The newly available NOAA/National Severe Storms Laboratory ground radar network-based National Multi-Sensor Mosaic QPE (NMQ/Q2) System has provided precipitation rates and types at unprecedented high spatiotemporal resolution. Here, four years of 1 km/5 min observations derived from the NMQ are used to probe spatiotemporal distribution and characteristics of precipitation types (stratiform, convective, snow, tropical/warm (T/W), and hail) over CONUS, resulting in Manuscript

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Mapping the world's tropical cyclone rainfall contribution over land using the TRMM Multi‐satellite Precipitation Analysis

Cited by 81 publications

References 66 publications

Tropical Cyclonic Rainfall in China: Changing Properties, Seasonality, and Causes

Tropical Cyclonic Rainfall in China: Changing Properties, Seasonality, and Causes

Relative contributions of weather systems to mean and extreme global precipitation

Mapping the Precipitation Type Distribution Over the Contiguous United States Using NOAA/NSSL National Multi-Sensor Mosaic QPE

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