On the role of serial correlation and field significance in detecting changes in extreme precipitation frequency

Using the methods of literature review, regression analysis and moving average, this paper selects the daily precipitation of Changsha and Chengde from 1951 to 1986 as samples, and analyzes the average precipitation, precipitation frequency, precipitation intensity, extreme precipitation time and other indicators of Changsha and Chengde from the perspective of interannual and seasonal changes Trends. The researches show that: the average precipitation of Changsha in the 36 years is 1151.2mm, spring is the wet season, autumn and winter are the dry seasons, and the maximum average precipitation is in spring; the average annual precipitation, precipitation frequency in spring, summer and winter, annual precipitation frequency, annual precipitation intensity and extreme precipitation events show a decreasing trend. The average annual precipitation of Chengde city is 454.1 mm, wet season in summer and dry season in spring, autumn and winter; the average annual precipitation, precipitation in four seasons, annual precipitation frequency, precipitation frequency in spring, autumn and winter, annual precipitation intensity and extreme precipitation events show a decreasing trend, while the precipitation frequency in summer shows an increasing trend. The study of regional climate change based on the time series data of this stage is of great significance to comprehensively understand the law of regional climate change and predict the future trend of climate change.

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Uncertainty in the future change of extreme precipitation over the Rhine basin: the role of internal climate variability

Climate Dynamics ◽

10.1007/s00382-014-2312-4 ◽

2014 ◽

Vol 44 (7-8) ◽

pp. 1789-1800 ◽

Cited By ~ 13

Author(s):

S. C. van Pelt ◽

J. J. Beersma ◽

T. A. Buishand ◽

B. J. J. M. van den Hurk ◽

J. Schellekens

Keyword(s):

Climate Variability ◽

Extreme Precipitation ◽

Future Change ◽

Internal Climate Variability ◽

Rhine Basin ◽

The Future

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Climate prediction of summer extreme precipitation frequency in the Yangtze River valley based on sea surface temperature in the southern Indian Ocean and ice concentration in the Beaufort Sea

International Journal of Climatology ◽

10.1002/joc.6446 ◽

2019 ◽

Vol 40 (9) ◽

pp. 4117-4130

Author(s):

Baoqiang Tian ◽

Ke Fan

Keyword(s):

Indian Ocean ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Extreme Precipitation ◽

Yangtze River ◽

Yangtze River Valley ◽

Sea Surface ◽

The Yangtze River ◽

Precipitation Frequency ◽

Ice Concentration

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Precipitation Extremes Estimated by GPCP and TRMM: ENSO Relationships

Journal of Hydrometeorology ◽

10.1175/jhm601.1 ◽

2007 ◽

Vol 8 (4) ◽

pp. 678-689 ◽

Cited By ~ 58

Author(s):

Scott Curtis ◽

Ahmed Salahuddin ◽

Robert F. Adler ◽

George J. Huffman ◽

Guojun Gu ◽

...

Keyword(s):

El Niño ◽

Extreme Precipitation ◽

Daily Precipitation ◽

El Nino ◽

Southern Oscillation ◽

Global Precipitation Climatology Project ◽

El Niño Southern Oscillation ◽

El Nino Southern Oscillation ◽

Precipitation Frequency ◽

Rain Rates

Abstract Global monthly and daily precipitation extremes are examined in relation to the El Niño–Southern Oscillation phenomenon. For each month around the annual cycle and in each 2.5° grid block, extremes in the Global Precipitation Climatology Project dataset are defined as the top five (wet) and bottom five (dry) mean rain rates from 1979 to 2004. Over the tropical oceans El Niño–Southern Oscillation events result in a spatial redistribution and overall increase in extremes. Restricting the analysis to land shows that El Niño is associated with an increase in frequency of dry extremes and a decrease in wet extremes resulting in no change in net extreme months. During La Niña an increase in frequency of dry extremes and no change in wet extremes are observed. Thus, because of the juxtaposition of tropical land areas with the ascending branches of the global Walker Circulation, El Niño (La Niña) contributes to generally dry (wet) conditions in these land areas. In addition, daily rain rates computed from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis are used to define extreme precipitation frequency locally as the number of days within a given season that exceeded the 95th percentile of daily rainfall for all seasons (1998–2005). During this period, the significant relationships between extreme daily precipitation frequency and Niño-3.4 in the Tropics are spatially similar to the significant relationships between seasonal mean rainfall and Niño-3.4. However, to address the shortness of the record extreme daily precipitation frequency is also related to seasonal rainfall for the purpose of identifying regions where positive seasonal rainfall anomalies can be used as proxies for extreme events. Finally, the longer (1979–2005) but coarser Global Precipitation Climatology Project analysis is reexamined to pinpoint regions likely to experience an increase in extreme precipitation during El Niño–Southern Oscillation events. Given the significance of El Niño–Southern Oscillation predictions, this information will enable the efficient use of resources in preparing for and mitigating the adverse effects of extreme precipitation.

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Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies

Water ◽

10.3390/w11051032 ◽

2019 ◽

Vol 11 (5) ◽

pp. 1032 ◽

Cited By ~ 2

Author(s):

Ariel Wang ◽

Francina Dominguez ◽

Arthur Schmidt

Keyword(s):

Extreme Precipitation ◽

General Circulation ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Change ◽

Regional Climate Models ◽

General Circulation Models ◽

Precipitation Frequency ◽

Spatio Temporal ◽

Climate Change Assessment

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.

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What is the role of green stormwater infrastructure in managing extreme precipitation events?

Sustainable and Resilient Infrastructure ◽

10.1080/23789689.2020.1754625 ◽

2020 ◽

pp. 1-10

Author(s):

Lauren E. McPhillips ◽

Marissa Matsler ◽

Bernice R. Rosenzweig ◽

Yeowon Kim

Keyword(s):

Extreme Precipitation ◽

Extreme Precipitation Events ◽

Green Stormwater Infrastructure ◽

Precipitation Events

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Predicting Accruals Based on Cash-Flow Properties

The Accounting Review ◽

10.2308/accr-52001 ◽

2018 ◽

Vol 93 (5) ◽

pp. 165-186 ◽

Cited By ~ 1

Author(s):

Richard M. Frankel ◽

Yan Sun

Keyword(s):

Cash Flow ◽

Serial Correlation ◽

Cycle Length ◽

Explanatory Power ◽

Cash Flows ◽

Flow Properties ◽

Operating Cycle ◽

Economic Role ◽

Flow Changes

ABSTRACT Our goal is to understand the extent to which cash-flow properties explain accruals. Using the Dechow, Kothari, and Watts (1998) model, we derive a negative relation between accruals and cash-flow changes, and show that the strength of the relation is linked to negative serial correlation in cash-flow changes. Dechow et al. (1998) also suggest that the strength of the relation between accruals and revenue changes relates to operating cycle length. Prior accrual models have not incorporated these theoretical relations. We show that incorporating cash-flow changes, serial correlation in cash-flow changes, and operating cycle length increases explanatory power of all accrual models considered (i.e., Jones 1991; Ball and Shivakumar 2006; McNichols 2002; Jeter and Shivakumar 1999). We find that incorporating these variables in accrual models also improves specification and power, aids detection of earnings management in AAER firms, and produces a nondiscretionary accrual estimate that better predicts future cash flows and earnings. These results suggest the importance of considering the economic role of accruals when predicting accruals.

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