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| Titel |
Climatological analysis of hail occurrence in China mainland using a Poisson regression model |
| VerfasserIn |
Xiang Ni, Qinghong Zhang |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250104995
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| Publikation (Nr.) |
 EGU/EGU2015-4441.pdf |
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| Zusammenfassung |
| Understanding the variability of hail events in the context of global climate change is a
challenge for researchers. Previous studies found significant decrease in annual hail
occurrence since 1980 in China, especially in the northern China. These changes are linked to
the variations in large-scale environmental conditions. This study explores the possible
connection between hail activities with some environmental parameters using a
Poisson regression model, and constructs a hail index to depict its climatology
during the period 1960-2012 over mainland China. The hail index takes the form
ofμ = exp(b /
x + log(n /
cos(φ)), in which n is the total number of stations in a
grid cell and φ isÂits associated latitude of the grid cell.x are the predictors and
b are the coefficients from the regression model. We use hail observations from
535 stations in China during the period and the NCEP monthly reanalysis in our
regression model. We calculate 25 large scale atmospheric parameters from the
reanalysis data as the predictors, and fit the monthly hail day count data. We perform the
regression for three regions: Tibet Plateau (Tibet), northern China (North), and southern
China (South), and show different seasonal variability of hail occurrence over these
regions. We found that the surface equivalent potential temperature (Surfte), Total
Totals (TT), and K index (K) are the best combination of predictors to formulate the
hail index. This index could capture the main climatological spatial distribution,
seasonal variation of hail day. The year-to-year variability fitting of observation and
model results is significant when annual values of hail day and predictors are applied
in this index. Based on a one-dimension hail growth model, surface water vapor
content and temperature profile in the lower troposphere are confirmed to have impact
on hail diameter at freezing level, which supports the use of surface equivalent
potential temperature as a predictor. Total Totals and K index are both related to
the lapse rate in lower troposphere, which contains information about the increase
in temperature below freezing level that promotes hail melting during descent. |
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