extreme precipitation

Natural risk assessment laboratory
faculty of geography, Moscow State University,
Moscow, Russia
Large-scale predictors of extreme precipitation in
the coastal natural economic zones of European
part of Russia
Gushchina Daria, Matveeva Tatiana
Motivation
The special attention drawn to the extreme rainfall is caused by the
damage they present for the economics and society:
strongest floods, mud torrents, land slips, avalanches etc.
• the climate changes involve change of precipitation amount
• the trends of precipitation amounts are not always consistent with the
changes of extreme rainfall occurrence
Problem :
Possible
solution
!
Models fairly reproduce extreme rainfall
Estimate the probability of extreme rainfall using
indirect indicators
Important: indicators may include the characteristics reliably reproduced be the
GCMs (air temperature, sea level pressure, geopotential heights)
Purpose
Assess the change of extreme precipitation occurrence in the warming climate
using large-scale synoptical indicators
Objectives
 Step 1: Define the threshold of extreme precipitation for observation and
model data
 Step 2: Emerge the reliable indicators of large-scale extreme precipitation
 Step 3: Validate the climate model skill in simulation of these indicators
 Step 4: Assess the extreme precipitation risk change in a warming climate
Coastal regions
Murmansk region
Pechora region
Black Sea Coast
Data
 Archive of meteorological observation
 NCEP/NCAR Reanalysis
17 vertical levels, grid 2.5 ° x 2.5°
 Climate model GFDL-ESM2M (The Geophysical Fluid Dynamics Laboratory)
24 vertical levels, grid 2.5 ° x 2.0 °
Model participates in the Coupled Model Intercomparison Project Phase 5 (CMIP5).
Experiments used:
• For model validation – «historical» scenario (preindustrial concentration of CO2)
• For global warming condition –– RCP8.5 scenario
Major problems in the study of extreme precipitation
 Complex spatial structure of rainfall fields
 Lack of uniform definition of the term “extreme precipitation”
The measure of extreme precipitation
Maximal value for the year or
the season
(RX1day, RX5day)
Precipitation amount larger than 95th
or 99th percentile of their distribution
(R95p), (R99p)
The number of days
exceeding the threshold value
(R10, R20)
The duration of periods
when precipitation is larger than the
threshold (CDD, CWD)
Our approach
Criteria of the dangerous hydrometeorological phenomena used by
the Russian Hydrometeorological service
Phenomenon
Rainfall
Period
Very heavy rain
≥50 mm
12 hours
Very heavy snow
≥20 mm
12 hours
Problem:
Different criteria for solid and liquid precipitation
It is impossible to use the uniform threshold
Possible
solution
Method to determine
precipitation types
- partial thickness methods
If
< 1540 м,
< 1310 м
Layer temperature is below freezing
Snow falls
Algorithm for extreme precipitation threshold definition in the
model
The model is not capable to simulated the real local rainfall extremes
Need to coincide the model and observation data
Compose the representative data samples
(less than 10% missing data [Zolina et al., 2006])
Obtain the empirical functions of distribution
Find the theoretical approximation of empirical distribution
The best consistence - Weibull distribution
x – sample unit, F(x) – probability obtained by the empirical cumulative distribution
observation
model
Find the percentile corresponding to the threshold of 50 mm and 20 mm in the
theoretical distribution for observation
Define the threshold for model data as corresponding to this percentile
Precipitation in
observation
50 mm
(rain)
20 mm
(snow)
Precipitation in model data
Murmansk
Pechora
region
region
Warm period
32.2 mm
30.4 mm
Cold period
19.4 mm
18.2 mm
Black Sea Coast
Summer
Winter
28.5 mm
36.3 mm
Winter
16.2 mm
Evaluation of extreme precipitation indicators
The structure of baric field
EOF-analysis of sea level pressure for the extreme precipitation days
> 90% of the variability of the pressure field
Evaluation of extreme precipitation indicators
summer
winter
The structure of baric field
Evaluation of extreme precipitation indicators
! Baric structure is not a sufficient indicator of extreme precipitation
Precipitation
Frontal
Indicators of frontal zone
The simplest - the horizontal temperature gradient
at 850 hPa exceeding some threshold :
In the Black Sea coast – 70-80% of days with
extreme precipitation are associated to this
indicator
Use of this threshold indicator is reliable
For the coastal zone of the Arctic – 30-40%
Requirement of other indicator of frontal zone
Non-frontal
Indicators include
moisture characteristics,
fairly simulated by the
climate models
For the moment we don't
consider these extreme
precipitation
Indicators of frontal zone
.
(for the coastal zone of Arctic)
Most informative is frontal parameter F [Shakina et al.]
F=P+ψ
Includes surface temperature gradient
!
on the Arctic coastal zone strong
temperature contrast during the days
with extreme precipitation is not
observed
Calculation of the P parameter is not
informative
Includes gradient of equivalent thickness as
a measure of baroclinity
Frontal parameter ψ
The area where the gradient of baroclinity has an extreme in the direction
of a layer thickness gradient, should be identified as the front.
in the layer 850-1000 hPa, in conventional unit
Murmansk
Pechora
the majority of days with extreme precipitation are associated with ψ maximum
the ψ may serve as indicator of the frontal zone
(for the Arctic coastal region)
The threshold for the frontal parameter ψ
threshold ψ=16
Daily precipitation, mm
The problem of "dry" fronts on the Arctic coast
Air temperature
at 2 m
at 850 hPa
An additional constraint on the temperature
Large-scale Indicators of extreme precipitation
Black Sea coast
structure of the pressure field
+
the horizontal temperature gradient
Arctic coastal region
structure of the pressure field
+
the frontal parameter ψ
+
constraint on the temperature
Model validation
The structure of the pressure field
NCEP/NCAR reanalysis
Climate model GFDL-ESM2M
The model successfully reproduces the main pressure patterns
associated to the extreme precipitation events
Validation of the model
Frontal parameter ψ
The maximum of ψ in GFDL are located in the region of extreme precipitation
threshold ψ=16
Daily precipitation, mm
The model successfully reproduces the frontal parameter ψ maximum and distribution
for the days with extreme precipitation
Occurrence of indicators of extreme precipitation
Region
1971-1990
2046-2065
2081-2100
Conditions
Winter
Black Sea
Coast
173
169 (-2.3%)
175 (+1.1%)
Structure of the pressure field
+
Frontal zone
Summer
122
115 (-5.7%)
129 (+5.7%)
Structure of the pressure field
+
Frontal zone
Cold season
Murmansk
region
Pechora
region
139
136 (-2.2%)
145 (+4.3%)
Structure of the pressure field
+
Frontal zone
118
132(+11.9%)
123 (+4.2%)
+
Constraint of the temperature
Warm season
Murmansk
region
Pechora
region
68
65 (-4.4%)
67 (-1.4%)
81
83 (+2.5)
80 (-1.2%)
Structure of the pressure field
+
Frontal zone
Main achievements
 The threshold of extreme precipitation was defined for observation and
climate model GFDL-ESM2M for the Black Sea and Arctic coastal zones of
European Russia.
 The most appropriate indicators of large-scale precipitation extremes
were emerged, particularly: pressure field structure and intensity of frontal
zone
 The skill of the GFDL-ESM2M model in simulation the precipitation
extreme indicators are demonstrated
 The changes of precipitation extremes risks under global warming
condition are estimated :
we do not expect dramatic changes of the risk of extreme frontal
precipitation in the Black Sea Coast and the Arctic coastal region during XXI
century.
Discussion and perspectives
 The last results does not mean that we have no suspicion about
floods increasing in future as they may result from other
reason
 Our key message – we do not observe the drastic changes of
conditions favorable for precipitation extremes of frontal
genesis.
To extend our conclusions we need
 Include convective precipitation in the assessment
 pass from traditional approach to extreme measurements (days
with heavy rain) to duration of wet period (talk of Zolina Olga)
Thank you for your attention
Additional
Интенсивная ВФЗ в дни в экстремальными осадками
Зима
Холодный период
Лето
Тёплый период
Согласно этому алгоритму, тип осадков предлагается определять по данным о
высоте поверхностей 1000, 850 и 700 гПа:
•снег выпадает, если толщина слоя 850–700 гПа < 1540 м и толщина слоя 1000-850
< 1290 м;
•дождь выпадает, если толщина слоя 1000–850 гПа > 1310 м;
• смешанные осадки выпадают, если толщина слоя 850–700 гПа лежит в
интервале 1540–1560 м, а толщина слоя 1000–850 гПа – в интервале 1290-1310 м.
Кавказ
2w
N 0 ( w)  f
 2div (Q)
2
z
2
2
 u v v u 
g  ~ v g ~ u g 
   f  g g  g g 
Q1   

 0  y x x x 
 x z x z 
~
~
 u g v g v g u g 
g  u g  v g  




Q2   f 

     y x  y y 

y

z

y

z
0 



Холодный период Арктика
Теплый период Арктика
ЧПК
Повторяемость случаев превышения порогового значения горизонтального
градиента температуры на 850 гПа в дни с экстремальными осадками
Регион
Период
Регион Мурманска
Регион Печоры
Холодный период
39%
37%
Теплый период
26%
24%
1971-1990
2046-2065
2081-2100
Условия
Зима
752
762 (+1.3%)
724 (-3.7%)
562
546 (-2.8%)
559 (-0.5%)
173
169 (-2.3%)
175 (+1.1%)
Барическое поле
Фронтальная зона
Барическое поле
+
Фронтальная зона
Лето
1102
1086 (-1.5%)
1093 (-0.8%)
Барическое поле
415
433 (+4.3%)
442 (+6.5%)
Фронтальная зона
129 (+5.7)
Барическое поле
+
Фронтальная зона
122
115 (-5.7%)
1971-1990
2046-2065
Условия
2081-2100
Холодный сезон
985
996 (+1.1%)
1072 (+8.8%)
Барическое поле
379
353 (-6.8%)
357 (-5.8%)
Фронтальная зона
145 (+4.3%)
Барическое поле
+
Фронтальная зона
+
Ограничение по температуре
139
136 (-2.2%)
Мурманск
Теплый сезон
654
611 (-6.6%)
646 (-1.2%)
Барическое поле
203
189 (-6.9%)
194 (-4.4%)
Фронтальная зона
67 (-1.4%)
Барическое поле
+
Фронтальная зона
68
65 (-4.4%)
1971-1990
2046-2065
2081-2100
Условия
Холодный сезон
Печора
852
820 (-3.8%)
874 (+2.6%)
Барическое поле
332
346 (+4.2%)
319 (-3.6%)
Фронтальная зона
123 (+4.2%)
Барическое поле
+
Фронтальная зона
+
Ограничение по температуре
118
132 (+11.9%)
Теплый сезон
591
604 (+2.1%)
608 (+2.9%)
Барическое поле
173
181 (+4.6%)
179 (+3.5%)
Фронтальная зона
80 (-1.2%)
Барическое поле
+
Фронтальная зона
81
83 (+2.5)