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![Page 1: Large-scale predictors of extreme precipitation in the coastal natural economic zones of European part of Russia Natural risk assessment laboratory faculty.](https://reader035.fdocuments.us/reader035/viewer/2022062806/5697bf931a28abf838c8f810/html5/thumbnails/1.jpg)
Large-scale predictors of extreme precipitation in Large-scale predictors of extreme precipitation in the coastal natural economic zones of European the coastal natural economic zones of European
part of Russiapart of Russia
Natural risk assessment laboratory faculty of geography, Moscow State University,
Moscow, Russia
Gushchina Daria, Matveeva Tatiana
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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 Problem :
Estimate the probability of extreme rainfall using indirect indicators
MotivationMotivation
!!
Models fairly reproduce extreme rainfall
Possible Possible solutionsolution
Important: indicators may include the characteristics reliably reproduced be the GCMs (air temperature, sea level pressure, geopotential heights)
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ObjectivesObjectives
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
PurposePurpose
Assess the change of extreme precipitation occurrence in the warming climate using large-scale synoptical indicators
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Coastal regionsCoastal regions
Pechora region
Murmansk region
Black Sea Coast
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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
DataData
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Complex spatial structure of rainfall fields Lack of uniform definition of the term “extreme precipitation”
The number of days exceeding the threshold value
(R10, R20)
Precipitation amount larger than 95th or 99th percentile of their distribution
(R95p), (R99p)
Maximal value for the year or the season
(RX1day, RX5day)
The duration of periodswhen precipitation is larger than the
threshold (CDD, CWD)
The measure of extreme precipitation
Major problems in the study of extreme precipitation
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Our approach Criteria of the dangerous hydrometeorological phenomena used by
the Russian Hydrometeorological service
Different criteria for solid and liquid precipitation
Phenomenon Rainfall Period
Very heavy rain ≥50 mm 12 hours
Very heavy snow ≥20 mm 12 hours
ProblemProblem:
Method to determineprecipitation types
It is impossible to use the uniform threshold
Possible Possible solutionsolution
- partial thickness methods
If < 1540 м, < 1310 м
Layer temperature is below freezing
Snow falls
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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
Algorithm for extreme precipitation threshold definition in the model
Need to coincide the model and observation data
The model is not capable to simulated the real local rainfall extremes
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observation
modelmodel
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Precipitation in
observation
Precipitation in model data
Murmansk
region
Pechora
regionBlack Sea Coast
50 mm
(rain)
Warm period Summer Winter
32.2 mm 30.4 mm 28.5 mm 36.3 mm
20 mm
(snow)
Cold period Winter
19.4 mm 18.2 mm 16.2 mm
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
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> 90% of the variability of the pressure field
EOF-analysis of sea level pressure for the extreme precipitation daysThe structure of baric field
Evaluation of extreme precipitation indicators
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Evaluation of extreme precipitation indicatorsThe structure of baric field
win
ter
sum
mer
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Baric structure is not a sufficient indicator of extreme precipitation!!Precipitation
Frontal Non-frontal
Indicators include moisture characteristics,
fairly simulated by the climate models
Indicators of frontal zone
For the moment we don't consider these extreme
precipitation
Use of this threshold indicator is reliable
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
For the coastal zone of the Arctic – 30-40%
Requirement of other indicator of frontal zone
Evaluation of extreme precipitation indicators
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. 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
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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
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)
Murmansk Pechora
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The threshold for the frontal parameter ψ
threshold ψ=16
Daily precipitation, mm
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The problem of "dry" fronts on the Arctic coast
An additional constraint on the temperature
Large-scale Indicators of extreme precipitation
structure of the pressure field+
the horizontal temperature gradient
Black Sea coast Arctic coastal region
structure of the pressure field+
the frontal parameter ψ+
constraint on the temperature
Air temperatureat 2 mat 850 hPa
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Model validation
NCEP/NCAR reanalysis
Climate model GFDL-ESM2M
The model successfully reproduces the main pressure patterns associated to the extreme precipitation events
The structure of the pressure field
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Validation of the modelFrontal parameter ψ
The maximum of ψ in GFDL are located in the region of extreme precipitation
The model successfully reproduces the frontal parameter ψ maximum and distribution for the days with extreme precipitation
threshold ψ=16
Daily precipitation, mm
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Occurrence of indicators of extreme precipitation
Region 1971-1990 2046-2065 2081-2100 Conditions
Black Sea Coast
Winter
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
139 136 (-2.2%) 145 (+4.3%) Structure of the pressure field +
Frontal zone+
Constraint of the temperaturePechora
region118 132(+11.9%) 123 (+4.2%)
Warm season
Murmansk region
68 65 (-4.4%) 67 (-1.4%) Structure of the pressure field +
Frontal zonePechora region
81 83 (+2.5) 80 (-1.2%)
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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.
Main achievements
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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)
Discussion and perspectives
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Thank you for your attention
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Additional
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Интенсивная ВФЗ в дни в экстремальными осадкамиЗима
Лето
Холодный период
Тёплый период
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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.
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Кавказ
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Холодный период Арктика
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Теплый период Арктика
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ЧПК
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Регион
Период Регион Мурманска Регион Печоры
Холодный период 39% 37%
Теплый период 26% 24%
Повторяемость случаев превышения порогового значения горизонтального
градиента температуры на 850 гПа в дни с экстремальными осадками
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1971-1990 2046-2065 2081-2100 Условия
Зима
752 762 (+1.3%) 724 (-3.7%) Барическое поле
562 546 (-2.8%) 559 (-0.5%) Фронтальная зона
173 169 (-2.3%) 175 (+1.1%)Барическое поле
+ Фронтальная зона
Лето
1102 1086 (-1.5%) 1093 (-0.8%) Барическое поле
415 433 (+4.3%) 442 (+6.5%) Фронтальная зона
122 115 (-5.7%) 129 (+5.7)Барическое поле
+ Фронтальная зона
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1971-1990 2046-2065 2081-2100 Условия
Холодный сезон
985 996 (+1.1%) 1072 (+8.8%) Барическое поле
379 353 (-6.8%) 357 (-5.8%) Фронтальная зона
139 136 (-2.2%) 145 (+4.3%)
Барическое поле+
Фронтальная зона +
Ограничение по температуре
Теплый сезон
654 611 (-6.6%) 646 (-1.2%) Барическое поле
203 189 (-6.9%) 194 (-4.4%) Фронтальная зона
68 65 (-4.4%) 67 (-1.4%)Барическое поле
+ Фронтальная зона
1971-1990 2046-2065 2081-2100 Условия
Холодный сезон
852 820 (-3.8%) 874 (+2.6%) Барическое поле
332 346 (+4.2%) 319 (-3.6%) Фронтальная зона
118 132 (+11.9%) 123 (+4.2%)
Барическое поле+
Фронтальная зона +
Ограничение по температуре
Теплый сезон
591 604 (+2.1%) 608 (+2.9%) Барическое поле
173 181 (+4.6%) 179 (+3.5%) Фронтальная зона
81 83 (+2.5) 80 (-1.2%)Барическое поле
+Фронтальная зона
Мурманск
Печора