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

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)

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

Coastal regionsCoastal regions

Pechora region

Murmansk region

Black Sea Coast

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

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

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

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

observation

modelmodel

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

> 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

Evaluation of extreme precipitation indicatorsThe structure of baric field

win

ter

sum

mer

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

. 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

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

The threshold for the frontal parameter ψ

threshold ψ=16

Daily precipitation, mm

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

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

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

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%)

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

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

Thank you for your attention

Additional

Интенсивная ВФЗ в дни в экстремальными осадкамиЗима

Лето

Холодный период

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.

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Холодный период Арктика

Теплый период Арктика

ЧПК

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

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

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