THE DEVELOPMENT THE DEVELOPMENT OF LAKE MODELS OF LAKE MODELS FOR - - PowerPoint PPT Presentation

THE DEVELOPMENT THE DEVELOPMENT OF LAKE MODELS OF LAKE MODELS FOR W EATHER AND FOR W EATHER AND CLI MATE STUDI ES CLI MATE STUDI ES

V V. .M M . . Stepanenko Stepanenko, , E E. .E E. . Machul Machul’ ’skaya skaya

Moscow State University Moscow State University

The young scientist school and conference CITES-2009, Krasnoyarsk, 2009 The w ork is supported by RFBR grants NN 0 9 -0 5 -0 0 3 7 9 -a and 0 7 -0 5 -0 0 2 0 0 -a

Outline Outline

• The overview of lake models
• Lake Model Intercomparison Project

(LakeMIP) project: goals and design

• The Lake Sparkling intercomparison results
• Observation evidences for the role of lakes in

methane budget of the climate system

• The methane model for thermokarst lakes
• Initial results of model’s evaluation
• Other issues in land surface hydrology

modeling

Num erical w ater reservoir m odels for Num erical w ater reservoir m odels for coupled lake coupled lake – – atm osphere studies atm osphere studies

1 ) 1 ) 3 3 -

• dim ensional

dim ensional (~ oceanic) (~ oceanic) 2 ) 2 ) 2 2 -

• dim ensional

dim ensional

• vertically averaged (Shlychkov, 2008)
• averaged in one lateral direction (CE-QUAL x.x model)

3 ) 3 ) 1 1 -

• dim ensional

dim ensional

• single-colum n (GOTM model (Burchard et al.),

LAKE model (Stepanenko & Lykosov, 2005);

• laterally averaged m odels (Vasiliev et al., 2007) –

applicable in many applications 4 ) 4 ) ½ ½ -

• dim ensional

dim ensional – the vertical profiles of temperature, salinity etc. are parameterized (FLake model, Mironov et al., 2008) – high computational efficiency → application in

• perational weather forecast

5 ) 5 ) 0 0 – – dim ensional dim ensional (mixed models, e.g. Goyette model)

Model Model FLake FLake

( ( Mironov, Golosov, Kirillin Mironov, Golosov, Kirillin et al. et al.) )

Advantages:

• computationally efficient

(orders of magnitude less than k-ε)

• capable of representing

surface temperature and heat fluxes with accuracy of k-ε models Shortcom ings:

• the bottom temperature
• does not capture the details of

real temperature profile (e.g. Brunt-Väisäla frequency)

• the maximal lake depth is

limited to 50-60 m Theoretical basis: the concept of self-similarity of temperature profile .

One One-

• dimensional

dimensional k k-

• ε

ε model (LAKE) model (LAKE)

( )

1 1

A

T p Г

T T S k u n Tdl t z z c z A ρ ∂ ∂ ∂ ∂   = − + ⋅   ∂ ∂ ∂ ∂  

∫

r r

2 2 2 2

tg , tg

M x veg M y veg

u u k fv g C u u v t z z v v k fu g C v u v t z z α α ∂ ∂ ∂ = + − ⋅ − + ∂ ∂ ∂ ∂ ∂ ∂ = − − ⋅ − + ∂ ∂ ∂

2

,

M e

E k C = ε

Snow Ice

Water Soil

U H,LE Es Ea S

,

M E

E k E P B t z z   ∂ ∂ ∂ = ν + + + − ε   ∂ ∂ σ ∂  

( )

1 3 2 M

k c P c B c t z z E

ε ε ε ε

  ∂ε ∂ ∂ε ε = ν + + + − ε   ∂ ∂ σ ∂  

K-ε turbulence closure Mom entum equations Heat equation

Workshop "Parameterization of Workshop "Parameterization of Lakes in Numerical Weather Lakes in Numerical Weather Prediction and Climate modeling Prediction and Climate modeling“ “ , , St St -

• Petersburg, September, 2008

Petersburg, September, 2008

Topics

• modeling the lake level changes

(paleoclimate tasks);

• CO2 and CH4 emissions by

lakes;

• lake ecosystems under the

climate changes;

• …

Topics

• lake parameterizations for

weather and climate models;

• the global databases on

lakes;

• data assimilation issues;
• …

LakeMI P project LakeMI P project

(Lake Model Intercomparison Project) (Lake Model Intercomparison Project)

http: / / www.unige.ch/ climate/ lakemip/ index.html http: / / www.unige.ch/ climate/ lakemip/ index.html

• V. Stepanenko, S. Goyette, A. Martynov, M. Perroud,
• V. Stepanenko, S. Goyette, A. Martynov, M. Perroud,
• X. Fang, D. Mironov, K. J
• X. Fang, D. Mironov, K. Jö

öhnk hnk Objectives:

• Assessment of the range of applicability of existing one-

dimensional model formulations, i.e. their capabilities and limitations in reproducing lake-atmosphere interactions, as well as internal lake thermodynamics.

• Evaluation of the interaction mechanisms between lakes and the

atmosphere in weather and climate models for weather prediction and climate projections. I m plem entation phases: 1) LakeMIP1, the intercomparison of one-dimensional models, using observations on a number of lakes representing a wide range of climate and lake mixing regimes. 2) LakeMIP2, will aim at studying the impacts of lakes on regional-scale weather and climate using coupled lake- atmosphere m odels.

Lake sites and models Lake sites and models

• FLake ( 1 / 2 – dim ensional)
• Hostetler
• MI NLAKE9 6
• LAKE ( k-ε m odel)
• Sim strat ( k-ε m odel)
• LAKEoneD ( k-ε m odel)

Latitude Deep/ shallow Example Average depth, m Equatorial deep

Geneva ( Sw itzerland, France)

153 shallow Mid-latitude non- freezing deep

Am erican Great Lakes ( USA, Canada)

19-147 shallow Sparkling Lake ( USA, W isconsin) 20 Mid-latitude freezing deep shallow Arctic deep shallow Toolik ( USA, Alaska)

7

Very shallow

Kossenblatter ( Germ any)

2 High- altitude Models:

Lake Sparkling intercom parison Lake Sparkling intercom parison

Surface tem perature

Mean m onthly tem perature profiles Experim ental setup:

• 2002 – 2005 yr m eteorological

forcing

• unified initial conditions,
• ptical characteristics

and other input parameters (e.g. bathymetry)

ΔT≈2-3 Celsius R = 0.99

Methane em ission from therm okarst lakes Methane em ission from therm okarst lakes

(Semiletov, 2005; K. Walter (Semiletov, 2005; K. Walter et al. et al., 2007) , 2007)

• 8 - 5 0 % of anthropogenic

m ethane em issions up to 2 0 0 0 depending on the em ission scenario

Unfrozen “hotspot” – wintertime methane source Therm okarst lakes are abundant in Northern Siberia ( 2 2 -4 8 % of land surface) , tending to expand in w arm ing clim ate Methane turbulent and ebullition flux from lake talik

INM RAS soil model with the Walter&Heimann methane model against BOREAS data

1994 1996

Zero methane fluxes when the top soil layers are not saturated by water. Methane model is highly sensitive to the soil moisture content, predicted by the soil model. To simulate realistic soil moisture the correct soil parameters should be set.

Methane m odel for therm okarst lakes Methane m odel for therm okarst lakes

Bastviken et al., 2 002

I n w ater colum n I n soil ( talik)

[ ] [ ] [ ] [ ]

4 2

4 4 2 2

, 2

CH

• xid

O

• xid

CH CH k V t z z O O k V t z z ∂ ∂ ∂ = − ∂ ∂ ∂ ∂ ∂ ∂ = − ∂ ∂ ∂

( ) [ ] [ ] [ ] [ ]

4 2

4 2 ,max 4 2

• xid
• xid

CH O

CH O V V T a CH a O = + +

• xidation ( Arah & Stephen, 199 8 )

[ ] [ ]

4

4 4 , CH m

• xid

plant

CH CH k P V V E t z z ∂ ∂ ∂ = + − − − ∂ ∂ ∂

production

• oxidation

plant-m ediated transport ebullition

[ ]

( ) [

] [ ]

( )

4 4 4 max e

E k f CH CH CH = − W alter & Heim ann, 1 9 9 6 , 2 0 0 1

( ) ( )

( ) ( )

0.1 10

m

T T

• rg

in

P R f z f t Q f T

⋅ −

=

• xid

V ≈

plant

V ≈

• step function

( ) f T

Bottom sedim ents tem perature Bottom sedim ents tem perature

• Krasnoe Lake,

( near S.-Petersburg)

• 1 9 6 9 – 1 9 7 9
• Sortavala station

forcing

Bottom tem perature Bottom sedim ents tem perature ( 3 m depth) Observations: Kusm enko, 1 9 7 6 . Soil heat conductance: Cote and Konrad m odel ( Sen Lu et al., 2 0 0 7 )

Methane ebullition flux Methane ebullition flux at Lake Shuchi at Lake Shuchi

30 60 90 120 150 180 210 240 270 300 330 360 390 100 200 300 400

CH4 flux, mg/(m

2*day)

Time, days (28.04.2003 - 30.06.2004) center non-thermokarst thermokarst margin

1110 1140 1170 1200 1230 1260 1290 1320 1350 1380 1410 1440 100 200 300 400 500 600 700 800 900

Ebullition flux, mg/(m

2*day)

Time, days depth = 3 m depth = 10 m

Sim ulations:

• atmospheric forcing – station

Kamenskoe, 1990-2000;

• Observations

(K. Walter et al., 2007):

• Lake Shuchi, 2003-2004, step

1 hour;

• different sections of the lake;
• background and point-source

fluxes. Background flux Modeling production term ( labile organic m atter) is crucial for sim ulating correct fluxes

• NPP modeling in lakes
• estimates of labile organic matter in

permafrost

• inclusion the CO2 equation in water

column

• parameterization of gas fluxes

through unfrozen hotspots

Further m ethane m odel Further m ethane m odel developm ent developm ent

Other issues Other issues

• the global database on depth and

lake optics (probably, other parameters) for land hydrology is needed;

• the rivers representation in GCMs

might require more sophisticated models then simple runoff schemes;

• coupling the hydrological model

(lakes + rivers + soil hydrology) to land carbon cycle model

ANY QUESTI ONS? ANY QUESTI ONS?

General points on the role of General points on the role of methane in climate system methane in climate system

• provides 23 times stronger greenhouse

effect than CO2 per molecule

• integral greenhouse effect is the second

after those for CO2

• the mean concentration over industrial

period has risen ?? times

• major sources are:
• rice fields
• wetlans
• domestic animals
• …

Зачем Зачем нужны нужны модели модели рек рек в в климатических климатических моделях моделях? ?

• изменения в режиме рек является одним

из важнейших последствий изменений климата

• речной сток играет важную роль для

термохалинной циркуляции океана

• речной сток измеряется, что может

служить валидацией водного баланса модели подстилающей поверхности

• термический режим рек существенно

отличается от режима озер

• вынос реками взвесей и растворенных

веществ с суши

База База данных данных по по озерам озерам

( ( Курзенева Курзенева и и др др.) .)

Чувствительность температуры поверхности к вариации глубины водоема Глубина водоема: 1)Измерена (национальные базы данных) 2)Неизвестна «значение по умолчанию» 10 м Минимизация целевого функционала (Balsamo at al.)

( )

2 , ,

1 2

s m s obs

• bs

J T T   = − σ  

Эмпирические функции распределения

Проблема Проблема базы базы данных данных по по гидрологической гидрологической системе системе суши суши

• Площадь объектов – снимки спутников
• Глубина водоемов – известна для небольшого

количества исследованных водоемов

• Прозрачность (коэффициент пропускания

солнечной радиации) – еще меньше данных

( ) (0) exp( ), 0.01 3 S z S z = −λ λ = ÷

Роль прозрачности для температуры поверхности

Современные Современные схемы схемы параметризации параметризации рек рек ( ( Community land model 3.0, HadCM3 Community land model 3.0, HadCM3) )

• нет термики рек
• нет стока примесей

(например, парниковых газов)

Баланс речной воды в ячейке

Сток из ячейки в соседнюю ячейку Сток с водосбора поверхностный сток подповерхностный сток сток с ледников и озер River routeing model – модель направления потоков

Сопряжение Сопряжение мезомасштабных мезомасштабных атмосферных атмосферных моделей моделей с с гидрологическими гидрологическими моделями моделями (Nagai et al.) (Nagai et al.)

С трехмерными моделями водоемов (Long et al., 2007) – модель океана POM

С моделями рек (Nagai, et al.)

Перспективы Перспективы

Производительность суперкомпьютеров Разрешение глобальных моделей N* 10 терафлопс (1012) ~ 100 км N* 100 петафлопс (1015) ~ 2020 год (рост производительности – 3 порядка/ 10 лет) ~ 1 км – современное разрешение мезомасштабных моделей

Разрешение климатических моделей

(World Modelling Summit on Climate Prediction, Reading, May, 2008)

Параметризация гидрологических объектов

Гидрологический объект Крупные Подсеточные Водоемы 3-мерная модель 1-мерная модель Реки 2-3(?) - мерная модель Модель направления потоков

Моделирование Моделирование термического термического режима режима Байкала Байкала ( ( данные данные наблюдений наблюдений – – MODIS SST MODIS SST) )

Нужны Нужны ли ли водоемы водоемы? ?

• спецификация

«озерных регионов» при повышенном разрешении атмосферных моделей

Данные Данные наблюдений наблюдений

The lake name, country, mean depth, coordinates Depth Limnological data, timestep Meteorological data, timestep Time period Website, contact person Terms of usage Toolik Lake, , 68° N 149° W 2.4 m LST, lake depth, evaporation (?), 3 hour temperature (1 & ), relative humidity (1 & ) wind speed (1 & ), wind direction (), net solar radiation, photosynthetically active solar radiation, barometric pressure, unfrozen precipitation, 1 hour, atmospheric radiation missing! 1988 - 2007 http://ecosystems.mbl.edu/ ARC/weather/tl/index.shtml, arc_im@mbl.edu ??, freely available at the website Alqueva lake, Portugal 40 m Lake temperature at 5, 10, 15, 20, 25, 30, 35, and 40 m, 1 hour wind speed (without direction!), temperature, humidity, pressure, net solar radiation, atmospheric radiation, 1 hour 2003-2007 rsal@uevora.pt Rui Salgado (Evora University, Portugal) ?? - Contact to Rui Salgado Geneva lake, Switzerland 309 m Temperature at 0-5m, 5- 10m, 10-15m, 15-50m, 50- 100m 1981 - 2006 Stephane Goyette, stephane.goyette@unige.ch ?? - Contact to Stephane Goyette Sparkling Lake, Wisconsin, USA 20 m max, 11 m mean temperature soundings, 10 min, 1hour, 1 day meteorological forcing, fluxes (annually!), 1 hour in datasets (source data: 10 min, 1 hour, 1 day) Source data: 1989- 2007(8?) Datasets are available for years 2000, 2002, 2005 Source data are available online: http://lter.limnology.wisc.edu/ Data owner’s contact: Steve Carpenter, srcarpen@wisc.edu Datasets: Andrey Martynov, andrey.martynov@uqam.ca http://lter.limnology.wisc .edu/data_policy.html Trout Bog, Wisconsin, USA 7.9 m max, 5.6 m mean temperature soundings, 10 min, 1 hour, 1 day meteorological forcing, 1 hour in datasets (source data: 10 min, 1 hour, 1 day) Source data: 2003- 2007(8?) A dataset is available for the year 2005 Source data are available online: http://lter.limnology.wisc.edu/ Data owner’s contact: Steve Carpenter, srcarpen@wisc.edu Datasets: Andrey Martynov, andrey.martynov@uqam.ca http://lter.limnology.wisc .edu/data_policy.html Great Lakes USA-Canada 409m max. (Lake Superio Bathymetry: GLERL; Surface

• bservations:

Meteorological forcing: ERA40 (resolution: 2.5°) 6 hours I Source data (ERA40): 1957-2002 Forcing dataset: ERA40: http://www.ecmwf.int Buoys : www.ndbc.noaa.gov Ice: http://www.glerl.noaa.gov/data/ic See web sites of data sources.

Гидрология Гидрология почвы почвы

• диффузия
• инфильтрация
• поверхностный сток
• подповерхностный сток

Модель Модель водоема водоема

Гидрология Гидрология суши суши в в моделях моделях прогноза прогноза погоды погоды и и климата климата

Гидрология Гидрология растительности растительности

• перехват осадков листьями
• стекание осадков с листьев
• испарение осадков с листьев
• транспирация
• питание корней

Гидрология Гидрология снега снега

• диффузия жидкой влаги
• метаморфизм
• …

Моделирование Моделирование пузырьковой пузырьковой конвекции конвекции в в задаче задаче аэрации аэрации водоема водоема ( ( Wuest et al., 1992 Wuest et al., 1992) )

( )

2

2

a

b wT bwT z π απ ∂ = ∂

• сохранение массы струи
• уравнение движения струи
• уравнение переноса тепла струи

( ) ( )

2 2 2 2 2 2

1

a p p a w p

b w g b z g b ρ ρ π π λ ρ ρ ρ π λ ρ − ∂ = + ∂ − −

( )

( )

2 2

1 2

g

b w V bw z π λ απ ∂ − = ∂