The main objective of this task is to provide harmonised and consolidated biome specific datasets to drive, calibrate and validate the models in WP2. We started with sites with easily accessible, good quality data that had already been used with one or more of the models. These datasets are now ready and are being used to carry out the first model optimisations (see section on WP2). It will be extended with more years of data and additional sites to cover all global PFT’s with as broad a spectrum of sites as possible, varying in soil types, dominant plant species and geographical location (within the limits of the climate zone).

 

Twenty site datasets have been prepared from publicly available data (Fluxnet, Carbodata). The length of the datasets ranges from one growing season (Upad) to seven years (Harvard Forest). All data sets are from the Northern Hemisphere (Europe, US or Canada) and most are from forests (figure 3.1a). Forests have also the longest running time series. The few datasets from non-forested flux sites all are from North-America.

 

In Europe, human pressure on land has long since converted the most fertile soils into agricultural land or pastures. Poorer, sandy soils were left for forests. The past strong focus of CARBOEUROPE to forested sites is thus reflected in a high representation of sandy soils within the European sites and in the datasets as a whole (Figure 3.1b).

 

Before the datasets were put together an inventory was made of model needs. A distinction was made between indispensable (meteorological, vegetation or soil) data, other information that was not crucial but could be used if available, and measurements that could be used to compare models output to for optimisation and validation.

 

image003

Figure 3.1:  Lefthand plot: location of flux sites in current data set. Righthand plot: distribution of flux sites in current data set over soil texture types

 

 

All three of the CAMELS TEMs need incoming shortwave radiation, average temperature, vapour pressure deficit, air CO2 concentration and precipitation over each time interval. Apart from these, all have further needs for meteorological input, covering the total set of standard meteorological measurements in CARBOEUROPE. Net and longwave radiation are the only variables outside the standard CARBOEUROPE measurements. Only these mandatory input data were gap-filled. Gap-filling was done using meteorological data from NCDC (8000 stations worldwide) and ERA15 data following a procedure developed by Nicholas Viovy (LSCE-partner). No attempt was made to estimate errors made by gap-filling, but gap-filled meteorological data were flagged in the final dataset. All driving variables were given along with estimated errors (see below).

 

Soil data needs are limited to soil type and texture, but even this information is often unavailable. Information about the vegetation (apart from the PFT class) is limited to LAI, which is needed and provided on a seasonal basis. Optionally, the models can use further information about plant and soil carbon pools.

 

All 3 TEMs were developed for their output to be compared against NEE, latent heat flux and sensible heat flux, and optionally ground heat flux. MOSES and ORCHIDEE can also use calculated radiation terms or plant carbon pools and LAI for that purpose. BETHY and ORCHIDEE can also use litter carbon. Variables that are used for model output comparison were not gap-filled, and all gap-filling that had occurred by others was removed. These variables were given along with preliminary estimated errors.

 

For the optimisation methods used in WP2 it is imperative to give a-priori estimates of uncertainties of driving and validation data. These have also been provided. A distinction must be made between stochastic errors, that may (partially) cancel out when averaged over longer that half-hourly time scales, and systematic errors that do not diminish with averaging.  Rough estimates of potential uncertainty in eddy correlation flux measurements were made. This analysis is based upon various studies showing sensitivity of fluxes to treatment and calculation method as well as variation of representativity. The estimates are assuming ignorance of the user (modeller) about maintenance conditions, quality control and field conditions at the data source. In almost all individual cases the uncertainties are likely to be much smaller and only in some cases a few sources of error may be larger.

 

All meteorological and flux data were converted to NetCDF format. Version numbers of all datasets are included. Dataset are available (CAMELS partners only for now) from the following ftp address ftp.bgc-jena.mpg.de

 

The main objective of this task is to provide harmonised and consolidated biome specific datasets to drive, calibrate and validate the models in WP2. We started with sites with easily accessible, good quality data that had already been used with one or more of the models. These datasets are now ready and are being used to carry out the first model optimisations (see section on WP2). In year two additional sites have been identified to cover all global PFT’s with as broad a spectrum of sites as possible, varying in soil types, dominant plant species and geographical location (within the limits of the climate zone). Some sites will be extended with more years of data (see table 3.1).

 

In the first year, twenty site datasets have been prepared from publicly available data (Fluxnet, Carbodata). The length of the datasets ranges from one growing season (Upad) to seven years (Harvard Forest). All data sets are from the Northern Hemisphere (Europe, US or Canada) and most are from forests. Forests have also the longest running time series. The few datasets from non-forested flux sites all are from North-America.

 

In this second year twenty-six additional sites have been identified and agreement has been reached with most of the site-PI’s to use these data. Only few datasets in the southern hemisphere are now included for the PFTs ‘Tropical broadleaf evergreen’ and for ‘Savanna’. For the grasslands/crops sites have been added distinguishing explicitly between C3 and C4 and between crops and (semi-) natural grasslands, thus including four distinct PFTs and 9 sites.

 

Another PFT newly represented in the database is ‘Boreal Needle leaved summer green’ with two Larix sites. The ‘Temperate Broad-leaved evergreen’class now includes 6 sites, allowing better analysis of intra PFT variability. Currently for two PFT’s,  ‘Tropical Broad-leaved Rain-green’ and ‘Deciduous Shrubs’, we have yet been unable to identify appropriate sites.

 

All meteorological and flux data for these new sites in the database will be identical in format, parameter content, treatment of missing values and calculation of a –priori uncertainties as those already in the database, see first annual report. Version numbers of all datasets are included. Dataset are available (CAMELS partners only for now) from the following ftp address ftp.bgc-jena.mpg.de

 

For the optimisation methods used in WP2 it is imperative to give a-priori estimates of uncertainties of driving and validation data. A distinction must be made between stochastic errors, that may (partially) cancel out when averaged over longer that half-hourly time scales, and systematic errors that do not diminish with averaging.  Rough estimates of potential uncertainty in eddy correlation flux measurements were made and included in the first version of the datasets in the database. Currently, an algorithm is under development by Alterra to compute improved uncertainty estimates based on a) the full uncertainty analysis table prepared in year one, on b) more site specific knowledge wherever available. The algorithm will allow estimation of cumulative uncertainties at the various time-scales represented by the datasets. Thus separate uncertainty estimates will become available for half hourly fluxes (the temporal resolution of the datasets), but also for fluxes at daily, weekly or decadal, monthly, seasonal and annual time scales.

 


Plant Functional Type

Site name

Country

species

Years of data

Tropical Broad-leaved Evergreen

Manaus K34

Brazil

Rainforest

1999-2002

Jaru forest Jiparana

Brazil

Rainforest

1999-2002

Tropical Broad-leaved Raingreen

 

 

 

 

Temperate Needle-leaved Evergreen

Griffin/Aberfeldy

UK

Picea abies

1997-1998 and 2000-2001

Brasschaat

Belgium

Pinus sylvestris

1996-2002

Bordeaux

France

Pinus pinaster

1997-1998 and 2000-2002

Loobos

Netherlands

Pinus sylvestris

1996-2002

Metolius

Oregon

Pinus ponderosa

1996-1997

Tharandt

Germany

Picea abies

1996-2002

Bayruth/Weiden Brunnen

Germany

Picea abies

1996-1999

San Rossore

Italy

Pinus pinaster

2000-2002

Yatir

Israel

Pinus halepensis

2001-2002

Lavarone

Italy

Spruce

2000-2002

Temperate Broad-leaved Evergreen

Castelpoziano

Italy

Quercus ilex

1997-1998 and 2000-2002

El Saler

Spain

Pinus halepensis

2000-2002

Mitra/Evora

Portugal

Quercus ilex

2002

Puechabon

France

Quercus ilex

2000-2002

Roccarespampani

Italy

Quercus cerris

2001-2002

Roccarespampani

Italy

Quercus cerris

2002

Temperate Broad-leaved Summergreen

Hesse

France

Fagus sylvatica

1996-2002

Harvard Forest Hemlock

USA

Tsuga

1992-1999

Soroe LilleBogeskov

Denmark

Fagus

1997-2002

Vielsam

Belgium

Fagus

1996-1998 and 2002

Walker Branch

Tennessee

mixed

1995-1998

Collelongo

Italy

Fagus sylvatica

2001

Hainich

Germany

Fagus sylvatica

2000-2002

Nonantola

Italy

Quercus robur mix

2001-2002

Boreal Needle-leaved Evergreen

Flakaliden

Sweden

Picea abies

1996-1998

Hyytiala

Finland

Pinus sylvestris

1996-2002

Sodankylä

Finland

Pinus sylvestris

2000-2002

Boreal Needle-leaved Summergreen

Tomakomai

Japan

Larix kaempferi

2000-2001

Spasskaya pad

Siberia

Larix gmelinii

???

Boreal Broad-leaved Summergreen

Gunnarsholt

Iceland

Populus trichocarpa

1996-1998

Sylvania Wilderness area

Michigan

hemlock/maple/birch

2001-2002

C3 Grass

Little Washita

USA

Grasses

1997-1998

Vaira Ranch Ione

California

C3 grasses grassland

2000-2001

Kaamanen

Finland

Wetland,

2000-2002

Tadham Moore

UK

Peatland

2000-2001

C4 Grass

Shidler

Oklahoma

C4 grasses

1997-2000

Maun, Floodplain

Botswana

C4 grasses

??

Nossa senhora

Brazil

C4 grasses

2000-2002

C3 Crops

Ponca city

Oklakoma

Winter wheat

1997-2000

Soroe wheat

Denmark

C4 grasses

 ???

Bondville

Illinois

cornC4/soybeanC3*)

1997-1999

C4 Crops

Bondville

Illinois

cornC4/soybeanC3

1997-1999

Deciduous Shrubs

 

 

 

 

Evergreen Shrubs

Kennedy space center

USA

scrub oak

2001-2003

Sky Oaks  (old)

California

Adenostoma

1997-2000

Tundra Vegetation

Upad

Alaska

tundra

1994

Atqasuk

Alaska

tundra

2000-2001

Savanna

Maun, Mopane woodland

Botswana

decidous savanna woodlands

1999-2000

·        In bold all sites already in the database from the following ftp address ftp.bgc-jena.mpg.de

·        Other sites will be available in the database early 2005 (jan/feb)

*) in crop rotation

 

  Table 3.1: Characteristics of biome-specific datasets.