Although coastal regions only amount to 7 % of the global oceans, their
contribution to the global oceanic air–sea
Across a heterogeneous surface consisting of a coastal marginal sea with
estuarine properties and varied land mosaics, the surface fluxes of
Understanding the natural processes responsible for absorbing just over half
of the anthropogenic carbon emitted to the atmosphere will help decipher
future climatic pathways. During the last decade, the ocean and the biosphere
are estimated to take up to
Biosphere models of various complexity have been developed to spatially
simulate surface fluxes of
Studying surface exchanges of
Heterogeneity can also be considerable in coastal oceans, and like
terrestrial surface fluxes, the high spatio-temporal variability leads to
large uncertainties in estimates of coastal air–sea
In this study we aim to simulate surface exchanges of
Section
The study area is comprised of Denmark, a country that is characterised by a
mainland (Jutland) and many smaller islands, all containing a varied land
mosaic of urban, forest and agricultural areas. With more than 7300 km of
coastline encircling approximately 43 000 km
The study region of Denmark (land masses in grey), with the location of the five EC sites shown in black and the Risø campus tall tower site indicated in red.
A tiling approach with the seven most common biospheric land cover
classifications were selected for the current study, including deciduous forest
(3348 km
One tall tower is found within the study area on the eastern inner shore of
Roskilde Fjord. Here atmospheric continuous measurements have been conducted
at the Risø campus tower site (55
The tall tower continuous measurements of atmospheric
The model framework used in the present study consists of two models: DEHM
and SPA. A coupling between the two was made for the innermost nest of DEHM
in order to simulate the exchange of
DEHM is an atmospheric chemical transport model covering the Northern
Hemisphere, with a polar stereographic projection true at 60
Anthropogenic emissions of
Hourly anthropogenic emissions on a 10 km
The exchange of
The necessary meteorological parameters for DEHM were simulated by the WRF
We did not have access to measurements from official meteorological
observational sites. Thus, for the evaluation of the meteorological drivers,
measurements from different types of monitoring sites were used, comprised of
three air pollution monitoring sites, three FLUXNET sites, and three sites
from the Danish Hydrological Observatory (HOBE; Table
Wind directions, investigated by comparing wind roses made from WRF outputs
and measurements, were at most sites reasonably captured by WRF (see
Figs. S1–S3 in the Supplement). At several sites the frequency of wind
directions from the west were overestimated by WRF, mainly at the expense of
southern winds. However, the opposite was the case at Aarhus, where the
effect of street canyons was likely causing higher occurrences from due west
in the observed wind directions. The wind velocities were in general
overestimated by WRF with an average of 1.1 m s
Location of the sites used for evaluation of the meteorological drivers together with the time period from which measurements are used and the meteorological variables (Met var.) included in the analysis. The measurements were obtained from Danish Hydrological Observatory (HOBE), FlUXNET and Department of Environmental Science at Aarhus University (AU).
Scatter plots of measured versus modelled 10 m wind velocity for
the nine sites used for evaluation of the meteorological drivers. Hourly
average values are used for both simulated and measured wind velocities.
Observed average wind velocity (Obs), simulated average wind velocity (Mod),
correlation squared (
Scatter plots of measured versus modelled 2 m temperatures for the
nine sites used for evaluation of the meteorological drivers. Hourly average
values are used for both simulated and measured temperatures. Observed
average 2 m temperature (Obs), simulated 2 m temperature (Mod), correlation
squared (
Only one site had available surface pressure measurements, and high
correlation of
When evaluating the meteorological variable also important for the biospheric
model component, the surface temperature showed high correlation with
Location, species and land cover classification in the model system for the five Danish eddy covariance (EC) sites used for calibration and validation of SPA.
SPA is a mechanistic
terrestrial biosphere model
Ecosystem carbon cycling and phenology is determined by a simple carbon cycle
model (DALEC;
SPA has been extensively validated against site observations from temperate
forests
SPA needs vegetation and soil input parameters. Initial soil carbon stock
estimates were obtained from the Regridded Harmonized World Soil Database
In the innermost nest of DEHM for the area of Denmark, a coupling was made
between DEHM and SPA. Thus, the coarser optimised biospheric fluxes from
CT2015 were, for Denmark, replaced by hourly SPA simulated
On an hourly basis, DEHM provides atmospheric
The calibration was conducted by selecting a set of inputs parameters (plant traits, carbon stocks, etc.), and for each parameter, five values within a realistic range were chosen. Next, 200 SPA simulations with randomly chosen parameter values were conducted. These results were statistically evaluated against observations of NEE from the different flux sites, with the aim of selecting the parameter combination with the lowest root-mean-square error (RMSE) in combination with highest correlation that captured the observed variability and onset of the growing season. However, it was not always possible to have all these conditions satisfied (e.g. Fig. S7). Based on this random parameter testing, it was possible to choose the best set of realistic vegetation input parameters that could improve the model performance at the Danish sites. The best found vegetation parameters values corresponded in some cases to the values already applied in SPA for the given land cover.
Comparing to observations of NEE, SPA was, in general, able to capture the
phenology and seasonal cycle throughout the entire simulation period
(Fig.
Monthly averaged values of measured (black dashed, calibration
period; black solid, validation period) and simulated (red) net ecosystem
exchange (NEE) for the Danish EC sites with measurements in the simulation
period. The shaded areas show the standard deviations for the modelled and
measured NEE calculated using hourly fluxes. The model mean
(Mean
Examining the performance of SPA at a higher temporal resolution
(Table
Statistic metrics for the validation period (2013–2014) for the
fives sites that have measurements of NEE during the validation period for
hourly, daily and monthly values. Measured mean (mean
The model system was run from 2008 to 2014, with the first 3 years
regarded as a spin-up period. In the following sections the terrestrial and
marine surface fluxes will be presented first, followed by measurements of
atmospheric
As shown in Fig.
Net ecosystem exchange (NEE) for January
Figure
Total monthly average of NEE for each land cover classification for
the simulation period of 2011–2014 together with the monthly air–sea
The air–sea
Simulated air–sea
The simulated annual air–sea
The time series of measured and simulated
Hourly averages and daily averages of modelled and continuously
measured atmospheric
To investigate the origin of the
Concentration roses of modelled atmospheric
The individual contribution from fossil fuel emissions, marine and biospheric
exchanges to the atmospheric
The local impact from Roskilde Fjord is difficult to detect in the marine
concentration plots. Flux measurements at Roskilde Fjord have shown uptake of
The simulated annual uptake by deciduous forest of
Previous annual estimates at Danish agricultural field sites found carbon
uptake of
The current study estimated the Danish grasslands to be a sink of
A tilling approach has been used for the land cover classification in the
SPA–DEHM modelling framework, including sub-grid heterogeneity in the model
system. However, the seven land cover classes do not fully encompass the
ecosystem variability in Denmark. Both grassland and agricultural other cover
a broad range of subcategories, with both heather and meadow included in the
grassland class, while agricultural other contains, for example, vegetables fields,
hedgerows, woodland patches and uncultivated land, highlighting the need to
adopt approaches allowing for generating novel spatially varying parameter
sets
Compatible marine fluxes to previous estimates are obtained for the study
region. On an annual basis, the Danish inner waters were found to be a source
of 30 gC m
WRF is in general capable of simulating the observed wind patterns, while
the overestimation of the wind velocity could lead to an overestimation
of the atmospheric mixing. However, the SPA–DEHM modelling system resembles
the synoptic and diurnal variability in the atmospheric
As Roskilde Fjord previously was found by a footprint analysis to have an
impact on the atmospheric
However, the air–sea
Some of the largest uncertainties lie in the parameters underlying the
terrestrial carbon cycle, in particular those governing allocation to plant
tissues and their subsequent turnover. Most often these are based on maps of
land cover or plant functional type, but parameter estimation via data
assimilation analysis has shown substantial spatial variation in terrestrial
ecosystem parameters within plant functional type groupings, with
consequences for carbon cycling predictions
While SPA also uses DALEC to simulate carbon allocation and turnover, it is
currently impractical to conduct a similar data assimilation analysis to
optimise DALEC (or SPA) parameters based on comparison with observations of
atmospheric
Uncertainties of the marine fluxes can be associated with both the choice of
transfer velocity parameterisation, choice of the wind speed product and the used
surface water
By usage of the designed mesoscale modelling framework, it was possible to
get detailed insight into the spatio-temporal variability in the Danish
surface exchanges of
Good accordance between simulated and observed concentrations was found
between modelled and observed atmospheric
In order to further examine the air–sea signal at the complex Risø site surrounded by a mosaic of fjord systems, land masses and the Danish inner water, more model experiments could be made, where a larger focus is put on other marine areas than Roskilde Fjord, e.g. the Danish inner straits, Kattegat and the Baltic Sea. Although the total annual marine flux was small, it disguises large monthly variations, and further investigations could help to understand the carbon dynamics in coastal regions. A runoff component in the modelling system would moreover be beneficial for such studies.
Scientists with an interest in the atmospheric chemical
transport model, DEHM, can contact Jesper H. Christensen (jc@envs.au.dk) with
enquiries. Scientists with an interest in the soil–plant–atmosphere model,
SPA, can visit its web page
(
The supplement related to this article is available online at:
ASL and CG designed the experiment. ASL was responsible for
coupling the model, which JHC assisted with, and running the experiments. LLS
made contributions to the marine set-up, while MW and TSL were responsible
for SPA. KP conducted the atmospheric measurements of
The authors declare that they have no conflict of interest.
This study was carried out as part of a PhD study within the Danish ECOCLIM
project funded by the Danish Strategic Research Council (grant
no. 10-093901). CarbonTracker CT2015 results that were provided by the NOAA
ESRL, Boulder, Colorado, USA, from the website
This paper was edited by Trevor Keenan and reviewed by two anonymous referees.