scholarly journals Air-Sea CO2 Exchange in the Strait of Gibraltar

2021 ◽  
Vol 8 ◽  
Author(s):  
David Curbelo-Hernández ◽  
J. Magdalena Santana-Casiano ◽  
Aridane González González ◽  
Melchor González-Dávila
Keyword(s):  
Spatial Variability ◽  
Interface Layer ◽  
Co2 Exchange ◽  
Strait Of Gibraltar ◽  
Net Community Production ◽  
Entire Area ◽  
High Resolution Data ◽  
Surface Ocean ◽  
Effect Ratio ◽  
Calculated Average

The seasonal and spatial variability of the CO2 system and air-sea fluxes were studied in surface waters of the Strait of Gibraltar between February 2019 and March 2021. High-resolution data was collected by a surface ocean observation platform aboard a volunteer observing ship. The CO2 system was strongly influenced by temperature and salinity fluctuations forced by the seasonal and spatial variability in the depth of the Atlantic–Mediterranean Interface layer and by the tidal and wind-induced upwelling. The changes in seawater CO2 fugacity (fCO2,sw) and fluxes were mainly driven by temperature despite the significant influence of non-thermal processes in the southernmost part. The thermal to non-thermal effect ratio (T/B) reached maximum values in the northern section (>1.8) and minimum values in the southern section (<1.30). The fCO2,sw increased with temperature by 9.02 ± 1.99 μatm °C–1 (r2 = 0.86 and ρ = 0.93) and 4.51 ± 1.66 μatm °C–1 (r2 = 0.48 and ρ = 0.69) in the northern and southern sections, respectively. The annual cycle of total inorganic carbon normalized to a constant salinity of 36.7 (NCT) was assessed. Net community production processes described 93.5–95.6% of the total NCT change, while air-sea exchange and horizontal and vertical advection accounted for <4.6%. The fCO2,sw in the Strait of Gibraltar since 1999 has been fitted to an equation with an interannual trend of 2.35 ± 0.06 μatm year–1 and a standard error of estimate of ±12.8 μatm. The seasonality of the air-sea CO2 fluxes reported the behavior as a strong CO2 sink during the cold months and as a weak CO2 source during the warm months. Both the northern and the southern sections acted as a net CO2 sink of −0.82 and −1.01 mol C m–2 year–1, respectively. The calculated average CO2 flux for the entire area was −7.12 Gg CO2 year–1 (−1.94 Gg C year–1).

Seasonal and spatial variability of the CO2 system parameters in the Northeast Atlantic based on measurements from a surface ocean observation platform.

2021 ◽  
Author(s):  
David Curbelo Hernández ◽  
Melchor González Dávila ◽  
Aridane González González ◽  
David González Santana ◽  
Juana Magdalena Santana Casiano
Keyword(s):  
Spatial Variability ◽  
Continental Shelf ◽  
Inorganic Carbon ◽  
Coastal Upwelling ◽  
Seasonal Temperature ◽  
Entire Area ◽  
Northeast Atlantic ◽  
System Parameters ◽  
The North ◽  
Effect Ratio

<p>The seasonal and spatial variability of the CO<sub>2</sub> system parameters and CO<sub>2</sub> air-sea exchange was studied in the Northeast Atlantic Ocean between the northwest African coastal upwelling and the oligotrophic open-ocean waters of the North Atlantic subtropical gyre. Data was collected aboard a volunteer observing ship (VOS) from February 2019 to February 2020. The seasonal and spatial variability of CO<sub>2 </sub>fugacity in seawater (fCO<sub>2,sw</sub>) was strongly driven by the seasonal temperature variation, which increased with latitude and was lower throughout the year in coastal regions where the upwelling and offshore transport was more intense. The thermal to biological effect ratio (T/B) was approximately 2, with minimum values along the African coastline related to higher biological activity in the upwelled waters. The fCO<sub>2,sw</sub> increased from winter to summer by 11.84 ± 0.28 µatmºC<sup>-1</sup> on the inter-island routes and by 11.71 ± 0.25 µatmºC<sup>-1</sup> along the northwest African continental shelf. The seasonality of total inorganic carbon (C<sub>T</sub>) normalized to constant salinity of 36.7 (NC<sub>T</sub>) was studied throughout the region. The effect of biological processes and calcification/dissolution on NC<sub>T</sub> between February and October represented >90% of the reduction of inorganic carbon while air-sea exchange described <6%. The seasonality of air-sea CO<sub>2</sub> exchange was controlled by temperature. The surface waters of the entire region acted as a CO<sub>2</sub> sink during the cold months and as a CO<sub>2 </sub>source during the warm months. The Canary basin acted as a net sink of -0.26 ± 0.04 molC m<sup>-2</sup> yr<sup>-1</sup>. The northwest African continental shelf behaved as a stronger sink at -0.48 ± 0.09 molC m<sup>-2</sup> yr<sup>-1</sup>. The calculated average CO<sub>2</sub> flux for the entire area was -2.65 ± 0.44 TgCO<sub>2</sub> yr<sup>-1</sup> (-0.72 ± 0.12 TgC yr<sup>-1</sup>).<strong> </strong></p>

scholarly journals Spatial variability of CO<sub>2</sub> uptake in polygonal tundra: assessing low-frequency disturbances in eddy covariance flux estimates

2017 ◽  
Vol 14 (12) ◽  
pp. 3157-3169 ◽  
Author(s):  
Norbert Pirk ◽  
Jakob Sievers ◽  
Jordan Mertes ◽  
Frans-Jan W. Parmentier ◽  
Mikhail Mastepanov ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Eddy Covariance ◽  
Low Frequency ◽  
Optimization Method ◽  
Co2 Exchange ◽  
Aerial Photographs ◽  
Strong Increase ◽  
Vulnerability To Climate Change ◽  
Flux Measurements ◽  
Ice Wedge

Abstract. The large spatial variability in Arctic tundra complicates the representative assessment of CO2 budgets. Accurate measurements of these heterogeneous landscapes are, however, essential to understanding their vulnerability to climate change. We surveyed a polygonal tundra lowland on Svalbard with an unmanned aerial vehicle (UAV) that mapped ice-wedge morphology to complement eddy covariance (EC) flux measurements of CO2. The analysis of spectral distributions showed that conventional EC methods do not accurately capture the turbulent CO2 exchange with a spatially heterogeneous surface that typically features small flux magnitudes. Nonlocal (low-frequency) flux contributions were especially pronounced during snowmelt and introduced a large bias of −46 gC m−2 to the annual CO2 budget in conventional methods (the minus sign indicates a higher uptake by the ecosystem). Our improved flux calculations with the ogive optimization method indicated that the site was a strong sink for CO2 in 2015 (−82 gC m−2). Due to differences in light-use efficiency, wetter areas with low-centered polygons sequestered 47 % more CO2 than drier areas with flat-centered polygons. While Svalbard has experienced a strong increase in mean annual air temperature of more than 2 K in the last few decades, historical aerial photographs from the site indicated stable ice-wedge morphology over the last 7 decades. Apparently, warming has thus far not been sufficient to initiate strong ice-wedge degradation, possibly due to the absence of extreme heat episodes in the maritime climate on Svalbard. However, in Arctic regions where ice-wedge degradation has already initiated the associated drying of landscapes, our results suggest a weakening of the CO2 sink in polygonal tundra.

scholarly journals Interannual sea–air CO<sub>2</sub> flux variability from an observation-driven ocean mixed-layer scheme

2014 ◽  
Vol 11 (17) ◽  
pp. 4599-4613 ◽  
Author(s):  
C. Rödenbeck ◽  
D. C. E. Bakker ◽  
N. Metzl ◽  
A. Olsen ◽  
C. Sabine ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Atmospheric Oxygen ◽  
Large Fraction ◽  
Co2 Flux ◽  
Co2 Exchange ◽  
Co2 Partial Pressure ◽  
Surface Ocean ◽  
The North ◽  
Ocean Carbon ◽  
Carbon Dioxide Co2

Abstract. Interannual anomalies in the sea–air carbon dioxide (CO2) exchange have been estimated from surface-ocean CO2 partial pressure measurements. Available data are sufficient to constrain these anomalies in large parts of the tropical and North Pacific and in the North Atlantic, in some areas covering the period from the mid 1980s to 2011. Global interannual variability is estimated as about 0.31 Pg C yr−1 (temporal standard deviation 1993–2008). The tropical Pacific accounts for a large fraction of this global variability, closely tied to El Niño–Southern Oscillation (ENSO). Anomalies occur more than 6 months later in the east than in the west. The estimated amplitude and ENSO response are roughly consistent with independent information from atmospheric oxygen data. This both supports the variability estimated from surface-ocean carbon data and demonstrates the potential of the atmospheric oxygen signal to constrain ocean biogeochemical processes. The ocean variability estimated from surface-ocean carbon data can be used to improve land CO2 flux estimates from atmospheric inversions.

scholarly journals Assessing the spatial variability in peak season CO<sub>2</sub> exchange characteristics across the Arctic tundra using a light response curve parameterization

2014 ◽  
Vol 11 (17) ◽  
pp. 4897-4912 ◽  
Author(s):  
H. N. Mbufong ◽  
M. Lund ◽  
M. Aurela ◽  
T. R. Christensen ◽  
W. Eugster ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Response Curve ◽  
Dark Respiration ◽  
Light Response ◽  
Arctic Tundra ◽  
Co2 Exchange ◽  
The Arctic ◽  
Model Parameters ◽  
Light Saturation ◽  
Light Response Curve

Abstract. This paper aims to assess the spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64–74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE–irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (α), (d) NEE when light is at 1000 μmol m−2 s−1 (Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000 and Psat, thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.

scholarly journals Climatic Trends in Hail Precipitation in France: Spatial, Altitudinal, and Temporal Variability

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Lucía Hermida ◽  
José Luis Sánchez ◽  
Laura López ◽  
Claude Berthet ◽  
Jean Dessens ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Kendall Test ◽  
Spatial And Temporal Variability ◽  
Positive Trend ◽  
High Concentration ◽  
Entire Area ◽  
Orographic Effects ◽  
June July ◽  
Pearson Correlations

Hail precipitation is characterized by enhanced spatial and temporal variability. Association Nationale d’Etude et de Lutte contre les Fléaux Atmosphériques (ANELFA) installed hailpad networks in the Atlantic and Midi-Pyrénées regions of France. Historical data of hail variables from 1990 to 2010 were used to characterize variability. A total of 443 stations with continuous records were chosen to obtain a first approximation of areas most affected by hail. The Cressman method was selected for this purpose. It was possible to find relationships between spatial distributions of the variables, which are supported by obtained Pearson correlations. Monthly and annual trends were examined using the Mann-Kendall test for each of the total affected hailpads. There were 154 pads with a positive trend; most were located between Tarbes and Saint-Gaudens. We found 177 pads with a negative trend, which were largely south of a pine forest in Landes. The remainder of the study area showed an elevated spatial variability with no pattern, even between relatively close hailpads. A similar pattern was found in Lérida (Spain) and Southeast France. In the entire area, monthly trends were predominantly negative in June, July, and August, whereas May had a positive trend; again, however, there was no spatial pattern. There was a high concentration of hailpads with positive trend near the Pyrenees, probably owing to orographic effects, and if we apply cluster analysis with the Mann-Kendall values, the spatial variability is accentuated for stations at higher altitude.

scholarly journals Interannual sea–air CO<sub>2</sub> flux variability from an observation-driven ocean mixed-layer scheme

2014 ◽  
Vol 11 (2) ◽  
pp. 3167-3207 ◽  
Author(s):  
C. Rödenbeck ◽  
D. C. E. Bakker ◽  
N. Metzl ◽  
A. Olsen ◽  
C. Sabine ◽  
...  
Keyword(s):  
Atmospheric Oxygen ◽  
Large Fraction ◽  
Co2 Flux ◽  
Co2 Exchange ◽  
Co2 Partial Pressure ◽  
Surface Ocean ◽  
Independent Information ◽  
Northern Pacific ◽  
Ocean Carbon ◽  
Carbon Dioxide Co2

Abstract. Interannual anomalies in the sea–air carbon dioxide (CO2) exchange have been estimated from surface-ocean CO2 partial pressure measurements. Available data are sufficient to constrain these anomalies in large parts of the tropical and Northern Pacific and in the Northern Atlantic, in some areas since the mid 1980s to 2011. Global interannual variability is estimated as about 0.31 Pg C yr−1 (temporal standard deviation 1993–2008). The tropical Pacific accounts for a large fraction of this global variability, closely tied to ENSO. Anomalies occur more than 6 months later in the East than in the West. The estimated amplitude and ENSO response are consistent with independent information from atmospheric oxygen data. Despite discrepancies in detail, this both supports the variability estimated from surface-ocean carbon data, and demonstrates the potential of the atmospheric oxygen signal to constrain ocean biogeochemical processes. The ocean variability estimated from surface-ocean carbon data can be used to improve land CO2 flux estimates from atmospheric inversions.

scholarly journals Spatial Disaggregation of Mean Areal Rainfall Using Gibbs Sampling

2012 ◽  
Vol 13 (1) ◽  
pp. 324-337 ◽  
Author(s):  
P. Gagnon ◽  
A. N. Rousseau ◽  
A. Mailhot ◽  
D. Caya
Keyword(s):  
Spatial Structure ◽  
Spatial Variability ◽  
Gibbs Sampling ◽  
Convective Available Potential Energy ◽  
Daily Rainfall ◽  
Stage Iv ◽  
Data Series ◽  
Model Parameters ◽  
Climate Projections ◽  
High Resolution Data

Abstract Precipitation has a high spatial variability, and thus some modeling applications require high-resolution data (&lt;10 km). Unfortunately, in some cases, such as meteorological forecasts and future regional climate projections, only spatial averages over large areas are available. While some attention has been given to the disaggregation of mean areal precipitation estimates, the computation of a disaggregated field with a realistic spatial structure remains a difficult task. This paper describes the development of a statistical disaggregation model based on Gibbs sampling. The model disaggregates 45.6-km-resolution rainfall fields to grids with pixel sizes ranging from 3.8 to 22.8 km. The model is conceptually simple, as the algorithm is straightforward to compute with only a few parameters to estimate. The rainfall depth at each grid pixel is related to the depths of the neighboring pixels, while the spatial variability is related to the convective available potential energy (CAPE) field. The model is developed using daily rainfall data over a 40 000-km2 area located in the southeastern United States. Four-kilometer-resolution rainfall estimates obtained from NCEP’s stage IV analysis were used to estimate the model parameters (2002–04) and as a reference to validate the disaggregated fields (2005/06). Results show that the model accurately simulates rainfall depths and the spatial structure of the observed field. Because the model has low computational requirements, an ensemble of disaggregated data series can be generated.

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