ALBERT

Description: Within the context of predicted and observed increase in droughts and floods with climate change, large summer floods are likely to become more frequent. These extreme events can alter typical biogeochemical patterns in coastal systems. The extreme Elbe River flood in June, 2013 not only caused major damages in several European countries, but also generated large scale biogeochemical changes in the Elbe Estuary and the adjacent German Bight. Due to a number of well documented and unusual atmospheric conditions, the early summer of 2013 in Central and Eastern Europe was colder and wetter than usual, with saturated soils, and higher than average cumulative precipitation. Additional precipitation at the end of May, and beginning of June, 2013, caused widespread floods within the Danube and Elbe Rivers, as well as billions of euros in damages. The floods generated the largest summer discharge on record within the last 140 years. The high-frequency monitoring network in the German Bight available within the Coastal Observing System for Northern and Arctic Seas (COSYNA) captured the flood influence on the German Bight. Monitoring data from a FerryBox station in the Elbe Estuary (Cuxhaven) and from a FerryBox platform aboard the M/V Funny Girl Ferry (traveling between Büsum and Helgoland) documented the salinity changes on the German Bight, which persisted for about 2 months after the peak discharge. The flood generated a large influx of nutrients, dissolved and particulate organic carbon on the coast. These conditions subsequently led to the onset of a chlorophyll bloom within the German Bight, observed by dissolved oxygen supersaturation, and higher than usual pH in surface coastal waters. The prolonged stratification also led to widespread bottom water dissolved oxygen depletion, unusual for the south eastern German Bight in the summer.

Description: NASAs Carbon Monitoring System (CMS) Flux Pilot Project (FPP) was designed to better understand contemporary carbon fluxes by bringing together state-of-the art models with remote sensing datasets. Here we report on simulations using NASAs Goddard Earth Observing System Model, version 5 (GEOS-5) which was used to evaluate the consistency of two different sets of observationally constrained land and ocean fluxes with atmospheric CO2 records. Despite the strong data constraint, the average difference in annual terrestrial biosphere flux between the two land (NASA Ames CASA and CASA-GFED) models is 1.7 Pg C for 2009-2010. Ocean models (NOBM and ECCO2-Darwin) differ by 35 in their global estimates of carbon flux with particularly strong disagreement in high latitudes. Based upon combinations of terrestrial and ocean fluxes, GEOS-5 reasonably simulated the seasonal cycle observed at northern hemisphere surface sites and by the Greenhouse gases Observing SATellite (GOSAT) while the model struggled to simulate the seasonal cycle at southern hemisphere surface locations. Though GEOS-5 was able to reasonably reproduce the patterns of XCO2 observed by GOSAT, it struggled to reproduce these aspects of AIRS observations. Despite large differences between land and ocean flux estimates, resulting differences in atmospheric mixing ratio were small, typically less than 5 ppmv at the surface and 3 ppmv in the XCO2 column. A statistical analysis based on the variability of observations shows that flux differences of these magnitudes are difficult to distinguish from natural variability, regardless of measurement platform.

Description: Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite 'IBUKI' (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (X(CO2)) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is approx.1132 for 1-yr of the 74 055 GOSAT X(CO2) observations, which indicates that GOSAT provides approx.1132 independent pieces of information about surface fluxes. We quantify the impact of GOSAT's spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.

Description: Offshore wind farms (OWF) is one of the most fast developing areas in wind energy industry. The number of OWF and area they occupy expand rapidly worldwide. According to the wind energy agency WAB only Germany planed to setup about 5000 turbines in North and Baltic Seas. Due to new technology OWF can now be constructed in the regions of 40 meters depth. Particularly in the North Sea the OWF are planned in the regions characterized by strong seasonal stratification, strong tidal currents and rather complex ecosystem with high nutrients concentrations and high primary production. Recent observations and model studies suggest the potential influence of single OWF on vertical structure and currents. In turn clusters of wind farms consisting of hundreds of turbines could result in an accumulative effect on the ecosystem behavior overall. In this study we want to investigate potential effects of OWF on the dynamics of the coast zone by applying newly developed coastal version of FESOM model. This is a three-dimensional model based on mixed unstructured-mesh methods and finite-volume discretization. It is based on three-dimensional primitive equations for the momentum, continuity, and density constituents. Vertically the model uses σ-coordinate system. Unstructured grid consists of quads and triangles zoomed in around the pile to best represent relatively small scale processes, and lower resolution around OWF allows to conduct comparatively large regional studies.