Influence of vascular plant photosynthetic rate on CH4 emission from peat monoliths from southern boreal Sweden

Peat monoliths taken from a boreal peatland system were incubated at two different light intensities to investigate the effect of the photosynthetic rate of vascular plants ( Eriophorum angustifolium ) on net CH₄ emission. The experimental set-up consisted of six replicate monoliths as controls and six where the photosynthetic active radiation (PAR) was reduced by 60%. NEP and total system respiration decreased significantly in response to reduced PAR. No significant changes in CH₄ emission were found, but two different trends were noted. Methane emissions from the shaded monoliths initially seemed to be higher than emissions from the controls. After approximately four weeks the trend was reversed. The pattern may have been caused by "leakage" of organic compounds from inactivated roots that fueled CH₄ production. It is suggested that a new balanced exchange of potential substrate carbon between the plants and the surrounding peat was established. Comparably less easily degradable carbon compounds would then become available for CH₄ production. The fact that there appeared to be an effect of decreased carbon flow on CH₄ emission is further supported by a tendency for lower concentrations of organic acids in porewater in the shaded monoliths at the end of the experiment. These results indicate a possible lagtime on the order of weeks before changes in photosynthesis rates and NEP have an effect onCH₄ emission rates. Nevertheless it confirms the linkage between CO₂ and CH₄ cycling in wetland ecosystems.     

Arctic climate change in 21st century CMIP5 simulations with EC-Earth

The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases.     

Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model

The upper limit of climate predictability in mid and high northern latitudes on seasonal to interannual time scales is investigated by performing two perfect ensemble experiments with the global coupled atmosphere–ocean–sea ice model ECHAM5/MPI-OM. The ensembles consist of six members and are initialized in January and July from different years of the model’s 300-year control integration. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric climate parameters. The predictability of the atmospheric circulation is small except for southeastern Europe, parts of North America and the North Pacific, where significant predictability occurs with a lead time of up to half a year. The predictability of 2 m air temperature shows a large land–sea contrast with highest predictabilities over the sub polar North Atlantic and North Pacific. A combination of relatively high persistence and advection of sea surface temperature anomalies into these areas leads to large predictability. Air temperature over Europe, parts of North America and Asia shows significant predictability of up to half a year in advance. Over the ice-covered Arctic, air temperature is not predictable at time scales exceeding 2 months. Sea ice thickness is highly predictable in the central Arctic mainly due to persistence and in the Labrador Sea due to dynamics. Surface salinity is highly predictable in the Arctic Ocean, northern North Atlantic and North Pacific for several years in advance. We compare the results to the predictability due to persistence and show the importance of dynamical processes for the predictability.     

Economic and distributional impacts of climate change: The case of Ethiopia

Climate change is likely to harm developing economies that generate major portion of their GDP from climate sensitive sectors. This paper computes economy-wide impact of climate change and its distributional consequence with the help of a sector wise disaggregated general equilibrium model using Ethiopia as a case. The projected climate shock reduces output in the sector with the strongest forward and backward linkage to the rest of the economy and redistributes income by changing the returns to inputs owned by various agents. The results suggest that climate change will make the prospect of economic development harder in at least two ways: first, by reducing agricultural production and output in the sectors linked to the agricultural sector, which is likely to reduce Ethiopia's GDP by about 10% from its benchmark level; and second, by raising the degree of income inequality in which the Gini-coefficient increases by 20%, which is likely to further decrease economic growth and fuel poverty. Thus, climate change is expected to increase the fraction of people in poverty by reducing the size of the total pie and redistributing it more unevenly.     

Impact of systematic errors on precise long-baseline kinematic GPS positioning

Many kinematic GPS applications rely on high accuracy, which usually requires the ambiguities to be fixed. Normally, a reference station in the rover’s vicinity is needed for successful ambiguity resolution. Alternatively, a network surrounding the rover and allowing one to derive area correction parameters is needed. Unfortunately, both approaches are not feasible in certain situations. This paper is a contribution to precise kinematic positioning over long baselines. Atmospheric refraction becomes critical in the error budget, but progress has been made to use numerical weather models to derive tropospheric corrections, for instance. The spatial correlation of both ionospheric and tropospheric propagation delays is investigated in this paper and special attention is paid on the systematic error behavior of tropospheric refraction. The principles developed are applied to an extended reliability test of the ambiguities. Finally, it is demonstrated in positioning experiments that kinematic positioning retrieval with fixed ambiguities is actually possible for baselines between 150 and 300 km with an accuracy of approximately 2 cm in post-mission processing.

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Observational and predictive uncertainties for multiple variables in a spatially distributed hydrological model

In this study, uncertainty in model input data (precipitation) and parameters is propagated through a physically based, spatially distributed hydrological model based on the MIKE SHE code. Precipitation uncertainty is accounted for using an ensemble of daily rainfall fields that incorporate four different sources of uncertainty, whereas parameter uncertainty is considered using Latin hypercube sampling. Model predictive uncertainty is assessed for multiple simulated hydrological variables (discharge, groundwater head, evapotranspiration, and soil moisture). Utilizing an extensive set of observational data, effective observational uncertainties for each hydrological variable are assessed. Considering not only model predictive uncertainty but also effective observational uncertainty leads to a notable increase in the number of instances, for which model simulation and observations are in good agreement (e.g., 47% vs. 91% for discharge and 0% vs. 98% for soil moisture). Effective observational uncertainty is in several cases larger than model predictive uncertainty. We conclude that the use of precipitation uncertainty with a realistic spatio‐temporal correlation structure, analyses of multiple variables with different spatial support, and the consideration of observational uncertainty are crucial for adequately evaluating the performance of physically based, spatially distributed hydrological models.     

Aquifer Vulnerability Assessment Based on Sequence Stratigraphic and 39Ar Transport Modeling

A large‐scale groundwater flow and transport model is developed for a deep‐seated (100 to 300 m below ground surface) sedimentary aquifer system. The model is based on a three‐dimensional (3D) hydrostratigraphic model, building on a sequence stratigraphic approach. The flow model is calibrated against observations of hydraulic head and stream discharge while the credibility of the transport model is evaluated against measurements of ³⁹Ar from deep wells using alternative parameterizations of dispersivity and effective porosity. The directly simulated 3D mean age distributions and vertical fluxes are used to visualize the two‐dimensional (2D)/3D age and flux distribution along transects and at the top plane of individual aquifers. The simulation results are used to assess the vulnerability of the aquifer system that generally has been assumed to be protected by thick overlaying clayey units and therefore proposed as future reservoirs for drinking water supply. The results indicate that on a regional scale these deep‐seated aquifers are not as protected from modern surface water contamination as expected because significant leakage to the deeper aquifers occurs. The complex distribution of local and intermediate groundwater flow systems controlled by the distribution of the river network as well as the topographical variation (Tóth 1963) provides the possibility for modern water to be found in even the deepest aquifers.