Warming effects on the urban hydrology in cold climate regions

While approximately 338 million people in the Northern hemisphere live in regions that are regularly snow covered in winter, there is little hydro-climatologic knowledge in the cities impacted by snow. Using observations and modelling we have evaluated the energy and water exchanges of four cities that are exposed to wintertime snow. We show that the presence of snow critically changes the impact that city design has on the local-scale hydrology and climate. After snow melt, the cities return to being strongly controlled by the proportion of built and vegetated surfaces. However in winter, the presence of snow masks the influence of the built and vegetated fractions. We show how inter-year variability of wintertime temperature can modify this effect of snow. With increasing temperatures, these cities could be pushed towards very different partitioning between runoff and evapotranspiration. We derive the dependency of wintertime runoff on this warming effect in combination with the effect of urban densification.Peer reviewe

Comparisons between SCIAMACHY atmospheric CO₂ retrieved using (FSI) WFM-DOAS to ground based FTIR data and the TM3 chemistry transport model

International audienceAtmospheric CO2 concentrations, retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS), are compared to ground based Fourier Transform Infrared (FTIR) data and to the output from a global chemistry-transport model. Analysis of the FSI WFM-DOAS retrievals with respect to the ground based FTIR instrument, located at Egbert, Canada, show good agreement with an average negative bias of approximately ?4.0% with a standard deviation of ~3.0%. This bias which exhibits an apparent seasonal trend, is of unknown origin, though slight differences between the averaging kernels of the instruments and the limited temporal coverage of the FTIR data may be the cause. The relative scatter of the retrieved vertical column densities is comparable to the spread of the FTIR measurements themselves. Normalizing the CO2 columns using the surface pressure does not affect the magnitude of this bias although it slightly increases the scatter of the FSI data. Comparisons of the FSI retrievals to the TM3 global chemistry-transport model, performed over four selected Northern Hemisphere scenes show good agreement. The correlation, between the time series of the SCIAMACHY and model monthly scene averages, are ~0.7 or greater, demonstrating the ability of SCIAMACHY to detect seasonal changes in the CO2 distribution. The amplitude of the seasonal cycle, peak to peak, observed by SCIAMACHY however, is overestimated by a factor of 2?3, which cannot be explained. The yearly means detected by SCIAMACHY are within 2% of those of the model with the mean difference between the CO2 distributions also approximately 2.0%. Additionally, analysis of the retrieved CO2 distributions reveals structure not evident in the model fields which correlates well with land classification type. From these comparisons, the overall precision and bias of the CO2 columns retrieved by the FSI algorithm are estimated to be close to 1.0% and <4.0% respectively

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Wetlands are one of the most significant natural sources of methane (CH4) to the atmosphere. They emit CH4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH4, in addition to carbon dioxide (CO2). Production of CH4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH4 emissions are thus needed for upscaling observations to estimate present CH4 emissions and for producing scenarios of future atmospheric CH4 concentrations. Aiming at a CH4 model that can be added to models describing peatland carbon cycling, we developed a model called HIMMELI that describes CH4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation and water table depth (WTD), it simulates the concentrations and transport of CH4, CO2 and oxygen (O2) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure, results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and an intercomparison of the modelled and measured CH4 fluxes at Siikaneva, a peatland flux measurement site in Southern Finland. As HIMMELI describes only the CH4-related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that 1) the model is flexible and robust and thus suitable for different environments; 2) the simulated CH4 emissions largely depend on the prescribed rate of anoxic respiration; 3) the sensitivity of the total CH4 emission to other input variables, LAI and WTD, is mainly mediated via the O2 concentrations that affect the CH4 production and oxidation rates; 4) with given input respiration, the peat column description does not affect significantly the simulated CH4 emissions

The effects of CO2, climate and land-use on terrestrial carbon balance, 1920-1992: An analysis with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system

Drainage of a deep magma reservoir near Mayotte inferred from seismicity and deformation

The dynamics of magma deep in the Earth’s crust are difficult to capture by geophysical monitoring. Since May 2018, a seismically quiet area offshore of Mayotte in the western Indian Ocean has been affected by complex seismic activity, including long-duration, very-long-period signals detected globally. Global Navigation Satellite System stations on Mayotte have also recorded a large surface deflation offshore. Here we analyse regional and global seismic and deformation data to provide a one-year-long detailed picture of a deep, rare magmatic process. We identify about 7,000 volcano-tectonic earthquakes and 407 very-long-period seismic signals. Early earthquakes migrated upward in response to a magmatic dyke propagating from Moho depth to the surface, whereas later events marked the progressive failure of the roof of a magma reservoir, triggering its resonance. An analysis of the very-long-period seismicity and deformation suggests that at least 1.3 km3 of magma drained from a reservoir of 10 to 15 km diameter at 25 to 35 km depth. We demonstrate that such deep offshore magmatic activity can be captured without any on-site monitoring

Spin dependent structure function g_1 at low x and low Q^2

Theoretical description of the spin dependent structure function g_1(x,Q^2) in the region of low values of x and Q^2 is presented. It contains the Vector Meson Dominance contribution and the QCD improved parton model suitably extended to the low Q^2 domain. Theoretical predictions are compared with the recent experimental data in the low x, low Q^2 region

Different behaviour of the spin structure functions g1(x)g_1(x) and h1(x)h_1(x) at x→0x\to 0

We consider low-$x$ behaviour of the spin structure functions $g_1(x)$ and $h_1(x)$ in the unitarized chiral quark model which combines ideas on the constituent quark structure of hadrons with a geometrical scattering picture and unitarity. A nondiffractive singular low-$x$ dependence of $g^p_1(x)$ and $g_1^n(x)$ indicated by the recent SMC experimental data is described. A diffractive type smooth behaviour of $h_1(x)$ is predicted at small $x$. The expectations for the double-spin asymmetries in the low-mass Drell-Yan production at RHIC in the central region are discussed alongside.Comment: LaTeX, 10 pages, 2 figure

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

Reduced insulin secretion correlates with decreased expression of exocytotic genes in pancreatic islets from patients with type 2 diabetes.

Reduced insulin release has been linked to defect exocytosis in β-cells. However, whether expression of genes suggested to be involved in the exocytotic process (exocytotic genes) is altered in pancreatic islets from patients with type 2 diabetes (T2D), and correlate to insulin secretion, needs to be further investigated. Analysing expression levels of 23 exocytotic genes using microarray revealed reduced expression of five genes in human T2D islets (χ(2)=13.25; p<0.001). Gene expression of STX1A, SYT4, SYT7, SYT11, SYT13, SNAP25 and STXBP1 correlated negatively to in vivo measurements of HbA1c levels and positively to glucose stimulated insulin secretion (GSIS) in vitro in human islets. STX1A, SYT4 and SYT11 protein levels correspondingly decreased in human T2D islets. Moreover, silencing of SYT4 and SYT13 reduced GSIS in INS1-832/13 cells. Our data support that reduced expression of exocytotic genes contributes to impaired insulin secretion, and suggest decreased expression of these genes as part of T2D pathogenesis

Potential, core-level and d band shifts at transition metal surfaces

We have extended the validity of the correlation between the surface 3d-core-level shift (SCLS) and the surface d band shift (SDBS) to the entire 4d transition metal series and to the neighboring elements Sr and Ag via accurate first-principles calculations. We find that the correlation is quasilinear and robust with respect to the differencies both between initial and final-state calculations of the SCLS's and two distinct measures of the SDBS's. We show that despite the complex spatial dependence of the surface potential shift (SPS) and the location of the 3d and 4d orbitals in different regions of space, the correlation exists because the sampling of the SPS by the 3d and 4d orbitals remains similar. We show further that the sign change of the SCLS's across the transition series does indeed arise from the d band-narrowing mechanism previously proposed. However, while in the heavier transition metals the predicted increase of d electrons in the surface layer relative to the bulk arises primarily from transfers from s and p states to d states within the surface layer, in the lighter transition metals the predicted decrease of surface d electrons arises primarily from flow out into the vacuum.Comment: RevTex, 22 pages, 5 figures in uufiles form, to appear in Phys.Rev.