Enhanced Atlantic subpolar gyre variability through baroclinic threshold in a coarse resolution model

Direct observations, satellite measurements and paleo records reveal strong variability in the Atlantic subpolar gyre on various time scales. Here we show that variations of comparable amplitude can only be simulated in a coupled climate model in the proximity of a dynamical threshold. The threshold and the associated dynamic response is due to a positive feedback involving increased salt transport in the subpolar gyre and enhanced deep convection in its centre. A series of sensitivity experiments is performed with a coarse resolution ocean general circulation model coupled to a statistical-dynamical atmosphere model which in itself does not produce atmospheric variability. To simulate the impact of atmospheric variability, the model system is perturbed with freshwater forcing of varying, but small amplitude and multi-decadal to centennial periodicities and observational variations in wind stress. While both freshwater and wind-stress-forcing have a small direct effect on the strength of the subpolar gyre, the magnitude of the gyre's response is strongly increased in the vicinity of the threshold. Our results indicate that baroclinic self-amplification in the North Atlantic ocean can play an important role in presently observed SPG variability and thereby North Atlantic climate variability on multi-decadal scales.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Climatology of Vb cyclones, physical mechanisms and their impact on extreme precipitation over Central Europe

Cyclones, which develop over the western Mediterranean and move northeastward are a major source of extreme weather and known to be responsible for heavy precipitation over the northern side of the Alpine range and Central Europe. As the relevant processes triggering these so-called Vb events and their impact on extreme precipitation are not yet fully understood, this study focuses on gaining insight into the dynamics of past events. For this, a cyclone detection and tracking tool is applied to the ERA-Interim reanalysis (1979–2013) to identify prominent Vb situations. Precipitation in the ERA-Interim and the E-OBS data sets is used to evaluate case-to-case precipitation amounts and to assess consistency between the two data sets. Both data sets exhibit high variability in precipitation amounts among different Vb events. While only 23 % of all Vb events are associated with extreme precipitation, around 15 % of all extreme precipitation days (99 percentile) over the northern Alpine region and Central Europe are induced by Vb events, although Vb cyclones are rare events (2.3 per year). To obtain a better understanding of the variability within Vb events, the analysis of the 10 heaviest and lowest precipitation Vb events reveals noticeable differences in the state of the atmosphere. These differences are most pronounced in the geopotential height and potential vorticity field, indicating a much stronger cyclone for heavy precipitation events. The related differences in wind direction are responsible for the moisture transport around the Alps and the orographical lifting along the northern slopes of the Alps. These effects are the main reasons for a disastrous outcome of Vb events, and consequently are absent in the Vb events associated with low precipitation. Hence, our results point out that heavy precipitation related to Vb events is mainly related to large-scale dynamics rather than to thermodynamic processes.

Quantifying differences in land use emission estimates implied by definition discrepancies

The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review differences of eLUC quantification methods and apply an Earth System Model (ESM) of Intermediate Complexity to quantify them. We find that the magnitude of effects due to merely conceptual differences between ESM and offline vegetation model-based quantifications is ~ 20 % for today. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate secondary component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offline vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions.

Retreat of top cliff of Kurungnakh Island, Lena Delta, Siberia, Russia, 2010-2014, with links to shapefiles

Thawing-induced cliff top retreat in permafrost landscapes is mainly due to thermo-erosion. Ground-ice-rich permafrost landscapes are specifically vulnerable to thermo-erosion and may show high degradation rates. Within the HGF Alliance Remote Sensing and the FP7 PAGE21 permafrost programs we investigated how SAR and optical remote sensing can contribute to the monitoring of erosion rates of ice-rich cliffs in Arctic Siberia (Lena Delta, Russia). We produced two different vector products: i) Intra-annual cliff top retreat based on TerraSAR-X (TSX) satellite data (2012-2014): High-temporal resolution time series of TSX satellite data allow the inter-annual and intra-annual monitoring of the upper cliff-line retreat also under bad weather conditions and continuous cloud coverage. This published SAR product contains the retreating upper cliff lines of a 1.5 km long part of eroding ice-rich coast of Kurungnakh Island in the central Lena Delta. The upper cliff line was mapped using a thresholding approach for images acquired in the years 2012, 2013 and 2014 for the months June (2013, 2014), July (2013, 2014), August (2012, 2013, 2014) and September (2013, 2014). The cliff top retreat vector product is called 'upper_cliff_TerraSAR-X'. While the 2014 cliff lines show a clear retreat of 2 to 3 m/month, the cliff top lines for 2012 and 2013 are not chronologically ordered. However, lines from the end of the season of a year are always close to the lines from the beginning of the next summer season, indicating low cliff retreat in winter. ii) 4-year cliff top retreat based on optical satellite data (2010-2014): Long-term cliff top retreat could be assessed with two high-spatial resolution optical satellite images (GeoEye-1, 2010-08-05 and Worldview-1, 2014-08-19). The cliff top retreat vector product is called 'upper_cliff_optical'. Results: The long-term cliff top retreat derived from optical satellite data are 35 m cliff retreat within 4 years. The higher-temporal resolution SAR data equivalently show long-term rates of 18 m within 2 years and nearly now degradation activities in winter but maximum erosion rates in summer months.The Intra-seasonal cliff top retreat lines from 2014 show a rate of 2 to 3 m per month.