Atmospheric circulation as a source of uncertainty in climate change projections

The evidence for anthropogenic climate change continues to strengthen, and concerns about severe weather events are increasing. As a result, scientific interest is rapidly shifting from detection and attribution of global climate change to prediction of its impacts at the regional scale. However, nearly everything we have any confidence in when it comes to climate change is related to global patterns of surface temperature, which are primarily controlled by thermodynamics. In contrast, we have much less confidence in atmospheric circulation aspects of climate change, which are primarily controlled by dynamics and exert a strong control on regional climate. Model projections of circulation-related fields, including precipitation, show a wide range of possible outcomes, even on centennial timescales. Sources of uncertainty include low-frequency chaotic variability and the sensitivity to model error of the circulation response to climate forcing. As the circulation response to external forcing appears to project strongly onto existing patterns of variability, knowledge of errors in the dynamics of variability may provide some constraints on model projections. Nevertheless, higher scientific confidence in circulation-related aspects of climate change will be difficult to obtain. For effective decision-making, it is necessary to move to a more explicitly probabilistic, risk-based approach.

In silico identification and three-dimensional modelling of the missense mutation in ADAMTS2 in a sheep flock with dermatosparaxis

Background Dermatosparaxis (Ehlers–Danlos syndrome in humans) is characterized by extreme fragility of the skin. It is due to the lack of mature collagen caused by a failure in the enzymatic processing of procollagen I. We investigated the condition in a commercial sheep flock. Hypothesis/Objectives Mutations in the ADAM metallopeptidase with thrombospondin type 1 motif, 2 (ADAMTS2) locus, are involved in the development of dermatosparaxis in humans, cattle and the dorper sheep breed; consequently, this locus was investigated in the flock. Animals A single affected lamb, its dam, the dam of a second affected lamb and the rams in the flock were studied. Methods DNA was purified from blood, PCR primers were used to detect parts of the ADAMS2 gene and nucleotide sequencing was performed using Sanger's procedure. Skin samples were examined using standard histology procedures. Results A missense mutation was identified in the catalytic domain of ADAMTS2. The mutation is predicted to cause the substitution in the mature ADAMTS2 of a valine molecule by a methionine molecule (V15M) affecting the catalytic domain of the enzyme. Both the ‘sorting intolerant from tolerant’ (SIFT) and the PolyPhen-2 methodologies predicted a damaging effect for the mutation. Three-dimensional modelling suggested that this mutation may alter the stability of the protein folding or distort the structure, causing the protein to malfunction. Conclusions and clinical importance Detection of the mutation responsible for the pathology allowed us to remove the heterozygote ram, thus preventing additional cases in the flock.

The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

Analysis of the regional pattern of sea level change due to ocean dynamics and density changes for 1993-2099 in observations and CMIP5 AOGCMs

Predictions of twenty-first century sea level change show strong regional variation. Regional sea level change observed by satellite altimetry since 1993 is also not spatially homogenous. By comparison with historical and pre-industrial control simulations using the atmosphere–ocean general circulation models (AOGCMs) of the CMIP5 project, we conclude that the observed pattern is generally dominated by unforced (internal generated) variability, although some regions, especially in the Southern Ocean, may already show an externally forced response. Simulated unforced variability cannot explain the observed trends in the tropical Pacific, but we suggest that this is due to inadequate simulation of variability by CMIP5 AOGCMs, rather than evidence of anthropogenic change. We apply the method of pattern scaling to projections of sea level change and show that it gives accurate estimates of future local sea level change in response to anthropogenic forcing as simulated by the AOGCMs under RCP scenarios, implying that the pattern will remain stable in future decades. We note, however, that use of a single integration to evaluate the performance of the pattern-scaling method tends to exaggerate its accuracy. We find that ocean volume mean temperature is generally a better predictor than global mean surface temperature of the magnitude of sea level change, and that the pattern is very similar under the different RCPs for a given model. We determine that the forced signal will be detectable above the noise of unforced internal variability within the next decade globally and may already be detectable in the tropical Atlantic.

A new understanding of El Niño's impact over East Asia: dominance of the ENSO combination mode

Previous studies have shown that the Indo-Pacific atmospheric response to ENSO comprises two dominant modes of variability: a meridionally quasi-symmetric response (independent from the annual cycle) and an anti-symmetric response (arising from the nonlinear atmospheric interaction between ENSO variability and the annual cycle), referred to as the combination mode (C-Mode). This study demonstrates that the direct El Niño signal over the tropics is confined to the equatorial region and has no significant impact on the atmospheric response over East Asia. The El Niño-associated equatorial anomalies can be expanded towards off-equatorial regions by the C-Mode through ENSO’s interaction with the annual cycle. The C-Mode is the prime driver for the development of an anomalous low-level anticyclone over the western North Pacific (WNP) during the El Niño decay phase, which usually transports more moisture to East Asia and thereby causes more precipitation over southern China. We use an Atmospheric General Circulation Model that well reproduces the WNP anticyclonic anomalies when both El Niño sea surface temperature (SST) anomalies as well as the SST annual cycle are prescribed as boundary conditions. However, no significant WNP anticyclonic circulation anomaly appears during the El Niño decay phase when excluding the SST annual cycle. Our analyses of observational data and model experiments suggest that the annual cycle plays a key role in the East Asian climate anomalies associated with El Niño through their nonlinear atmospheric interaction. Hence, a realistic simulation of the annual cycle is crucial in order to correctly capture the ENSO-associated climate anomalies over East Asia.

An assessment of the impact of local processes on dust lifting in martian climate models

Simulation of the lifting of dust from the planetary surface is of substantially greater importance on Mars than on Earth, due to the fundamental role that atmospheric dust plays in the former’s climate, yet the dust emission parameterisations used to date in martian global climate models (MGCMs) lag, understandably, behind their terrestrial counterparts in terms of sophistication. Recent developments in estimating surface roughness length over all martian terrains and in modelling atmospheric circulations at regional to local scales (less than O(100 km)) presents an opportunity to formulate an improved wind stress lifting parameterisation. We have upgraded the conventional scheme by including the spatially varying roughness length in the lifting parameterisation in a fully consistent manner (thereby correcting a possible underestimation of the true threshold level for wind stress lifting), and used a modification to account for deviations from neutral stability in the surface layer. Following these improvements, it is found that wind speeds at typical MGCM resolution never reach the lifting threshold at most gridpoints: winds fall particularly short in the southern midlatitudes, where mean roughness is large. Sub-grid scale variability, manifested in both the near-surface wind field and the surface roughness, is then considered, and is found to be a crucial means of bridging the gap between model winds and thresholds. Both forms of small-scale variability contribute to the formation of dust emission ‘hotspots’: areas within the model gridbox with particularly favourable conditions for lifting, namely a smooth surface combined with strong near-surface gusts. Such small-scale emission could in fact be particularly influential on Mars, due both to the intense positive radiative feedbacks that can drive storm growth and a strong hysteresis effect on saltation. By modelling this variability, dust lifting is predicted at the locations at which dust storms are frequently observed, including the flushing storm sources of Chryse and Utopia, and southern midlatitude areas from which larger storms tend to initiate, such as Hellas and Solis Planum. The seasonal cycle of emission, which includes a double-peaked structure in northern autumn and winter, also appears realistic. Significant increases to lifting rates are produced for any sensible choices of parameters controlling the sub-grid distributions used, but results are sensitive to the smallest scale of variability considered, which high-resolution modelling suggests should be O(1 km) or less. Use of such models in future will permit the use of a diagnosed (rather than prescribed) variable gustiness intensity, which should further enhance dust lifting in the southern hemisphere in particular.

A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: theoretical analysis

Using a combination of idealized radiative transfer simulations and a case study from the first field campaign of the Saharan Mineral Dust Experiment (SAMUM) in southern Morocco, this paper provides a systematic assessment of the limitations of the widely used Spinning Enhanced Visible and Infrared Imager (SEVIRI) red-green-blue (RGB) thermal infrared dust product. Both analyses indicate that the ability of the product to identify dust, via its characteristic pink coloring, is strongly dependent on the column water vapor, the lower tropospheric lapse rate, and dust altitude. In particular, when column water vapor exceeds ∼20–25 mm, dust presence, even for visible optical depths of the order 0.8, is effectively masked. Variability in dust optical properties also has a marked impact on the imagery, primarily as a result of variability in dust composition. There is a moderate sensitivity to the satellite viewing geometry, particularly in moist conditions. The underlying surface can act to confound the signal seen through variations in spectral emissivity, which are predominantly manifested in the 8.7μm SEVIRI channel. In addition, if a temperature inversion is present, typical of early morning conditions over the Sahara and Sahel, an increased dust loading can actually reduce the pink coloring of the RGB image compared to pristine conditions. Attempts to match specific SEVIRI observations to simulations using SAMUM measurements are challenging because of high uncertainties in surface skin temperature and emissivity. Recommendations concerning the use and interpretation of the SEVIRI RGB imagery are provided on the basis of these findings.

Evaluating nitrogen utilization efficiency of nonpregnant dry cows offered solely fresh cut grass at maintenance levels

The present study aimed to identify key parameters influencing N utilization and develop prediction equations for manure N output (MN), feces N output (FN), and urine N output (UN). Data were obtained under a series of digestibility trials with nonpregnant dry cows fed fresh grass at maintenance level. Grass was cut from 8 different ryegrass swards measured from early to late maturity in 2007 and 2008 (2 primary growth, 3 first regrowth, and 3 second regrowth) and from 2 primary growth early maturity swards in 2009. Each grass was offered to a group of 4 cows and 2 groups were used in each of the 8 swards in 2007 and 2008 for daily measurements over 6 wk; the first group (first 3 wk) and the second group (last 3 wk) assessed early and late maturity grass, respectively. Average values of continuous 3-d data of N intake (NI) and output for individual cows ( = 464) and grass nutrient contents ( = 116) were used in the statistical analysis. Grass N content was positively related to GE and ME contents but negatively related to grass water-soluble carbohydrates (WSC), NDF, and ADF contents ( < 0.01), indicating that accounting for nutrient interrelations is a crucial aspect of N mitigation. Significantly greater ratios of UN:FN, UN:MN, and UN:NI were found with increased grass WSC contents and ratios of N:WSC, N:digestible OM in total DM (DOMD), and N:ME ( < 0.01). Greater NI, animal BW, and grass N contents and lower grass WSC, NDF, ADF, DOMD, and ME concentrations were significantly associated with greater MN, FN, and UN ( < 0.05). The present study highlighted that using grass lower in N and greater in fermentable energy in animals fed solely fresh grass at maintenance level can improve N utilization, reduce N outputs, and shift part of N excretion toward feces rather than urine. These outcomes are highly desirable in mitigation strategies to reduce nitrous oxide emissions from livestock. Equations predicting N output from BW and grass N content explained a similar amount of variability as using NI and grass chemical composition (excluding DOMD and ME), implying that parameters easily measurable in practice could be used for estimating N outputs. In a research environment, where grass DOMD and ME are likely to be available, their use to predict N outputs is highly recommended because they strongly improved of the equations in the current study.

Variability and trends in England and Wales precipitation

The England and Wales precipitation (EWP) dataset is a homogeneous time series of daily accumulations from 1931 to 2014, composed from rain gauge observations spanning the region. The daily regional-average precipitation statistics are shown to be well described by a Weibull distribution, which is used to define extremes in terms of percentiles. Computed trends in annual and seasonal precipitation are sensitive to the period chosen, due to large variability on interannual and decadal timescales. Atmospheric circulation patterns associated with seasonal precipitation variability are identified. These patterns project onto known leading modes of variability, all of which involve displacements of the jet stream and storm-track over the eastern Atlantic. The intensity of daily precipitation for each calendar season is investigated by partitioning all observations into eight intensity categories contributing equally to the total precipitation in the dataset. Contrary to previous results based on shorter periods, no significant trends of the most intense categories are found between 1931 and 2014. The regional-average precipitation is found to share statistical properties common to the majority of individual stations across England and Wales used in previous studies. Statistics of the EWP data are examined for multi-day accumulations up to 10 days, which are more relevant for river flooding. Four recent years (2000, 2007, 2008 and 2012) have a greater number of extreme events in the 3-and 5-day accumulations than any previous year in the record. It is the duration of precipitation events in these years that is remarkable, rather than the magnitude of the daily accumulations.

The atomic structure of low-index surfaces of the intermetallic compound InPd

The intermetallic compound InPd (CsCl type of crystal structure with a broad compositional range) is considered as a candidate catalyst for the steam reforming of methanol. Single crystals of this phase have been grown to study the structure of its three low-index surfaces under ultra-high vacuum conditions, using low energy electron diffraction (LEED), X-ray photoemission spectroscopy (XPS), and scanning tunneling microscopy (STM). During surface preparation, preferential sputtering leads to a depletion of In within the top few layers for all three surfaces. The near-surface regions remain slightly Pd-rich until annealing to ∼580 K. A transition occurs between 580 and 660 K where In segregates towards the surface and the near-surface regions become slightly In-rich above ∼660 K. This transition is accompanied by a sharpening of LEED patterns and formation of flat step-terrace morphology, as observed by STM. Several superstructures have been identified for the different surfaces associated with this process. Annealing to higher temperatures (≥750 K) leads to faceting via thermal etching as shown for the (110) surface, with a bulk In composition close to the In-rich limit of the existence domain of the cubic phase. The Pd-rich InPd(111) is found to be consistent with a Pd-terminated bulk truncation model as shown by dynamical LEED analysis while, after annealing at higher temperature, the In-rich InPd(111) is consistent with an In-terminated bulk truncation, in agreement with density functional theory (DFT) calculations of the relative surface energies. More complex surface structures are observed for the (100) surface. Additionally, individual grains of a polycrystalline sample are characterized by micro-spot XPS and LEED as well as low-energy electron microscopy. Results from both individual grains and “global” measurements are interpreted based on comparison to our single crystals findings, DFT calculations and previous literature.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Mid-holocene and last glacial maximum climate simulations with the IPSL model-part I: comparing IPSLCM5A to IPSLCM4

The climates of the mid-Holocene (MH), 6,000 years ago, and of the Last Glacial Maximum (LGM), 21,000 years ago, have extensively been simulated, in particular in the framework of the Palaeoclimate Modelling Intercomparion Project. These periods are well documented by paleo-records, which can be used for evaluating model results for climates different from the present one. Here, we present new simulations of the MH and the LGM climates obtained with the IPSL_CM5A model and compare them to our previous results obtained with the IPSL_CM4 model. Compared to IPSL_CM4, IPSL_CM5A includes two new features: the interactive representation of the plant phenology and marine biogeochemistry. But one of the most important differences between these models is the latitudinal resolution and vertical domain of their atmospheric component, which have been improved in IPSL_CM5A and results in a better representation of the mid-latitude jet-streams. The Asian monsoon’s representation is also substantially improved. The global average mean annual temperature simulated for the pre-industrial (PI) period is colder in IPSL_CM5A than in IPSL_CM4 but their climate sensitivity to a CO2 doubling is similar. Here we show that these differences in the simulated PI climate have an impact on the simulated MH and LGM climatic anomalies. The larger cooling response to LGM boundary conditions in IPSL_CM5A appears to be mainly due to differences between the PMIP3 and PMIP2 boundary conditions, as shown by a short wave radiative forcing/feedback analysis based on a simplified perturbation method. It is found that the sensitivity computed from the LGM climate is lower than that computed from 2 × CO2 simulations, confirming previous studies based on different models. For the MH, the Asian monsoon, stronger in the IPSL_CM5A PI simulation, is also more sensitive to the insolation changes. The African monsoon is also further amplified in IPSL_CM5A due to the impact of the interactive phenology. Finally the changes in variability for both models and for MH and LGM are presented taking the example of the El-Niño Southern Oscillation (ENSO), which is very different in the PI simulations. ENSO variability is damped in both model versions at the MH, whereas inconsistent responses are found between the two versions for the LGM. Part 2 of this paper examines whether these differences between IPSL_CM4 and IPSL_CM5A can be distinguished when comparing those results to palaeo-climatic reconstructions and investigates new approaches for model-data comparisons made possible by the inclusion of new components in IPSL_CM5A.

The impact of a thermodynamic sea-ice module in the COSMO numerical weather prediction model on simulations for the Laptev Sea, Siberian Arctic

Previous versions of the Consortium for Small-scale Modelling (COSMO) numerical weather prediction model have used a constant sea-ice surface temperature, but observations show a high degree of variability on sub-daily timescales. To account for this, we have implemented a thermodynamic sea-ice module in COSMO and performed simulations at a resolution of 15 km and 5 km for the Laptev Sea area in April 2008. Temporal and spatial variability of surface and 2-m air temperature are verified by four automatic weather stations deployed along the edge of the western New Siberian polynya during the Transdrift XIII-2 expedition and by surface temperature charts derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. A remarkable agreement between the new model results and these observations demonstrates that the implemented sea-ice module can be applied for short-range simulations. Prescribing the polynya areas daily, our COSMO simulations provide a high-resolution and high-quality atmospheric data set for the Laptev Sea for the period 14-30 April 2008. Based on this data set, we derive a mean total sea-ice production rate of 0.53 km3/day for all Laptev Sea polynyas under the assumption that the polynyas are ice-free and a rate of 0.30 km3/day if a 10-cm-thin ice layer is assumed. Our results indicate that ice production in Laptev Sea polynyas has been overestimated in previous studies.

Interfaces in the acquisition of syntax

We introduce empirical work on Romance language acquisition with respect to the interfaces of syntax with other modules of grammar (internal interfaces) and other domains of cognition (external interfaces). We do so by choosing specific phenomena within the following interfaces: syntax-morphology, syntax-semantics and syn-tax-pragmatics. In the domain of syntax-morphology we focus on grammatical gender, with respect to the syntax-semantics interface we focus on adjectival placement (pre- and post-nominal) and with regard to the syntax-discourse/pragmatics interface we review work on the null/overt subject distribution. Finally, we summarize research on articles, suggesting that articles represent a multiple interface. We provide examples from different types of learners and across the four major Romance languages French, Italian, Portuguese and Spanish. While our central goal is to summarize and generalize across major findings, we will also point to potential problems concerning the interface approach, e.g. the association of particular phenomena with a specific interface and the assumption that internal interfaces are less problematic than external ones.

Abrupt transitions in the NAO control of explosive North Atlantic cyclone development

Explosive cyclones are intense extra-tropical low pressure systems featuring large deepening rates. In the Euro-Atlantic sector, they are a major source of life-threatening weather impacts due to their associated strong wind gusts, heavy precipitation and storm surges. The wintertime variability of the North Atlantic cyclonic activity is primarily modulated by the North Atlantic Oscillation (NAO). In this study, we investigate the interannual and multi-decadal variability of explosive North Atlantic cyclones using track density data from two reanalysis datasets (NCEP and ERA-40) and a control simulation of an atmosphere/ocean coupled General Circulation Model (GCM—ECHAM5/MPIOM1). The leading interannual and multi-decadal modes of variability of explosive cyclone track density are characterized by a strengthening/weakening pattern between Newfoundland and Iceland, which is mainly modulated by the NAO at both timescales. However, the NAO control of interannual cyclone variability is not stationary in time and abruptly fluctuates during periods of 20–25 years long both in NCEP and ECHAM5/MPIOM1. These transitions are accompanied by structural changes in the leading mode of explosive cyclone variability, and by decreased/enhanced baroclinicity over the sub-polar/sub-tropical North Atlantic. The influence of the ocean is apparently important for both the occurrence and persistence of such anomalous periods. In the GCM, the Atlantic Meridional Overturning Circulation appears to influence the large-scale baroclinicity and explosive cyclone development over the North Atlantic. These results permit a better understanding of explosive cyclogenesis variability at different climatic timescales and might help to improve predictions of these hazardous events.