Local-scale urban meteorological parameterization scheme (LUMPS): longwave radiation parameterization and seasonality-related developments

Recent developments to the Local-scale Urban Meteorological Parameterization Scheme (LUMPS), a simple model able to simulate the urban energy balance, are presented. The major development is the coupling of LUMPS to the Net All-Wave Radiation Parameterization (NARP). Other enhancements include that the model now accounts for the changing availability of water at the surface, seasonal variations of active vegetation, and the anthropogenic heat flux, while maintaining the need for only commonly available meteorological observations and basic surface characteristics. The incoming component of the longwave radiation (L↓) in NARP is improved through a simple relation derived using cloud cover observations from a ceilometer collected in central London, England. The new L↓ formulation is evaluated with two independent multiyear datasets (Łódź, Poland, and Baltimore, Maryland) and compared with alternatives that include the original NARP and a simpler one using the National Climatic Data Center cloud observation database as input. The performance for the surface energy balance fluxes is assessed using a 2-yr dataset (Łódź). Results have an overall RMSE < 34 W m−2 for all surface energy balance fluxes over the 2-yr period when

Habitat re-creation and restoration at the landscape scale: woodlands in Wales

The aim of this three year project funded by the Countryside Council for Wales (CCW) is to develop techniques firstly, to refine and update existing targets for habitat restoration and re-creation at the landscape scale and secondly, to develop a GIS-based model for the implementation of those targets at the local scale. Landscape Character Assessment (LCA) is being used to map Landscape Types across the whole of Wales as the first stage towards setting strategic habitat targets. The GIS habitat model uses data from the digital Phase I Habitat Survey for Wales to determine the suitability of individual sites for restoration to specific habitat types, including broadleaf woodland. The long-term aim is to develop a system that strengthens the character of Welsh landscapes and provides real biodiversity benefits based upon realistic targets given limited resources for habitat restoration and re-creation.

Arthropod community structure in pastures of an island archipelago (Azores): looking for local-regional species richness patterns at fine-scales

The arthropod species richness of pastures in three Azorean islands was used to examine the relationship between local and regional species richness over two years. Two groups of arthropods, spiders and sucking insects, representing two functionally different but common groups of pasture invertebrates were investigated. The local-regional species richness relationship was assessed over relatively fine scales: quadrats (= local scale) and within pastures (= regional scale). Mean plot species richness was used as a measure of local species richness (= alpha diversity) and regional species richness was estimated at the pasture level (= gamma diversity) with the 'first-order-Jackknife' estimator. Three related issues were addressed: (i) the role of estimated regional species richness and variables operating at the local scale (vegetation structure and diversity) in determining local species richness; (ii) quantification of the relative contributions of alpha and beta diversity to regional diversity using additive partitioning; and (iii) the occurrence of consistent patterns in different years by analysing independently between-year data. Species assemblages of spiders were saturated at the local scale (similar local species richness and increasing beta-diversity in richer regions) and were more dependent on vegetational structure than regional species richness. Sucking insect herbivores, by contrast, exhibited a linear relationship between local and regional species richness, consistent with the proportional sampling model. The patterns were consistent between years. These results imply that for spiders local processes are important, with assemblages in a particular patch being constrained by habitat structure. In contrast, for sucking insects, local processes may be insignificant in structuring communities.

Realism of rainfall in a very high-resolution regional climate model

The realistic representation of rainfall on the local scale in climate models remains a key challenge. Realism encompasses the full spatial and temporal structure of rainfall, and is a key indicator of model skill in representing the underlying processes. In particular, if rainfall is more realistic in a climate model, there is greater confidence in its projections of future change. In this study, the realism of rainfall in a very high-resolution (1.5 km) regional climate model (RCM) is compared to a coarser-resolution 12-km RCM. This is the first time a convection-permitting model has been run for an extended period (1989–2008) over a region of the United Kingdom, allowing the characteristics of rainfall to be evaluated in a climatological sense. In particular, the duration and spatial extent of hourly rainfall across the southern United Kingdom is examined, with a key focus on heavy rainfall. Rainfall in the 1.5-km RCM is found to be much more realistic than in the 12-km RCM. In the 12-km RCM, heavy rain events are not heavy enough, and tend to be too persistent and widespread. While the 1.5-km model does have a tendency for heavy rain to be too intense, it still gives a much better representation of its duration and spatial extent. Long-standing problems in climate models, such as the tendency for too much persistent light rain and errors in the diurnal cycle, are also considerably reduced in the 1.5-km RCM. Biases in the 12-km RCM appear to be linked to deficiencies in the representation of convection.

Conditioning model output statistics of regional climate model precipitation on circulation patterns

Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potentially improves the usability of the output for hydrological impact studies. However, a further downscaling or interpolation of precipitation from RCMs is often needed to match the precipitation characteristics at the local scale. This study analysed three Model Output Statistics (MOS) techniques to adjust RCM precipitation; (1) a simple direct method (DM), (2) quantile-quantile mapping (QM) and (3) a distribution-based scaling (DBS) approach. The modelled precipitation was daily means from 16 RCMs driven by ERA40 reanalysis data over the 1961–2000 provided by the ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts) project over a small catchment located in the Midlands, UK. All methods were conditioned on the entire time series, separate months and using an objective classification of Lamb's weather types. The performance of the MOS techniques were assessed regarding temporal and spatial characteristics of the precipitation fields, as well as modelled runoff using the HBV rainfall-runoff model. The results indicate that the DBS conditioned on classification patterns performed better than the other methods, however an ensemble approach in terms of both climate models and downscaling methods is recommended to account for uncertainties in the MOS methods.

Improving a convection-permitting model simulation of a cold air outbreak

A convection-permitting local-area model was used to simulate a cold air outbreak crossing from the Norwegian Sea into the Atlantic Ocean near Scotland. A control model run based on an operational configuration of the Met Office UKV high-resolution (1.5 km grid spacing) NWP model was compared to satellite, aircraft and radar data. While the control model captured the large-scale features of the synoptic situation, it was not able to reproduce the shallow (<1.5 km) stratiform layer to the north of the open cellular convection. Liquid water paths were found to be too low in both the stratiform and convective cloud regions. Sensitivity analyses including a modified boundary-layer diagnosis to generate a more well-mixed boundary layer and inhibition of ice formation to lower temperatures improved cloud morphology and comparisons with observational data. Copyright © 2013 Royal Meteorological Society and British Crown Copyright, the Met Office

Multi-scale sensible heat fluxes in the urban environment from large aperture scintillometry and eddy covariance

Sensible heat fluxes (QH) are determined using scintillometry and eddy covariance over a suburban area. Two large aperture scintillometers provide spatially integrated fluxes across path lengths of 2.8 km and 5.5 km over Swindon, UK. The shorter scintillometer path spans newly built residential areas and has an approximate source area of 2-4 km2, whilst the long path extends from the rural outskirts to the town centre and has a source area of around 5-10 km2. These large-scale heat fluxes are compared with local-scale eddy covariance measurements. Clear seasonal trends are revealed by the long duration of this dataset and variability in monthly QH is related to the meteorological conditions. At shorter time scales the response of QH to solar radiation often gives rise to close agreement between the measurements, but during times of rapidly changing cloud cover spatial differences in the net radiation (Q*) coincide with greater differences between heat fluxes. For clear days QH lags Q*, thus the ratio of QH to Q* increases throughout the day. In summer the observed energy partitioning is related to the vegetation fraction through use of a footprint model. The results demonstrate the value of scintillometry for integrating surface heterogeneity and offer improved understanding of the influence of anthropogenic materials on surface-atmosphere interactions.

First look at changes in flood hazard in the inter-sectoral impact model intercomparison project ensemble

Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global scale. As an indicator of flood hazard we looked at changes in the 30-y return level of 5-d average peak flows under representative concentration pathway RCP8.5 at the end of this century. Not everywhere does climate change result in an increase in flood hazard: decreases in the magnitude and frequency of the 30-y return level of river flow occur at roughly one-third (20-45%) of the global land grid points, particularly in areas where the hydro-graph is dominated by the snowmelt flood peak in spring. In most model experiments, however, an increase in flooding frequency was found in more than half of the grid points. The current 30-y flood peak is projected to occur in more than 1 in 5 y across 5-30% of land grid points. The large-scale patterns of change are remarkably consistent among impact models and even the driving climate models, but at local scale and in individual river basins there can be disagreement even on the sign of change, indicating large modeling uncertainty which needs to be taken into account in local adaptation studies.

Catchment-scale modelling of flow and nutrient transport in the Chalk unsaturated zone

The unsaturated zone exerts a major control on the delivery of nutrients to Chalk streams, yet flow and transport processes in this complex, dual-porosity medium have remained controversial. A major challenge arises in characterising these processes, both at the detailed mechanistic level and at an appropriate level for inclusion within catchment-scale models for nutrient management. The lowland catchment research (LOCAR) programme in the UK has provided a unique set of comprehensively instrumented groundwater-dominated catchments. Of these, the Pang and Lambourn, tributaries of the Thames near Reading, have been a particular focus for research into subsurface processes and surface water-groundwater interactions. Data from LOCAR and other sources, along with a new dual permeability numerical model of the Chalk, have been used to explore the relative roles of matrix and fracture flow within the unsaturated zone and resolve conflicting hypotheses of response. From the improved understanding gained through these explorations, a parsimonious conceptualisation of the general response of flow and transport within the Chalk unsaturated zone was formulated. This paper summarises the modelling and data findings of these explorations, and describes the integration of the new simplified unsaturated zone representation with a catchment-scale model of nutrients (INCA), resulting in a new model for catchment-scale flow and transport within Chalk systems: INCA-Chalk. This model is applied to the Lambourn, and results, including hindcast and forecast simulations, are presented. These clearly illustrate the decadal time-scales that need to be considered in the context of nutrient management and the EU Water Framework Directive. (C) 2007 Elsevier B.V. All rights reserved.

Magnetic cloud distortion resulting from propagation through a structured solar wind: Models and observations

Numerical simulations of magnetic clouds (MCs) propagating through a structured solar wind suggest that MC-associated magnetic flux ropes are highly distorted by inhomogeneities in the ambient medium. In particular, a solar wind configuration of fast wind from high latitudes and slow wind at low latitudes, common at periods close to solar minimum, should distort the cross section of magnetic clouds into concave-outward structures. This phenomenon has been reported in observations of shock front orientations, but not in the body of magnetic clouds. In this study an analytical magnetic cloud model based upon a kinematically distorted flux rope is modified to simulate propagation through a structured medium. This new model is then used to identify specific time series signatures of the resulting concave-outward flux ropes. In situ observations of three well studied magnetic clouds are examined with comparison to the model, but the expected concave-outward signatures are not present. Indeed, the observations are better described by the convex-outward flux rope model. This may be due to a sharp latitudinal transition from fast to slow wind, resulting in a globally concave-outward flux rope, but with convex-outward signatures on a local scale.

C–H local modes in cyclobutene. II. Laser photoacoustic studies 10 000–17 000 cm−1. Vibrational structure and C–H local mode dynamics

In part I of this study [Baggott, Clase, and Mills, Spectrochim. Acta Part A 42, 319 (1986)] we presented FTIR spectra of gas phase cyclobutene and modeled the v=1–3 stretching states of both olefinic and methylenic C–H bonds in terms of a local mode model. In this paper we present some improvements to our original model and make use of recently derived ‘‘x,K relations’’ to find the equivalent normal mode descriptions. The use of both the local mode and normal mode approaches to modeling the vibrational structure is described in some detail. We present evidence for Fermi resonance interactions between the methylenic C–H stretch overtones and ring C–C stretch vibrations, revealed in laser photoacoustic spectra in the v=4–6 region. An approximate model vibrational Hamiltonian is proposed to explain the observed structure and is used to calculate the dynamics of the C–H stretch local mode decay resulting from interaction with lower frequency ring modes. The implications of our experimental and theoretical studies for mode‐selective photochemistry are discussed briefly.

Constraining a North Atlantic Ocean general circulation model with chlorofluorocarbon observations

Measurements of anthropogenic tracers such as chlorofluorocarbons and tritium must be quantitatively combined with ocean general circulation models as a component of systematic model development. The authors have developed and tested an inverse method, using a Green's function, to constrain general circulation models with transient tracer data. Using this method chlorofluorocarbon-11 and -12 (CFC-11 and -12) observations are combined with a North Atlantic configuration of the Miami Isopycnic Coordinate Ocean Model with 4/3 degrees resolution. Systematic differences can be seen between the observed CFC concentrations and prior CFC fields simulated by the model. These differences are reduced by the inversion, which determines the optimal gas transfer across the air-sea interface, accounting for uncertainties in the tracer observations. After including the effects of unresolved variability in the CFC fields, the model is found to be inconsistent with the observations because the model/data misfit slightly exceeds the error estimates. By excluding observations in waters ventilated north of the Greenland-Scotland ridge (sigma (0) < 27.82 kg m(-3); shallower than about 2000 m), the fit is improved, indicating that the Nordic overflows are poorly represented in the model. Some systematic differences in the model/data residuals remain and are related, in part, to excessively deep model ventilation near Rockall and deficient ventilation in the main thermocline of the eastern subtropical gyre. Nevertheless, there do not appear to be gross errors in the basin-scale model circulation. Analysis of the CFC inventory using the constrained model suggests that the North Atlantic Ocean shallower than about 2000 m was near 20% saturated in the mid-1990s. Overall, this basin is a sink to 22% of the total atmosphere-to-ocean CFC-11 flux-twice the global average value. The average water mass formation rates over the CFC transient are 7.0 and 6.0 Sv (Sv = 10(6) m(3) s(-1)) for subtropical mode water and subpolar mode water, respectively.

Statistical downscaling of river flows

An extensive statistical ‘downscaling’ study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily ‘integrated approach’. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.

Pollination and other ecosystem services produced by mobile organisms: a conceptual framework for the effects of land-use change

Many ecosystem services are delivered by organisms that depend on habitats that are segregated spatially or temporally from the location where services are provided. Management of mobile organisms contributing to ecosystem services requires consideration not only of the local scale where services are delivered, but also the distribution of resources at the landscape scale, and the foraging ranges and dispersal movements of the mobile agents. We develop a conceptual model for exploring how one such mobile-agent-based ecosystem service (MABES), pollination, is affected by land-use change, and then generalize the model to other MABES. The model includes interactions and feedbacks among policies affecting land use, market forces and the biology of the organisms involved. Animal-mediated pollination contributes to the production of goods of value to humans such as crops; it also bolsters reproduction of wild plants on which other services or service-providing organisms depend. About one-third of crop production depends on animal pollinators, while 60-90% of plant species require an animal pollinator. The sensitivity of mobile organisms to ecological factors that operate across spatial scales makes the services provided by a given community of mobile agents highly contextual. Services vary, depending on the spatial and temporal distribution of resources surrounding the site, and on biotic interactions occurring locally, such as competition among pollinators for resources, and among plants for pollinators. The value of the resulting goods or services may feed back via market-based forces to influence land-use policies, which in turn influence land management practices that alter local habitat conditions and landscape structure. Developing conceptual models for MABES aids in identifying knowledge gaps, determining research priorities, and targeting interventions that can be applied in an adaptive management context.