A comprehensive benchmarking system for evaluating global vegetation models

We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

The effects of a soft drink tax in the UK

The majority of the UK population is either overweight or obese. Health economists, nutritionists and doctors are calling for the UK to follow the example of other European countries and introduce a tax on soft drinks as a result of the perception that high intakes contribute to diet-related disease. We use a demand model estimated with household-level data on beverage purchases in the UK to investigate the effects of a tax on soft drink consumption. The model is a Quadratic Almost Ideal Demand System, and censoring is handled by applying a double hurdle. Separate models are estimated for low, moderate and high consumers to allow for a differential impact on consumption between these groups. Applying different hypothetical tax rates, we conclude that understanding the nature of substitute/complement relationships is crucial in designing an effective policy as these relationships differ between consumers depending on their consumption level. The overall impact of a soft drink tax on calorie consumption is likely to be small.

An evaluation of the theoretical potential and practical opportunity for using greywater for domestic purposes in Ghana

Assessments concerning the effects of climate change, water resource availability and water deprivation in West Africa have not frequently considered the positive contribution to be derived from collecting and reusing water for domestic purposes. Where the originating water is taken from a clean water source and has been used the first time for washing or bathing, this water is commonly called “greywater”. Greywater is a prolific resource that is generated wherever people live. Treated greywater can be used for domestic cleaning, for flushing toilets where appropriate, for washing cars, sometimes for watering kitchen gardens, and for clothes washing prior to rinsing. Therefore, a large theoretical potential exists to increase total water resource availability if greywater were to be widely reused. Locally treated greywater reduces the distribution network requirement, lower construction effort and cost and, wherever possible, minimising the associated carbon footprint. Such locally treated greywater offers significant practical opportunities for increasing the total available water resources at a local level. The reuse of treated greywater is one important action that will help to mitigate the reducing availability of clean water supplies in some areas, and the expected mitigation required in future aligns well with WHO/UNICEF (2012) aspirations. The evaluation of potential opportunities for prioritising greywater systems to support water reuse takes into account the availability of water resources, water use indicators and published estimates in order to understand typical patterns of water demand. The approach supports knowledge acquisition regarding local conditions for enabling capacity building for greywater reuse, the understanding of systems that are most likely to encourage greywater reuse, and practices and future actions to stimulate greywater infrastructure planning, design and implementation. Although reuse might be considered to increase the uncertainty of achieving a specified quality of the water supply, robust methods and technologies are available for local treatment. Resource strategies for greywater reuse have the potential to consistently improve water efficiency and availability in water impoverished and water stressed regions of Ghana and West Africa. Untreated greywater is referred to as “greywater”; treated greywater is referred to as “treated greywater” in this paper.

A high-order arbitrarily unstructured finite-volume model of the global atmosphere: tests solving the shallow-water equations

Simulations of the global atmosphere for weather and climate forecasting require fast and accurate solutions and so operational models use high-order finite differences on regular structured grids. This precludes the use of local refinement; techniques allowing local refinement are either expensive (eg. high-order finite element techniques) or have reduced accuracy at changes in resolution (eg. unstructured finite-volume with linear differencing). We present solutions of the shallow-water equations for westerly flow over a mid-latitude mountain from a finite-volume model written using OpenFOAM. A second/third-order accurate differencing scheme is applied on arbitrarily unstructured meshes made up of various shapes and refinement patterns. The results are as accurate as equivalent resolution spectral methods. Using lower order differencing reduces accuracy at a refinement pattern which allows errors from refinement of the mountain to accumulate and reduces the global accuracy over a 15 day simulation. We have therefore introduced a scheme which fits a 2D cubic polynomial approximately on a stencil around each cell. Using this scheme means that refinement of the mountain improves the accuracy after a 15 day simulation. This is a more severe test of local mesh refinement for global simulations than has been presented but a realistic test if these techniques are to be used operationally. These efficient, high-order schemes may make it possible for local mesh refinement to be used by weather and climate forecast models.

A fast radiative transfer model for the assimilation of water vapor radiances from the Kalpana very high resolution radiometer

A fast radiative transfer model (RTM) to compute emitted infrared radiances for a very high resolution radiometer (VHRR), onboard the operational Indian geostationary satellite Kalpana has been developed and verified. This work is a step towards the assimilation of Kalpana water vapor (WV) radiances into numerical weather prediction models. The fast RTM uses a regression‐based approach to parameterize channel‐specific convolved level to space transmittances. A comparison between the fast RTM and the line‐by‐line RTM demonstrated that the fast RTM can simulate line‐by‐line radiances for the Kalpana WV channel to an accuracy better than the instrument noise, while offering more rapid radiance calculations. A comparison of clear sky radiances of the Kalpana WV channel with the ECMWF model first guess radiances is also presented, aiming to demonstrate the fast RTM performance with the real observations. In order to assimilate the radiances from Kalpana, a simple scheme for bias correction has been suggested.

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.

A comparison of two methods for developing the linearization of a shallow-water model

We develop the linearization of a semi-implicit semi-Lagrangian model of the one-dimensional shallow-water equations using two different methods. The usual tangent linear model, formed by linearizing the discrete nonlinear model, is compared with a model formed by first linearizing the continuous nonlinear equations and then discretizing. Both models are shown to perform equally well for finite perturbations. However, the asymptotic behaviour of the two models differs as the perturbation size is reduced. This leads to difficulties in showing that the models are correctly coded using the standard tests. To overcome this difficulty we propose a new method for testing linear models, which we demonstrate both theoretically and numerically. © Crown copyright, 2003. Royal Meteorological Society

The retrieval of ice water content from radar reflectivity factor and temperature and its use in evaluating a mesoscale model

Ice clouds are an important yet largely unvalidated component of weather forecasting and climate models, but radar offers the potential to provide the necessary data to evaluate them. First in this paper, coordinated aircraft in situ measurements and scans by a 3-GHz radar are presented, demonstrating that, for stratiform midlatitude ice clouds, radar reflectivity in the Rayleigh-scattering regime may be reliably calculated from aircraft size spectra if the "Brown and Francis" mass-size relationship is used. The comparisons spanned radar reflectivity values from -15 to +20 dBZ, ice water contents (IWCs) from 0.01 to 0.4 g m(-3), and median volumetric diameters between 0.2 and 3 mm. In mixed-phase conditions the agreement is much poorer because of the higher-density ice particles present. A large midlatitude aircraft dataset is then used to derive expressions that relate radar reflectivity and temperature to ice water content and visible extinction coefficient. The analysis is an advance over previous work in several ways: the retrievals vary smoothly with both input parameters, different relationships are derived for the common radar frequencies of 3, 35, and 94 GHz, and the problem of retrieving the long-term mean and the horizontal variance of ice cloud parameters is considered separately. It is shown that the dependence on temperature arises because of the temperature dependence of the number concentration "intercept parameter" rather than mean particle size. A comparison is presented of ice water content derived from scanning 3-GHz radar with the values held in the Met Office mesoscale forecast model, for eight precipitating cases spanning 39 h over Southern England. It is found that the model predicted mean I WC to within 10% of the observations at temperatures between -30 degrees and - 10 degrees C but tended to underestimate it by around a factor of 2 at colder temperatures.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Stratospheric water vapour and high climate sensitivity in a version of the HadSM3 climate model

It has been shown previously that one member of the Met Office Hadley Centre single-parameter perturbed physics ensemble – the so-called "low entrainment parameter" member – has a much higher climate sensitivity than other individual parameter perturbations. Here we show that the concentration of stratospheric water vapour in this member is over three times higher than observations, and, more importantly for climate sensitivity, increases significantly when climate warms. The large surface temperature response of this ensemble member is more consistent with stratospheric humidity change, rather than upper tropospheric clouds as has been previously suggested. The direct relationship between the bias in the control state (elevated stratospheric humidity) and the cause of the high climate sensitivity (a further increase in stratospheric humidity) lends further doubt as to the realism of this particular integration. This, together with other evidence, lowers the likelihood that the climate system's physical sensitivity is significantly higher than the likely upper range quoted in the Intergovernmental Panel on Climate Change's Fourth Assessment Report.

A model-based assessment of the effects of projected climate change on the water resources of Jordan

This paper is concerned with the quantification of the likely effect of anthropogenic climate change on the water resources of Jordan by the end of the twenty-first century. Specifically, a suite of hydrological models are used in conjunction with modelled outcomes from a regional climate model, HadRM3, and a weather generator to determine how future flows in the upper River Jordan and in the Wadi Faynan may change. The results indicate that groundwater will play an important role in the water security of the country as irrigation demands increase. Given future projections of reduced winter rainfall and increased near-surface air temperatures, the already low groundwater recharge will decrease further. Interestingly, the modelled discharge at the Wadi Faynan indicates that extreme flood flows will increase in magnitude, despite a decrease in the mean annual rainfall. Simulations projected no increase in flood magnitude in the upper River Jordan. Discussion focuses on the utility of the modelling framework, the problems of making quantitative forecasts and the implications of reduced water availability in Jordan.

Use of a crop model ensemble to quantify CO2 stimulation of water-stressed and well-watered crops

Increased atmospheric concentrations of carbon dioxide (CO2) will benefit the yield of most crops. Two free air CO2 enrichment (FACE) meta-analyses have shown increases in yield of between 0 and 73% for C3 crops. Despite this large range, few crop modelling studies quantify the uncertainty inherent in the parameterisation of crop growth and development. We present a novel perturbed-parameter method of crop model simulation, which uses some constraints from observations, that does this. The model used is the groundnut (i.e. peanut; Arachis hypogaea L.) version of the general large-area model for annual crops (GLAM). The conclusions are of relevance to C3 crops in general. The increases in yield simulated by GLAM for doubled CO2 were between 16 and 62%. The difference in mean percentage increase between well-watered and water-stressed simulations was 6.8. These results were compared to FACE and controlled environment studies, and to sensitivity tests on two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., Bell, M.J., 1995. A peanut simulation model. I. Model development and testing. Agron. J. 87, 1085-1093]. The relationship between CO2 and water stress in the experiments and in the models was examined. From a physiological perspective, water-stressed crops are expected to show greater CO2 stimulation than well-watered crops. This expectation has been cited in literature. However, this result is not seen consistently in either the FACE studies or in the crop models. In contrast, leaf-level models of assimilation do consistently show this result. An analysis of the evidence from these models and from the data suggests that scale (canopy versus leaf), model calibration, and model complexity are factors in determining the sign and magnitude of the interaction between CO2 and water stress. We conclude from our study that the statement that 'water-stressed crops show greater CO2 stimulation than well-watered crops' cannot be held to be universally true. We also conclude, preliminarily, that the relationship between water stress and assimilation varies with scale. Accordingly, we provide some suggestions on how studies of a similar nature, using crop models of a range of complexity, could contribute further to understanding the roles of model calibration, model complexity and scale. (C) 2008 Elsevier B.V. All rights reserved.