Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.

Towards an improved understanding of the nitrate dynamics in lowland, permeable river-systems: Applications of INCA-N

The Integrated Catchment Model of Nitrogen (INCA-N) was applied to the Lambourn and Pang river-systems to integrate current process-knowledge and available-data to test two hypotheses and thereby determine the key factors and processes controlling the movement of nitrate at the catchment-scale in lowland, permeable river-systems: (i) that the in-stream nitrate concentrations were controlled by two end-members only: groundwater and soil-water, and (ii) that the groundwater was the key store of nitrate in these river-systems. Neither hypothesis was proved true or false. Due to equifinality in the model structure and parameters at least two alternative models provided viable explanations for the observed in-stream nitrate concentrations. One model demonstrated that the seasonal-pattern in the stream-water nitrate concentrations was controlled mainly by the mixing of ground- and soil-water inputs. An alternative model demonstrated that in-stream processes were important. It is hoped further measurements of nitrate concentrations made in the catchment soil- and ground-water and in-stream may constrain the model and help determine the correct structure, though other recent studies suggest that these data may serve only to highlight the heterogeneity of the system. Thus when making model-based assessments and forecasts it is recommend that all possible models are used, and the range of forecasts compared. In this study both models suggest that cereal production contributed approximately 50% the simulated in-stream nitrate toad in the two catchments, and the point-source contribution to the in-stream load was minimal. (c) 2006 Elsevier B.V. All rights reserved.

Redefinition of the kilogram: a decision whose time has come

The kilogram, the base unit of mass in the International System of Units (SI), is defined as the mass m(K) of the international prototype of the kilogram. Clearly, this definition has the effect of fixing the value of m(K) to be one kilogram exactly. In this paper, we review the benefits that would accrue if the kilogram were redefined so as to fix the value of either the Planck constant h or the Avogadro constant NA instead of m(K), without waiting for the experiments to determine h or NA currently underway to reach their desired relative standard uncertainty of about 10−8. A significant reduction in the uncertainties of the SI values of many other fundamental constants would result from either of these new definitions, at the expense of making the mass m(K) of the international prototype a quantity whose value would have to be determined by experiment. However, by assigning a conventional value to m(K), the present highly precise worldwide uniformity of mass standards could still be retained. The advantages of redefining the kilogram immediately outweigh any apparent disadvantages, and we review the alternative forms that a new definition might take.

The timing of eukaryotic evolution: Does a relaxed molecular clock reconcile proteins and fossils?

The use of nucleotide and amino acid sequences allows improved understanding of the timing of evolutionary events of life on earth. Molecular estimates of divergence times are, however, controversial and are generally much more ancient than suggested by the fossil record. The limited number of genes and species explored and pervasive variations in evolutionary rates are the most likely sources of such discrepancies. Here we compared concatenated amino acid sequences of 129 proteins from 36 eukaryotes to determine the divergence times of several major clades, including animals, fungi, plants, and various protists. Due to significant variations in their evolutionary rates, and to handle the uncertainty of the fossil record, we used a Bayesian relaxed molecular clock simultaneously calibrated by six paleontological constraints. We show that, according to 95% credibility intervals, the eukaryotic kingdoms diversified 950-1,259 million years ago (Mya), animals diverged from choanoflagellates 761-957 Mya, and the debated age of the split between protostomes and deuterostomes occurred 642-761 Mya. The divergence times appeared to be robust with respect to prior assumptions and paleontological calibrations. Interestingly, these relaxed clock time estimates are much more recent than those obtained under the assumption of a global molecular clock, yet bilaterian diversification appears to be approximate to100 million years more ancient than the Cambrian boundary.

Bayesian estimation of ancestral character states on phylogenies

Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods ( BayesMultiState) is available from the authors.

Full-dimensional quantum calculations of ground-state tunneling splitting of malonaldehyde using an accurate ab initio potential energy surface

Quantum calculations of the ground vibrational state tunneling splitting of H-atom and D-atom transfer in malonaldehyde are performed on a full-dimensional ab initio potential energy surface (PES). The PES is a fit to 11 147 near basis-set-limit frozen-core CCSD(T) electronic energies. This surface properly describes the invariance of the potential with respect to all permutations of identical atoms. The saddle-point barrier for the H-atom transfer on the PES is 4.1 kcal/mol, in excellent agreement with the reported ab initio value. Model one-dimensional and "exact" full-dimensional calculations of the splitting for H- and D-atom transfer are done using this PES. The tunneling splittings in full dimensionality are calculated using the unbiased "fixed-node" diffusion Monte Carlo (DMC) method in Cartesian and saddle-point normal coordinates. The ground-state tunneling splitting is found to be 21.6 cm(-1) in Cartesian coordinates and 22.6 cm(-1) in normal coordinates, with an uncertainty of 2-3 cm(-1). This splitting is also calculated based on a model which makes use of the exact single-well zero-point energy (ZPE) obtained with the MULTIMODE code and DMC ZPE and this calculation gives a tunneling splitting of 21-22 cm(-1). The corresponding computed splittings for the D-atom transfer are 3.0, 3.1, and 2-3 cm(-1). These calculated tunneling splittings agree with each other to within less than the standard uncertainties obtained with the DMC method used, which are between 2 and 3 cm(-1), and agree well with the experimental values of 21.6 and 2.9 cm(-1) for the H and D transfer, respectively. (C) 2008 American Institute of Physics.

Global oil production: forecasts and methodologies

A range of forecasts of global oil production made between 1956 and the present day are listed. For the majority of these the methodology used to generate the forecast is described. The paper distinguishes between three types of forecast: group 1-quantitative analyses which predict that global oil production will reach a resource-limited peak in the near term, and certainly before the year 2020; group 2-forecasts that use quantitative methods, but which see no production peak within the forecast's time horizon (typically 2020 or 2030); group 3-nonquantitative analyses that rule out a resource-limited oil peak within the foreseeable future. The paper analyses these forecast types and suggests that group 1 forecasts are the most realistic.

Overview of the West African monsoon 2011

Although the 2011 West African monsoon (WAM) season was, overall, near normal, rainfall was patchy. The irregularity of the rainfall during the crucial July-August-September (JAS) season proved difficult to predict - highlighting the significant challenges we continue to face for this region. The vagaries of the rainfall in sub-Saharan Africa have profound and often dire effects on African society and economy. To reduce the vulnerability of African communities to variations in the strength of the WAM, the scientific community needs to improve the reliability of forecasts so as to enable forward planning, and national governments need to adopt coordinated policies in order to increase their capacity to cope with extended periods of water shortages due to drought. With the launch of the Africa Climate Exchange (Afclix), the UK and African climate communies are working with both the humanitarian sector and policy-makers to channel the latest climate science into policy. Such policies have the potential to build resilience and in-country capacity for climate compatible development in sub-Saharan Africa. The emphasis is on ‘feet on the (African) ground’ mechanisms of knowledge-sharing activities at the science-policy interface.

Representativity of in situ precipitation measurements - a case study for the LITFASS area in North-Eastern Germany

In situ precipitation measurements can extremely differ in space and time. Taking into account the limited spatial–temporal representativity and the uncertainty of a single station is important for validating mesoscale numerical model results as well as for interpreting remote sensing data. In situ precipitation data from a high resolution network in North-Eastern Germany are analysed to determine their temporal and spatial representativity. For the dry year 2003 precipitation amounts were available with 10 min resolution from 14 rain gauges distributed in an area of 25 km 25 km around the Meteorological Observatory Lindenberg (Richard-Aßmann Observatory). Our analysis reveals that short-term (up to 6 h) precipitation events dominate (94% of all events) and that the distribution is skewed with a high frequency of very low precipitation amounts. Long-lasting precipitation events are rare (6% of all precipitation events), but account for nearly 50% of the annual precipitation. The spatial representativity of a single-site measurement increases slightly for longer measurement intervals and the variability decreases. Hourly precipitation amounts are representative for an area of 11 km 11 km. Daily precipitation amounts appear to be reliable with an uncertainty factor of 3.3 for an area of 25 km 25 km, and weekly and monthly precipitation amounts have uncertainties of a factor of 2 and 1.4 when compared to 25 km 25 km mean values.

Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convective-scale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.

The impact of country risk on international real estate returns

Commercial real estate investors have well-established methods to assess the risks of a property investment in their home country. However, when the investment decision is overseas another dimension of uncertainty overlays the analysis. This additional dimension, typically called country risk, encompasses the uncertainty of achieving expected financial results solely due to factors relating to the investment’s location in another country. However, very little has been done to examine the effects of country risk on international real estate returns, even though in international investment decisions considerations of country risk dominate asset investment decisions. This study extends the literature on international real estate diversification by empirically estimating the impact of country risk, as measured by Euromoney, on the direct real estate returns of 15 countries over the period 1998-2004, using a pooled regression analysis approach. The results suggest that country risk data may help investor’s in their international real estate decisions since the country risk data shows a significant and consistent impact on real estate return performance.

Expert judgement in the processes of commercial property market forecasting

In this paper, we investigate the role of judgement in the formation of forecasts in commercial property markets. The investigation is based on interview surveys with the majority of UK forecast producers, who are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self‐censorship’ or are ‘censored’ following in‐house consultation. It is concluded that the forecasting process is significantly more complex than merely carrying out econometric modelling, forecasts are mediated and contested within organisations and that impacts can vary considerably across different organizational contexts.

Expert judgement in the processes of commercial property market forecasting

In this paper we investigate the role of judgement in the formation of forecasts in commercial real estate markets. Based on interview surveys with the majority of forecast producers, we find that real estate forecasters are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self-censorship’ or are ‘censored’ following in-house consultation. It is concluded that the forecasting process is more complex than merely carrying out econometric modelling and that the impact of the influences within this process vary considerably across different organizational contexts.

Absolute high spectral resolution measurements of surface solar radiation for detection of water vapour continuum absorption

Solar-pointing Fourier transform infrared (FTIR) spectroscopy offers the capability to measure both the fine scale and broadband spectral structure of atmospheric transmission simultaneously across wide spectral regions. It is therefore suited to the study of both water vapour monomer and continuum absorption behaviours. However, in order to properly address this issue, it is necessary to radiatively calibrate the FTIR instrument response. A solar-pointing high-resolution FTIR spectrometer was deployed as part of the ‘Continuum Absorption by Visible and Infrared radiation and its Atmospheric Relevance’ (CAVIAR) consortium project. This paper describes the radiative calibration process using an ultra-high-temperature blackbody and the consideration of the related influence factors. The result is a radiatively calibrated measurement of the solar irradiation at the ground across the IR region from 2000 to 10 000 cm−1 with an uncertainty of between 3.3 and 5.9 per cent. This measurement is shown to be in good general agreement with a radiative-transfer model. The results from the CAVIAR field measurements are being used in ongoing studies of atmospheric absorbers, in particular the water vapour continuum.