A variational method to retrieve the extinction profile in liquid clouds using multiple field-of-view lidar

Liquid clouds play a profound role in the global radiation budget but it is difficult to remotely retrieve their vertical profile. Ordinary narrow field-of-view (FOV) lidars receive a strong return from such clouds but the information is limited to the first few optical depths. Wideangle multiple-FOV lidars can isolate radiation scattered multiple times before returning to the instrument, often penetrating much deeper into the cloud than the singly-scattered signal. These returns potentially contain information on the vertical profile of extinction coefficient, but are challenging to interpret due to the lack of a fast radiative transfer model for simulating them. This paper describes a variational algorithm that incorporates a fast forward model based on the time-dependent two-stream approximation, and its adjoint. Application of the algorithm to simulated data from a hypothetical airborne three-FOV lidar with a maximum footprint width of 600m suggests that this approach should be able to retrieve the extinction structure down to an optical depth of around 6, and total opticaldepth up to at least 35, depending on the maximum lidar FOV. The convergence behavior of Gauss-Newton and quasi-Newton optimization schemes are compared. We then present results from an application of the algorithm to observations of stratocumulus by the 8-FOV airborne “THOR” lidar. It is demonstrated how the averaging kernel can be used to diagnose the effective vertical resolution of the retrieved profile, and therefore the depth to which information on the vertical structure can be recovered. This work enables exploitation of returns from spaceborne lidar and radar subject to multiple scattering more rigorously than previously possible.

The Aqua-Planet Experiment (APE): Response to changed meridional SST profile

This paper explores the sensitivity of Atmospheric General Circulation Model (AGCM) simulations to changes in the meridional distribution of sea surface temperature (SST). The simulations are for an aqua-planet, a water covered Earth with no land, orography or sea-ice and with specified zonally symmetric SST. Simulations from 14 AGCMs developed for Numerical Weather Prediction and climate applications are compared. Four experiments are performed to study the sensitivity to the meridional SST profile. These profiles range from one in which the SST gradient continues to the equator to one which is flat approaching the equator, all with the same maximum SST at the equator. The zonal mean circulation of all models shows strong sensitivity to latitudinal distribution of SST. The Hadley circulation weakens and shifts poleward as the SST profile flattens in the tropics. One question of interest is the formation of a double versus a single ITCZ. There is a large variation between models of the strength of the ITCZ and where in the SST experiment sequence they transition from a single to double ITCZ. The SST profiles are defined such that as the equatorial SST gradient flattens, the maximum gradient increases and moves poleward. This leads to a weakening of the mid-latitude jet accompanied by a poleward shift of the jet core. Also considered are tropical wave activity and tropical precipitation frequency distributions. The details of each vary greatly between models, both with a given SST and in the response to the change in SST. One additional experiment is included to examine the sensitivity to an off-equatorial SST maximum. The upward branch of the Hadley circulation follows the SST maximum off the equator. The models that form a single precipitation maximum when the maximum SST is on the equator shift the precipitation maximum off equator and keep it centered over the SST maximum. Those that form a double with minimum on the equatorial maximum SST shift the double structure off the equator, keeping the minimum over the maximum SST. In both situations only modest changes appear in the shifted profile of zonal average precipitation. When the upward branch of the Hadley circulation moves into the hemisphere with SST maximum, the zonal average zonal, meridional and vertical winds all indicate that the Hadley cell in the other hemisphere dominates.

Estimating reliability and resolution of probability forecasts through decomposition of the empirical score

References (20)Cited By (1)Export CitationAboutAbstract Proper scoring rules provide a useful means to evaluate probabilistic forecasts. Independent from scoring rules, it has been argued that reliability and resolution are desirable forecast attributes. The mathematical expectation value of the score allows for a decomposition into reliability and resolution related terms, demonstrating a relationship between scoring rules and reliability/resolution. A similar decomposition holds for the empirical (i.e. sample average) score over an archive of forecast–observation pairs. This empirical decomposition though provides a too optimistic estimate of the potential score (i.e. the optimum score which could be obtained through recalibration), showing that a forecast assessment based solely on the empirical resolution and reliability terms will be misleading. The differences between the theoretical and empirical decomposition are investigated, and specific recommendations are given how to obtain better estimators of reliability and resolution in the case of the Brier and Ignorance scoring rule.

Evaluating raw ensembles with the continuous ranked probability score

The continuous ranked probability score (CRPS) is a frequently used scoring rule. In contrast with many other scoring rules, the CRPS evaluates cumulative distribution functions. An ensemble of forecasts can easily be converted into a piecewise constant cumulative distribution function with steps at the ensemble members. This renders the CRPS a convenient scoring rule for the evaluation of ‘raw’ ensembles, obviating the need for sophisticated ensemble model output statistics or dressing methods prior to evaluation. In this article, a relation between the CRPS score and the quantile score is established. The evaluation of ‘raw’ ensembles using the CRPS is discussed in this light. It is shown that latent in this evaluation is an interpretation of the ensemble as quantiles but with non-uniform levels. This needs to be taken into account if the ensemble is evaluated further, for example with rank histograms.

Assessing wind profile effects on the global atmospheric torque

The impact of a new approach to the evaluation of surface gravity wave drag (GWD) is assessed. This approach uses linear theory, but incorporates the effects of wind profile shear and curvature, by means of a second-order WKB approximation. While the theory predicts the possibility of either drag enhancement or reduction, depending on the wind profile, results obtained with the ERA-40 reanalysis data clearly indicate the predominance of local drag enhancement. However, the global impact of shear on the atmospheric axial GWD torque comes mostly from regions with predominantly easterly flow, contributing to a slight reduction of the bias found in different studies of the global angular momentum budget. The relative correction due to shear on linear GWD is found not to depend too strongly on the levels chosen for the computation of the low-level wind derivatives.

Probability of survival in a random exchange economy with dependent agents

In this paper I analyze the general equilibrium in a random Walrasian economy. Dependence among agents is introduced in the form of dependency neighborhoods. Under the uncertainty, an agent may fail to survive due to a meager endowment in a particular state (direct effect), as well as due to unfavorable equilibrium price system at which the value of the endowment falls short of the minimum needed for survival (indirect terms-of-trade effect). To illustrate the main result I compute the stochastic limit of equilibrium price and probability of survival of an agent in a large Cobb-Douglas economy.

Flavour profile of three novel acidic varieties of muskmelon (Cucumis melo L.)

Novel acidic varieties of muskmelon (Cucumis melo L.) are emerging onto the UK market. These melons contain almost twice the amount of citric acid compared to standard melons and are described as ‘zesty and fresh’. This study compared the flavour components of three acidic varieties with a standard Galia-type melon. The volatile and semivolatile compounds were extracted using dynamic headspace extraction (DHE) or solid-phase microextraction (SPME) and solid phase extraction (SPE) respectively, followed by gas chromatography – mass spectrometry (GC-MS) and gas chromatography – olfactometry (GC-O). More than 50 volatile and 50 semivolatile compounds were identified in the headspace and the SPE extracts respectively. GC-O revealed 15 odour-active components in the headspace, with esters being consistently higher in acidic variety. This study showed quantitative and qualitative differences between all four varieties and key differences between acidic varieties and standard melons.

Sparse probability density function estimation using the minimum integrated square error

We develop a new sparse kernel density estimator using a forward constrained regression framework, within which the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Our main contribution is to derive a recursive algorithm to select significant kernels one at time based on the minimum integrated square error (MISE) criterion for both the selection of kernels and the estimation of mixing weights. The proposed approach is simple to implement and the associated computational cost is very low. Specifically, the complexity of our algorithm is in the order of the number of training data N, which is much lower than the order of N2 offered by the best existing sparse kernel density estimators. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to those of the classical Parzen window estimate and other existing sparse kernel density estimators.

The probability of sale and price premiums in withdrawn auctioned properties

This paper examines the impact of the auction process of residential properties that whilst unsuccessful at auction sold subsequently. The empirical analysis considers both the probability of sale and the premium of the subsequent sale price over the guide price, reserve and opening bid. The findings highlight that the final achieved sale price is influenced by key price variables revealed both prior to and during the auction itself. Factors such as auction participation, the number of individual bidders and the number of bids are significant in a number of the alternative specifications.

Natural caprine whey oligosaccharides separated by membrane technology and profile evaluation by capillary electrophoresis

The functional food market is growing rapidly and membrane processing offers several advantages over conventional methods for separation, fractionation and recovery of bioactive components. The aim of the present study was to select a process that could be implemented easily on an industrial scale for the isolation of natural lactose-derived oligosaccharides (OS) from caprine whey, enabling the development of functional foods for clinical and infant nutrition. The most efficient process was the combination of a pre-treatment to eliminate proteins and fat, using an ultrafiltration (UF) membrane of 25 kDa molecular weight cut off (MWCO), followed by a tighter UF membrane with 1 kDa MWCO. Circa 90% of the carbohydrates recovered in the final retentate were OS. Capillary electrophoresis was used to evaluate the OS profile in this retentate. The combined membrane-processing system is thus a promising technique for obtaining natural concentrated OS from whey. Powered

Mapping the platelet profile for functional genomic studies and demonstration of the effect size of the GP6 locus

BACKGROUND: Evidence suggests the wide variation in platelet response within the population is genetically controlled. Unraveling the complex relationship between sequence variation and platelet phenotype requires accurate and reproducible measurement of platelet response. OBJECTIVE: To develop a methodology suitable for measuring signaling pathway-specific platelet phenotype, to use this to measure platelet response in a large cohort, and to demonstrate the effect size of sequence variation in a relevant model gene. METHODS: Three established platelet assays were evaluated: mobilization of [Ca(2+)](i), aggregometry and flow cytometry, each in response to adenosine 5'-diphosphate (ADP) or the glycoprotein (GP) VI-specific crosslinked collagen-related peptide (CRP). Flow cytometric measurement of fibrinogen binding and P-selectin expression in response to a single, intermediate dose of each agonist gave the best combination of reproducibility and inter-individual variability and was used to measure the platelet response in 506 healthy volunteers. Pathway specificity was ensured by blocking the main subsidiary signaling pathways. RESULTS: Individuals were identified who were hypo- or hyper-responders for both pathways, or who had differential responses to the two agonists, or between outcomes. 89 individuals, retested three months later using the same methodology, showed high concordance between the two visits in all four assays (r(2) = 0.872, 0.868, 0.766 and 0.549); all subjects retaining their phenotype at recall. The effect of sequence variation at the GP6 locus accounted for approximately 35% of the variation in the CRP-XL response. CONCLUSION: Genotyping-phenotype association studies in a well-characterized, large cohort provides a powerful strategy to measure the effect of sequence variation in genes regulating the platelet response.

Forecast encompassing tests and probability forecasts

We consider tests of forecast encompassing for probability forecasts, for both quadratic and logarithmic scoring rules. We propose test statistics for the null of forecast encompassing, present the limiting distributions of the test statistics, and investigate the impact of estimating the forecasting models' parameters on these distributions. The small-sample performance is investigated, in terms of small numbers of forecasts and model estimation sample sizes. We show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables, and for evaluating survey-based probability forecasts.

A fast algorithm for sparse probability density function construction

A new sparse kernel density estimator is introduced. Our main contribution is to develop a recursive algorithm for the selection of significant kernels one at time using the minimum integrated square error (MISE) criterion for both kernel selection. The proposed approach is simple to implement and the associated computational cost is very low. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.