On the equivalence between radiance and retrieval assimilation

The need for consistent assimilation of satellite measurements for numerical weather prediction led operational meteorological centers to assimilate satellite radiances directly using variational data assimilation systems. More recently there has been a renewed interest in assimilating satellite retrievals (e.g., to avoid the use of relatively complicated radiative transfer models as observation operators for data assimilation). The aim of this paper is to provide a rigorous and comprehensive discussion of the conditions for the equivalence between radiance and retrieval assimilation. It is shown that two requirements need to be satisfied for the equivalence: (i) the radiance observation operator needs to be approximately linear in a region of the state space centered at the retrieval and with a radius of the order of the retrieval error; and (ii) any prior information used to constrain the retrieval should not underrepresent the variability of the state, so as to retain the information content of the measurements. Both these requirements can be tested in practice. When these requirements are met, retrievals can be transformed so as to represent only the portion of the state that is well constrained by the original radiance measurements and can be assimilated in a consistent and optimal way, by means of an appropriate observation operator and a unit matrix as error covariance. Finally, specific cases when retrieval assimilation can be more advantageous (e.g., when the estimate sought by the operational assimilation system depends on the first guess) are discussed

Representation of model error in a convective-scale ensemble prediction system

In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone

Sudden death associated with lipoma of the cerebellopontine angle

Intracranial lipomas are rare benign tumors considered exceptional when localized in the cerebellopontine angle (CPA), with an incidence of 0.1% of the total number of expansive processes located in this area. We present a case of the sudden death of a 26-year-old young woman in which an unencapsulated neoformation of 0.8 cm was documented at the right cerebellopontine angle and was histologically characterized as intracranial lipoma. The cause of death was then identified as a cardiocirculatory failure secondary to supratentorial (uncal right) herniation caused by the lipoma of the pontocerebellar angle with high-grade diffuse cerebral edema

Methods of investigating forecast error sensitivity to ensemble size in a limited-area convection-permitting ensemble

Ensemble-based predictions are increasingly used as an aid to weather forecasting and to data assimilation, where the aim is to capture the range of possible outcomes consistent with the underlying uncertainties. Constraints on computing resources mean that ensembles have a relatively small size, which can lead to an incomplete range of possible outcomes, and to inherent sampling errors. This paper discusses how an existing ensemble can be relatively easily increased in size, it develops a range of standard and extended diagnostics to help determine whether a given ensemble is ‘large enough’ to be useful for forecasting and data assimilation purposes, and it applies the diagnostics to a convective-scale case study for illustration. Diagnostics include the effect of ensemble size on various aspects of rainfall forecasts, kinetic energy spectra, and (co)variance statistics in the spatial and spectral domains. The work here extends the Met Office’s 24 ensemble members to 93. It is found that the extra members do develop a significant degree of linear independence, they increase the ensemble spread (although with caveats to do with non-Gaussianity), they reduce sampling error in many statistical quantities (namely variances, correlations, and length-scales), and improve the effective spatial resolution of the ensemble. The extra members though do not improve the probabilistic rain rate forecasts. It is assumed that the 93-member ensemble approximates the error-free statistics, which is a practical assumption, but the data suggests that this number of members is ultimately not enough to justify this assumption, and therefore more ensembles are likely required for such convective-scale systems to further reduce sampling errors, especially for ensemble data assimilation purposes

Mycorrhizal activity and diversity in a long-term organic Mediterranean agroecosystem

In organic agriculture, soil fertility and productivity rely on biological processes carried out by soil microbes, which represent the key elements of agroecosystem functioning. Arbuscular mycorrhizal fungi (AMF), fundamental microorganisms for soil fertility, plant nutrition and health, may play an important role in organic agriculture by compensating for the reduced use of fertilizers and pesticides. Though, AMF activity and diversity following conversion from conventional to organic farming are poorly investigated. Here we studied AMF abundance, diversity and activity in short- and long-term organically and conventionally managed Mediterranean arable agroecosystems. Our results show that both AMF population activity, as assessed by the mycorrhizal inoculum potential (MIP) assay, the percentage of colonized root length of the field crop (maize) and glomalin-related soil protein (GRSP) content were higher in organically managed fields and increased with time since transition to organic farming. Here, we showed an increase of GRSP content in arable organic systems and a strong correlation with soil MIP values. The analysis of AMF spores showed differences among communities of the three microagroecosystems in terms of species richness and composition as suggested by a multivariate analysis. All our data indicate that AMF respond positively to the transition to organic farming by a progressive enhancement of their activity that seems independent from the species richness of the AMF communities. Our study contributes to the understanding of the effects of agricultural managements on AMF, which represent a promising tool for the implementation of sustainable agriculture

A spatial view of ensemble spread in convection permitting ensembles

With movement toward kilometer-scale ensembles, new techniques are needed for their characterization. A new methodology is presented for detailed spatial ensemble characterization using the fractions skill score (FSS). To evaluate spatial forecast differences, the average and standard deviation are taken of the FSS calculated over all ensemble member–member pairs at different scales and lead times. These methods were found to give important information about the ensemble behavior allowing the identification of useful spatial scales, spinup times for the model, and upscale growth of errors and forecast differences. The ensemble spread was found to be highly dependent on the spatial scales considered and the threshold applied to the field. High thresholds picked out localized and intense values that gave large temporal variability in ensemble spread: local processes and undersampling dominate for these thresholds. For lower thresholds the ensemble spread increases with time as differences between the ensemble members upscale. Two convective cases were investigated based on the Met Office United Model run at 2.2-km resolution. Different ensemble types were considered: ensembles produced using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and an ensemble produced using different model physics configurations. Comparison of the MOGREPS and multiphysics ensembles demonstrated the utility of spatial ensemble evaluation techniques for assessing the impact of different perturbation strategies and the need for assessing spread at different, believable, spatial scales

Abundance and biodiversity of soil arthropods in one conventional and two organic fields of maize in stockless arable systems

Soil arthropod community was evaluated, in three different farming systems in Central Italy, in the context of a long-term experimental stockless arable system (MOLTE). The soil arthropodofauna was recorded in two organic agrosystems of different age (16-year old organic, named OldO; 6-year young organic, named YngO) and in one conventional (Co), at a fixed time on maize. Arthropods, extracted by Berlese-Tullgren funnels, were counted and identified at order or suborder taxonomic level. In the three maize fields, the farming system affected both abundance and biodiversity of arthropods. The arthropod density ranged from about 20,000 individuals/m2 in OldO to about 45,000 in YngO. The number of oribatid mites was higher in Co than in OldO, while YngO showed the highest density of collembolans. The mite/collembolan ratio was the highest in Co (6.43), the lowest in YngO (1.95). Both biodiversity indices adopted – V, synthetic index of degree of diversity change of ecological systems and QBS, index of biological soil quality – showed the highest values for YngO. On the whole, differences in the arthropod community were higher in the YngO-OldO comparison than in OldO-Co. The soil arthropod community tended to be characterized by lower density of specimens and lower number of taxa in the OldO organic system than in the YngO

Rate-control vs rhythm-control of atrial fibrillation in elderly patients. From new, age-oriented outcomes to a more complex management strategy

Atrial fibrillation (AF) is the most frequent arrhythmia in elderly people. Findings derived from clinical trials seem to demonstrate that a rate-control strategy of AF in aged patients improves prognosis if compared to a rhythm-control one. However, epidemiological studies concordantly show that the arrhythmia is associated to increased hospitalization and mortality rates. In last years, the proportion of patients admitted to hospital for AF has progressively increased; this trend is observed in subjects >75 and >85 years, while no change was found in younger cohorts. Importantly, in aged individuals, probably because of the loss of atrial activity, the increase of heart rate and the irregularity of RR intervals, AF begins a vicious cycle, leading from heart failure, through the compromise of functional and neurocognitive status, to overt disability, dementia and increased mortality. Evidence specifically aimed at clarifying the effects of arrhythmia management on outcomes characteristic of aged people is completely lacking. In the elderly, the question regarding the effects of a rate- or a rhythm-control strategy of AF should be considered as an aspect of a more complex strategy, addressed to reduce disability and hospitalizations, and to improve quality of life and survival

Erratum: "Northern JHK Standard Stars for Array Detectors" [Astron. J. 115, 2594 (1998)]

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Production of grain legume crops alternative to soya bean and their use in organic dairy production

This work evaluates the possibility to substitute external soya bean, a high risk GMO alimentary source, with other legumes produced on farm, such as sweet lupin, protein pea and field bean, as alternative protein source in the formulation of diet in organic dairy cattle nutrition. In 2005/2007 periods both the field and feeding trials were carried out in an organic dairy farm in Tuscany. The performances of grain legumes crops were evaluated in terms of grain yield and quality of grains. The alimentary experiment was carried out on dairy cattle fed with two diets: A with extruded soya bean and B with bitter lupin + field bean + high protein pea. In the field trial the Italian sweet lupin varieties (Multitalia) were the most interesting for CP production and pea the best for yield. The feeding trial provided that the protein content was higher for the A diet (with soya bean) while fat, somatic cells and urea content did not differ