Dynamical and cloud-radiation feedbacks in El Niño and greenhouse warming

An El Niño-like steady response is found in a greenhouse warming simulation resulting from coupled ocean-atmosphere dynamical feedbacks similar to those producing the present-day El Niños. There is a strong negative cloud-radiation feedback on the sea surface temperature (SST) anomaly associated with this enhanced eastern equatorial Pacific warm pattern. However, this negative feedback is overwhelmed by the positive dynamical feedbacks and cannot diminish the sensitivity of the tropical SST to enhanced greenhouse gas concentrations. The enhanced eastern-Pacific warming in the coupled ocean-atmosphere system suggests that coupled dynamics can strengthen this sensitivity.

Past and future conditions for polar stratospheric cloud formation simulated by the Canadian Middle Atmosphere Model

We analyze here the polar stratospheric temperatures in an ensemble of three 150-year integrations of the Canadian Middle Atmosphere Model (CMAM), an interactive chemistry-climate model which simulates ozone depletion and recovery, as well as climate change. A key motivation is to understand possible mechanisms for the observed trend in the extent of conditions favourable for polar stratospheric cloud (PSC) formation in the Arctic winter lower stratosphere. We find that in the Antarctic winter lower stratosphere, the low temperature extremes required for PSC formation increase in the model as ozone is depleted, but remain steady through the twenty-first century as the warming from ozone recovery roughly balances the cooling from climate change. Thus, ozone depletion itself plays a major role in the Antarctic trends in low temperature extremes. The model trend in low temperature extremes in the Arctic through the latter half of the twentieth century is weaker and less statistically robust than the observed trend. It is not projected to continue into the future. Ozone depletion in the Arctic is weaker in the CMAM than in observations, which may account for the weak past trend in low temperature extremes. In the future, radiative cooling in the Arctic winter due to climate change is more than compensated by an increase in dynamically driven downwelling over the pole.

A design of evaluation method for SaaS in cloud computing

Purpose: This paper aims to design an evaluation method that enables an organization to assess its current IT landscape and provide readiness assessment prior to Software as a Service (SaaS) adoption. Design/methodology/approach: The research employs a mixed of quantitative and qualitative approaches for conducting an IT application assessment. Quantitative data such as end user’s feedback on the IT applications contribute to the technical impact on efficiency and productivity. Qualitative data such as business domain, business services and IT application cost drivers are used to determine the business value of the IT applications in an organization. Findings: The assessment of IT applications leads to decisions on suitability of each IT application that can be migrated to cloud environment. Research limitations/implications: The evaluation of how a particular IT application impacts on a business service is done based on the logical interpretation. Data mining method is suggested in order to derive the patterns of the IT application capabilities. Practical implications: This method has been applied in a local council in UK. This helps the council to decide the future status of the IT applications for cost saving purpose.

The formation of ice in a long-lived supercooled layer cloud

This article focuses on the characteristics of persistent thin single-layer mixed-phase clouds. We seek to answer two important questions: (i) how does ice continually nucleate and precipitate from these clouds, without the available ice nuclei becoming depleted? (ii) how do the supercooled liquid droplets persist in spite of the net flux of water vapour to the growing ice crystals? These questions are answered quantitatively using in situ and radar observations of a long-lived mixed-phase cloud layer over the Chilbolton Observatory. Doppler radar measurements show that the top 500 m of cloud (the top 250 m of which is mixed-phase, with ice virga beneath) is turbulent and well-mixed, and the liquid water content is adiabatic. This well-mixed layer is bounded above and below by stable layers. This inhibits entrainment of fresh ice nuclei into the cloud layer, yet our in situ and radar observations show that a steady flux of ≈100 m−2s−1 ice crystals fell from the cloud over the course of ∼1 day. Comparing this flux to the concentration of conventional ice nuclei expected to be present within the well-mixed layer, we find that these nuclei would be depleted within less than 1 h. We therefore argue that nucleation in these persistent supercooled clouds is strongly time-dependent in nature, with droplets freezing slowly over many hours, significantly longer than the few seconds residence time of an ice nucleus counter. Once nucleated, the ice crystals are observed to grow primarily by vapour deposition, because of the low liquid water path (21 g m−2) yet vapour-rich environment. Evidence for this comes from high differential reflectivity in the radar observations, and in situ imaging of the crystals. The flux of vapour from liquid to ice is quantified from in situ measurements, and we show that this modest flux (3.3 g m−2h−1) can be readily offset by slow radiative cooling of the layer to space.

(PDF, 406 KB) On L3 acquisition and phonological permeability: a new test case for debates on the mental representation of non-native phonological systems

The goal of this article is to make an epistemological and theoretical contribution to the nascent field of third language (L3) acquisition and show how examining L3 development can offer a unique view into longstanding debates within L2 acquisition theory. We offer the Phonological Permeability Hypothesis (PPH), which maintains that examining the development of an L3/Ln phonological system and its effects on a previously acquired L2 phonological system can inform contemporary debates regarding the mental constitution of postcritical period adult phonological acquisition. We discuss the predictions and functional significance of the PPH for adult SLA and multilingualism studies, detailing a methodology that examines the effects of acquiring Brazilian Portuguese on the Spanish phonological systems learned before and after the so-called critical period (i.e., comparing simultaneous versus successive adult English-Spanish bilinguals learning Brazilian Portuguese as an L3).

Knowledge of A/A'-dependencies on subject extraction with two types of infinitives in non-native Portuguese adult bilingualism

Within generative L2 acquisition research there is a longstanding debate as to what underlies observable differences in L1/L2 knowledge/ performance. On the one hand, Full Accessibility approaches maintain that target L2 syntactic representations (new functional categories and features) are acquirable (e.g., Schwartz & Sprouse, 1996). Conversely, Partial Accessibility approaches claim that L2 variability and/or optionality, even at advanced levels, obtains as a result of inevitable deficits in L2 narrow syntax and is conditioned upon a maturational failure in adulthood to acquire (some) new functional features (e.g., Beck, 1998; Hawkins & Chan, 1997; Hawkins & Hattori, 2006; Tsimpli & Dimitrakopoulou, 2007). The present study tests the predictions of these two sets of approaches with advanced English learners of L2 Brazilian Portuguese (n = 21) in the domain of inflected infinitives. These advanced L2 learners reliably differentiate syntactically between finite verbs, uninflected and inflected infinitives, which, as argued, only supports Full Accessibility approaches. Moreover, we will discuss how testing the domain of inflected infinitives is especially interesting in light of recent proposals that Brazilian Portuguese colloquial dialects no longer actively instantiate them (Lightfoot, 1991; Pires, 2002, 2006; Pires & Rothman, 2009; Rothman, 2007).

Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

Proteolysis of milk heated at high temperatures by native enzymes analysed by trinitrobenzene sulphonic acid (TNBS) method

Native enzymes play a significant role in proteolysis of milk during storage. This is significant for heat resistant native enzymes. Plasmin is one of the most heat resistant enzymes found in milk. It has been reported to survive several heat treatments, causing spoilage during storage. The aim of this study was to assess susceptibility of high temperature heated milk to proteolysis by native enzymes. The trinitrobenzene sulphonic acid (TNBS) method was used for this purpose. Raw milk was heated at 110, 120, 130,142°C for 2 s and 85°C for 15 s and milk processed at low temperature (85°C /15s) was selected to mimic pasteurisation. TNBS method confirmed that raw milk and milk processed at 85°C /15s were the most proteolysed, whereas treatment of milk at high temperatures (110, 120, 130 and 142°C for 2 s) inactivated the native enzymes. It may thus be concluded that high temperature processing positively affects proteolysis by lowering its susceptibility to spoilage during storage.

Generalized Bayesian cloud detection for satellite imagery. part 1: technique and validation for night-time imagery over land and sea

Numerical Weather Prediction (NWP) fields are used to assist the detection of cloud in satellite imagery. Simulated observations based on NWP are used within a framework based on Bayes' theorem to calculate a physically-based probability of each pixel with an imaged scene being clear or cloudy. Different thresholds can be set on the probabilities to create application-specific cloud-masks. Here, this is done over both land and ocean using night-time (infrared) imagery. We use a validation dataset of difficult cloud detection targets for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) achieving true skill scores of 87% and 48% for ocean and land, respectively using the Bayesian technique, compared to 74% and 39%, respectively for the threshold-based techniques associated with the validation dataset.

Generalised Bayesian cloud detection for satellite imagery. part 2: technique and validation for day-time imagery

Numerical Weather Prediction (NWP) fields are used to assist the detection of cloud in satellite imagery. Simulated observations based on NWP are used within a framework based on Bayes' theorem to calculate a physically-based probability of each pixel with an imaged scene being clear or cloudy. Different thresholds can be set on the probabilities to create application-specific cloud masks. Here, the technique is shown to be suitable for daytime applications over land and sea, using visible and near-infrared imagery, in addition to thermal infrared. We use a validation dataset of difficult cloud detection targets for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) achieving true skill scores of 89% and 73% for ocean and land, respectively using the Bayesian technique, compared to 90% and 70%, respectively for the threshold-based techniques associated with the validation dataset.

3D cloud reconstructions: evaluation of scanning radar scan strategy with a view to surface shortwave radiation closure

The ability of six scanning cloud radar scan strategies to reconstruct cumulus cloud fields for radiation study is assessed. Utilizing snapshots of clean and polluted cloud fields from large eddy simulations, an analysis is undertaken of error in both the liquid water path and monochromatic downwelling surface irradiance at 870 nm of the reconstructed cloud fields. Error introduced by radar sensitivity, choice of radar scan strategy, retrieval of liquid water content (LWC), and reconstruction scheme is explored. Given an in␣nitely sensitive radar and perfect LWC retrieval, domain average surface irradiance biases are typically less than 3 W m␣2 ␣m␣1, corresponding to 5–10% of the cloud radiative effect (CRE). However, when using a realistic radar sensitivity of ␣37.5 dBZ at 1 km, optically thin areas and edges of clouds are dif␣cult to detect due to their low radar re-ectivity; in clean conditions, overestimates are of order 10 W m␣2 ␣m␣1 (~20% of the CRE), but in polluted conditions, where the droplets are smaller, this increases to 10–26 W m␣2 ␣m␣1 (~40–100% of the CRE). Drizzle drops are also problematic; if treated as cloud droplets, reconstructions are poor, leading to large underestimates of 20–46 W m␣2 ␣m␣1 in domain average surface irradiance (~40–80% of the CRE). Nevertheless, a synergistic retrieval approach combining the detailed cloud structure obtained from scanning radar with the droplet-size information and location of cloud base gained from other instruments would potentially make accurate solar radiative transfer calculations in broken cloud possible for the first time.

Cloud optical and microphysical properties derived from ground-based and satellite sensors over a site in the Yangtze Delta region

Comprehensive surface-based retrievals of cloud optical and microphysical properties were made at Taihu, a highly polluted site in the central Yangtze Delta region, during a research campaign from May 2008 to December 2009. Cloud optical depth (COD), effective radius (Re), and liquid water path (LWP) were retrieved from measurements made with a suite of ground-based and spaceborne instruments, including an Analytical Spectral Devices spectroradiometer, a multi␣lter rotating shadowband radiometer, a multichannel microwave radiometer profiler, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua satellites. Retrievals from zenith radiance measurements capture better the temporal variation of cloud properties than do retrievals from hemispherical fluxes. Annual mean LWP, COD, and Re are 115.8 ± 90.8 g/m2, 28.5 ± 19.2, and 6.9 ± 4.2 microns. Over 90% of LWP values are less than 250 g/m2. Most of the COD values (>90%) fall between 5 and 60, and ~80% of Re values are less than 10 microns. Maximum (minimum) values of LWP and Re occur in summer (winter); COD is highest in winter and spring. Raining and nonraining clouds have signi␣cant differences in LWP, COD, and Re. Rainfall frequency is best correlated with LWP, followed by COD and Re. Cloud properties retrieved from multiple ground-based instruments are also compared with those from satellite retrievals. On average, relative to surface retrievals, mean differences of satellite retrievals in cloud LWP, COD, and Re were -33.6 g/m2 (-26.4%), -5.8 (-31.4%), and 2.9 ␣m (29.3%) for 11 MODIS-Terra overpasses and -43.3 g/m2 (-22.3%), -3.0 (-10.0%), and -1.3 ␣m (-12.0%) for 8 MODIS-Aqua overpasses, respectively. These discrepancies indicate that MODIS cloud products still suffer from large uncertainties in this region.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

A molecular, morphological and cytological investigation of the identity of non-native Ludwigia (Onagraceae) populations in Britain

A combined molecular, morphological and cytological analysis was used to study the identity and number of species of Ludwigia section Oligospermum occurring in British waterways. Only one taxon was identified for which the name L. grandiflora subsp. hexapetala (Hook. & Arn.) G.L. Nesom & Kartesz is preferred. A chromosome count of 2n = 80 was made for all plants tested and DNA evidence demonstrates that at least two clones are present in Britain. Morphological characters to differentiate L.grandiflora subsp. hexapetala and L. peploides subsp. montevidensis (Spreng.) P.H. Raven are provided. Though the production of fruit in Britain by apparently isolated populations is noted, repeated introduction into the wild from gardens is judged to be primarily responsible for the British distribution of the taxon. Legislative implications are considered and an amendment to Schedule 9 of the UK Wildlife and Countryside Act (1981) is strongly advocated.