Connections between clouds, radiation, and midlatitude dynamics: a review

We review the effects of dynamical variability on clouds and radiation in observations and models and discuss their implications for cloud feedbacks. Jet shifts produce robust meridional dipoles in upper-level clouds and longwave cloud-radiative effect (CRE), but low-level clouds, which do not simply shift with the jet, dominate the shortwave CRE. Because the effect of jet variability on CRE is relatively small, future poleward jet shifts with global warming are only a second-order contribution to the total CRE changes around the midlatitudes, suggesting a dominant role for thermodynamic effects. This implies that constraining the dynamical response is unlikely to reduce the uncertainty in extratropical cloud feedback. However, we argue that uncertainty in the cloud-radiative response does affect the atmospheric circulation response to global warming, by modulating patterns of diabatic forcing. How cloud feedbacks can affect the dynamical response to global warming is an important topic of future research.

Trends in the CERES dataset, 2000–13: the effects of sea ice and jet shifts and comparison to climate models

We review the effects of dynamical variability on clouds and radiation in observations and models and discuss their implications for cloud feedbacks. Jet shifts produce robust meridional dipoles in upper-level clouds and longwave cloud-radiative effect (CRE), but low-level clouds, which do not simply shift with the jet, dominate the shortwave CRE. Because the effect of jet variability on CRE is relatively small, future poleward jet shifts with global warming are only a second-order contribution to the total CRE changes around the midlatitudes, suggesting a dominant role for thermodynamic effects. This implies that constraining the dynamical response is unlikely to reduce the uncertainty in extratropical cloud feedback. However, we argue that uncertainty in the cloud-radiative response does affect the atmospheric circulation response to global warming, by modulating patterns of diabatic forcing. How cloud feedbacks can affect the dynamical response to global warming is an important topic of future research.

Resources, staff beliefs and organizational culture: factors in the use of information and communication technology for adults with intellectual disabilities

Background  Access to, and the use of, information and communication technology (ICT) is increasingly becoming a vital component of mainstream life. First-order (e.g. time and money) and second-order factors (e.g. beliefs of staff members) affect the use of ICT in different contexts. It is timely to investigate what these factors may be in the context of service provision for adults with intellectual disabilities given the role ICT could play in facilitating communication and access to information and opportunities as suggested in Valuing People. Method  Taking a qualitative approach, nine day service sites within one organization were visited over a period of 6 months to observe ICT-related practice and seek the views of staff members working with adults with intellectual disabilities. All day services were equipped with modern ICT equipment including computers, digital cameras, Internet connections and related peripherals. Results  Staff members reported time, training and budget as significant first-order factors. Organizational culture and beliefs about the suitability of technology for older or less able service users were the striking second-order factors mentioned. Despite similar levels of equipment, support and training, ICT use had developed in very different ways across sites. Conclusion  The provision of ICT equipment and training is not sufficient to ensure their use; the beliefs of staff members and organizational culture of sites play a substantial role in how ICT is used with and by service users. Activity theory provides a useful framework for considering how first- and second-order factors are related. Staff members need to be given clear information about the broader purpose of activities in day services, especially in relation to the lifelong learning agenda, in order to see the relevance and usefulness of ICT resources for all service users.

Rossby wave propagation on potential vorticity fronts with finite width

The horizontal gradient of potential vorticity (PV) across the tropopause typically declines with lead time in global numerical weather forecasts and tends towards a steady value dependent on model resolution. This paper examines how spreading the tropopause PV contrast over a broader frontal zone affects the propagation of Rossby waves. The approach taken is to analyse Rossby waves on a PV front of finite width in a simple single-layer model. The dispersion relation for linear Rossby waves on a PV front of infinitesimal width is well known; here an approximate correction is derived for the case of a finite width front, valid in the limit that the front is narrow compared to the zonal wavelength. Broadening the front causes a decrease in both the jet speed and the ability of waves to propagate upstream. The contribution of these changes to Rossby wave phase speeds cancel at leading order. At second order the decrease in jet speed dominates, meaning phase speeds are slower on broader PV fronts. This asymptotic phase speed result is shown to hold for a wide class of single-layer dynamics with a varying range of PV inversion operators. The phase speed dependence on frontal width is verified by numerical simulations and also shown to be robust at finite wave amplitude, and estimates are made for the error in Rossby wave propagation speeds due to the PV gradient error present in numerical weather forecast models.

Triple isotope (δD, δ17O, δ18O) study on precipitation, drip water and speleothem fluid inclusions for a central European cave (NW Switzerland)

Deuterium (dD) and oxygen (d18O) isotopes are powerful tracers of the hydrological cycle and have been extensively used for paleoclimate reconstructions as they can provide information on past precipitation, temperature and atmospheric circulation. More recently, the use of 17Oexcess derived from precise measurement of d17O and d18O gives new and additional insights in tracing the hydrological cycle whereas uncertainties surround this proxy. However, 17Oexcess could provide additional information on the atmospheric conditions at the moisture source as well as about fractionations associated with transport and site processes. In this paper we trace water stable isotopes (dD, d17O and d18O) along their path from precipitation to cave drip water and finally to speleothem fluid inclusions for Milandre cave in northwestern Switzerland. A two year-long daily resolved precipitation isotope record close to the cave site is compared to collected cave drip water (3 months average resolution) and fluid inclusions of modern and Holocene stalagmites. Amount weighted mean dD, d18O and d17O are �71.0‰, �9.9‰, �5.2‰ for precipitation, �60.3‰, �8.7‰, �4.6‰ for cave drip water and �61.3‰, �8.3‰, �4.7‰ for recent fluid inclusions respectively. Second order parameters have also been derived in precipitation and drip water and present similar values with 18 per meg for 17Oexcess whereas d-excess is 1.5‰ more negative in drip water. Furthermore, the atmospheric signal is shifted towards enriched values in the drip water and fluid inclusions (D of ~ þ 10‰ for dD). The isotopic composition of cave drip water exhibits a weak seasonal signal which is shifted by around 8e10 months (groundwater residence time) when compared to the precipitation. Moreover, we carried out the first d17O measurement in speleothem fluid inclusions, as well as the first comparison of the d17O behaviour from the meteoric water to the fluid inclusions entrapment in speleothems. This study on precipitation, drip water and fluid inclusions will be used as a speleothem proxy calibration for Milandre cave in order to reconstruct paleotemperatures and moisture source variations for Western Central Europe.

Heterogeneous tensor decomposition for clustering via manifold optimization

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

Sparse density estimation on multinomial manifold combining local component analysis

A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since the constraint on the mixing coefficients of a finite mixture model is on the multinomial manifold, we then use the well-known Riemannian trust-region algorithm to find the set of sparse mixing coefficients. The first and second order Riemannian geometry of the multinomial manifold are utilized in the Riemannian trust-region algorithm. 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.