Impacts of increasing the aerosol complexity in the Met Office global numerical weather prediction model.

The inclusion of the direct and indirect radiative effects of aerosols in high-resolution global numerical weather prediction (NWP) models is being increasingly recognised as important for the improved accuracy of short-range weather forecasts. In this study the impacts of increasing the aerosol complexity in the global NWP configuration of the Met Office Unified Model (MetUM) are investigated. A hierarchy of aerosol representations are evaluated including three-dimensional monthly mean speciated aerosol climatologies, fully prognostic aerosols modelled using the CLASSIC aerosol scheme and finally, initialised aerosols using assimilated aerosol fields from the GEMS project. The prognostic aerosol schemes are better able to predict the temporal and spatial variation of atmospheric aerosol optical depth, which is particularly important in cases of large sporadic aerosol events such as large dust storms or forest fires. Including the direct effect of aerosols improves model biases in outgoing long-wave radiation over West Africa due to a better representation of dust. However, uncertainties in dust optical properties propagate to its direct effect and the subsequent model response. Inclusion of the indirect aerosol effects improves surface radiation biases at the North Slope of Alaska ARM site due to lower cloud amounts in high-latitude clean-air regions. This leads to improved temperature and height forecasts in this region. Impacts on the global mean model precipitation and large-scale circulation fields were found to be generally small in the short-range forecasts. However, the indirect aerosol effect leads to a strengthening of the low-level monsoon flow over the Arabian Sea and Bay of Bengal and an increase in precipitation over Southeast Asia. Regional impacts on the African Easterly Jet (AEJ) are also presented with the large dust loading in the aerosol climatology enhancing of the heat low over West Africa and weakening the AEJ. This study highlights the importance of including a more realistic treatment of aerosol–cloud interactions in global NWP models and the potential for improved global environmental prediction systems through the incorporation of more complex aerosol schemes

A study of the thermal runaway of lithium-ion batteries : a Gaussian process based global sensitivity analysis

A particular safety issue with Lithium-ion (Li-ion) cells is thermal runaway (TR), which is the exothermic decomposition of cell components creating an uncontrollable temperature rise leading to fires and explosions. The modelling of TR is difficult due to the broad range of cell properties and potential conditions. Understanding the effect that thermophysical and heat transfer characteristics have on the TR abuse model output is essential to develop more accurate and robust TR models. This study uses global sensitivity analysis (GSA) to investigate the effect of the cell parameters on the outcome of TR events. Using a Gaussian Process (GP) surrogate model to calculate the Sobol’ indices, it is shown that the emissivity value is the dominant thermo-characteristic throughout the overall abuse scenario. Further analysis, investigating three key TR features shows the conductivity coefficient to be the most important with respect to the maximum temperature reached during TR. Results demonstrate that researchers can confidently estimate some thermo-characteristics but require accurate characterisation of the emissivity and conductivity coefficient to ensure robust predictions. Given the importance of battery technology to aid in global de-carbonisation, these findings are key to increasing their safe design and operation

APLICAÇÃO DA TÉCNICA DE MODELO LINEAR DE MISTURA ESPECTRAL PARA O MAPEAMENTO DA PLUMA DO RIO AMAZONAS

This paper aims to verify the applicability of Spectral Mixture Analysis (SMA) for mapping the plume of the Amazonas River, a feature of great importance for the coastal dynamics at the South-American Northeastern coast. Remote sensing reflectance data acquired by Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were utilized to identify 5 water masses with different spectral and color characteristics. Through one SeaWiFS image were identified 5 water masses with different spectral and color characteristics, of what mean spectral signatures were obtained. The 5 types of water masses were classified according to its spectral characteristics, of what demonstrated typical behavior of waters with (i) suspended sediment, (ii) dissolved organic matter, (iii) oceanic water, and (iv and v) with different chlorophyll concentration. The mean spectral signatures were applied as endmembers in the SMA resulting in 5 fraction images. The fraction image related to the oceanic water allowed the best classification and mapping of the plume. The mapped area in the image shows the great extension (510 x 103 km2) that the plume can reach in the Northwestern direction from the Amazonas River mouth and into the Equatorial Atlantic, driven by the North Equatorial Counter Current and the North Brazil Current, respectively. Key words: Spectral mixture analysis. Amazon River plume. Remote sensing, SeaWiFS.Este artigo tem como objetivo verificar a aplicação da técnica de Modelo Linear de Mistura Espectral (MLME) para o mapeamento da pluma do Rio Amazonas, uma feição de grande importância na dinâmica costeira da região nordeste da América do Sul. Foram utilizados dados de reflectância de sensoriamento remoto obtidos pelo sensor Sea-viewing Wide Field-of-view Sensor (SeaWiFS) para identificar 5 massas de água com características espectrais e de cor distintas, das quais se obtiveram assinaturas espectrais médias. Os 5 tipos de massas de água foram classificados de acordo com suas características espectrais, sendo estas, típicas de águas com (i) sedimentos em suspensão, (ii) matéria orgânica dissolvida, (iii) água oceânica e (iv e v) com diferentes concentrações de concentrações de clorofila. As assinaturas espectrais médias foram utilizadas como endmembers no MLME o que resultou em 5 imagens fração. A imagem fração referente à água oceânica foi a que possibilitou a melhor identificação e mapeamento da pluma. A área mapeada na imagem mostrou a grande extensão (510 x 103 km2) que a pluma alcança na direção noroeste da desembocadura do Rio Amazonas e para o Oceano Atlântico sob o efeito da Contra Corrente Norte Equatorial e Corrente Norte do Brasil, respectivamente. Palavras chave: Modelo linear de mistura espectral. Pluma do Rio Amazonas. Sensoriamento remoto. SeaWiFS

Exploitation of Geostationary Earth Radiation Budget data using simulations from a numerical weather prediction model: Methodology and data validation

We describe a new methodology for comparing satellite radiation budget data with a numerical weather prediction (NWP) model. This is applied to data from the Geostationary Earth Radiation Budget (GERB) instrument on Meteosat-8. The methodology brings together, in near-real time, GERB broadband shortwave and longwave fluxes with simulations based on analyses produced by the Met Office global NWP model. Results for the period May 2003 to February 2005 illustrate the progressive improvements in the data products as various initial problems were resolved. In most areas the comparisons reveal systematic errors in the model's representation of surface properties and clouds, which are discussed elsewhere. However, for clear-sky regions over the oceans the model simulations are believed to be sufficiently accurate to allow the quality of the GERB fluxes themselves to be assessed and any changes in time of the performance of the instrument to be identified. Using model and radiosonde profiles of temperature and humidity as input to a single-column version of the model's radiation code, we conduct sensitivity experiments which provide estimates of the expected model errors over the ocean of about ±5–10 W m−2 in clear-sky outgoing longwave radiation (OLR) and ±0.01 in clear-sky albedo. For the more recent data the differences between the observed and modeled OLR and albedo are well within these error estimates. The close agreement between the observed and modeled values, particularly for the most recent period, illustrates the value of the methodology. It also contributes to the validation of the GERB products and increases confidence in the quality of the data, prior to their release

Efficient global sensitivity-based model calibration of a high-shear wet granulation process

Model-driven design requires a well-calibrated model and therefore needs efficient workflows to achieve this. This efficiency can be achieved with the identification of the critical process parameters (CPPs) and the most impactful modelling parameters followed by a targeted experimental campaign to prioritise the calibration of these. To identify these parameters it is essential to perform a global sensitivity analysis (GSA). Here, an efficient GSA is applied to a wet granulation case study with the Sobol’ indices used to identify the CPPs and impactful modelling parameters. The population balance, mechanistic model that is used requires considerable computational effort for a GSA so a Gaussian Process surrogate is utilised to interrogate the underlying model. These key results reduce the input-space by 80% enabling the proposal of a targeted experimental design and model calibration workflow. This substantially improves the ability to deploy model-based design to determine the impactful parameter values, reducing the experimental effort by 42.1% compared to a conventional experimental design

Electronic excitation cross section in positron scattering by H

In this work we have applied for the first time the distorted-wave approximation (DWA) combined with Schwinger Variational Iterative Method (SVIM) to describe electronic excitation of H2 molecules by positron collisions. The integral (ICS) and differential (DCS) excitation cross sections for X1Σg+→B1Σu+ X1Σg+ → B1Σu+ transition of H2 molecule, in the range from near threshold up to 45 eV of positron energies, were reported in static (ST) and static-correlation-polarization (STPOL) levels. Our two-state ICS in DWA-ST level have quantitative agreement with experimental measurement at energies from threshold up to 18 eV and the inclusion of polarization effects increases the cross sections. Comparison with 2-state close-coupling approximation (CCA), 2-state Schwinger Multichannel (SMC), 5-state SMC and 1013-state from Convergent Close-Coupling (CCC) methods are done and is encouraging. The relative steeper drop above 22 eV in experimental ICS was not observed by any theoretical calculations indicating that new measurements would be interesting for this transition in this energy range

A seamless approach to understanding and predicting Arctic sea ice in Met Office modelling systems

Recent CMIP5 models predict large losses of summer Arctic sea ice, with only mitigation scenarios showing sustainable summer ice. Sea ice is inherently part of the climate system, and heat fluxes affecting sea ice can be small residuals of much larger air–sea fluxes. We discuss analysis of energy budgets in the Met Office climate models which point to the importance of early summer processes (such as clouds and meltponds) in determining both the seasonal cycle and the trend in ice decline. We give examples from Met Office modelling systems to illustrate how the seamless use of models for forecasting on time scales from short range to decadal might help to unlock the drivers of high latitude biases in climate models