Analysis of surface variables and parameterization of surface processes in HIRLAM. Part II: Seasonal assimilation experiment

The HIRLAM analysis of surface variables and parameterization of surface processes described in the companion paper is applied to a one year long assimilation experiment in order to evaluate the performance of the new package over an extended period covering a complete annual hydrological cycle. The time evolution of the slow evolving variables and the usage of diagnostic tools to assess the performance of the surface analysis are thoroughly discussed in the text. In particular, the usefulness of the screen level variables and soil moisture analyses to diagnose and identify model biases is highlighted. There are also sections devoted to discuss the behaviour of different tiles within a grid square and the convergence of the assimilation algorithm. The need of soil moisture analysis is justified by an additional experiment showing the appearance of long-term drift in near surface parameters when soil moisture analysis is switched off

Analysis of surface variables and parameterization of surface processes in HIRLAM. Part I: Approach and verification by parallel runs

The analysis of surface variables and parameterization of surface processes of the reference HIRLAM system is described. Special emphasis has been put on the treatment of surface heterogeneity making that surface uxes of heat and momentum inherit such high spacial variability. The so called “tiling" approach has been adopted to prevent the problems associated with the use of efective parameters in case of strongly changing surface conditions. The tiles are defined by coupling independently each homogeneous patch or “tile" of a grid square to the lowest level of the model. Tiles interact each other only through the atmosphere. Average surface uxes are then computed by averaging surface uxes over each land-use tile weighted by their fractional area. The model allows up to five diferent tiles (water, sea ice, bare ground, low vegetation, forest) within each grid square. Fractional snow cover is also allowed within each tile. The ISBA scheme has been selected to model land surface processes. The surface analysis initializes the following surface variables: sea surface temperature (SST), fraction of water and ice, snow depth, 2-metre temperature, 2-metre relative humidity, surface soil temperature, mean soil temperature, surface soil water content and total soil water content. The algorithm is able to cope with the tiled structure by averaging some variables only over land tiles. SST and snow depth analyses are based on the successive correction method. 2-metre temperature and relative humidity analyses are based on the optimal interpolation method. Finally, soil water content analysis is based on the sequential method, which corrects water content depending on 2-metre temperature and relative humidity forecast errors, only in those synoptic cases where screen variables are strongly inuenced by the surface beneath. A comprehensive list of parallel runs covering all seasons of the year have been conducted to demonstrate the superiority of the new package against the previous surface treatment. Special emphasis has been put on summer time and midlatitude regions were the inuence of soil wáter content on screen temperature and humidity is extremely high

Sensitivity of aerosol concentrations and cloud properties to nucleation and secondary organic distribution in ECHAM5-HAM global circulation model

The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2×10⁻⁷s⁻¹, 2×10⁻⁶s⁻¹ and 2×10⁻⁵s⁻¹ to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions

SALSA - a sectional aerosol module for large scale applications

"The sectional aerosol module SALSA is introduced. The model has been designed to be implemented in large scale climate models, which require both accuracy and computational efficiency. We have used multiple methods to reduce the computational burden of different aerosol processes to optimize the model performance without losing physical features relevant to problematics of climate importance. The optimizations include limiting the chemical compounds and physical processes available in different size sections of aerosol particles; division of the size distribution into size sections using size sections of variable width depending on the sensitivity of microphysical processing to the particles sizes; the total amount of size sections to describe the size distribution is kept to the minimum; furthermore, only the relevant microphysical processes affecting each size section are calculated. The ability of the module to describe different microphysical processes was evaluated against explicit microphysical models and several microphysical models used in air quality models. The results from the current module show good consistency when compared to more explicit models. Also, the module was used to simulate a new particle formation event typical in highly polluted conditions with comparable results to more explicit model setup.""The sectional aerosol module SALSA is introduced. The model has been designed to be implemented in large scale climate models, which require both accuracy and computational efficiency. We have used multiple methods to reduce the computational burden of different aerosol processes to optimize the model performance without losing physical features relevant to problematics of climate importance. The optimizations include limiting the chemical compounds and physical processes available in different size sections of aerosol particles; division of the size distribution into size sections using size sections of variable width depending on the sensitivity of microphysical processing to the particles sizes; the total amount of size sections to describe the size distribution is kept to the minimum; furthermore, only the relevant microphysical processes affecting each size section are calculated. The ability of the module to describe different microphysical processes was evaluated against explicit microphysical models and several microphysical models used in air quality models. The results from the current module show good consistency when compared to more explicit models. Also, the module was used to simulate a new particle formation event typical in highly polluted conditions with comparable results to more explicit model setup.""The sectional aerosol module SALSA is introduced. The model has been designed to be implemented in large scale climate models, which require both accuracy and computational efficiency. We have used multiple methods to reduce the computational burden of different aerosol processes to optimize the model performance without losing physical features relevant to problematics of climate importance. The optimizations include limiting the chemical compounds and physical processes available in different size sections of aerosol particles; division of the size distribution into size sections using size sections of variable width depending on the sensitivity of microphysical processing to the particles sizes; the total amount of size sections to describe the size distribution is kept to the minimum; furthermore, only the relevant microphysical processes affecting each size section are calculated. The ability of the module to describe different microphysical processes was evaluated against explicit microphysical models and several microphysical models used in air quality models. The results from the current module show good consistency when compared to more explicit models. Also, the module was used to simulate a new particle formation event typical in highly polluted conditions with comparable results to more explicit model setup."Peer reviewe

Sensitivity of aerosol concentrations and cloud properties to nucleation and secondary organic distribution in ECHAM5-HAM global circulation model

The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2 x 10(-7) s(-1), 2 x 10(-6) s(-1) and 2 x 10(-5) s(-1) to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions.The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2 x 10(-7) s(-1), 2 x 10(-6) s(-1) and 2 x 10(-5) s(-1) to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions.The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2 x 10(-7) s(-1), 2 x 10(-6) s(-1) and 2 x 10(-5) s(-1) to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions.Peer reviewe

Technology enhanced assessment in complex collaborative settings

Building upon discussions by the Assessment Working Group at EDUsummIT 2013, this article reviews recent developments in technology enabled assessments of collaborative problem solving in order to point out where computerised assessments are particularly useful (and where non-computerised assessments need to be retained or developed) while assuring that the purposes and designs are transparent and empowering for teachers and learners. Technology enabled assessments of higher order critical thinking in a collaborative social context can provide data about the actions, communications and products created by a learner in a designed task space. Principled assessment design is required in order for such a space to provide trustworthy evidence of learning, and the design must incorporate and take account of the engagement of the audiences for the assessment as well as vary with the purposes and contexts of the assessment. Technology enhanced assessment enables in-depth unobtrusive documentation or ‘quiet assessment’ of the many layers and dynamics of authentic performance and allows greater flexibility and dynamic interactions in and among the design features. Most important for assessment FOR learning, are interactive features that allow the learner to turn up or down the intensity, amount and sharpness of the information needed for self-absorption and adoption of the feedback. Most important in assessment OF learning, are features that compare the learner with external standards of performance. Most important in assessment AS learning, are features that allow multiple performances and a wide array of affordances for authentic action, communication and the production of artefacts

Regulation of emotions in socially challenging learning situations: An instrument to measure the adaptive and social nature of the regulation process

Self-regulated learning (SRL) research has conventionally relied on measures, which treat SRL as an aptitude. To study self-regulation and motivation in learning contexts as an ongoing adaptive process, situation-specific methods are needed in addition to static measures. This article presents an 18Adaptive Instrument for Regulation of Emotions 19 aimed at accessing students 19 experiences of individual and socially shared regulation of emotions in a socially challenging learning situation. The instrument, grounded in self-regulated and socially regulated learning theory, comprises four interrelated components: the socio-emotional challenges experienced in a collaborative learning situation; individual and group-level attempts to regulate the immediate emotions evoked by the challenges; the personal goals; and goal attainment pursued in that situation. The theoretical foundation of the instrument and its components are outlined and some reliability issues illustrated. The limitations but also educational potential of the instrument to understand regulation of emotions in socially challenging learning situations are discussed

Research on motivation in collaborative learning: Moving beyond the cognitive-situative divide and combining individual and social processes

In this article we propose that in order to advance our understanding of motivation in collaborative learning we should move beyond the cognitive-situative epistemological divide and combine individual and social processes. Our claim is that although recent research has recognized the importance of social aspects in emerging and sustained motivation in collaborative learning activities, the social is mainly conceived as a unidirectional source of influence on individual motivation. In the article we examine the significance of motivation in research on collaborative learning. We discuss two characterizations of the role of the social in conceptualizations of motivation, namely, social influence and social construction, and outline our case for moving beyond the cognitive-situative divide and combining individual and social processes in research on motivation. Finally, we present illustrations from recent research on motivation in collaborative learning that has attempted to bridge the cognitive-situative divide across theoretical perspectives or using different methods