Instructional Design in Online Learning: Components of Quality

Although there are obvious differences between online instruction and face-to-face instruction, this paper focuses on their similarities. One of the challenges when designing a course that has been successfully taught in a face-to-face format is deciding what will stay the same versus what will be changed. How does one replace what happens in class with meaningful online content? In what ways can content be presented aside from reading text on one\u27s computer screen? With these questions in mind, an instructor began collaborating with an instructional designer to develop her first online course, a graduate level course in pupil assessment and evaluation. This paper describes the structure and components of that course. The instructor and instructional designer worked together to infuse three principles of instruction: a) developing a community of learners, (b) promoting critical thinking, and (c) defining clear expectations. Data from course evaluations indicated that overall, students perceived themselves as part of a community of learners, engaged in critical thinking, and found the course expectations to be clear. Applying the same principles of learning from a face-to-face course in an online course seems to have resulted in a successful course, at least from the students\u27 perspective. The major problem identified is common to both face-to-face and online formats -- balancing the demands of the student workload in this challenging course with the expectations and life realities of students who maintain full time jobs and active family commitments

How accurate did GCMs compute the insolation at TOA for AMIP-2?

Monthly averages of solar radiation reaching the Top of the Atmosphere (TOA) as simulated by 20 General Circulation Models (GCMs) during the period 1985–1988 are compared. They were part of submissions to AMIP-2 (Atmospheric Model Intercomparison Project). Monthly averages of ISCCP-FD (International Satellite Cloud Climatology Project – Flux Data) are considered as reference. Considerable discrepancies are found: Most models reproduce the prescribed Total Solar Irradiance (TSI) value within ±0.7 Wm−2. Monthly zonal averages disagree between ±2 to ±7 Wm−2, depending on latitude and season. The largest model diversity occurs near polar regions. Some models display a zonally symmetric insolation, while others and ISCCP show longitudinal deviations of the order of ±1 Wm−2. With such differences in meridional gradients impacts in multi-annual simulations cannot be excluded. Sensitivity studies are recommended

Evaluation of black carbon estimations in global aerosol models

We evaluate black carbon (BC) model predictions from the AeroCom model intercomparison project by considering the diversity among year 2000 model simulations and comparing model predictions with available measurements. These model-measurement intercomparisons include BC surface and aircraft concentrations, aerosol absorption optical depth (AAOD) from AERONET and Ozone Monitoring Instrument (OMI) retrievals and BC column estimations based on AERONET. In regions other than Asia, most models are biased high compared to surface concentration measurements. However compared with (column) AAOD or BC burden retrievals, the models are generally biased low. The average ratio of model to retrieved AAOD is less than 0.7 in South American and 0.6 in African biomass burning regions; both of these regions lack surface concentration measurements. In Asia the average model to observed ratio is 0.6 for AAOD and 0.5 for BC surface concentrations. Compared with aircraft measurements over the Americas at latitudes between 0 and 50 N, the average model is a factor of 10 larger than observed, and most models exceed the measured BC standard deviation in the mid to upper troposphere. At higher latitudes the average model to aircraft BC is 0.6 and underestimates the observed BC loading in the lower and middle troposphere associated with springtime Arctic haze. Low model bias for AAOD but overestimation of surface and upper atmospheric BC concentrations at lower latitudes suggests that most models are underestimating BC absorption and should improve estimates of refractive index, particle size, and optical effects of BC coating. Retrieval uncertainties and/or differences with model diagnostic treatment may also contribute to the model-measurement disparity. Largest AeroCom model diversity occurred in northern Eurasia and the remote Arctic, regions influenced by anthropogenic sources. Changing emissions, aging, removal, or optical properties within a single model generated a smaller change in model predictions than the range represented by the full set of AeroCom models. Upper tropospheric concentrations of BC mass from the aircraft measurements are suggested to provide a unique new benchmark to test scavenging and vertical dispersion of BC in global models

Comparison of radiative energy flows in observational datasets and climate modeling

This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10 W m-2 each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30 W m-2 over trade wind cumulus regions, yet smaller CRE by about -30 W m-2 over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15 W m-2 smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference. © 2016 American Meteorological Society

The aerosol-climate model ECHAM5-HAM

The aerosol-climate modelling system ECHAM5-HAM is introduced. It is based on a flexible microphysical approach and, as the number of externally imposed parameters is minimised, allows the application in a wide range of climate regimes. ECHAM5-HAM predicts the evolution of an ensemble of microphysically interacting internally- and externally-mixed aerosol populations as well as their size-distribution and composition. The size-distribution is represented by a superposition of log-normal modes. In the current setup, the major global aerosol compounds sulfate (SU), black carbon (BC), particulate organic matter (POM), sea salt (SS), and mineral dust (DU) are included. The simulated global annual mean aerosol burdens (lifetimes) for the year 2000 are for SU: 0.80 Tg(S) (3.9 days), for BC: 0.11 Tg (5.4 days), for POM: 0.99 Tg (5.4 days), for SS: 10.5 Tg (0.8 days), and for DU: 8.28 Tg (4.6 days). An extensive evaluation with in-situ and remote sensing measurements underscores that the model results are generally in good agreement with observations of the global aerosol system. The simulated global annual mean aerosol optical depth (AOD) is with 0.14 in excellent agreement with an estimate derived from AERONET measurements (0.14) and a composite derived from MODIS-MISR satellite retrievals (0.16). Regionally, the deviations are not negligible. However, the main patterns of AOD attributable to anthropogenic activity are reproduced

monthly averaged anthropogenic aerosol direct radiative forcing over the mediterranean based on aeronet aerosol properties

Abstract. The all-sky direct radiative effect by anthropogenic aerosol (DREa) is calculated in the solar (0.3–4 μm) and infrared (4–200 μm) spectral ranges for six Mediterranean sites. The sites are differently affected by pollution and together reflect typical aerosol impacts that are expected over land and coastal sites of the central Mediterranean basin. Central to the simulations are aerosol optical properties from AERONET sun-/sky-photometer statistics for the year 2003. A discussion on the variability of the overall (natural + anthropogenic) aerosol properties with site location is provided. Supplementary data include MODIS satellite sensor based solar surface albedos, ISCCP products for high- mid- and low cloud cover and estimates for the anthropogenic aerosol fraction from global aerosol models. Since anthropogenic aerosol particles are considered to be smaller than 1 μm in size, mainly the solar radiation transfer is affected with impacts only during sun-light hours. At all sites the (daily average) solar DREa is negative all year round at the top of the atmosphere (ToA). Hence, anthropogenic particles produce over coastal and land sites of the central Mediterranean a significant cooling effect. Monthly DREa values vary from site to site and are seasonally dependent as a consequence of the seasonal dependence of available sun-light and microphysical aerosol properties. At the ToA the monthly average DREa is −(4±1) W m−2 during spring-summer (SS, April–September) and −(2±1) W m−2 during autumn-winter (AW, October–March) at the polluted sites. In contrast, it varies between −(3±1) W m−2 and −(1±1) W m−2 on SS and AW, respectively at the less polluted site. Due to atmospheric absorption the DREa at the surface is larger than at the ToA. At the surface the monthly average DREa varies between the most and the least polluted site between −(7±1) W m−2 and −(4±1) W m−2 during SS, and between −(4±3) W m−2 and −(1±1) W m−2 during AW. The DREa at infrared wavelengths is positive but negligible, especially at the ToA (<0.3 W m−2). The average of DREa monthly-means referring to all sites has allowed getting a ToA- and sfc-DREa yearly-mean value of −(3±2) and −(5±3) W m−2, respectively at solar wavelengths. Last data, even if refer to a particular year, indicate that the radiative energy-balance of Central Mediterranean land and coastal sites is quite affected by anthropogenic particles

The role of ice particle shapes and size distributions in the single scattering properties of cirrus clouds

The roles of ice particle size distributions (SDs) and particle shapes in cirrus cloud solar radiative transfer are investigated by analyzing SDs obtained from optical array probe measurements (particle sizes larger than 20–40 μm) during intensive field observations of the International Cirrus Experiment, the European Cloud and Radiation Experiment, the First ISCCP Regional Experiment, and the Central Equatorial Pacific Experiment. It is found that the cloud volume extinction coefficient is more strongly correlated with the total number density than with the effective particle size. Distribution-averaged mean single scattering properties are calculated for hexagonal columns, hexagonal plates, and polycrystals at a nonabsorbing (0.5 μm), moderately absorbing (1.6 μm), and strongly absorbing (3.0 μm) wavelength. At 0.5 μm (1.6 μm) (3.0 μm), the spread in the resulting mean asymmetry parameters due to different SDs is smaller than (comparable to) (smaller than) the difference caused by applying different particle shapes to these distributions. From a broadband solar radiative transfer point of view it appears more important to use the correct particle shapes than to average over the correct size distributions