Non-thermal plasma observations using EISCAT: Aspect angle dependence

Recent observations with the EISCAT incoherent scatter radar have shown large rises in dayside, auroral plasma velocities (>2 km s^{−1}) over a wide range of latitudes and lasting about an hour. These are larger than the neutral thermal speed, and allow, for the first time, observations of a non-thermal plasma over a range of observing angles, revealing a clear angular dependence. The observed ion temperature anisotropy, deduced by assuming a Maxwellian line-of-sight ion velocity distribution, is at least 1.75, which exceeds the theoretical value for a bi-Maxwellian based on a realistic ion-neutral collision model. The aspect angle dependence of the signal spectra also indicates non-Maxwellian plasma.

The modelled occurrence of non-thermal plasma in the ionospheric F-region and the possible consequences for ion outflows into the magnetosphere

A global, time-dependent, three-dimensional, coupled ionosphere-thermosphere model is used to predict the spatial distribution of non-thermal plasma in the F-layer. It is shown that, even for steady-state conditions with Kp as low as 3, the difference between the ion and neutral velocities often exceeds the neutral thermal speed by a factor, D', which can be as large as 4. Theoretically, highly non-Maxwellian, and probably toroidal, ion velocity distributions are expected when D' exceeds about 1.5. The lack of response of the neutral winds to sunward ion drifts in the dawn sector of the auroral oval cause this to be the region most likely to contain toroidal distributions. The maximum in D' is found in the throat region of the convection pattern, where the strong neutral winds of the afternoon sector meet the eastward ion flows of the morning sector. These predictions are of interest, not only to radar scientists searching for non-thermal ionospheric plasma, but also as one possible explanation of the initial heating and upward flows of ions in the cleft ion fountain and nightside auroral oval, both of which are a major source of plasma for the magnetosphere.

Assessing the sensitivities of a distributed snow model to forcing data resolution

Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

Simulations of a photovoltaic-thermal ground source heat pump system

A ground source heat pump assisted by an array of photovoltaic (PV)-thermal modules was studied in this work. Extracting heat from an array of PV modules should improve the performance of both the PV cells and the heat pump. A series of computer simulations compare the performance of a ground source heat pump with a short ground circuit, used to provide space heating and domestic hot water at a house in southern England. The results indicate that extracting heat from an array of PV-thermal modules would improve the performance of a ground source heat pump with an undersized ground loop. Nevertheless, open air thermal collectors could be more effective, especially during winter. In one model more electricity was saved in ohmic heating than was generated by cooling the PV cells. Cooling the PV modules was found to increase their electrical output up to 4%, but much of the extra electricity was consumed by the cooling pumps.

Simulation of long-term thermal characteristics of three Estonian lakes

A one-dimensional surface energy-balance lake model, coupled to a thermodynamic model of lake ice, is used to simulate variations in the temperature of and evaporation from three Estonian lakes: Karujärv, Viljandi and Kirjaku. The model is driven by daily climate data, derived by cubic-spline interpolation from monthly mean data, and was run for periods of 8 years (Kirjaku) up to 30 years (Viljandi). Simulated surface water temperature is in good agreement with observations: mean differences between simulated and observed temperatures are from −0.8°C to +0.1°C. The simulated duration of snow and ice cover is comparable with observed. However, the model generally underpredicts ice thickness and overpredicts snow depth. Sensitivity analyses suggest that the model results are robust across a wide range (0.1–2.0 m−1) of lake extinction coefficient: surface temperature differs by less than 0.5°C between extreme values of the extinction coefficient. The model results are more sensitive to snow and ice albedos. However, changing the snow (0.2–0.9) and ice (0.15–0.55) albedos within realistic ranges does not improve the simulations of snow depth and ice thickness. The underestimation of ice thickness is correlated with the overestimation of snow cover, since a thick snow layer insulates the ice and limits ice formation. The overestimation of snow cover results from the assumption that all the simulated winter precipitation occurs as snow, a direct consequence of using daily climate data derived by interpolation from mean monthly data.

Thermal aspects of satellite downscaling

The strong trend toward nanosatellites creates new challenges in terms of thermal balance control. The thermal balance of a satellite is determined by the heat dissipation in its subsystems and by the thermal connections between them. As satellites become smaller, heat dissipation in their subsystems tends to decrease and thermal connectivity scales down with dimension. However, these two terms do not necessarily scale in the same way, and so the thermal balance may alter and the temperature of subsystems may reach undesired levels. This paper focuses on low-Earth-orbit satellites. We constructed a generalized lumped thermal model that combines a generalized low-Earth-orbit satellite configuration with scaling trends in subsystem heat dissipation and thermal connectivity. Using satellite mass as a scaling parameter, we show that subsystems do not become thermally critical by scaling mass alone.

A study of adaptive thermal comfort in a well-controlled climate chamber

This paper aims to critically examine the application of Predicted Mean Vote (PMV) in an air-conditioned environment in the hot-humid climate region. Experimental studies have been conducted in a climate chamber in Chongqing, China, from 2008 to 2010. A total of 440 thermal responses from participants were obtained. Data analysis reveals that the PMV overestimates occupants' mean thermal sensation in the warm environment (PMV > 0) with a mean bias of 0.296 in accordance with the ASHRAE thermal sensation scales. The Bland–Altman method has been applied to assess the agreement of the PMV and Actual Mean Vote (AMV) and reveals a lack of agreement between them. It is identified that habituation due to the past thermal experience of a long-term living in a specific region could stimulate psychological adaptation. The psychological adaptation can neutralize occupants’ actual thermal sensation by moderating the thermal sensibility of the skin. A thermal sensation empirical model and a PMV-revised index are introduced for air-conditioned indoor environments in hot-humid regions. As a result of habituation, the upper limit effective thermal comfort temperature SET* can be increased by 1.6 °C in a warm season based on the existing international standard. As a result, a great potential for energy saving from the air-conditioning system in summer could be achieved.

Improvement and sensitivity analysis of thermal thin-ice thickness retrievals

Considering the sea ice decline in the Arctic during the last decades, polynyas are of high research interest since these features are core areas of new ice formation. The determination of ice formation requires accurate retrieval of polynya area and thin-ice thickness (TIT) distribution within the polynya.We use an established energy balance model to derive TITs with MODIS ice surface temperatures (Ts) and NCEP/DOE Reanalysis II in the Laptev Sea for two winter seasons. Improvements of the algorithm mainly concern the implementation of an iterative approach to calculate the atmospheric flux components taking the atmospheric stratification into account. Furthermore, a sensitivity study is performed to analyze the errors of the ice thickness. The results are the following: 1) 2-m air temperatures (Ta) and Ts have the highest impact on the retrieved ice thickness; 2) an overestimation of Ta yields smaller ice thickness errors as an underestimation of Ta; 3) NCEP Ta shows often a warm bias; and 4) the mean absolute error for ice thicknesses up to 20 cm is ±4.7 cm. Based on these results, we conclude that, despite the shortcomings of the NCEP data (coarse spatial resolution and no polynyas), this data set is appropriate in combination with MODIS Ts for the retrieval of TITs up to 20 cm in the Laptev Sea region. The TIT algorithm can be applied to other polynya regions and to past and future time periods. Our TIT product is a valuable data set for verification of other model and remote sensing ice thickness data.

Assessing how retrofit of traditional buildings impacts indoor environment and occupant’s thermal comfort

Buildings consume a large amount of energy, in both their use and production. Retrofitting aims to achieve a reduction in this energy consumption. However, there are concerns that retrofitting can cause negative impacts on the internal environment including poor thermal comfort and health issues. This research investigates the impact of retrofitting the façade of existing traditional buildings and the resulting impact on the indoor environment and occupant thermal comfort. A Case building located at the University of Reading has been monitored experimentally and modelled using IES software with monitored values as input conditions for the model. The proposed façade related retrofit options have been simulated and provide information on their effect on the indoor environment. The findings show a positive impact on the internal environment. The data shows a 16.2% improvement in thermal comfort after retrofit is simulated. This also achieved a 21.6% reduction in energy consumption from the existing building.

How do green roofs mitigate urban thermal stress under heat waves?

As the climate warms, heat waves (HW) are projected to be more intense and to last longer, with serious implications for public health. Urban residents face higher health risks because urban heat islands (UHIs) exacerbate HW conditions. One strategy to mitigate negative impacts of urban thermal stress is the installation of green roofs (GRs) given their evaporative cooling effect. However, the effectiveness of GRs and the mechanisms by which they have an effect at the scale of entire cities are still largely unknown. The Greater Beijing Region (GBR) is modeled for a HW scenario with the Weather Research and Forecasting (WRF) model coupled with a state-of-the-art urban canopy model (PUCM) to examine the effectiveness of GRs. The results suggest GR would decrease near-surface air temperature (ΔT2max = 2.5 K) and wind speed (ΔUV10max = 1.0 m s-1) but increase atmospheric humidity (ΔQ2max = 1.3 g kg-1). GRs are simulated to lessen the overall thermal stress as indicated by apparent temperature (ΔAT2max = 1.7 °C). The modifications by GRs scale almost linearly with the fraction of the surface they cover. Investigation of the surface-atmosphere interactions indicate that GRs with plentiful soil moisture dissipate more of the surface energy as latent heat flux and subsequently inhibit the development of the daytime planetary boundary layer (PBL). This causes the atmospheric heating through entrainment at the PBL top to be decreased. Additionally, urban GRs modify regional circulation regimes leading to decreased advective heating under HW.