Modeling Impacts of Mining Activity-induced Landscape Change on Local Climate

As a major energy source, coal has been mined on an increasingly larger scale as the social economy has continuously developed, resulting in drastic land type changes. These changes in turn cause changes in the local climate and affect the local ecological environment. Therefore, for coal cities, mining activities are an important factor influencing the local climate, and clarifying the impact of mining activities on the ecological environment is important for guiding regional development. In this paper, the impact of land use/cover changes (LUCCs) on local temperature in the spring and summer seasons from 1980 to 2018 was simulated using the Weather Research and Forecasting (WRF) model with Xilinhot city as the study area, and the regional distribution of local surface energy was analyzed in conjunction with the ground-air energy transfer process. The results show that the grassland area in Xilinhot remained above 85% from 1980 to 2018, so mining activities had a small impact on the average temperature of the whole region. However, in the mining area, the warming effect caused by mining activities was more obvious, with an average temperature increase of 0.822 K. Among other land transformation types, the conversion to water bodies had a very obvious cooling effect, lowering the temperature by an average of 2.405 K. By comparing the latent heat flux (LH), sensible heat flux (SH) and ground heat flux (GRD) under different land use types, it was found that in 2018, the LH decreased by 0.487 W/m2, the SH decreased by 0.616 W/m2 and the GRD decreased by 0.753 W/m2. The conversion to built-up urban land caused a significant decrease in the LH in the corresponding area, allowing more energy to be used to increase SH values, which resulted in significantly higher urban temperatures than in other areas.

An estimate of ground heat flux for a seasonal snow cover

An estimation of ground heat flux for two locations has been done using temperature gradient method. Effective media approach has been adopted for predicting the effective thermal conductivity of ground. For comparison, in situ measurement of effective thermal conductivity of ground has also been done by thermal probe method. The measured values of thermal conductivity are in agreement with the calculated values. The estimated values of ground heat flux have been used to evaluate the melt rate at ground-snow interface.

Validation of AVHRR Land Surface Temperature with MODIS and In Situ LST—A TIMELINE Thematic Processor

Land Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been available since the early 1980s. In the TIMELINE project, LST is derived for the entire operating period of AVHRR sensors over Europe at a 1 km spatial resolution. In this study, we present the validation results for the TIMELINE AVHRR daytime LST. The validation approach consists of an assessment of the temporal consistency of the AVHRR LST time series, an inter-comparison between AVHRR LST and in situ LST, and a comparison of the AVHRR LST product with concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) LST. The results indicate the successful derivation of stable LST time series from multi-decadal AVHRR data. The validation results were investigated regarding different LST, TCWV and VA, as well as land cover classes. The comparisons between the TIMELINE LST product and the reference datasets show seasonal and land cover-related patterns. The LST level was found to be the most determinative factor of the error. On average, an absolute deviation of the AVHRR LST by 1.83 K from in situ LST, as well as a difference of 2.34 K from the MODIS product, was observed.

Study of energy balance components at different growth stages of green gram grown in new alluvial zone of West Bengal

An experiment was conducted in the experimental farm of Bidhan Chandra KrishiViswavidyalaya, Nadia, West Bengal to study the radiation pattern and its balance over green gram (Vignaradiata var. Samrat). The BREB method was used to determine the sensible heat flux and latent energy. The net radiation was measured through net radiometer and the ground heat flux was measured using Fourier's law. Both the diurnal and seasonal variation of net radiation were studied. Similarly, the energy balance components were studied regularly for different crop growth stages as well as on diurnal basis. It is observed that the net radiation varies from 6.32 Wm-2 to 606.43 Wm-2. The latent heat flux constitutes more than 50% of the net radiation for all growth stages as depicted by energy balance partitioning. The sensible heat flux is partitioned into 10% to 20% of total net radiation throughout the growth stages of green gram, which is the lowest in magnitude among all three energy fluxes. The relationship between Bowen ratio and Vapour pressure deficit (VPD), Bowen ratio and Canopy air temperature difference (CATD) was studied. It was found that Bowen ratio is negatively correlated with VPD but positively correlated with CATD. This study enables to monitor ET pattern through latent heat flux and microclimatic characteristics through sensible and ground heat flux.

Latent Heat Flux (Evapotranspiration) in Summer Season on Rooftop Greening Soil with Bamboo Charcoal Sublayer at a Building in West Japan

The effect of a thin and light greening system with bamboo charcoal layer for water retention on heat fluxes, in particular latent heat flux (evapotranspiration rate), under no irrigation condition, on the rooftop of a building in Higashi-Hiroshima, West Japan, was investigated. In April 2019, lawn seeds (Zoysia tenuifolia) were sown which were germinated, reached a height of 70 mm by May when 100% of the vegetation area was covered. The air temperature and humidity at two different heights (0.3 m and 1.8 m) above greening soil surface, latent, and sensible heat fluxes were estimated. Bowen ratio was employed to collect the data on surface heat balance and soil water content during the summer season (June to September) in 2019 on the rooftop of a building in Higashi-Hiroshima, West Japan. The latent heat during daytime for a week without rainfall in each month was compared with the evapotranspiration rate. Owning to the vegetation development, the ground heat flux on greening soil surface decreased from -400 W/m2 to -200 W/m2 (flux from air to soil) during sunny daytime in July, and it was less than -100 W/m2 in August, although net radiation was maintained around 800 W/m2 over the season except in September. The monthly net radiation flux for an entire day (daytime and nighttime) ranged between 55 and 125 W/m2 (average: 95 W/m2) for the summer season of which 32-66% (average: 48%) was occupied by latent heat. Evapotranspiration from greening soil ranged between 1.24 and 1.82 mm/day, averaged at 1.51 mm/day throughout the season, which corresponded to about 26% of total rainfall over the season ( r 2 = 0.88 , p < 0.01 ; S . E = 0.06 ) between the estimated and measured values. These observations suggested that the thin and bamboo coal light soil layer greening system, even without constant irrigation, could maintain the development of lawn grass and transformed more than half of net radiation to latent heat, i.e., evapotranspiration, insulating most ground heat in midsummer, which may be mostly due to bamboo charcoal sublayer.

A comparison of gap-filling algorithms for eddy covariance fluxes and their drivers

The errors and uncertainties associated with gap-filling algorithms of water, carbon, and energy fluxes data have always been one of the main challenges of the global network of microclimatological tower sites that use the eddy covariance (EC) technique. To address these concerns and find more efficient gap-filling algorithms, we reviewed eight algorithms to estimate missing values of environmental drivers and nine algorithms for the three major fluxes typically found in EC time series. We then examined the algorithms' performance for different gap-filling scenarios utilising the data from five EC towers during 2013. This research's objectives were (a) to evaluate the impact of the gap lengths on the performance of each algorithm and (b) to compare the performance of traditional and new gap-filling techniques for the EC data, for fluxes, and separately for their corresponding meteorological drivers. The algorithms' performance was evaluated by generating nine gap windows with different lengths, ranging from a day to 365 d. In each scenario, a gap period was chosen randomly, and the data were removed from the dataset accordingly. After running each scenario, a variety of statistical metrics were used to evaluate the algorithms' performance. The algorithms showed different levels of sensitivity to the gap lengths; the Prophet Forecast Model (FBP) revealed the most sensitivity, whilst the performance of artificial neural networks (ANNs), for instance, did not vary as much by changing the gap length. The algorithms' performance generally decreased with increasing the gap length, yet the differences were not significant for windows smaller than 30 d. No significant differences between the algorithms were recognised for the meteorological and environmental drivers. However, the linear algorithms showed slight superiority over those of machine learning (ML), except the random forest (RF) algorithm estimating the ground heat flux (root mean square errors – RMSEs – of 28.91 and 33.92 for RF and classic linear regression – CLR, respectively). However, for the major fluxes, ML algorithms and the MDS showed superiority over the other algorithms. Even though ANNs, random forest (RF), and eXtreme Gradient Boost (XGB) showed comparable performance in gap-filling of the major fluxes, RF provided more consistent results with slightly less bias against the other ML algorithms. The results indicated no single algorithm that outperforms in all situations, but the RF is a potential alternative for the MDS and ANNs as regards flux gap-filling.

Local evaporation controlled by regional atmospheric circulation in the Altiplano of the Atacama Desert

We investigate the influence of regional atmospheric circulation on the evaporation of a saline lake in the Altiplano (also known as the Andean Plateau) region of the Atacama Desert. For that, we conducted a field experiment in the Salar del Huasco (SDH) basin (135 km east of the Pacific Ocean), in November 2018. The measurements were based on surface energy balance (SEB) stations and airborne observations. Additionally, we simulate the meteorological conditions on a regional scale using the Weather Research and Forecasting Model. Our findings show two evaporation regimes: (1) a morning regime controlled by local conditions, in which SEB is dominated by the ground heat flux (∼0.5 of net radiation), very low evaporation (LvE<30 W m−2) and wind speed <1 m s−1; and (2) an afternoon regime controlled by regional-scale forcing that leads to a sudden increase in wind speed (>15 m s−1) and a jump in evaporation to >500 W m−2. While in the morning evaporation is limited by very low turbulence (u*∼0.1 m s−1), in the afternoon strong winds (u*∼0.65 m s−1) enhance mechanical turbulence, increasing evaporation. We find that the strong winds in addition to the locally available radiative energy are the principal drivers of evaporation. These winds are the result of a diurnal cyclic circulation between the Pacific Ocean and the Atacama Desert. Finally, we quantify the advection and entrainment of free-tropospheric air masses driven by boundary layer development. Our research contributes to untangling and linking local- and regional-scale processes driving evaporation across confined saline lakes in arid regions.

Long-term energy balance measurements at three different mountain permafrost sites in the Swiss Alps

The surface energy balance is a key factor influencing the ground thermal regime. With ongoing climate change, it is crucial to understand the interactions of the individual heat fluxes at the surface and within the subsurface layers as well as their relative impacts on permafrost thermal regime. A unique set of high-altitude meteorological measurements has been analysed to determine the energy balance at three mountain permafrost sites in the Swiss Alps (Murtèl-Corvatsch, Schilthorn and Stockhorn), where data is being collected since the late 1990s in collaboration with the Swiss Permafrost Monitoring Network (PERMOS). All stations are equipped with sensors for four-component radiation, air temperature, humidity, wind speed and direction as well as ground temperatures and snow height. The three sites differ considerably in their surface and ground material composition as well as their ground ice contents. The energy fluxes are calculated based on two decades of field measurements. While the determination of the radiation budget and the ground heat flux is comparatively straightforward (by the four-component radiation sensor and thermistor measurements within the boreholes), larger uncertainties exist for the determination of turbulent sensible and latent heat fluxes. Our results show that mean air temperature at Murtèl-Corvatsch (1997–2018, 2600 m asl.) is −1.66 °C and has increased by about 0.7 °C during the measurement period. At the Schilthorn site (1999–2018, 2900 m asl.) a mean air temperature of −2.60 °C with a mean increase of 1.0 °C was measured. The Stockhorn site (2003–2018, 3400 m asl.) recorded lower air temperatures with a mean of −6.18 °C and an increase of 0.7 °C. Measured net radiation, as the most important energy input at the surface, shows substantial differences with mean values of 30.59 W m−2 for Murtèl-Corvatsch, 32.40 W m−2 for Schilthorn and 6.91 W m−2 for Stockhorn. The calculated turbulent fluxes show values of around 7 to 13 W m−2 using the Bowen ratio method and 3 to 15 W m−2 using the bulk method at all sites. Large differences are observed regarding the energy used for melting of the snow cover: at Schilthorn a value of 8.46 W m−2, at Murtèl-Corvatsch of 4.17 W m−2 and at Stockhorn of 2.26 W m−2 is calculated reflecting the differences in snow height at the three sites. In general, we found considerable differences in the energy fluxes at the different sites. These differences may help to explain and interpret the causes of the varying reactions of the permafrost thermal regime at the three sites to a warming atmosphere. We recognize a strong relation between the net radiation and the ground heat flux. Our results further demonstrate the importance of long-term monitoring in order to better understand the impacts of changes in the surface energy balance components on the permafrost thermal regime. The dataset presented can be used to improve permafrost modelling studies aiming at e.g. advancing knowledge about permafrost thaw processes. The data presented and described in this study is available for download at the following site http://dx.doi.org/10.13093/permos-meteo-2021-01 (Hoelzle et al., 2021).