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Evaporative fraction (EF) is the ratio of latent heat (LE in W m−2) to available energy at the land surface. It can aid in partitioning the Sun's energy available at the Earth's surface into surface energy fluxes to understand land–atmosphere interactions as well as monitoring Evapotranspiration and terrestrial drought conditions. In this study, the feasibility of estimating instantaneous, diurnal, and daily EF with minimal satellite and meteorological inputs based on the temperature difference-vegetation index framework is explored in South Florida, United States (US). The model performance is assessed against the ground observations collected at three flux stations between 2008 and 2011. It was found that the energy balance closure was improved by 9% at the long hydroperiod marsh site (i.e. US-Elm) and 6% at the short hydroperiod marsh site (i.e. US-Esm) after water heat storage (W) correction was applied on energy fluxes since W is more important than soil heat flux (G) for wetland ecosystems. The results further indicated that the model produced accurate EF estimates and performed the best on diurnal, then instantaneous, and lastly daily periods. Overall, the model can be used to produce spatially continuous EF and ET maps since the flux towers are no longer active. [ABSTRACT FROM AUTHOR]

Downward shortwave radiation (DSR) is a critical variable in energy balance driving Earth's surface processes. Satellite-derived and reanalysis DSR products have been developed and continuously improved during the last decades. However, as those products have different temporal resolutions, their performances in different time scales have not been well-documented, particularly in China. This study intended to evaluate several DSR products across multiple time scales (i.e. instantaneous, 1-hourly, daily, and monthly average) and ecosystems in China. Six DSR products, including GLASS, BESS, CLARA-A2, MCD18A1, ERA5 and MERRA-2, were evaluated against ground measurements at Chinese Ecosystem Research Network (CERN) and integrated land-atmosphere interaction observation (TPDC) sites from 2009 to 2012. The instantaneous DSR of MCD18 showed a root mean square error (RMSE) of 146.02 W/m2. The hourly RMSE of ERA5 (155.52 W/m2) was largely smaller than MERRA-2 (188.53 W/m2). On the daily and monthly scale, BESS had the most optimized accuracy among the six products (RMSE of 36.82 W/m2). For the satellite-derived DSR products, the monthly accuracy at CERN can meet the threshold accuracy requirement set by World Meteorological Organization (WMO) for Global Numerical Weather Prediction (20 W/m2). [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is an atmosphere-land interaction, which represents the first thermal reaction of the environmental changes occurring in the earth surface, being one of the most important factors used in the earth sciences. Jazmourian basin, in the southeast of Iran, is a fertile agricultural land with diverse topography and unique climatic conditions. Due to its significance as one of the most important agricultural poles of Iran, the LST variations are of great interest due to their high impact on the environmental processes, especially in the land cover. In recent years, Moderate Resolution Imaging Spectroradiometer images have been extensively used to estimate the LST due to their spatial and temporal homogeneity and freely available showing improved capabilities of climate analysis in the areas with scarce observation networks. We used a combination of MOD11C3 and MYD11C3 products of daytime and nighttime LST, covering the complete circadian cycle over Jazmourian basin, from 2003 to 2019. Results showed varied trends by months with a significantly positive increase in January. The spatial distribution revealed a generalized positive anomaly in the whole study area, with the highest values in central lowlands and lowest at eastern high elevations of the basin. The temporal and spatial analyses indicated high temperature differences between months and seasons as well as a wide range from −10°C to 65°C. [ABSTRACT FROM AUTHOR]

The surface energy budget over the Qinghai-Tibet Plateau (QTP) and the Arctic significantly influences the climate system with global consequences. The performances of 30 selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models were evaluated based on six sites in the QTP and Arctic. The simulation results for latent heat flux (LE) were more accurate in the QTP, where the correlation coefficient and root mean square error (RMSE) were 0.9 and 30 W m−2, respectively. The results for sensible heat flux (H) were more accurate in the Arctic, the correlation coefficient and RMSE were 0.8 and 24 W m−2, respectively. Furthermore, the multiple models mean results revealed that the surface energy flux had seasonal variation and regional differences over the QTP and the Arctic. In the QTP, H was the lowest in winter, increased in spring, and reached the maximum in summer. However, the transitional changes in spring and autumn were not apparent in the Arctic, mainly due to seasonal net radiation difference between the two places. LE was affected by precipitation and surface soil moisture content. This work is important for understanding land-atmosphere interactions and useful for improving the accuracy of land surface models simulations. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is an important variable to understand surface energy fluxes, land–atmosphere interactions, and urban thermal environments. Time series analysis of LSTs through semi-physical models such as the annual temperature cycle (ATC) model has become critical for these understandings. However, studies are lacking in examining and reconciling the inconsistency of time series LST modelling results across spatial scales, weakening the reliability of these semi-physical models to characterize landscape thermal patterns. In this study, a percentile approach was used to reveal and reconcile discrepancies of ATC parameters estimated from Landsat (100 m) and Moderate Resolution Imaging Spectroradiometer (MODIS, 1000 m) LSTs. Results showed substantial differences across spatial scales for each of the ATC parameters, i.e. mean annual surface temperature (MAST), yearly amplitude of surface temperature (YAST), and revised phase shift (RPS), within the same land cover (e.g. 4.0 K difference between MAST estimated from Landsat LSTs and that from MODIS LSTs for grassland). The spatial distribution of ATC parameters estimated from MODIS LSTs across land cover types was quite different from that from Landsat LSTs. The percentile aggregation analysis suggested that the difference between MAST/YAST (and RPS) derived from MODIS LSTs and Landsat-aggregated values at the 25th (and 40th) percentile within a MODIS block was close to zero. Further regression analysis showed that differences in ATC parameters, particularly MAST and YAST, derived from different datasets could be reconciled. Our study offers new insights into understanding inconsistencies in and reconciliations of ATC parameters modelled at different spatial scales for quantifying landscape thermal patterns spatially and temporally. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a critical variable in energy and water partitioning at the interface between the land surface and atmosphere. In this study, we provided a robust method to retrieve soil moisture using optimal remotely sensed soil evaporative efficiency (SEE) information. Specifically, SEE was deduced from the triangle space constituted by remotely sensed land surface temperature (LST) and fractional vegetation cover (Fc). Theoretical solutions of the dry and wet boundaries were derived by annual-scale optimization and microwave SM calibration. The two limits of SM were obtained by linear fit function between SEE and microwave-based SM. The proposed method was validated at the Liaoning Province of China in the year 2011 by using MODerate Resolution Imaging Spectroradiometer (MODIS) and Soil Moisture and Ocean Salinity (SMOS) satellite images as input. Results indicated that the new method has not only bypassed the complex parametric scheme in the calculation of boundaries within the LST-Fc feature space but also performed superior in the estimation of soil moisture status at all-sky days. Besides, the optimal method has reproduced the spatial and temporal patterns of soil moisture reasonably well, with a root mean square error of 0.07 m3 m−3. Therefore, the proposed method can be regarded as a suitable tool to provide accurate and continuous monitoring of soil moisture. [ABSTRACT FROM AUTHOR]

Multiple parameters (brightness temperature, soil moisture, surface latent heat flux, surface air temperature and carbon monoxide) before and after the 2015 Nepal M7.8 Gorkha main earthquake and M7.3 Dolakha aftershock were analysed using satellite observation data. The thermal anomalies from optical and microwave data appear about two months prior to the 2015 Gorkha earthquake. Some of the parameters show anomalous changes at different altitudes about 20 days prior to the main earthquake event and 10 days prior to the strong aftershock. Our results show that pre-earthquake anomalous signals propagate from the in situ to the top of atmosphere, and the anomalies in the atmosphere often observed prior to an impending earthquake. The changes on the land surface and corresponding changes in meteorological and atmospheric parameters show existence of strong coupling during the seismogenic period, although the transfer mechanism of seismic/electromagnetic is still has to be investigated and understood. [ABSTRACT FROM AUTHOR]

Spatio-temporally continuous leaf area index (LAI) is required for surface process simulation, climate modelling and global change study. As a result of cloud contamination and other factors, the current LAI products are spatially and temporally discontinuous. A multi-sensor integration method was proposed in this paper to combine Terra-Moderate Resolution Imaging Spectroradiometer (MODIS), Aqua-MODIS, FY (FengYun) 3A-MEdium Resolution Spectrum Imager (MERSI) and FY3B-MERSI data to improve LAI spatio-temporal continuity. It consists of a normalization algorithm to eliminate the difference between MODIS and MERSI data in spatial and spectral aspects, a daily LAI retrieval algorithm based on neural networks and a maximum value compositing algorithm. The feasibility of our LAI retrieval method to improve continuity was assessed at national scale (in China). Results show that (1) the combination of multi-sensor data can significantly improve LAI temporal continuity, especially for mountainous regions which are characterized by high frequency of cloud coverage; (2) the improvement in spatial continuity is obvious as can be seen from the increase of retrieval ratio, defined as the ratio of the number of retrieved pixels to the total number of pixels, from 0.78 for GEOV1 LAI product, and 0.88 for MOD15A2 LAI product to 0.98 for multi-sensor LAI product. [ABSTRACT FROM AUTHOR]

Western Siberia's thermokarst lakes are highly dynamic hydrochemical systems that receive chemical elements from the surrounding peat soil and exchange greenhouse gases with the atmosphere, delivering dissolved carbon and metals to adjacent hydrological systems. Climate warming is likely to intensify the magnitude of these processes, thus seriously affecting the biogeochemical fluxes both on land and in the coastal zone of the Arctic Ocean. In this work, we review biogeochemical and morphological features of thermokarst water bodies comprising frozen palsa depressions up to large, kilometre-size lakes and drained lakes. Based on a compilation of more than a hundred analyses of these water bodies, we discuss the average concentration of organic carbon, as well as the major and trace elements, and predict the development of their chemical composition, CO2 and CH4 exchange with the atmosphere and effect on the riverine fluxes from the land to the ocean under the climate-warming scenario. The accelerating permafrost thaw and rising water temperatures in this region will probably shorten the life cycle of the thermokarst thaw water bodies, increase the fluxes of both CO2 and CH4 into the atmosphere, increase the concentration and delivery of dissolved organic carbon and related trace metals to the hydrological network and increase the potential bioavailability of micronutrients. Thus, the impact of permafrost thaw in Western Siberia on the global plantery processes, via the retroactive link between climate change and the thermokarst lakes' geochemical activity, may be more significant than is currently expected. [ABSTRACT FROM AUTHOR]

The seasonal variation of land–atmosphere coupling strength has been examined using an extended series of atmospheric general circulation model (AGCM) simulations. In the Western Sahel of Africa, strong coupling strength for precipitation is found in April and May, just prior to and at the beginning of the monsoon season. At this time, heat and water fluxes from the surface are strongly controlled by land conditions, and the unstable conditions in the lower level of the troposphere, as induced by local land state, allow the surface fluxes to influence the variability of convective precipitation—and thus the timing of monsoon onset. EditorZ. W. Kundzewicz CitationYamada, T.J., Kanae, S., Oki, T., and Koster, R.D., 2013. Seasonal variation of land–atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model.Hydrological Sciences Journal, 58 (6), 1276–1286. [ABSTRACT FROM AUTHOR]

To better understand the basic characteristics of the land surface energy budget, nearly 7 years of continuous measurements at the Qomolangma Station for Atmospheric and Environmental Observation and Research, Chinese Academy of Sciences (QOMS/CAS) (28.21°N, 86.56°E, 4276 m a.s.l.) have been analyzed systematically. Seasonal and annual variations of micrometeorological measurements and land surface energy balance were analyzed. The general nature of the diurnal variation of the surface winds on the north of Mt. Everest is represented by a maximum in the afternoon and a constant wind speed in the early morning, which is controlled not only by the significant glacier wind but also by the local mountain-valley circulation and upper-level wind. Surface albedo decreases with increasing soil moisture content, showing the typical exponential relation between surface albedo and soil moisture. The data set disclosed that the high soil moisture in summer is coordinated with low albedo. The ratio between sensible heat and net radiation (H/Rn) can be as high as 0.49 when the soil is dry. The ratio (H/Rn) decreases to 0.14 with the increasing of soil moisture. On the contrary, the ratio between latent heat flux and net radiation (LE/Rn) is increased when soil moisture is rising. The highest ratio (LE/ Rn) can be as high as 0.5 when soil moisture changes between 15% and 20%. After defining the effects of different soil moisture level on partitioning of surface available energy into sensible and latent heat fluxes, we can qualify how much the sensible heating is decreasing and the latent heating is increasing in this region under current plateau environment changes of warming and moistening. [ABSTRACT FROM AUTHOR]

Biomass burning is a major source of black carbon aerosols. These aerosols have negative human health impacts and can affect the radiation budget and climate both directly and indirectly. Uncertainty regarding the contribution of biomass burning to the concentration of aerosols is higher in Southeast Asia than in some other regions of substantial biomass burning because of other sources of pollution such as significant fossil fuel combustion. The shifting agricultural tradition is still evident in the region. Significant expansion of cash crop production is also associated with biomass burning, as is the seasonal burning of crop residue. The effects of such land-use processes extend into the atmosphere, and localized events have regional and global implications for air-pollution-related health effects and climate. This article synthesizes the issue of biomass burning and aerosols in the context of land-use practices in Southeast Asia and makes suggestions of how to use available data sources in an integrated analysis. [ABSTRACT FROM AUTHOR]