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Knowing the Freeze-Thaw (FT) state/ice content/freezing front depth of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not well known. We present a series of new frozen soil detection algorithms based on the daily variation of the H-polarized brightness temperature. Exploiting the daily variation signal allows for a more reliable state detection, particularly during the transition periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithms explore and prove that we can get the Freeze-Thaw (FT) state/ice content/freezing front depth of the land surface with a delicate analysis of the L-band passive brightness temperature signals. These studies are expected to extend L-band microwave remote sensing data for improved FT detection.

The dynamic change of frozen soil is crucial to land-surface modeling, carbon feedback studies, ground engineering (e.g., constructions), and microwave remote sensing. L-Band satellite missions Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) are currently exploited to characterize soil into freeze or thaw (FT) states. However, brightness temperatures (TB) at L-band contain more information besides the FT state, particularly over permafrost or seasonally frozen soil, which has not been explored via current retrieval algorithms. To examine the potential for L-band TB observations, we define an index called Profile-Averaged Frozen Soil Fraction (Ff) related to Diurnal Amplitude Variation (DAV) of TB (i.e., ΔTB) based on the optical depth of the frozen soil column. We evaluated Ff inferred from the 0th-order microwave transfer model with the SMAP L1c product, the ground-based European Space Agency L-Band Radiometer III (ELBARA-III) TB observations, and temperature profiles collected at the Maqu station in northeastern Tibet. While there is a clear relationship between Ff and ΔTB, no apparent link exists with the ice content fraction (Ffi) within a fixed-depth soil column. The proposed model certifies that the profile-averaged soil ice content Ff relates to the dynamic microwave penetration depth by math and field measurement. The model reproduces well ΔTB in Period Freezing but has problems in Period Thawing when melted surface water obstruct the microwave signals. Our findings can be used to exploit ΔTB between 6 am and 6 pm, as a typically overpassing time by the SMOS and SMAP satellites, for estimating Ff, which can be further applied in weather/climate forecasting and for improving land-surface modeling.

Knowing the Freeze-Thaw (FT) state of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Near-surface air temperature and land surface temperature are usually used in meteorology to infer the FT-state. However, the uncertainty is large because both temperatures can hardly be distinguished from remote sensing. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not known sufficiently well. We present a new FT-state detection algorithm based on the daily variation of the H-polarized brightness temperature of the SMAP L3c FT global product for the northern hemisphere, which is available from 2015 to 2021. The exploitation of the daily variation signal allows for a more reliable state detection, particularly during the transitions periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithm requires no reference values; its results agree with the SMAP FT state product by up to 98 % in summer and up to 75 % in winter. Compared to the FT state inferred indirectly from the 2-m air temperature of the ERA5-land reanalysis, the new FT algorithm has a similar performance as the SMAP FT product. The most significant differences occur over the midlatitudes, including the Tibetan plateau and its downstream area. Here, daytime surface heating may lead to daily FT transitions, which are not considered by the SMAP FT state product but are correctly identified by the new algorithm. The new FT algorithm suggests a 15 days earlier start of the frozen-soil period than the ERA5-land’s 2-m air temperature estimate. This study is expected to extend L-band microwave remote sensing data for improved FT detection.

Microwave remote sensing is the most promising tool for monitoring near-surface soil moisture distributions globally. With the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions in orbit, considerable efforts are being made to evaluate derived soil moisture products via ground observations, microwave transfer simulation, and independent remote sensing retrievals. Due to the large footprint of the satellite radiometers of about 40 km in diameter and the spatial heterogeneity of soil moisture, minimum sampling densities for soil moisture are required to challenge the targeted precision. Here we use 400 m resolution simulations with the regional Terrestrial System Modeling Platform (TerrSysMP) and its coupling with the Community Microwave Emission Modelling platform (CMEM) to quantify the maximum sampling distance allowed for soil moisture and brightness temperature validation. Our analysis suggests that an overall sampling distance of finer than 6 km is required to validate the targeted accuracy of 0.04 cm3 cm−3 with a 70 % confidence level in SMOS and SMAP estimates over typical mid-latitude European regions. The maximum allowed sampling distance depends on the land-surface heterogeneity and the meteorological situation, which influences the soil moisture patterns, and ranges from about 6 to 17 km for a 70 % confidence level for a typical year. At the maximum allowed sampling distance on a 70 % confidence level, the accuracy of footprint-averaged soil moisture is equal to or better than brightness temperature estimates over the same area. Estimates strongly deteriorate with larger sampling distances. For the evaluation of the smaller footprints of the active and active–passive products of SMAP the required sampling densities increase; e.g., when a grid resolution of 3 km diameter is sampled by three sites of footprints of 9 km sampled by five sites required, only 50 %–60 % of the pixels have a sampling error below the nominal values. The required minimum sampling densities for ground-based radiometer networks to estimate footprint-averaged brightness temperature are higher than for soil moisture due to the non-linearities of radiative transfer, and only weakly correlated in space and time. This study provides a basis for a better understanding of the sometimes strong mismatches between derived satellite soil moisture products and ground-based measurements.

L-band passive microwave remote sensing is one of the most effective methods to map the global soil moisture distribution, yet, at which soil depth satellites are measuring is still inconclusive. Recently, with the Lv’s multilayer soil effective temperature scheme, such depth information can be revealed in the framework of the zeroth-order incoherent model when soil temperature varies linearly with soil optical depth. In this paper, we examine the relationships between soil temperature microwave sensing depth, penetration depth, and soil effective temperature, considering the nonlinear case. The soil temperature sensing depth often also named penetration depth is redefined as the depth where soil temperature equals the soil effective temperature. A method is developed to estimate soil temperature sensing depth from one pair of soil temperature and moisture measurement at an arbitrary depth, the soil surface temperature, and the deep soil temperature which is assumed to be constant in time. The method can be used to estimate the soil effective temperature and soil temperature sensing depth.

Soil information (e.g. soil texture and porosity) from existing soil datasets over the Tibetan Plateau (TP) is claimed to be inadequate and even inaccurate for determining soil hydraulic properties(SHP) and soil thermal properties (STP), hampering the understanding of the land surface process. As the soil varies across three dominant climate zones (i.e. arid, semi-arid, and semi-humid) over the TP, the associated SHP/STP is expected to vary correspondingly. To obtain an explicit insight into the soil hydro-thermal consistency for land surface modelling over the TP, in situ and laboratory measurements of over 40 soil property profiles were obtained across the climate zones. Results show that porosity and SHP/STP differ across the climate zones and strongly depend on soil texture. In particular, it is proposed that gravel impact on porosity and SHP/STP are both considered in the arid zone and in deep layers of the semi-arid zone. Parameterization schemes for porosity, SHP and STP are investigated and compared with measurements taken. This reveals that the porosity determined by the bulk density scheme is the most applicable for the TP. To determine the SHP, including soil water retention curves and hydraulic conductivities, the pedotransfer functions (PTFs) developed by Cosby et al. (1984) (for the Clapp-Hornberger model) and the continuous Wösten et al. (1999) (for the van Genuchten-Mualem model) are recommended. The STP parameterization scheme proposed by Farouki (1981) based on the mode of De Vries (1963) performed better across the TP than other schemes. Using the parameterization schemes mentioned above, the uncertainties of five existing regional and global soil datasets and their derived SHP/STP over the TP are quantified through comparison with in situ and laboratory measurements. The measured soil property dataset is available at http://doi.org/10.4121/uuid:61db65b1-b2aa-4ada-b41e-61ef70e57e4a.

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave radiative transfer modeling system. This new system improves the modeling of brightness temperature in both horizontal and vertical polarization. (3) A multiyear (2001–2018) monthly terrestrial actual evapotranspiration and its spatial distribution on the Tibetan Plateau is generated using the surface energy balance system (SEBS) forced by a combination of meteorological and satellite data. (4) A comparison of four large scale soil moisture products to in situ measurements is presented. (5) The trajectory of water vapor transport in the canyon area of Southeast Tibet in different seasons is analyzed, and (6) the vertical water vapor exchange between the upper troposphere and the lower stratosphere in different seasons is presented.

Microwave remote sensing is the most promising tool for monitoring global-scale near-surface soil moisture distributions. With the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions in orbit, considerable efforts are made to evaluate their soil moisture products via ground observations, forward microwave transfer simulation, and retrievals. Due to the large footprint of the satellite radiometers of about 40 km in diameter and the spatial heterogeneity of soil moisture, minimum sampling densities for soil moisture are required to challenge the targeted precision. Here we use 400 m resolution simulations with the regional terrestrial system model TerrSysMP and its coupling with the Community Microwave Emission Modelling platform (CMEM) to quantify sampling distance required for soil moisture and brightness temperature validation. Our analysis suggests that an overall sampling resolution of better than 6 km is required to validate the targeted accuracy of 0.04 cm3/cm3 (70 % confidence level) in SMOS and SMAP over typical midlatitude European regions. The minimum sampling resolution depends on the land-surface inhomogeneity and the meteorological situation, which influence the soil moisture patterns, and ranges from about 7 km to 17 km for a 70 % confidence level for a typical year. At the minimum sampling resolution for a 70 % confidence level also the accuracy of footprint-averaged brightness temperature estimates is equal or better than 15 K/10 K for H/V polarization. Estimates strongly deteriorate with sparser sampling densities, e.g., at 3/9 km with 3/5 sampling sites the confidence level of derived footprint estimates can reach about 0.5–0.6 for soil moisture which is much less than the standard 0.7 requirements for ground measurements. The representativeness of ground-based soil moisture and brightness temperature observations – and thus their required minimum sampling densities – are only weakly correlated in space and time. This study provides a basis for a better understanding of sometimes strong mismatches between derived satellite soil moisture products and ground-based measurements.

Traditionally, effective soil temperature (Teff) has been considered to be a secondary intermediate variable in microwave radiative transfer theory. However, its impact on microwave radiometry is comparable to that of vegetation cover, soil surface roughness and dielectric constant. Teff is defined as the weighted temperature of the emitting layers, where the weighting involved depends on the soil moisture profile. In this study, we evaluate the suitability of various models for estimating Teff using temperature and moisture profiles obtained from a land surface model. MERRA-Land (the Modern-Era Retrospective analysis for Research and Applications-Land) soil moisture profiles and temperature profiles were used to reproduce global Teff data sets with single parameter schemes (e.g. the Beta Soil Moisture Active Passive, SMAP scheme), two-parameter Choudhury's schemes (e.g. the current SMAP's scheme), two-parameter Wigneron schemes (e.g. the current Soil Moisture and Ocean Salinity scheme, SMOS), and multilayer Teff schemes (e.g. Lv′s scheme). The results show that differences in Teff between these schemes are usually

Soil moisture is an essential variable in Earth surface modeling. Two dedicated satellite missions, the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP), are currently in operation to map the global distribution of soil moisture. However, at the longer L-band wavelength of these satellites, the emitting behavior of the land becomes very complex due to the unknown deeper penetration depth. This complexity leads to more uncertainty in calibration and validation of satellite soil moisture product and their applications. In the framework of zeroth-order incoherent microwave radiative transfer model, the soil effective temperature is the only component that contains depth information and thus provides the necessary link to quantify the penetration depth. By means of the multi-layer soil effective temperature (Lv’s T e f f ) scheme, we have determined the relationship between the penetration depth and soil effective temperature and verified it against field observations at the Maqu Network. The key findings are that the penetration depth can be estimated according to Lv’s T e f f scheme with the assumption of linear soil temperature gradient along the optical depth; and conversely, the soil temperature at the penetration depth should be equal to the soil effective temperature with the same linear assumption. The accuracy of this inference depends on to what extent the assumption of linear soil temperature gradient is satisfied. The result of this study is expected to advance understanding of the soil moisture products retrieved by SMOS and SMAP and improve the techniques in data assimilation and climate research.

Polycrystalline cubic boron nitride cutting tools in hard dry precision cutting bearing steel has got more and more widely used, on account of their higher hardness, high wear resistance and high temperature red hardness. It is set as an example that the GCr15 rod is dry hard turned with welded PcBN cutting tools. In the present study, the temperature distribution cloud and equivalent stress distribution nephogram of PcBN tool rake surface were obtained by using the finite element simulation analysis method under different processing parameters. Then reasonable processing parameters of dry hard-turning were obtained by comparison and analysis. Based on orthogonal experiment design, the appropriate parameters such as cutting speed, cutting depth and feed rate were given in taking surface roughness of the workpiece and the tool flank wear as the evaluation indexes. The result of the turning test was as same as that of the finite element analysis, which confirms the validity of the finite element analysis. The experiments and finite element analysis results showed that the equivalent low stress, workpiece ideal surface roughness and the smaller flank wear of cutting tool could be obtained in which the cutting speed was at 200 m/min, the cut depth was 0.20 mm and the feed rate was 0.15 mm/rev. This research provides an important experimental basis for a reasonable formulation of the process of dry turning ball bearing steel.

The effective soil temperature (Teff) is essential for the retrieval of soil moisture information, when satellite microwave remote sensing data are used. In this investigation, a new two-layer scheme (Lv's scheme) is developed to estimate Teff considering wavelength, soil moisture, sampling depth, and soil temperature. The accuracy of the estimated Teff is verified with data collected in a field experiment at the Maqu Climate and Environment Observatory in the source region of the Yellow River. In addition to clearly defining the physical meaning of Lv's scheme, this study explains the physical meaning of Choudhury's C parameter, which is empirically determined by a least-square method. It was found that Lv's scheme does not require the fitting parameters. Further, Lv's scheme can be used to estimate Teff based on soil moisture data at surface level or any other specified soil depths, thus creating the opportunity to use observation and modeled data from different depths.

Glycaemic control is recognized as one of the important aspects in managing critically ill patients. Both hyperglycaemia and hypoglycaemia independently increase the risk of patient mortality. Hence, the identification of optimal glycaemic control is of paramount importance in the management of critically ill patients.The aim of this literature review is to examine the current status of glycaemic control in critically ill adult patients. This literature review will focus on randomized controlled trials comparing intensive insulin therapy to conventional insulin therapy, with an objective to identify optimal blood glucose level targets for critically ill adult patients.A literature review was conducted to identify large randomized controlled trials for the optimal targeted blood glucose level for critically ill adult patients published since 2000. A total of eight studies fulfilled the selection criteria of this review.With current human and technology resources, the results of the studies support commencing glycaemic control once the blood glucose level of critically ill patients reaches 10 mmol/L and maintaining this level between 8 mmol/L and 10 mmol/L.This literature review provides a recommendation for targeting the optimal blood glucose level for critically ill patients within moderate blood glucose level target range (8-10 mmol/L). The need for uniformed glucometrics for unbiased reporting and further research for optimal blood glucose target is required, especially in light of new technological advancements in closed-loop insulin delivery and monitoring devices.This literature review has revealed a need to call for consensus in the measurement and reporting of glycaemic control using standardized glucometrics.

Effective soil temperature T e f f is one of the basic parameters in passive microwave remote sensing of soil moisture. At present, dedicated satellite soil moisture monitoring missions use the L-band as the operating frequency. However, T e f f at the L-band is strongly affected by soil moisture and temperature profiles. Recently, a two-layer scheme and a corresponding multilayer form have been developed to accommodate such influences. In this study, the soil moisture/temperature data collected and simulated by the Noah land surface model across the Maqu Network are used to verify the newly developed schemes. There are two key findings. Firstly, the new two-layer scheme is able to assess which site provides relatively higher accuracy when estimating T e f f . It is found that, on average, nearly 20% of the T e f f signal cannot be captured by the Maqu Network, in the currently assumed common installation configuration. This knowledge is important, since the spatial averaged brightness temperature (a function of T e f f ) is used to determine soil moisture. Secondly, the developed method has made it possible to identify that the optimal mounting depths for the observation pair are 5 cm and 20 cm for calculating T e f f at the center station in the Maqu Network. It has been suggested that the newly developed method can provide an objective way to configure an optimal soil moisture/temperature network and improve the representativeness of the existing networks regarding the calculation of T e f f .

Surface energy partitioning and the characteristics of the water and energy cycle provide important information for improving land surface and weather forecast modelling. In this study, the land-atmospheric water and energy cycle of winter wheat was investigated on Loess Plateau in the northwest of China, using the eddy covariance technique, soil heat flux, and four component radiation measurements during the period from 8 April 2006 to 15 July 2006. Results show that the four components underwent daily changes throughout the period, and varied diurnally according to the synoptic conditions. Latent heat flux was the main consumer of available energy during the studied period. The daily energy partitionings LE/Rn, Hs/Rn and G0/Rn were on average 45%, 34% and 10%, respectively, and the Bowen ratio is estimated at 0.90. Surface albedo of winter wheat field was on average 0.19, over the total period from 8 April to 15 July, but decreased at the time of the heading of the wheat as compared to other seasons because of increased vegetation cover. The energy closure results show that the energy balance closure reached 89% through a thermal storage term of soil correction, which indicates that an energy imbalance of 11% was encountered in our observations. The daily variations in the water and energy fluxes were also analysed, including the diurnal variations on cloudy and clear sky days. Results show that the available sensible as well as latent heat flux both changed daily. The latent heat flux was primarily controlled by antecedent precipitation, with several high latent heat flux days being produced after intensive rain events. The sensible heat flux was mainly controlled by net radiation.