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Ginger, valued for its medicinal properties and economic significance, is vulnerable to environmental stressors such as intense light and high temperatures, which can hinder its growth and development. Class III peroxidases (PRXs) are plant-specific oxidoreductases essential for plant development, growth, and stress responses. Despite their importance, there is limited information available on the function of the class III peroxidase gene family in ginger (ZoPRX). In this study, 103 ZoPRX members within the ginger genome were identified, unevenly distributed across 11 chromosomes. The identified ZoPRX members were categorized into five subfamilies based on gene structures, protein motifs, and phylogenetic analysis. Gene duplication analysis revealed that ZoPRX has primarily undergone segmental duplication. Interspecies homology analysis between ginger and Arabidopsis thaliana, Oryza sativa, and Musa acuminata suggested most ZoPRXs in ginger originated after the divergence of dicotyledon and monocotyledon. Analysis of promoter cis-acting elements identified defense and stress response elements in 39 genes and hormone response elements in 95 genes, indicating their potential roles in responding to environmental stresses. Quantitative Real-Time PCR (qRT-PCR) analysis confirmed that the majority of ZoPRX members are responsive to high temperature and intense light stress. This study provides a comprehensive understanding of the PRX family in ginger, thereby laying the groundwork for future investigations into the functional role of ZoPRX genes under high-temperature and intense light-stress conditions. [ABSTRACT FROM AUTHOR]

Ginger (Zingiber officinale Roscoe) is a significant medicinal and culinary plant, with its growth influenced by various biotic and abiotic factors. The FWL gene, containing the PLAC8 motif, is prevalent in fungi, algae, higher plants, and animals. In plants, FWL primarily regulates fruit weight, cell division, and participates in heavy metal transport. However, the FWL family members in ginger have not been previously identified. This study identified 21 FWL members within the ginger genome, distributed across nine chromosomes. These 21 FWL genes were categorized into five subfamilies based on the phylogenetic analysis. Gene-structure and motif analyses revealed that ZoFWL has been conserved throughout evolution. Concurrently, the ZoFWL gene exhibits a homologous evolutionary relationship only with Musa acuminata. We identified three pairs of fragment-repeat events encompassing five genes, which likely represent the primary mechanism for amplification within the ZoFWL gene family. The promoter regions of the ZoFWL genes are enriched with numerous cis-acting elements implicated in plant growth, development, and responses to abiotic stress. These include elements responsive to low temperatures, anaerobic induction, MYB binding sites integral to defense and stress responses, and drought inducibility. Expression profiling revealed that the ZoFWL genes are responsive to a quartet of abiotic stressors, with ZoFWL18, in particular, demonstrating a pronounced response to osmotic, low-temperature, heat, and salinity stresses. This underscores the pivotal role of ZoFWLs in abiotic-stress responses. Our findings offer valuable insights into the potential of the ZoFWL gene family in modulating ginger rhizome development and the genes' response to abiotic stressors, laying a foundational framework for future research into ginger's resistance breeding. [ABSTRACT FROM AUTHOR]

Purpose: Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance. Design/methodology/approach: This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm. Findings: This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments. Originality/value: It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional "cheating" information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs' decision-making abilities, thus improving the performance of both tasks at hand. [ABSTRACT FROM AUTHOR]

The passive microwave land surface emissivity (MLSE) plays a crucial role in retrieving various land surface and atmospheric parameters and in Numerical Weather Prediction models. The retrieval accuracy of MLSE depends on many factors, including the consistency of the input data acquisition time. The FengYun-3D (FY-3D) polar-orbiting meteorological satellite, equipped with passive microwave and infrared bands, offers time-consistent data crucial for MLSE retrieval. This study proposes a physics-based MLSE retrieval algorithm using all the input data from the FY-3D satellite. Based on the retrieved MLSE, the spatial distribution of the MLSE is closely correlated with the land cover types and topography. Lower emissivities prevailed over barren or sparsely vegetated regions, river basins, and coastal areas. Higher emissivities dominated densely vegetated regions and mountainous areas. Moderate emissivities dominated grasslands and croplands. Lower-frequency channels showed larger emissivity differences with different polarizations than those of higher-frequency channels in barren or sparsely vegetated regions. The MLSE across densely vegetated land areas, mountainous areas, and deserts showed small seasonal variations. However, woody savannas, grasslands, croplands, and seasonal snow-covered areas showed noticeable seasonal variations. For most land cover types, the differences between vertically and horizontally polarized emissivities remained relatively constant across seasons. However, certain grasslands in eastern Inner Mongolia and southern Mongolia showed clear seasonal variations. It is very difficult to verify the MLSE on a large scale. Consequently, the possible error sources in the retrieved MLSE were analyzed, including the brightness temperature errors (correlation coefficient ranging from 0.92 to 0.99) and the retrieved land surface temperature errors (Root Mean Square Error was 3.34 K and relation coefficient was 0.958). [ABSTRACT FROM AUTHOR]

The advantages of performing aerosol retrieval with multi-angle, multi-spectral photopolarimetric measurements over intensity-only measurements come from this technique's sensitivity to aerosols' microphysical properties, such as their particle size, shape, and complex refraction index. In this study, an extended LUT (Look Up Table) algorithm inherited from a previous work based on the assumption of surface reflectance spectral shape invariance is proposed and applied to PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) measurements to retrieve aerosols' optical properties including aerosol optical depth (AOD) and aerosol fine-mode fraction (FMF). Case studies conducted over East China for different aerosol scenes are investigated. A comparison between the retrieved AOD regional distribution and the corresponding MODIS (Moderate-resolution Imaging Spectroradiometer) C6 AOD products shows similar spatial distributions in the Jing-Jin-Ji (Beijing–Tianjin–Hebei, China's mega city cluster) region. The PARASOL AOD retrievals were compared against the AOD measurements of seven AERONET (Aerosol Robotic Network) stations in China to evaluate the performance of the retrieval algorithm. In the fine-particle-dominated regions, lower RMSEs were found at Beijing and Hefei urban stations (0.16 and 0.18, respectively) compared to those at other fine-particle-dominated AERONET stations, which can be attributed to the assumption of surface reflectance spectral shape invariance that has significant advantages in separating the contribution of surface and aerosol scattering in urban areas. For the FMF validation, an RMSE of 0.23, a correlation of 0.57, and a bias of −0.01 were found. These results show that the algorithm performs reasonably in distinguishing the contribution of fine and coarse particles. [ABSTRACT FROM AUTHOR]

Objective To explore the clinical significance of monitoring neuron specific enolase (NSE), carbohydrate antigen 125 (CA125), and carbohydrate antigen 199 (CA199) in patients with pneumoconiosis. Methods A retrospective analysis was conducted among 222 patients with pneumoconiosis admitted to this hospital from January 2018 to December 2022. The patients were divided into three groups according to the stage of pneumoconiosis (stage I, II, and III). The serum levels and abnormal rates of NSE, CA125, and CA199 among these groups were compared. Results Among the 222 patients with pneumoconiosis, 51 (22.97%) were in stage I, 52 (23.42%) were in stage II, and 119 (53.61%) were in stage III. There were statistically significant differences in serum NSE and CA125 levels among pneumoconiosis patients at different stages (P < 0.001), and serum NSE and CA125 levels in patients at stage III were higher than those in stage I and stage II (P < 0.001). There was no statistically significant difference in serum CA199 level among pneumoconiosis patients at different stages (P = 0.163). The abnormal rates of serum NSE, CA125, and CA199 levels among 222 patients were 45.05%, 27.93%, and 2.70%, respectively. There were statistically significant differences in serum NSE and CA125 abnormal rates among pneumoconiosis patients at different stages (both P < 0.001), and both showed an increasing trend with the increase of stage. Conclusions Monitoring serum NSE and CA125 in patients with pneumoconiosis can indicate the progression of their condition and provide references for the treatment plan. [ABSTRACT FROM AUTHOR]

Currently, there is variability in the spectral band thresholds for snow cover recognition using remote sensing in different regions and for complex terrains. Using Fengyun-3B Visible and Infra-Red Radiometer (FY-3B VIRR) satellite data, we applied random forest (RF) methodology and selected 13 feature variables to obtain snow cover. A training set was generated, containing approximately 1 million snow and nonsnow samples obtained in China from the snow monitoring reports issued by the National Satellite Meteorological Centre and four snow cover products from the Interactive Multi-sensor Snow and Ice Mapping System (IMS), the FY-3B Multi-Sensor Synergy (MULSS), the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product (MYD10A1), and the National Cryosphere Desert Data Center (NCDC). This training set contained many different samples of cloud types and snow under forest cover to help effectively distinguish snow and clouds and improve the recognition rate of snow under forest cover. Then, two RF snow cover recognition models were constructed for the snow and nonsnow seasons and they were used to conduct daily snow cover recognition in China from 2011 to 2020. The results show that the RF models constructed based on FY-3B VIRR data have good recognition performance for shallow snow, understory snow, and snow on the Qinghai-Tibetan Plateau. The recognition accuracy against weather stations and the spatial consistency with the IMS product are better than the MULSS, MYD10A1, and NCDC products. The overall accuracy of the RF product is 90.6%, and the recall rate is 93.8%. The omission and commission errors are 6.2% and 11.1%, respectively. Unlike other existing snow cover algorithms, the established RF model skips the complicated atmospheric correction and cloud identification processes and does not involve external auxiliary data; thus, it is more easily popularized and operationally applicable to generating long-time series snow cover products. [ABSTRACT FROM AUTHOR]

Cotton plays an essential role in global human life and economic development. However, diseases such as leaf blight pose a serious threat to cotton production. This study aims to advance the existing approach by identifying cotton blight infection and classifying its severity at a higher accuracy. We selected a cotton field in Shihezi, Xinjiang in China to acquire multispectral images with an unmanned airborne vehicle (UAV); then, fifty-three 50 cm by 50 cm ground framed plots were set with defined coordinates, and a photo of its cotton canopy was taken of each and converted to the L*a*b* color space as either a training or a validation sample; finally, these two kinds of images were processed and combined to establish a cotton blight infection inversion model. Results show that the Red, Rededge, and NIR bands of multispectral UAV images were found to be most sensitive to changes in cotton leaf color caused by blight infection; NDVI and GNDVI were verified to be able to infer cotton blight infection information from the UAV images, of which the model calibration accuracy was 84%. Then, the cotton blight infection status was spatially identified with four severity levels. Finally, a cotton blight inversion model was constructed and validated with ground framed photos to be able to explain about 86% of the total variance. Evidently, multispectral UAV images coupled with ground framed cotton canopy photos can improve cotton blight infection identification accuracy and severity classification, and therefore provide a more reliable approach to effectively monitoring such cotton disease damage. [ABSTRACT FROM AUTHOR]

The thermal infrared data of Fengyun 4A (FY-4A) geostationary meteorological satellite can be used to retrieve hourly land surface temperature (LST). In this paper, seven candidate algorithms are compared and evaluated. The Ulivieri (1985) algorithm is determined to be optimal for the algorithm of FY-4A LST official products. The refined algorithm coefficients for distinguishing dry and moist atmosphere were established for daytime and nighttime, respectively. Then, FY-4A LST official products under clear-sky conditions are produced. The validation results show that: (1) Compared with in-situ measured LST data at the HeBi crop measurement network, the root mean square errors (RMSE) were 2.139 and 2.447 K. Compared with in-situ measured LST data at Naqu alpine meadow site of Tibet plateau, the RMSE was 2.86 K. (2) When compared with the MODIS LST product, the RMSE was 1.64, 2.17, 2.6, and 1.73 K in March, July, October, and December, respectively. By the bias long-time change at a single site, RMSE of the XLHT (city) and GZH (desert) sites were 2.735 and 2.97 K, respectively. Overall, the preferred algorithm exhibits good accuracy and meets the required accuracy of the FY-4A mission. [ABSTRACT FROM AUTHOR]

The Directional Polarization Camera (DPC) onboard the Chinese Gaofen-5 satellite, launched in May 2018, has similar specifications as the POLDER-3 instrument. The SRON Remote Sensing of Trace gas and Aerosol Products (RemoTAP) full retrieval algorithm is applied to DPC measurements to retrieve aerosol properties including the total Aerosol Optical Depth (AOD), the fine/coarse mode AOD and the SSA (Single Scattering Albedo). Measurements of the global ground-based AERONET network between December 2019 and April 2020 have been used for the validation of the DPC retrievals. According to the average Fine Mode Fraction (FMF) of the selected AERONET stations, the stations are divided into urban stations (FMF ≥ 0.5) and dust stations (FMF < 0.5). For the total AOD validation, DPC retrievals show better performance over urban stations than over dust stations, with average biases of 0.055 and 0.106, and RMSEs of 0.151 and 0.228, respectively. Regarding the fine mode AOD, the retrieval also performs better over urban stations. Compared with the total AOD validation, both the relatively lower bias (0.021 and 0.065) and the higher Gfrac (Fraction of Good retrieval, 63.8% and 47.3%, respectively) further indicate that DPC performs better when fine mode aerosols dominate. For the land SSA validation, most of our SSA retrievals (~71%) show differences with AERONET SSA retrievals lower than 0.05. Case studies over fire spots and dust over northern China demonstrate the encouraging application potential of DPC aerosol products. The difference between fine and coarse AOD can provide more aerosol source information compared with the total AOD alone. Since the SSA retrievals are particularly sensitive to absorbing fine particles, they can be easily used in the tracking of biomass burning aerosol. [ABSTRACT FROM AUTHOR]

Typhoon-related precipitation over land can result in severe disasters such as floods and landslides, and satellites are a valuable tool for estimating surface precipitation with high spatial-temporal resolutions. Accordingly, this study develops a surface precipitation integration framework to combine high-resolution observations from the radiometers of two geostationary satellites, Fengyun-4A (F4) and Himawari-8 (H8), with high-density rain-gauge observations or IMERG data and atmospheric reanalysis data based on a random forest (RF) algorithm. The RF algorithm integrates cloud and atmospheric features from radiometric observations and reanalysis information, and the intensity and spatial distribution of precipitation can be revealed by high-density rain-gauge or IMERG data. We take three typhoons that made landfall in South China during 2018 as examples. The F4-based and H8-based results using rain-gauge data as the predictand both show excellent results, yielding correlation coefficients (R) of ∼ 0.75 and probabilities of detection (POD) of ∼ 0.95. In contrast, when IMERG data are used as the predictand, the corresponding R and POD drop to ∼ 0.5 and 0.93, respectively, due to the uncertainties related to IMERG retrievals. By carefully choosing the predictor, our RF algorithm successfully integrates the information from satellite observations, surface measurements and atmospheric reanalyses, resulting in precipitation estimates that are highly consistent with actual ground observations. Consequently, our proposed integration framework can reconstruct hourly surface precipitation estimates at high spatial-temporal resolutions for historical typhoon studies. [ABSTRACT FROM AUTHOR]

Currently, the satellite data used to estimate terrestrial net primary productivity (NPP) in China are predominantly from foreign satellites, and very few studies have based their estimates on data from China's Fengyun satellites. Moreover, despite their importance, the influence of land cover types and the normalized difference vegetation index (NDVI) on NPP estimation has not been clarified. This study employs the Carnegie—Ames—Stanford approach (CASA) model to compute the fraction of absorbed photosynthetically active radiation and the maximum light use efficiency suitable for the main vegetation types in China in accordance with the finer resolution observation and monitoring-global land cover (FROM-GLC) classification product. Then, the NPP is estimated from the Fengyun-3D (FY-3D) data and compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product. The FY-3D NPP is also validated with existing research results and historical field-measured NPP data. In addition, the effects of land cover types and the NDVI on NPP estimation are analyzed. The results show that the CASA model and the FY-3D satellite data estimate an average NPP of 441.2 g C m−2 yr−1 in 2019 for China's terrestrial vegetation, while the total NPP is 3.19 Pg C yr−1. Compared with the MODIS NPP, the FY-3D NPP is overestimated in areas of low vegetation productivity and is underestimated in high-productivity areas. These discrepancies are largely due to the differences between the FY-3D NDVI and MODIS NDVI. Compared with historical field-measured data, the FY-3D NPP estimation results outperformed the MODIS NPP results, although the deviation between the FY-3D NPP estimate and the in-situ measurement was large and may exceed 20% at the pixel scale. The land cover types and the NDVI significantly affected the spatial distribution of NPP and accounted for NPP deviations of 17.0% and 18.1%, respectively. Additionally, the total deviation resulting from the two factors reached 29.5%. These results show that accurate NDVI products and land cover types are important prerequisites for NPP estimation. [ABSTRACT FROM AUTHOR]

Background: Secondhand smoke is an important risk factor to breast cancer patients' survival. This article aimed to describe the epidemiological changes of health loss caused by female breast cancer attributable to secondhand smoke from 1990 to 2019. Methods: Data on breast cancer was derived from the Global Burden of Disease study 2019. The epidemiological status and trends were estimated using the number, age-standardized rate (ASR), and estimated annual percentage change (EAPC). Results: In 2019, secondhand smoke-related breast cancer caused 168.33×102 death, 5242.58×102 years of life lost (YLLs), and 334.03×102 years lived with disability (YLDs) globally. The overall ASR of death and YLLs caused by breast cancer attributable to secondhand smoke presented decreasing trends from 1990 to 2019, with the respective EAPCs of −0.78 and −0.87. Meanwhile, decreasing trends occurred in most geographic regions, particularly that of YLLs in high-income North America (EAPC = −3.35). At the national level, most countries/territories had decreasing trends of death and YLLs, particularly Denmark, in which the respective EAPCs were −4.26 and −4.64. However, the ASR of YLDs showed an increasing trend globally (EAPC = 0.32). Meanwhile, increasing trends were observed in most regions and countries, particularly the Solomon Islands and Lesotho, with the respective EAPCs being 6.18 and 4.33. The changing trends were closely associated with sociodemographic development. Conclusions: Trends in secondhand smoke-related death and YLLs caused by breast cancer declined from 1990 to 2019. However, secondhand smoke remains a challenge to the patients' longevity and quality of life. The findings informed strategies should be strengthened the control of secondhand smoking. [ABSTRACT FROM AUTHOR]

Methods of rainstorm disaster risk monitoring (RDRM) based on retrieved satellite rainfall data are studied. Due to significant regional differences, the global rainstorm disasters are not only affected by geography (such as topography and surface properties), but also by climate events. It is necessary to study rainstorm disaster-causing factors, hazard-formative environments, and hazard-affected incidents based on the climate distribution of precipitation and rainstorms worldwide. According to a global flood disaster dataset for the last 20 years, the top four flood disaster causes (accounting for 96.8% in total) related to rainstorms, from most to least influential, are heavy rain (accounting for 61.6%), brief torrential rain (16.7%), monsoonal rain (9.4%), and tropical cyclone/storm rain (9.1%). A dynamic global rainstorm disaster threshold is identified by using global climate data based on 3319 rainstorm-induced floods and rainfall data retrieved by satellites in the last 20 years. Taking the 7-day accumulated rainfall, 3- and 12-h maximum rainfall, 24-h rainfall, rainstorm threshold, and others as the main parameters, a rainstorm intensity index is constructed. Calculation and global mapping of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are performed based on terrain and river data, population data, and economic data. Finally, a satellite remote sensing RDRM model is developed, incorporating the above three factors (rainstorm intensity index, hazard-formative environment factor, and hazard-affected body factor). The results show that the model can well capture the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020. [ABSTRACT FROM AUTHOR]

Typhoon-related precipitation over land can result in severe disasters such as floods and landslides, and satellites are a valuable tool to estimate surface precipitation with high spatial-temporal resolutions. This study develops a high-resolution surface precipitation integration framework to combine observations from geostationary Fengyun-4A/ Himawari-8 (F4/H8) satellite radiometers, high-density rain-gauge observations (or Integrated Multisatellite Retrievals for GPM (IMERG) data) and atmospheric reanalysis (ERA5) based on a random forest (RF) algorithm. The RF methods fuse cloud and atmospheric features from radiometric observations and reanalysis information, and the intensity and spatial distribution of rainfall can be revealed by high-density rain-gauge or IMERGE observations. We take three typhoons made landfall in South China in 2018 as examples. Both F4- and H8-based results using rain-gauge data as the predictand show excellent results with correlation coefficients (R) with the references ~0.75 and probabilities of detection (POD) as large as 0.98, higher than current satellite-only results. However, if the IMERG data are used as the predictand, the corresponding R and POD drop to ~0.5 and 0.93, respectively, due to the uncertainties related to IMERG retrievals. By carefully choosing the predictors, the RF algorithm can clearly summarize the information from satellite observations, surface observations and atmospheric reanalysis, resulting in precipitation results that are highly consistent with the actual ground observations. Our proposed integration framework can not only reconstruct hourly surface precipitation estimation datasets at high-spatial resolution for historical typhoon studies but also potentially monitor the fine- resolution surface precipitation of frequent typhoons in near-real time. [ABSTRACT FROM AUTHOR]

Missing values in land surface temperature (LST) data are often observed in the cloud-sheltered area, thereby seriously limiting the spatiotemporal continuity of LST. In this work, Remotely Sensed Daily Land Surface Temperature Reconstruction model(RSDAST) is used to gap-fill the pixels sheltered by clouds in FY-3 C/VIRR LST. Result shows that the cloud pixels in VIRR and MODIS original LST (OLST) product can be reconstructed accurately, but the reconstruction accuracy of MODIS LST is better compared to VIRR based on the RSDAST model. In addition, the reconstruction accuracy of VIRR and MODIS LST decreases with the increase in cloud coverage, and the reduction of the reconstruction accuracy of VIRR LST is larger than that of MODIS data. The number of effective dry-wet edge fitted by VIRR RLST/NDVI scatterplot was higher than that of OLST/NDVI, and the number of clear sky pixels in Reconstructed TVDI (RTVDI) images increased significantly, indicating that the RSDAST expands the temporal resolution and spatial coverage of infrared remote sensing data under cloudy conditions. Moreover, in DOY150–DOY243, the correlation between RTVDI and soil moisture is better than that of Original TVDI (OTVDI), indicating that the RSDAST improves the monitoring ability of soil moisture in these conditions. [ABSTRACT FROM AUTHOR]

The green vegetation fraction (GVF) can greatly influence the partitioning of surface sensible and latent heat fluxes in numerical weather prediction (NWP) models. However, the multiyear averaged monthly GVF climatology—the most commonly used representation of the vegetation state in models—cannot capture the real-time vegetation state well. In this study, a near real-time (NRT) GVF dataset generated from an 8-day composite of the normalized difference vegetation index is compared with the 10-yr averaged monthly GVF provided by the WRF model. The annual variability of the GVF over North China is examined in detail. Many differences between the two GVF datasets are found over dryland, grassland, and cropland/grassland mosaic areas. Two experiments using different GVF datasets are performed to assess the impacts of GVF on forecasts of screen-level temperature and humidity. The results show that using NRT GVF can lead to a widespread reduction of 2-m temperature forecast errors from April to October. Evaluation against in-situ observations shows that the positive impact on 2-m temperature forecasts in the morning is more distinct than that in the afternoon. Our study demonstrates that NRT GVF can provide a more realistic representation of the vegetation state, which in turn helps to improve short-range forecasts in arid and semiarid regions of North China. Moreover, our study shows that the negative effect of using NRT GVF is closely related to the initial soil moisture. [ABSTRACT FROM AUTHOR]

Wildfire occurs throughout the world, resulting in global ecology, society, and economic impacts. Burned areas are important for fire monitoring. In order to develop the capability of the Fengyun (FY) satellite to detect burned areas, a burned area mapping method based on the Fengyun-3D satellite (FY-3D) Medium Resolution Spectral Imager (MERSI) L1 data and daily active fire products is presented in this paper. Referring to other methods based on the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High-Resolution Radiometer (AVHRR), active fires based on daily active fire products are selected and clustered as burned samples. Two indices are used as spectral features of burned areas based on the single temporal FY-3D MERSI 250-m post-fire data. By taking advantage of spatial and spectral features for land cover in each burned cluster, burned samples are extended to identify burned areas by a region growing algorithm. The method is applied in two study areas and the result is compared with the Collection 6 MODIS burned area products (MCD64A1) based on the reference values obtained by the human-machine interface for validation. The results show that this method has a relatively high correspondence with the reference values, and its accuracy is higher than that of the MCD64A1. Certainly, this method inevitably has some limitations. But overall, the method can be used to extract burned areas by using the FY-3D MERSI data quickly and precisely, especially over large areas. [ABSTRACT FROM AUTHOR]

Absorption enhancements of polydisperse black carbon (BC) aggregates with brown coatings, decomposed into those due to lensing effect (Elen) and blocking effect (Eblo), are numerically studied based on recent observations with an accurate multiple‐sphere T‐matrix method. Both Elen and Eblo of BC with brown coating are predominantly determined by coated volume fraction of BC in ultraviolet and visible spectral regions, and the impacts of other microphysical parameters of coated BC are trivial if BC is no more than half encapsulated. If more volume fraction of BC is coated, scattering coating can focus more photons onto BC core with stronger lensing effect whereas absorptive coating blocks more photons originally induced by lensing effect onto BC core. The Elen may not be further enhanced with increased shell/core ratio after reaching a threshold, whereas the Eblo has sizable wavelength dependence and becomes close to the Elen in ultraviolet region. Moreover, the lensing and blocking effects of BC with brown coatings are simply parameterized, and the convenient treatments are expected to find wide applications for BC absorption enhancements due to coating. Plain Language Summary: Black carbon (BC) absorption enhancement due to coating is an important factor for observation‐model discrepancy, whereas the results of absorption enhancement of coated BC from experimental and theoretical studies are generally conflicting. Thorough understanding of the absorption enhancements of BC with brown coatings influenced by various BC microphysics and proposing their simple parameterizations for applications are a challenging and interesting topic. In our study, an exact multiple‐sphere T‐matrix method is employed to thoroughly examine the effects of observation‐based BC microphysics on absorption enhancements of BC with brown coatings modeled with more realistic geometries, which are decomposed into lensing effect and blocking effect due to absorptive coating. The results reveal that coated volume fraction of BC is dominant in determining both lensing and blocking effects of BC with brown coatings in ultraviolet and visible regions whereas other BC microphysics are their perturbations, which plausibly give a reconciliation of conflicting results that largely variable BC absorption enhancements are seen. Simple parameterizations of lensing and blocking effects of BC with brown coatings are then proposed for a quantitative understanding and further application. The findings are useful to the communities for understanding BC absorption enhancements and a more accurate prediction of climate. Key Points: Coated volume fraction of black carbon (BC) is dominant in determining lensing and blocking effects of BC with brown coating and others are perturbationsLensing effect may not be further enhanced with increased shell/core ratio after reaching a thresholdParameterizing lensing and blocking effects of BC with brown coating are proposed for a quantitative understanding and further application [ABSTRACT FROM AUTHOR]

It is crucial to maintain the balance of economic development and ecosystem protection. The value of ecosystem services is an indicator to help people understand the importance of ecosystem protection. Traditional models estimate ecosystem service values only according to land use/cover data while ignoring vegetation status differences in the same land use/cover. This study uses the normalized difference vegetation index (NDVI), the leaf area index (LAI), and net primary productivity (NPP) as vegetation status data to describe the differences in the same land use/cover type. The principal component analysis (PCA) approach is used to reduce the correlations among the three types of vegetation status data. Then, the calculated vegetation status index after PCA is input into the estimation model. The case study in China shows that the improved model has two major advantages. First, it can clearly distinguish the differences in ecosystem service values even for the same land use/cover type. Second, it can clearly describe the transitional zones between different land use/cover types through continuous changes in ecosystem service values. This improved model can provide a more detailed description of the distribution characteristics of ecosystem service values in China and help policymakers balance economic development and ecosystem protection. [ABSTRACT FROM AUTHOR]

High-precision microelectromechanical inertial sensors based on spring-mass structures are of great interests for a wide range of applications, including inertial navigation, disaster warning and resource exploration. Lowering the resonant frequency is essential to further improve the sensitivity of the sensors. However, conventional approaches are facing insurmountable difficulties from size reduction to machining precision. This paper proposed a novel quasi-zero-stiffness mechanism that is compatible with MEMS technologies together with a micromaching approach for adjusting the stiffness precisely. By improving the compliance of a typical spring with a negative-stiffness compensation mechanism induced by axial force, the resonant frequency of the micro spring-mass structure is lowered to 0.7 Hz, which is at least 3 times lower than current state-of-the-art micro structures. Based on this ultra-sensitive micro structure base on the quasi-zero-stiffness mechanism, the micro inertial sensor, with a chip size of a postage stamp, has shown a low self-noise of 0.6 nrad/ $\surd $ Hz at 0.04 Hz and a high long-term stability that are comparable to traditional pendulum inertial sensors. It is the first micro device, to our knowledge, that can successfully measure the tidal tilt signal. [2020-0048] [ABSTRACT FROM AUTHOR]

Precipitable water vapour (PWV) plays an important role in weather prediction, hydrological cycles and climate change. In this study, a physics-based algorithm was proposed to retrieve PWV over land using satellite passive microwave observations near 165.50 GHz and 183.31 GHz, which have higher spatial resolution and lower sensitivity to land surface emissivity than low-frequency channels. The algorithm uses a perturbation formulation of simplified radiative transfer equation to derive PWV and at-surface brightness temperature (BT) in 165.50 GHz simultaneously. It directly derives the at-surface BT instead of land surface temperature, so the algorithm needs no prior information of surface emissivity. Sensitivity analysis and retrieval experiments from simulated data were carried out for Advanced Technology Microwave Sounder (ATMS) onboard the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) satellite. The results showed that the algorithm using ATMS channels 17, 18 and 19 measurements can significantly reduce the PWV retrieval errors caused by surface emissivity uncertainty. The coefficient of determination (R2), root-mean-square error (RMSE), and bias of the retrieved PWV from ATMS data by the proposed algorithm and SuomiNet Global Positioning System (GPS) PWV were 0.90, 0.43 cm and −0.02 cm, respectively. In addition, the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud products were used to evaluate the effects of cloud on the PWV retrievals. The results showed that the presence of cloud does not decrease the accuracy of the PWV retrievals. [ABSTRACT FROM AUTHOR]

The aerosol absorption Ångstrom exponent (AAE) is a crucial optical parameter for apportionment and characterization. Due to considerable inconsistences associated with observations, numerical research is a powerful means to give a better understanding of the AAE of aged black carbon (BC) aerosols. Numerical studies of the AAE of polydisperse BC aggregates with brown coatings using the exact multiple-sphere T-matrix method (MSTM) are performed. The objective of the study is to thoroughly assess the AAE of coated BC influenced by their observation-based detailed microphysics and then provide a new AAE parameterization for application. At odds with our expectations, more large-sized BC particles coated by thin brown carbon can have an AAE smaller than 1.0, indicating that BC aerosols internally mixing with brown carbon can even show lower AAE than pure BC particles. The AAE of BC with brown coatings is highly sensitive to the absorbing volume fraction of the coating, coated volume fraction of BC, shell / core ratio, and particle size distribution with a wide variation, whereas the impacts of BC geometry and BC position within the coating are negligible. The AAE of BC with brown coatings can be larger than 3.0 if there are plenty of small-sized coated BC particles, heavy coating, or a large amount of brown carbon. However, the AAE of BC with non-absorbing coating appears to be weakly sensitive to particle microphysics with values around 1.0 (i.e., 0.7–1.4), suggesting the substantial role of the absorbing volume fraction of the coating in AAE determination. With more realistic BC geometries, our study also indicates that the occurrence of brown carbon may not be confidently determined unless AAE > 1.4. The currently popular core–shell Mie model reasonably approximates the AAE of fully coated BC by brown carbon, whereas it underestimates the AAE of partially coated or externally attached BC and underestimates more for a lower coated volume fraction of BC. In addition, we present a parameterization of the AAE of coated BC with a size distribution on the basis of numerical results, which can act as a guide for the AAE response to the absorbing volume fraction of the coating, coated volume fraction of BC, and shell / core ratio. The proposed parameterization of coated BC AAE generates a decent prediction for moderate BC microphysics, whereas caution should be taken in applying it for extreme cases, such as externally attached coated BC morphology. Our findings could improve the understanding and application of the AAE of BC with brown coatings. [ABSTRACT FROM AUTHOR]

The surface vegetation condition has been operationally monitored from space for many years by the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. As these instruments are close to the end of their design life, the surface vegetation products are required by many users from the new satellite missions. The MEdium Resolution Spectral Imager-II (MERSI-II) onboard the Fengyun (FY) satellite (FY-3 series; FY-3D) is used to retrieve surface vegetation parameters. First, MERSI-II solar channel measurements at the red and near-infrared (NIR) bands at the top of atmosphere (TOA) are corrected to the surface reflectances at the top of canopy (TOC) by removing the contributions of scattering and absorption of molecules and aerosols. The normalized difference vegetation index (NDVI) at both the TOA and TOC is then produced by using the same algorithms as the MODIS and AVHRR. The MERSI-II enhanced VI (EVI) at the TOC is also developed. The MODIS technique of compositing the NDVI at various timescales is applied to MERSI-II to generate the gridded products at different resolutions. The MERSI-II VI products are consistent with the MODIS data without systematic biases. Compared to the current MERSI-II EVI generated from the ground operational system, the MERSI-II EVI from this study has a much better agreement with MODIS after atmospheric correction. [ABSTRACT FROM AUTHOR]

Background and Aim: Treatment modalities of variceal bleeding or rebleeding for extrahepatic portal vein obstruction (EHPVO) are limited, and their long‐term results and prognostic factors are unclear. This study aimed at assessing the long‐term results of EHPVO treated with current recommendations and investigating the influencing factors. Methods: Between 2009 and 2016, 302 consecutive patients with EHPVO were included. Watch‐and‐wait policy was applied for those with no (n = 59) or small varices (n = 55), nonselective beta‐adrenergic blocker and nonselective beta‐adrenergic blocker plus endotherapy were for primary (n = 115) and secondary prophylaxis (n = 87), transjugular intrahepatic portosystemic shunt (TIPS) or combination therapy was for those with recurrent bleeding (n = 92). Results: The median follow up was 58.8 months. The 1‐, 3‐, and 5‐year cumulative rates were 3.6%, 19.2%, 32.3% for small varices development and 4.5%, 30.9%, 53.4% for large varices development. The 1‐, 3‐, and 5‐year cumulative rates were 11.1%, 20.9%, and 34.9% for first variceal bleeding and 16.0%, 26.9%, and 33.6% for variceal rebleeding. For those with recurrent variceal bleeding, only TIPS (n = 37, technical success rate: 90.2%) was associated with a reduced risk of variceal rebleeding (1‐, 3‐, and 5‐year: 5.6%, 11.7%, and 21.9%). The 1‐, 3‐, and 5‐year survival rates were 96.9%, 95.8%, and 91.9%. Prothrombotic factors and anticoagulation did not influence the risk of variceal bleeding, rebleeding, and survival. Conclusions: By applying the same variceal management as recommended for patients with liver cirrhosis, patients with non‐cirrhotic EHPVO showed a similar development of varices and variceal bleeding. This is also true for the beneficial effect of TIPS to prevent rebleeding. [ABSTRACT FROM AUTHOR]

A novel communication and navigation fusion system (CNFS) based on cellular communication system is developed to realize high-accuracy localization. Because of the small signal coverage of every transmitter and the fluctuation of received signal and noise, the CNFS positioning receiver requires fast processing of signal and stable performance. As the first operation performed by receiver, signal acquisition with fast speed and stable detection performance should be realized. This paper proposed a novel fast acquisition method with fine detection performance using search space reduction (SSR) and DD-MAX/TC-CACFAR techniques. SSR method is utilized to reduce the size and number of search space in the cross ambiguity function (CAF) evaluation stage. DD-MAX/TC-CACFAR method is employed to realize fine and stable detection performance in signal detection stage. The expressions of acquisition time are then derived considering the size and number of search space and the detection performance. Theoretical performance analysis and Monte Carlo simulation, which contain the comparison with other acquisition method, are presented to demonstrate the effectiveness of proposed method. Simulation and analysis results show that the proposed method can realize fast acquisition with fine and stable detection performance. [ABSTRACT FROM AUTHOR]

Aerosol absorption Angstrom exponent (AAE) is a crucial optical parameter for their apportionment and characterization. Due to considerable inconsistences associated with observations, a numerical research is a powerful means to give better understanding of the AAE of aged BC aerosols. Numerical studies of the AAE of polydisperse BC aggregates with brown coatings using the exact multiple-sphere T-matrix method (MSTM) are performed. The objective of the study is to thoroughly assess the AAE of coated BC influenced by their observation-based detailed microphysics and then provide a new AAE parameterization for application. At odds with our expectations, BC coated by thin brown carbon with more large particles can have an AAE smaller than 1.0, indicating that BC aerosols internally mixing with brown carbon can even show lower AAE than pure BC particles. The AAE of BC with brown coatings is highly sensitive to absorbing volume fraction of coating, coated volume fraction of BC, shell/core ratio, and particle size distribution with a wide variation, whereas the impacts of BC geometry and BC position within coating are trivial. The AAE of BC with brown coatings can be larger than 3.0, if there are more small coated BC particles, heavy coating, or more brown carbon. However, the AAE of BC with non-absorbing coating shows weakly sensitive to particle microphysics with values around 1.0 (i.e., 0.7-1.4), suggesting the substantial role of absorbing volume fraction of coating in the AAE determination. With more realistic BC geometries, our study also indicates that occurrence of brown carbon may be made confidently unless AAE>1.4. In addition, we present a parameterization of the AAE of coated BC with a size distribution on the basis of numerical results, which can act as a guide for the AAE response to absorbing volume fraction of coating, coated volume fraction of BC, and shell/core ratio. Our findings can improve the understanding and application of the AAE of BC with brown coatings. [ABSTRACT FROM AUTHOR]

Pinhole matrix based fingerprint on display technology is possibly the only optical solution for CFOT OLED due to its low module transmittance. We have investigated the fingerprint on CFOT technology in both display with lens and folding module. Countermeasures of discrete light source in folding module are discussed. [ABSTRACT FROM AUTHOR]

From the viewpoint of earth system science, this paper discusses the observation capability of the second-generation of Chinese polar-orbiting, sun-synchronous operational meteorological satellite observation systems, Fengyun-3 (FY-3), based on the function and performance test results from the FY-3D satellite observation system in orbit. The FY-3 series of satellites have numerous remote sensing instruments and a wide range of imaging and sounding electromagnetic spectrometers onboard. These instruments can obtain reflectivity data for land surface, soil, vegetation, water body, snow cover, ocean color, and sea ice on earth's surface over a wide spectral range, as well as information on the absorption and scattering radiative transfer of molecules and particles (clouds and aerosols) in earth's atmosphere. All of these data can be used to retrieve physical and chemical information about the land, ocean, and atmosphere of the earth system. Comprehensive observation of the earth system by the FY-3 meteorological satellites is preliminarily realized. [ABSTRACT FROM AUTHOR]

Featured Application: User terminal positioning based on the 5G system or other ground-based wireless systems. Cellular communication systems support mobile phones positioning function for Enhanced-911 (E-911) location requirements, but the positioning accuracy is poor. The fifth-generation (5G) cellular communication system can use indoor distribution systems to provide accurate multiple time-difference-of-arrival (TDOA) and single time-of-arrival (TOA) measurements, which could significantly improve the indoor positioning ability. Unlike iterative localization algorithms for TDOA or TOA, the existing closed-form algorithms, such as the Chan-Ho algorithm, do not have convergence problems, but can only estimate position based on one kind of measurement. This paper proposes a closed-form localization algorithm for multiple TDOAs and single TOA measurements. The proposed algorithm estimates the final position result using three-step weighted least squares (WLSs). The first WLS provides an initial position for the last two steps. Then the algorithm uses two WLSs to estimate position based on heteroscedastic TDOA and TOA measurements. In addition, the geometric dilution of precision (GDOP) of the proposed hybrid TDOA and TOA positioning has been derived. The analysis of GDOP shows that the proposed hybrid positioning has lower GDOP than TDOA-only positioning, which means the proposed hybrid positioning has a higher accuracy limitation than TDOA-only positioning. The simulation shows that the proposed localization algorithm could have better performance than closed-form TDOA-only positioning methods, and the positioning accuracy could approximate Cramer-Rao lower bound (CRLB) when the TDOA measurement errors are small. [ABSTRACT FROM AUTHOR]

In this paper, we developed a unified and operational cloud mask algorithm for the new-generation geostationary (GEO) meteorological satellite imagers of the Advanced Geostationary Radiation Imager (AGRI) aboard Fengyun-4A (FY-4A) and the Advanced Himawari Imager (AHI) aboard Himawari-8 (H08). We investigated the all-round performance of the cloud mask algorithm. Spatiotemporally, the algorithm matches the official Collection-6 cloud mask products of a Moderate Resolution Imaging Spectroradiometer (MODIS) from both the Terra and Aqua platforms, which we employed as the benchmark for performing intercomparisons and validations. The robust cloud mask algorithm can show high consistency between FY-4A/AGRI and H08/AHI. The MODIS-based validation results suggest that cloudy scene identification is better than that observed for clear skies for both FY-4A/AGRI and H08/AHI; there is also a relatively low false-alarm ratio (FAR). Moreover, the algorithm is more reliable during daytime hours, with a hit rate (HR) of approximately 92% for both FY-4A/AGRI and H08/AHI. We found slightly higher accuracy in cloud-masking results over water than those over land. Furthermore, we found that more than 67% of the matched pixels for both advanced GEO imagers had no bias when taking MODIS as the benchmark. Overall, HR values were approximately 91.04% and 91.82% for FY-4A/AGRI and H08/AHI, respectively. These results confirm the high quality of the algorithm for retrieving real-time cloud mask products. [ABSTRACT FROM AUTHOR]

Aboveground forest biomass (Bagf) and height of forest canopy (Hfc) are of great significance for the determination of carbon sources and sinks, carbon cycling and global change research. In this paper, Bagf of coniferous and broadleaf forest in the Chinese Three Gorges region is estimated by integrating light detection and ranging (LiDAR) and Landsat derived data. For a better Bagf estimation, a synergetic extrapolation method for regional Hfc is explored based on a specific relationship between LiDAR footprint Hfc and optical data such as vegetation index (VI), leaf area index (LAI) and forest vegetation cover (FVC). Then, an ordinary least squares regression (OLSR) and a back propagation neural network (BP-NN) model for regional Bagf estimation from synergetic LiDAR and optical data are developed and compared. Validation results show that the OLSR can achieve higher accuracy of Hfc estimation for all forest types (R2 = 0.751, Root mean square error (RMSE) = 5.74 m). The OLSR estimated Bagf shows a good agreement with field measurements. The accuracy of regional Bagf estimated by the BP-NN model (RMSE = 12.23 t ha–1) is superior to that estimated by the OLSR method (RMSE = 17.77 t ha–1) especially in areas with complex topography. [ABSTRACT FROM AUTHOR]

Based on the infrared black body temperature (TBB) observed by the geostationary meteorological satellite FY-2E from 2010 to 2014, the seasonal migration, occurrence frequency, and intraseasonal variability of summer convection over the Tibetan Plateau (TP) and its surrounding areas are analyzed. The results show that in May, convection mainly occurs over the eastern edge of the TP; in June, following the onset of the Asian summer monsoon, the strongest (severe) convection occurs in the southeastern part of the TP; and in July–August, strong southwesterly winds transport abundant moisture to the eastern and central areas of the TP, leading to formation of an active convection belt over southeastern TP. The results also show that in the western TP, the area with convection frequency greater than 6% occupies the southern plateau around the 37th pentad, and gradually moves northward until the end of July; in the central plateau, convection (severe convection) becomes active since early (mid) June, and maintains through the entire late summer with three major northward movements until reaching 34°N; and in the eastern TP, the convection is relatively active since the beginning of May and its northward stretching is slightly later than that over the central plateau. Overall, summer convective activities are unevenly distributed over the TP, with frequency of convection decreasing from south to north; and they also exhibit considerable intraseasonal variability, the maximum of which is found over the middle reach of the Yarlung Zangbo River and the southeastern plateau. EOF analysis of summer convection frequency over the TP reveals two leading modes, with the first mode being a dipole variation pattern between the Indian monsoon region and the southeastern TP, and the second mode a tripole pattern over the western TP, the Indian continent west of 80°E, and the South Asian continent east of 80°E. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is a key area affecting forecasts of weather and climate in China and occurrences of extreme weather and climate events over the world. The China Meteorological Administration, the National Natural Science Foundation of China, and the Chinese Academy of Sciences jointly initiated the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-III) in 2013, with an 8–10-yr implementation plan. Since its preliminary field measurements conducted in 2013, routine automatic sounding systems have been deployed at Shiquanhe, Gaize, and Shenzha stations in western TP, where no routine sounding observations were available previously. The observational networks for soil temperature and soil moisture in the central and western TP have also been established. Meanwhile, the plateau-scale and regional-scale boundary layer observations, cloud-precipitation microphysical observations with multiple radars and aircraft campaigns, and tropospheric-stratospheric air composition observations at multiple sites, were performed. The results so far show that the turbulent heat exchange coefficient and sensible heat flux are remarkably lower than the earlier estimations at grassland, meadow, and bare soil surfaces of the central and western TP. Climatologically, cumulus clouds over the main body of the TP might develop locally instead of originating from the cumulus clouds that propagate northward from South Asia. The TIPEX-III observations up to now also reveal diurnal variations, macro- and microphysical characteristics, and water-phase transition mechanisms, of cumulus clouds at Naqu station. Moreover, TIPEX-III related studies have proposed a maintenance mechanism responsible for the Asian "atmospheric water tower" and demonstrated the effects of the TP heating anomalies on African, Asian, and North American climates. Additionally, numerical modeling studies show that the Γ distribution of raindrop size is more suitable for depicting the TP raindrop characteristics compared to the M-P distribution, the overestimation of sensible heat flux can be reduced via modifying the heat transfer parameterization over the TP, and considering climatic signals in some key areas of the TP can improve the skill for rainfall forecast in the central and eastern parts of China. Furthermore, the TIPEX-III has been promoting the technology in processing surface observations, soundings, and radar observations, improving the quality of satellite retrieved soil moisture and atmospheric water vapor content products as well as high-resolution gauge-radar-satellite merged rainfall products, and facilitating the meteorological monitoring, forecasting, and data sharing operations. [ABSTRACT FROM AUTHOR]

Random forests (RFs), an advanced machine learning (ML) method, was used here to develop a robust and rapid quantitative precipitation estimates (QPEs) algorithm for the new-generation geostationary satellite of Himawari-8. In this algorithm, the global precipitation measurement (GPM) product has been employed to train QPE prediction model. The real-time multiband infrared brightness temperature from Himawari-8, combined with the spatiotemporally matched numerical weather prediction (NWP) data from the global forecast system, have been used as predictor variables for QPE. Among the variables used in RF learning model, total precipitable water and $K$ -index from NWP data have the highest rankings, indicating the importance of atmospheric environment for QPE. To enhance the accuracy of RF models or to optimize model training, a sample-balance technique has been utilized to adjust the ratios of samples in nonprecipitation/precipitation classification and quantitative precipitation regression data sets. Further sensitivity and validation analyses help determine the optimal RF classification and regression models for predicting nonprecipitation/precipitation pixel and rain rate. The selected RF classification model is found to predict precipitation area with an accuracy of 0.87. For predicted QPE product, the mean-absolute-error and root-mean-square error of RF regression model are 0.51 and 2.0 mm/h, respectively. Overall, the RF ML algorithm has a higher detection rate over homogenous ocean surface as compared with over land. Meanwhile, this RF algorithm tends to underestimate rain rate, especially in the presence of heavy rainfall. Despite this, it still produces a reasonable pattern of rainfall area and intensity, which are highly consistent with GPM observations. [ABSTRACT FROM AUTHOR]

Forest canopy height (FCH) is a key parameter in the estimation of forest biomass and productivity. However, areas with hilly or mountainous terrain present a genuine challenge to extract the vertical structural parameters by using the large footprint Lidar full waveform data. In this study, a mathematical method based on the inflection point of Lidar waveform is developed and applied to process geoscience laser altimeter system data. Furthermore, an improved model, the centroid-terrain index model (CTIM), is proposed to estimate FCH of different forest types in hilly areas. The accuracy of the CTIM model is evaluated by using different field measurement data collected from multiple forest districts in China. For conifer and broadleaf forests, the RMSE is 3.8 m in areas with slope angles larger than 5°. Compared to the ground-based Lidar data, the accuracy is satisfactory in hilly areas. The proposed approach makes a significant contribution toward improving the FCH estimation in hilly areas from large footprint full waveform data, and toward the forest ecosystem monitoring at the global scale. [ABSTRACT FROM AUTHOR]

The Visible and Infrared Spin-Scan Radiometer (VISSR) onboard the Fengyun-2 (FY-2) satellite can provide valuable thermal infrared observations to help create a precipitable water vapor (PWV) product with high spatial and temporal resolutions. The current FY-2/VISSR PWV product in operation is produced by using a traditional two-band physical split-window (PSW) method, which produces low quality results under dry atmospheric conditions. Based on the sensitivity characteristics of FY-2F/VISSR water vapor channel and two split-window channels to atmospheric water vapor, this study developed a new, robust operational PWV retrieval algorithm for FY-2F to improve the operational precision of the current PWV product. The algorithm uses a modified three-band PSW method, which adds a scale for the water vapor channel in the improved three-band PSW method. Integrated PWV products from the radiosonde data in 2016 are used here to validate the precision of the PWV retrieved by the modified three-band and traditional two-band PSW methods. The mean bias, root mean square error (RMSE), and correlation coefficient of the PWV retrieved by the modified three-band PSW method are 0.28 mm, 4.53 mm, and 0.969, respectively. The accuracy is much better than the PWV retrieved by the two-band method, whose mean bias, RMSE, and correlation coefficient are 12.67 mm, 29.35 mm, and 0.23. Especially, in mid- or high-latitude regions, the RMSE of the PWV is improved from 10 to 2 mm by changing the inversion in the two-band method to the modified three-band PSW method. Furthermore, the modified three-band PSW results show a better consistency with the radiosonde PWV at any zonal belt and season than the two-band PSW results. This new algorithm could significantly improve the quality of the current FY-2F/VISSR PWV product, especially at sites where the actual PWV are lower than 15 mm. [ABSTRACT FROM AUTHOR]

El Niño has distinctive oceanic and atmospheric signatures that have different influences on tropical cyclone (TC) activity over the western North Pacific (WNP). This study compares TC activity over the WNP basin among strong Central-Pacific (CP), mixed CP, and strong Eastern-Pacific (EP) El Niño. Results suggest that TC activity with strong intensity and long lifespan occurred more frequently during strong (i.e. strong EP and strong CP) El Niño years than during mixed-CP El Niño years. This is attributed primarily to a combined modulation of the amplitude and duration of warm sea-surface temperature anomalies (SSTAs) over the tropical Pacific, and variations in large-scale environmental conditions; i.e. eddy kinetic energy, omega, relative humidity, and vertical wind shear (VWS). During CP (i.e. strong CP and mixed CP) El Niño events, enhanced TC genesis is observed over a large part of the WNP. During strong-CP El Niño events, more TCs are generated east of 140°E in the southwestern WNP, whereas more TCs are generated west of 140°E during mixed-CP El Niño events. This is due to a reduced magnitude of VWS and a westward shift in warm SSTAs over the central equatorial Pacific. When an anomalous anticyclonic circulation over the Indo-China Peninsula is combined with a westward extension of the western North Pacific subtropical high, TCs heading northward are associated with strong mean winds during strong El Niño events, resulting primarily from enhanced eddy kinetic energy, omega, and relative humidity, and weak VWS. Overall, TC activity during the three types of El Niño shows distinct generation locations, evolution patterns, and intensities, and the evolving spatial patterns of SSTA play an important role in modulating TC activity. [ABSTRACT FROM AUTHOR]

This paper presents the background, scientific objectives, experimental design, and preliminary achievements of the Third Tibetan Plateau (TP) Atmospheric Scientific Experiment (TIPEX-III) for 8-10 years. It began in 2013 and has expanded plateau-scale observation networks by adding observation stations in data-scarce areas; executed integrated observation missions for the land surface, planetary boundary layer, cloud-precipitation, and troposphere-stratosphere exchange processes by coordinating ground-based, air-based, and satellite facilities; and achieved noticeable progress in data applications. A new estimation gives a smaller bulk transfer coefficient of surface sensible heat over the TP, which results in a reduction of the possibly overestimated heat intensity found in previous studies. Summer cloud-precipitation microphysical characteristics and cloud radiative effects over the TP are distinguished from those over the downstream plains. Warm rain processes play important roles in the development of cloud and precipitation over the TP. The lower-tropospheric ozone maximum over the northeastern TP is attributed to the regional photochemistry and long-range ozone transports, and the heterogeneous chemical processes of depleting ozone near the tropopause might not be a dominant mechanism for the summer upper-tropospheric-lower-stratospheric ozone valley over the southeastern TP. The TP thermodynamic function not only affects the local atmospheric water maintenance and the downstream precipitation and haze events but also modifies extratropical atmospheric teleconnections like the Asia-Pacific Oscillation, subtropical anticyclones over the North Pacific and Atlantic, and temperature and precipitation over Africa, Asia, and North America. These findings provide new insights into understanding land-atmosphere coupled processes over the TP and their effects, improving model parameterization schemes, and enhancing weather and climate forecast skills. [ABSTRACT FROM AUTHOR]

In this paper, we analyzed the spatial patterns of cultivated land change between 1982 and 2011 using global vector-based land use/land cover data. (1) Our analysis showed that the total global cultivated land area increased by 528.768×10 km with a rate of 7.920×10 km/a, although this increasing trend was not significant. The global cultivated land increased fastest in the 1980s. Since the 1980s, the cultivated land area in North America, South America and Oceania increased by 170.854×10 km, 107.890×10 km, and 186.492×10 km, respectively. In contrast, that in Asia, Europe and Africa decreased by 23.769×10 km, 4.035×10 km and 86.76×10 km, respectively. Furthermore, the cultivated land area in North America, South America and Oceania exhibited significant increasing trends of 7.236× 10 km/a, 2.780×10 km/a and 3.758×10 km/a, respectively. On the other hand, that of Asia, Europe and Africa exhibited decreasing trend rates of-5.641×10 km/a,-0.831×10 km/a and-0.595×10 km/a, respectively. Moreover, the decreasing trend in Asia was significant. (2) Since the 1980s, the increase in global cultivated lands was mainly due to converted grasslands and woodlands, which accounted for 53.536% and 26.148% of the total increase, respectively. The increase was found in southern and central Africa, eastern and northern Australia, southeastern South America, central US and Alaska, central Canada, western Russia, northern Finland and northern Mongolia. Among them, Botswana in southern Africa experienced an 80%-90% increase, making it the country with the highest increase worldwide. (3) Since the 1980s, the total area of cultivated lands converted to other types of land was 1071.946×10 km. The reduction was mainly converted to grasslands and woodlands, which accounted for 57.482% and 36.000%, respectively. The reduction occurred mainly in southern Sudan in central Africa, southern and central US, southern Russia, and southern European countries including Bulgaria, Romania, Serbia and Hungary. The greatest reduction occurred in southern Africa with a 60% reduction. (4) The cultivated lands in all the continents analyzed exhibited a trend of expansion to high latitudes. Additionally, most countries displayed an expansion of newly increased cultivated lands and the reduction of the original cultivated lands. [ABSTRACT FROM AUTHOR]

Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as 'virtual' in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. [ABSTRACT FROM AUTHOR]

Malignant glioma is the most prevalent form of malignant brain tumor. Although radiotherapy is widely used in glioma treatment, the radioresistance of glioma cells limits the success of the glioma treatment. The lack of effective targets and signaling pathways to reverse glioma radioresistance is the critical obstacle in successful treatment. In this study, we demonstrate that mitochondrial ATP-sensitive potassium channels (mtK channels) are overexpressed in glioma cells and are closely related to the malignancy grade and the overall survival of the patients. Importantly, we showed that mtK channels could control glioma radioresistance by regulating reactive oxygen species (ROS)-induced ERK activation. The inhibition of mtK channels suppresses glioma radioresistance by inhibiting ERK activation both in vitro and in vivo. These findings reveal the important roles of the mitochondria and mtK channels as key regulators in the radioresistance of glioma cells, and suggest that mtK channel blockers and MAPK/ERK kinase (MEK) inhibitors are potential targets for drug development of glioma treatments. [ABSTRACT FROM AUTHOR]

Radiosonde data collected from 83 stations in China from January to December 2012 were used to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) and thermal infrared (IR) total precipitable water vapour (PWV) products. The results indicate that MODIS NIR PWV products shows better agreement with radiosonde data than with IR PWV products, with the correlation coefficients up to 0.95. The root mean square errors (RMSEs) of NIR PWV range from 2 to 8 mm with different stations, which shows significant regional differences over China. The mean RMSE is about 5.03 mm (~35%) with a positive deviation of 2.56 mm (~18%), indicating the occurrence of a slight overestimation. Moreover, MODIS IR PWV during night-time has a better agreement with radiosonde PWV than that during daytime. The mean RMSE of IR PWV during daytime was ~6.02 mm (~42%), with a positive deviation of 1.54 mm (~11%). The mean RMSE of IR PWV during night-time was ~5.81 mm (~40%), with a negative deviation of approximately −0.04 mm (~0.25%). Both the NIR and IR PWV products during daytime tend to be higher than radiosonde PWV. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is a key surface parameter that describes the structure of vegetation and plays an important role in Earth system process modeling. In this paper, a new set of LAI products (MERSI GLOBCARBON LAI) has been developed based on the GLOBCARBON LAI algorithm and one year of FY-3A/MERSI land surface reflectance data. MERSI GLOBCARBON LAI has been inter-compared and validated over mainland China against MODIS land surface reflectance (LSR) derived LAI (using the same algorithm) and field LAI measurements. MERSI GLOBCARBON LAI and MODIS GLOBCARBON LAI show continuous and smooth LAI distributions at the start and end of the growing season. For most areas in China, the two LAI products agree well. The temporal variation in MERSI GLOBCARBON LAI and MODIS GLOBCARBON LAI consistently follows the growing season. The largest LAI difference occurs during July, when MERSI shows a much higher frequency of retrievals than does MODIS. Through validation of LAI retrievals with field measurements, our study demonstrates that LAI derived from MERSI and MODIS land surface reflectance products have comparable accuracy. MODIS top-of-atmosphere simple ratio (MODIS TOA SR) is related to MERSI TOA SR with linear correlation coefficients greater than 0.6. After atmospheric correction, the correlation coefficient increases from 0.69 to 0.75 over cropland and from 0.82 to 0.93 over grassland. However, atmospheric correction can still give rise to substantial differences in the reflectance data between the two sensors. Furthermore, different land cover types and different terrain relief have contrasting influences on the atmospheric correction, and these influences reduce the agreement between the two LAI products. This study shows the great potential of FY-3A/MERSI data for global LAI retrieval. [ABSTRACT FROM PUBLISHER]

The land surface broadband emissivity (LSBE) is a key parameter for estimating surface radiation, and there have been many studies of the LSBE at global or local scales. However, few studies have validated the surface emissivity database with multi-point field measurement data using infrared radiometry, especially in China. In this study, we focus on the validation of the emissivity product of the global land surface satellite (GLASS) LSBE database for northern China for the period from 2006 to 2011. Specifically, we have employed an eight-day averaged, gridded emissivity product in the 8–13.5 µm spectral range produced at a spatial resolution of 1000 m from the Moderate Resolution Imaging Spectrometer albedo product using a new algorithm. The GLASS LSBE database was validated over bare surfaces with field measurement data from sand samples collected at many pseudo-invariant sand dune sites located in western and northwestern China. By comparing measured emissivity for different land surface types at different sites and different times, it was shown that the results were consistent and that the accuracy of the field measurements was reliable. The results of the validation of GLASS LSBE with these field emissivity data showed very good agreement. [ABSTRACT FROM PUBLISHER]

Neutrophil polarization is a basic activity involved in the innate immune response, and it may be initiated by extracellular Ca2+ entry, a process primarily mediated through store-operated Ca2+ entry (SOCE). Yet, the mechanisms by which SOCE participates in cell polarization remain unclear. We hypothesized that Akt- and Src-dependent pathways, traditionally linked to neutrophil polarization, may interact with SOCE in this event. In this study, SKF96365 and 2-APB, inhibitors of SOCE as proved by their inhibition on Mn2+ influx, were observed to inhibit the formyl-methionyl-leucyl-phenylalanine (fMLP)-induced influx of Ca2+, the activation of Akt, Src, Rac1, Rac2, and Cdc42, and the polarization of differentiated HL-60 (dHL-60) cells. Downregulation of stromal interaction molecule 1 (STIM1), a Ca2+ sensor identified to induce SOCE, by siRNA led to decreases in the following indexes: Ca2+ entry, activation of Akt, Src, Rac2 (rather than Rac1) and Cdc42, and fMLP-induced polarization. This study suggests that SOCE might be the predominant form of Ca2+ entry involved in the regulation of cell polarization, and it may act through the Akt/Src/Rac pathways, as modeled in dHL-60 cells. It also suggests that STIM1 is a key modulator of cell polarization, potentially serving as a target for the designation of anti-immune deficiency therapies. Copyright © 2012 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]