Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing−Tianjin−Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Temperature extremes over rapidly urbanizing regions with high population densities have been scrutinized due to their severe impacts on human safety and economics.First of all,the performance of the regional climate model RegCM4 with a hydrostatic or non-hydrostatic dynamic core in simulating seasonal temperature and temperature extremes was evaluated over the historical period of 1991–99 at a 12-km spatial resolution over China and a 3-km resolution over the Beijing−Tianjin−Hebei(JJJ)region,a typical urban agglomeration of China.Simulations of spatial distributions of temperature extremes over the JJJ region using RegCM4 with hydrostatic and non-hydrostatic cores showed high spatial correlations of more than 0.8 with the observations.Under a warming climate,temperature extremes of annual maximum daily temperature(TXx)and summer days(SU)in China and the JJJ region showed obvious increases by the end of the 21st century while there was a general reduction in frost days(FD).The ensemble of RegCM4 with different land surface components was used to examine population exposure to temperature extremes over the JJJ region.Population exposure to temperature extremes was found to decrease in 2091−99 relative to 1991−99 over the majority of the JJJ region due to the joint impacts of increases in temperature extremes over the JJJ and population decreases over the JJJ region,except for downtown areas.Furthermore,changes in population exposure to temperature extremes were mainly dominated by future population changes.Finally,we quantified changes in exposure to temperature extremes with temperature increase over the JJJ region.This study helps to provide relevant policies to respond future climate risks over the JJJ region.

Effects of the extrusion parameters on microstructure,texture and room temperature mechanical properties of extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy

Microstructure,texture,and mechanical properties of the extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy were investigated at different extrusion temperatures(260 and 320℃),extrusion ratios(10:1,15:1,and 30:1),and extrusion speeds(3 and 6 mm/s).The experimental results exhibited that the grain sizes after extrusion were much finer than that of the homogenized alloy,and the second phase showed streamline distribution along the extrusion direction(ED).With extrusion temperature increased from 260 to 320℃,the microstructure,texture,and mechanical properties of alloys changed slightly.The dynamic recrystallization(DRX)degree and grain sizes enhanced as the extrusion ratio increased from 10:1 to 30:1,and the strength gradually decreased but elongation(EL)increased.With the extrusion speed increased from 3 to 6 mm/s,the grain sizes and DRX degree increased significantly,and the samples presented the typical<2111>-<1123>rare-earth(RE)textures.The alloy extruded at 260℃ with extrusion ratio of 10:1 and extrusion speed of 3 mm/s showed the tensile yield strength(TYS)of 213 MPa and EL of 30.6%.After quantitatively analyzing the contribution of strengthening mechanisms,it was found that the grain boundary strengthening and dislocation strengthening played major roles among strengthening contributions.These results provide some guidelines for enlarging the industrial application of extruded Mg-RE alloy.

Generation of high resolution sea surface temperature using multi-satellite data for operational oceanography

In the present article, we introduce a high resolution sea surface temperature （SST） product generated daily by Korea Institute of Ocean Science and Technology （KIOST）. The SST product is comprised of four sets of data including eight-hour and daily average SST data of I km resolution, and is based on the four infrared （IR） satellite SST data acquired by advanced very high resolution radiometer （AVHRR）, Moderate Resolution Imaging Spectroradiometer （MODIS）, Multifunctional Transport Satellites-2 （MTSAT-2） Imager and Meteorological Imager （MI）, two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2 （AMSR2）, and WindSAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation （OI） algorithm. The root-mean-square-errors （RMSEs） of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from Ianuary to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71~C and the bias value was -0.08~C. The largest RMSE and bias were 0.86 and -0.26~C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Iapan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60~C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature （GHRSST） product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System （KOOS） as an input parameter for data assimilation.

Detection of Land-Use and Surface Temperature Change at Different Resolutions

Understanding the relationship between land-use/land-cover change (LULCC) and environment is seriously important to manage arid land. However, information on how environmental factors influence the LULCC patterns at different scales in arid area is lacking. This paper investigates the application of RS/GIS for detecting LULCC and assessing its impact on surface temperature in the Ismailia Governorate, Egypt. Landsat images have been utilized to quantify the changes from 1984 to 2011. The images were pre-processed using calibration techniques and the geometric and atmos- pheric corrections were performed. Different ratios, indices, and optimized index factor were implemented to decide the best band combination. Supervised classification using Maximum Likelihood technique and spatial reclassification have been employed. Six land-use/land-cover categories (urban, vegetation, waterlogged 1 and 2, bare land, and water) were identified. The highest overall accuracy and Kappa coefficient is 93.04% and 80.65%, respectively. The integration of RS and GIS was further applied to examine the impact of land-use change on surface temperatures. The results revealed a notable land-use change in the study area. The Built-up area has rapidly increased in Ismailia during the 27 years pe- riod. The built-up area (37.65?C in 1984 and 43.876?C in 2011) and Barren land (37.34?C in 1984 and 42.801?C in 2011) exhibit the highest surface radiant temperature, while vegetated surfaces (28.73?C in 1984 and 32.96?C in 2011), water (25.94?C in 1984 and 27.32?C in 2011), waterlogged1 (34.54?C in 1984 and 35.60?C in 2011) recorded low radiant temperature respectively. Waterlogged2 is the class that shows an unexpected radiant temperature (26.38?C in 1984 and 27.75?C in 2011). The urban development between 1984 and 2011 has given rise to an average of 6.23?C in surface radiant temperature. During 27 years, the change rate of land-use types which are decreased are barren land (1.12% an- nually) and waterlogged1 and 2 (0.76 and 6.61% annually). The area of vegetation, water, and built-up are increased by 0.98%, 0.82%, and 0.61% per year, respectively.

CLDASSD:Reconstructing Fine Textures of the Temperature Field Using Super-Resolution Technology

Before 2008,the number of surface observation stations in China was small.Thus,the surface observation data were too sparse to effectively support the High-resolution China Meteorological Administration’s Land Assimilation System(HRCLDAS)which ultimately inhibited the output of high-resolution and high-quality gridded products.This paper proposes a statistical downscaling model based on a deep learning algorithm in super-resolution to research the above problem.Specifically,we take temperature as an example.The model is used to downscale the 0.0625°×0.0625°,2-m temperature data from the China Meteorological Administration’s Land Data Assimilation System(CLDAS)to 0.01°×0.01°,named CLDASSD.We performed quality control on the paired data from CLDAS and HRCLDAS,using data from 2018 and 2019.CLDASSD was trained on the data from 31 March 2018 to 28 February 2019,and then tested with the remaining data.Finally,extensive experiments were conducted in the Beijing-Tianjin-Hebei region which features complex and diverse geomorphology.Taking the HRCLDAS product and surface observation data as the"true values"and comparing them with the results of bilinear interpolation,especially in complex terrain such as mountains,the root mean square error(RMSE)of the CLDASSD output can be reduced by approximately 0.1℃,and its structural similarity(SSIM)was approximately 0.2 higher.CLDASSD can estimate detailed textures,in terms of spatial distribution,with greater accuracy than bilinear interpolation and other sub-models and can perform the expected downscaling tasks.

A NUMERICAL STUDY OF THE INFLUENCE OF SEA SURFACE TEMPERATURES WITH DIFFERENT TEMPORAL RESOLUTIONS ON TYPHOON DUJUAN OVER THE SOUTH CHINA SEA

Daily and weekly sea surface temperature data of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Advanced Microwave Scanning Radiometer-Earth Observing System sensors are used as forcing of the underlying sea surface in the mesoscale numerical model to simulate Typhoon Dujuan that moved across the South China Sea in 2003. The numerical results show that different SSTs near the typhoon center result in differences in the atmospheric wind field, indicating that the model has a fast and obvious response to SSTs. Different SST influences the intensity and track of Dujuan to some degree and has significant impacts on its precipitation and latent heat flux near the eye. The SST influence on Dujuan is mainly fulfilled by changing the latent heat flux between the ocean surface and the atmosphere above.

Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature(CMST) Dataset

According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Borehole Heat Budget Calculator: A New Tool for the Quick Exploitation of High-Resolution Temperature Profiles by Hydrogeologists

Distributed temperature sensing is known to provide sharp signals which are very efficient for mapping hydraulically active fractures in wellbores. High-resolution temperature sensing has specifically demonstrated its capacity to characterize very low flows in wellbores. But as sharp as they can be, temperature profiles are often difficult to decipher. The aim of the present work is to provide and to test the “Borehole Heat Budget Calculator” (BHB Calculator), which is implemented as a fast and easy to use tool for the quantitative analysis of depth-temperature profiles. The Calculator is suitable for most pumping and draining configurations, as the heat budget is generalized for modelling multidirectional flow systems within the same wellbore. The formatted worksheet allows the quick exploitation of temperature logs, and is applicable for the characterization of distributed fractures in long screened wellbores. Objectives of the heat modelling are to enhance the readability of complex depth-temperature data, as well as to quantify distribution of inflow intensities and temperatures with depth. The use of heat budget helps to clearly visualize how heat conduction and heat advection contributions are distributed along wellbores profiles. Calculations of inflow temperatures and their evolution through pumping duration is a prerequisite to infer about the nature of aquifer properties (i.e. conduits, distributed or discrete fractures, porous media), as well as to give insight information about the mapping of effective flow paths draining the aquifer. The efficiency and limitations of the BHB Calculator are being tested through high-resolution temperature logging, along with complementary flowmetering and televiewing logging in fractured aquifers located in the St-Lawrence Lowlands, Quebec, Canada.

A bHLH transcription factor,CsSPT,regulates high-temperature resistance in cucumber

High-temperature stress threatens the growth and yield of crops. Basic helix-loop-helix(bHLH) transcription factors(TFs) have been shown to play important roles in regulating high-temperature resistance in plants. However, the bHLH TFs responsible for high-temperature tolerance in cucumbers have not been identified. We used transcriptome profiling to screen the high temperature-responsive candidate bHLH TFs in cucumber. Here, we found that the expression of 75 CsbHLH genes was altered under high-temperature stress. The expression of the CsSPT gene was induced by high temperatures in TT(Thermotolerant) cucumber plants. However, the Csspt mutant plants obtained by the CRISPR-Cas9 system showed severe thermosensitive symptoms, including wilted leaves with brown margins and reduced root density and cell activity.The Csspt mutant plants also exhibited elevated H_(2)O_(2) levels and down-regulated photosystem-related genes under normal conditions.Furthermore, there were high relative electrolytic leakage(REC), malondialdehyde(MDA), glutathione(GSH), and superoxide radical(O_(2)^(·-)) levels in the Csspt mutant plants, with decreased Proline content after the high-temperature treatment. Transcriptome analysis showed that the photosystem and chloroplast activities in Csspt mutant plants were extremely disrupted by the high-temperature stress compared with wildtype(WT) plants. Moreover, the plant hormone signal transduction, as well as MAPK and calcium signaling pathways were activated in Csspt mutant plants under high-temperature stress. The HSF and HSP family genes shared the same upregulated expression patterns in Csspt and WT plants under high-temperature conditions. However, most bHLH, NAC, and bZIP family genes were significantly down-regulated by heat in Csspt mutant plants. Thus, these results demonstrated that CsSPT regulated the high-temperature response by recruiting photosynthesis components, signaling pathway molecules, and transcription factors. Our results provide important insights into the heat response mechanism of CsSPT in cucumber and its potential as a target for breeding heat-resistant crops.

Alkyl dimethyl betaine activates the low-temperature collection capacity of sodium oleate for scheelite

The impact of alkyl dimethyl betaine (ADB) on the collection capacity of sodium oleate (NaOl) at low temperatures was evaluated using flotation tests at various scales. The low-temperature synergistic mechanism of ADB and NaOl was explored by infrared spectroscopy, X-ray photoelectron spectroscopy, surface tension measurement, foam performance test, and flotation reagent size measurement.The flotation tests revealed that the collector mixed with octadecyl dimethyl betaine (ODB) and NaOl in a mass ratio of 4:96 exhibited the highest collection capacity. The combined collector could increase the scheelite recovery by 3.48% at low temperatures of 8–12℃. This is particularly relevant in the Luanchuan area, which has the largest scheelite concentrate output in China. The results confirmed that ODB enhanced the collection capability of NaOl by improving the dispersion and foaming performance. Betaine can be introduced as an additive to NaOl to improve the recovery of scheelite at low temperatures.

Energy Resolution Effects on Plasma Electron Temperature Measurements by Soft X-Ray Pulse-Height-Analysis

The soft x-ray pulse-height-analysis technique is a conventional tool to measure electron temperature on tokamak.The soft x-ray spectra distortion due to energy resolution of detector will affect the temperature and impurity concentration determination.To evaluate these effects,distorted spectra as functions of energy resolution are derived by numerical modeling.The results show that the low energy resolution detector can fit for the large-sized tokamak soft x-ray spectra.

Image super‐resolution via dynamic network

Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution.However,obtained information of these con-volutional neural networks cannot completely express predicted high‐quality images for complex scenes.A dynamic network for image super‐resolution(DSRNet)is presented,which contains a residual enhancement block,wide enhancement block,feature refine-ment block and construction block.The residual enhancement block is composed of a residual enhanced architecture to facilitate hierarchical features for image super‐resolution.To enhance robustness of obtained super‐resolution model for complex scenes,a wide enhancement block achieves a dynamic architecture to learn more robust information to enhance applicability of an obtained super‐resolution model for varying scenes.To prevent interference of components in a wide enhancement block,a refine-ment block utilises a stacked architecture to accurately learn obtained features.Also,a residual learning operation is embedded in the refinement block to prevent long‐term dependency problem.Finally,a construction block is responsible for reconstructing high‐quality images.Designed heterogeneous architecture can not only facilitate richer structural information,but also be lightweight,which is suitable for mobile digital devices.Experimental results show that our method is more competitive in terms of performance,recovering time of image super‐resolution and complexity.The code of DSRNet can be obtained at https://github.com/hellloxiaotian/DSRNet.

Competitive oxidation behavior of Ni-based superalloy GH4738 at extreme temperature

A high thrust-to-weight ratio poses challenges to the high-temperature performance of Ni-based superalloys. The oxidation behavior of GH4738 at extreme temperatures has been investigated by isothermal and non-isothermal experiments. As a result of the competitive diffusion of alloying elements, the oxide scale included an outermost porous oxide layer (OOL), an inner relatively dense oxide layer (IOL), and an internal oxide zone (IOZ), depending on the temperature and time. A high temperature led to the formation of large voids at the IOL/IOZ interface. At 1200℃, the continuity of the Cr-rich oxide layer in the IOL was destroyed, and thus, spallation occurred. Extension of oxidation time contributed to the size of Al-rich oxide particles with the increase in the IOZ. Based on this finding,the oxidation kinetics of GH4738 was discussed, and the corresponding oxidation behavior at 900-1100℃ was predicted.

Flexible,high-density,laminated ECoG electrode array for high spatiotemporal resolution foci diagnostic localization of refractory epilepsy

High spatiotemporal resolution brain electrical signals are critical for basic neuroscience research and high-precision focus diagnostic localization,as the spatial scale of some pathologic signals is at the submillimeter or micrometer level.This entails connecting hundreds or thousands of electrode wires on a limited surface.This study reported a class of flexible,ultrathin,highdensity electrocorticogram(ECoG)electrode arrays.The challenge of a large number of wiring arrangements was overcome by a laminated structure design and processing technology improvement.The flexible,ultrathin,high-density ECoG electrode array was conformably attached to the cortex for reliable,high spatial resolution electrophysiologic recordings.The minimum spacing between electrodes was 15μm,comparable to the diameter of a single neuron.Eight hundred electrodes were prepared with an electrode density of 4444 mm^(-2).In focal epilepsy surgery,the flexible,high-density,laminated ECoG electrode array with 36 electrodes was applied to collect epileptic spike waves inrabbits,improving the positioning accuracy of epilepsy lesions from the centimeter to the submillimeter level.The flexible,high-density,laminated ECoG electrode array has potential clinical applications in intractable epilepsy and other neurologic diseases requiring high-precision electroencephalogram acquisition.

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Effect of Cleaving Temperature on the Surface and Bulk Fermi Surface of Sr2RuO4 Investigated by High Resolution Angle-Resolved Photoemission

High resolution angle-resolved photoemission measurements are carried out to systematically investigate the effect of cleaving temperature on the electronic structures and Fermi surfaces of Sr2RuO4.Unlike previous reports,which found that a high cleaving temperature can suppress the surface Fermi surface,we find that the surface Fermi surface remains obvious and strong in Sr2RuO4 cleaved at high temperature,even at room temperature.This indicates that cleaving temperature is not a key effective factor in suppressing surface bands.On the other hand,the bulk bands can be enhanced in an aged surface of Sr2RuO4 that has been cleaved and held for a long time.We have also carried out laser ARPES measurements on Sr_(2)RuO_(4) by using a vacuum ultra-violet laser (photon energy at 6.994eV) and found an obvious enhancement of bulk bands even for samples cleaved at low temperature.This information is important for realizing an effective approach to manipulating and detecting the surface and bulk electronic structure of Sr2RuO4.In particular,the enhancement of bulk sensitivity,along with the super-high instrumental resolution of VUV laser ARPES,will be advantageous in investigating fine electronic structure and superconducting properties of Sr_(2)RuO_(4) in the future.

High-resolution neutronics model for ^(238)Pu production in high-flux reactors

We proposed and compared three methods(filter burnup,single energy burnup,and burnup extremum analysis)to build a high-resolution neutronics model for 238Pu production in high-flux reactors.The filter burnup and single energy burnup methods have no theoretical approximation and can achieve a spectrum resolution of up to~1 eV,thereby constructing the importance curve and yield curve of the full energy range.The burnup extreme analysis method combines the importance and yield curves to consider the influence of irradiation time on production efficiency,thereby constructing extreme curves.The three curves,which quantify the transmutation rate of the nuclei in each energy region,are of physical significance because they have similar distributions.A high-resolution neutronics model for ^(238)Pu production was established based on these three curves,and its universality and feasibility were proven.The neutronics model can guide the neutron spectrum optimization and improve the yield of ^(238)Pu by up to 18.81%.The neutronics model revealed the law of nuclei transmutation in all energy regions with high spectrum resolution,thus providing theoretical support for high-flux reactor design and irradiation production of ^(238)Pu.

Comprehensive analyses of the proteome and ubiquitome revealed mechanism of high temperature accelerating petal abscission in tree peony

Tree peony(Paeonia suffruticosa Andrews)is a well-known ornamental plant with high economic value,but the short fluorescence is a key obstacle to its ornamental value and industry development.High temperature accelerates flower senescence and abscission,but the associated mechanisms are poorly understood.In this study,the tandem mass tag(TMT)proteome and label-free quantitative ubiquitome from tree peony cut flowers treated with 20℃for 0 h(RT0),20℃or 28℃for 60 h(RT60 or HT60)were examined based on morphological observation,respectively.Totally,6970 proteins and 1545 lysine ubiquitinated(Kub)sites in 844 proteins were identified.Hydrophilic residues(such as glutamate and aspartate)neighboring the Kub sites were in preference,and 36.01%of the Kub sites were located on the protein surface.The differentially expressed proteins(DEPs)and Kub-DEPs in HT60 vs RT60 were mainly enriched in ribosomal protein,protein biosynthesis,secondary metabolites biosynthesis,flavonoid metabolism,carbohydrate catabolism,and auxin biosynthesis and signaling revealed by GO and KEGG analysis,accompanying the increase of endogenous abscisic acid(ABA)accumulation and decrease of endogenous indoleacetic acid(IAA)level.Additionally,the expression patterns of six enzymes(SAMS,ACO,YUC,CHS,ANS and PFK)putatively with Kub modifications were analyzed by proteome and real-time quantitative RT-PCR.The cell-free degradation assays showed PsSAMS and PsACO proteins could be degraded via the 26 S proteasome system in tree peony flowers.Finally,a working model was proposed for the acceleration of flower senescence and abscission by high temperature.In summary,all results contributed to understanding the mechanism of flower senescence induced by high temperature and prolonging fluorescence in tree peony.

Diphylleia Grayi-Inspired Intelligent Temperature-Responsive Transparent Nanofiber Membranes

Nanofiber membranes(NFMs) have become attractive candidates for next-generation flexible transparent materials due to their exceptional flexibility and breathability. However, improving the transmittance of NFMs is a great challenge due to the enormous reflection and incredibly poor transmission generated by the nanofiber-air interface. In this research, we report a general strategy for the preparation of flexible temperature-responsive transparent(TRT) membranes,which achieves a rapid transformation of NFMs from opaque to highly transparent under a narrow temperature window. In this process, the phase change material eicosane is coated on the surface of the polyurethane nanofibers by electrospray technology. When the temperature rises to 37 ℃, eicosane rapidly completes the phase transition and establishes the light transmission path between the nanofibers, preventing light loss from reflection at the nanofiber-air interface. The resulting TRT membrane exhibits high transmittance(> 90%), and fast response(5 s). This study achieves the first TRT transition of NFMs, offering a general strategy for building highly transparent nanofiber materials, shaping the future of next-generation intelligent temperature monitoring, anti-counterfeiting measures, and other high-performance devices.