Food scarcity, population growth, and global climate change have propelled crop yield growth driven by high-throughput phenotyping into the era of big data. However, access to large-scale phenotypic data has now become a critical barrier that phenomics urgently must overcome. Fortunately, the high-throughput plant phenotyping platform (HT3P), employing advanced sensors and data collection systems, can take full advantage of non-destructive and high-throughput methods to monitor, quantify, and evaluate specific phenotypes for large-scale agricultural experiments, and it can effectively perform phenotypic tasks that traditional phenotyping could not do. In this way, HT3Ps are novel and powerful tools, for which various commercial, customized, and even self-developed ones have been recently introduced in rising numbers. Here, we review these HT3Ps in nearly 7 years from greenhouses and growth chambers to the field, and from ground-based proximal phenotyping to aerial large-scale remote sensing. Platform configurations, novelties, operating modes, current developments, as well the strengths and weaknesses of diverse types of HT3Ps are thoroughly and clearly described. Then, miscellaneous combinations of HT3Ps for comparative validation and comprehensive analysis are systematically present, for the first time. Finally, we consider current phenotypic challenges and provide fresh perspectives on future development trends of HT3Ps. This review aims to provide ideas, thoughts, and insights for the optimal selection, exploitation, and utilization of HT3Ps, and thereby pave the way to break through current phenotyping bottlenecks in botany.

No abstract

Based on C-LSAT2.0, using high- and low-frequency components reconstruction methods, combined with observation constraint masking, a reconstructed C-LSAT2.0 with 756 ensemble members from the 1850s to 2018 has been developed. These ensemble versions have been merged with the ERSSTv5 ensemble dataset, and an upgraded version of the CMST-Interim dataset with 5° × 5° resolution has been developed. The CMST-Interim dataset has significantly improved the coverage rate of global surface temperature data. After reconstruction, the data coverage before 1950 increased from 78%–81% of the original CMST to 81%–89%. The total coverage after 1955 reached about 93%, including more than 98% in the Northern Hemisphere and 81%–89% in the Southern Hemisphere. Through the reconstruction ensemble experiments with different parameters, a good basis is provided for more systematic uncertainty assessment of C-LSAT2.0 and CMST-Interim. In comparison with the original CMST, the global mean surface temperatures are estimated to be cooler in the second half of 19th century and warmer during the 21st century, which shows that the global warming trend is further amplified. The global warming trends are updated from 0.085 ± 0.004°C (10 yr)−1 and 0.128 ± 0.006°C (10 yr)−1 to 0.089 ± 0.004°C (10 yr)−1 and 0.137 ± 0.007°C (10 yr)−1, respectively, since the start and the second half of 20th century.

Interfacial properties play a significant role in the photovoltaic performance of kesterite solar cells. Different from its predecessor of Cu(In,Ga)S(e) 2 , the interface between Cu 2 ZnSnS(e) 4 (CZTSSe) and the back contact electrode of Mo is chemically unstable during selenization of the absorbing layer at high temperature. Raman spectra reveal that the MoS 2 interfacial layer is easily formed because of more negative change of free energy. However, in reality, the band offset between CZTSSe and MoS 2 is unfavorable for hole transfer. By selenizing the Mo electrode, the as-prepared MoSe 2 interfacial layer can suppress the diffusion of S and improve the band structure, which is beneficial for charge carrier separation and transfer. Therefore, the conversion efficiency of CZTSSe solar cells is increased from 10.28 to 11.46%.

No abstract

Quaternary East Asian winter monsoon (EAWM) evolution has long been attributed to high‐latitude Northern Hemisphere climate change. However, it cannot explain the distinct relationships of the EAWM in the northern and southern East Asian marginal sea in paleoclimatic records. Here we present an EAWM record of the northern East China Sea over the past 300 ka and a transient climate simulation with the Kiel Climate Model through the Holocene. Both proxy record and simulation suggest anticorrelated long‐term EAWM evolution between the northern East China Sea and the South China Sea. We suggest that this spatial discrepancy of EAWM can be interpreted as El Niño–Southern Oscillation (ENSO)‐like controlling, which generates cyclonic/anticyclonic wind anomalies in the northern/southern East Asian marginal sea. This research explains much of the controversy in nonorbital scale variability of Quaternary EAWM records in the East Asian marginal sea and supports a potent role of tropical forcing in East Asian winter climate change.

Reanalysis data are widely used to investigate long-term surface temperature changes due to insufficient spatial coverage of observational data. However, because of the limitations of data assimilation and model performance in the reanalysis datasets, it is essential to evaluate the quality of the reanalysis datasets. Based on the newly released version of China global Merged Surface Temperature dataset, Interim version (CMST-Interim), the performance of five reanalysis datasets (ERA5, NCEP/NCAR R1, JRA-55, CERA-20C, and 20CRv3), covering more than 50 years, is compared in terms of long-term variation bias, warming trend, and the consistency of the extreme temperature years from the period 1958-2010. The results reflect that the above reanalysis datasets have reasonable representativeness of global temperature change. ERA5 and 20CRv3 perform better than the other reanalysis datasets, with relatively small deviation, their warming trends are closer to the observation results, the appearance of extreme temperature years are also more consistent with the observed, and CERA-20C is the next. JRA-55 is slightly better in detecting the extremely cold years, while NCEP/NCAR R1 is slightly worse in biases but performs well in high-temperature years reproduction.

Turbulent vertical mixing in the stratified ocean interior has a huge impact on global ocean circulations and the climate system. Although parameterizations of vertical mixing furnished by internal tides have been built into state-of-the-art coupled global climate models (CGCMs), efforts in parameterizing wind-driven vertical mixing in CGCMs are still limited. In this study, we apply a modified finescale parameterization (MFP) to an eddy-resolving Community Earth System Model (CESM) to represent the wind's contribution to vertical mixing in the stratified ocean interior. The spatial pattern of the MFP-parameterized wind-driven vertical mixing in the thermocline agrees with the observation derived from the finestructure measurements of Argo floats, reproducing the enhanced values in the Kuroshio, Gulf Stream extensions, and the Southern Ocean where the winds inject great amount of energy into the internal wave field. The MFP also captures the observed seasonal variation of wind-driven vertical mixing in the thermocline of these regions that exhibits enhancement and weakening in winter and summer, respectively. Application of the MFP to a non-eddy-resolving CESM fails to reproduce the observed wind-driven vertical mixing. Specifically, the magnitude of parameterized wind-driven vertical mixing in the thermocline of Kuroshio, Gulf Stream extensions, and the Southern Ocean is systemically smaller than those in the observation and eddy-resolving CESM; so is the case for the amplitude of seasonal cycle. The results highlight the benefit of eddy-resolving CESM compared to its standardresolution counterpart in parameterizing the wind-driven vertical mixing and provide insight into developing parameterizations for wind-driven vertical mixing in eddy-resolving CGCMs.Plain Language Summary Vertical mixing of fluids with different properties caused by small-scale turbulence plays an important role in the global ocean circulations and climate system. Yet it is far from being resolved by state-of-the-art climate models and thus needs to be parameterized. Parameterizing the vertical mixing driven by wind-generated internal waves turns out to be challenging mainly due to the strong interaction of wind-generated internal waves with ocean mesoscale eddies that are swirling, time-dependent circulations about 100 km. In this study, we apply a modified finescale parameterization (MFP) to an eddy-resolving (ocean model's grid size of ∼0.1°) Community Earth System Model (CESM) to parameterize the wind-driven vertical mixing in the stratified ocean interior. The MFP-parameterized wind-driven vertical mixing in the thermocline agrees well with the observations, reproducing enhanced values in the regions where winds input large amount of energy into the internal wave field as well as an evident seasonal cycle. However, applying the MFP to a non-eddy-resolving (∼1°) CESM fails to reproduce the spatial and temporal variations of wind-driven vertical mixing as in the observations. The results suggest that the eddy-resolving climate models pr...