Integrated efficient radiative transfer model named Dayu for simulating the imager measurements in cloudy atmospheres.

Rapid radiative transfer models are crucial to remote sensing and data assimilation. An integrated efficient radiative transfer model named Dayu, which is an updated version of the Efficient Radiative Transfer Model (ERTM) is developed to simulate the imager measurements in cloudy atmospheres. In Dayu model, the Optimized alternate Mapping Correlated K-Distribution model (OMCKD) which is predominant in dealing with the overlap of multiple gaseous lines is employed to efficiently calculate the gaseous absorption. The cloud and aerosol optical properties are pre-calculated and parameterized by the particle effective radius or length. Specifically, the ice crystal model is assumed as a solid hexagonal column, of which the parameters are determined based on massive aircraft observations. For the radiative transfer solver, the original 4-stream Discrete ordinate aDding Approximation (4-DDA) is extended to 2N-DDA (2N is the number of streams) which can calculate not only the azimuthally dependent radiance in the solar spectrum (including solar and infrared spectra overlap) but also the azimuthally averaged radiance in the thermal infrared spectrum through a unified adding method. Then the accuracy and efficiency of Dayu model are evaluated by comparing it with the benchmark model, i.e., Line-By-Line Radiative Transfer Model (LBLRTM) and DIScrete Ordinate Radiative Transfer (DISORT). Under the standard atmospheric profile, the maximum relative biases between Dayu model with 8-DDA / 16-DDA and the benchmark model (OMCKD with 64-stream DISORT) are 7.63% / 2.62% at solar channels but decreased to 2.66% / 1.39% at spectra-overlapping channel (3.7 µm). The computational efficiency of Dayu model with 8-DDA / 16-DDA is approximately three / two orders of magnitude higher than that of the benchmark model. At thermal infrared channels, the brightness temperature (BT) differences between Dayu model with 4-DDA and the benchmark model (LBLRTM with 64-stream DISORT) are bounded by 0.65K. Compared to the benchmark model, Dayu model with 4-DDA improves the computational efficiency by five orders of magnitude. In the application to the practical Typhoon Lekima case, the simulated reflectances and BTs by Dayu model have a high consistency with the imager measurements, demonstrating the superior performance of Dayu model in satellite simulation.

Discrete Ordinate Adding Method (DOAM), a new solver for Advanced Radiative transfer Modeling System (ARMS).

Satellite data assimilation requires a computationally fast and accurate radiative transfer model. Currently, three fast models are commonly used in the Numerical Weather Prediction models (NWP) for satellite data assimilation, including Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV), Community Radiative Transfer Model (CRTM), and Advanced Radiative transfer Modeling System (ARMS). ARMS was initiated in 2018 and is now becoming the third pillar supporting many users in NWP and remote sensing fields. Its radiative transfer solvers (e.g. Doubling Adding method) is inherited from CRTM. In this study, we propose a Discrete Ordinate Adding Method (DOAM) to solve the radiative transfer equation including both solar and thermal source terms. In order to accelerate the DOAM computation, the single scattering approximation is used in the layer with an optical depth less than 10-8 or a single scattering albedo less than 10-10. From principles of invariance, the adding method is then applied to link the radiances between the layers. The accuracy of DOAM is evaluated through four benchmark cases. It is shown that the difference between DOAM and DIScrete Ordinate Radiative Transfer (DISORT) decreases with an increase of stream number. The relative bias of the 4-stream DOAM ranges from -5.03 % to 5.92 % in the triple layers of a visible wavelength case, while the maximum bias of the 8-stream DOAM is only about 1 %. The biases can be significantly reduced by the single scattering correction. Comparing to the visible case, the accuracy of the 4-stream DOAM is much higher in the thermal case with a maximum bias -1.69 %. Similar results are also shown in two multiple-layer cases. In the MacBook Pro (15-inch, 2018) laptop, the 2-stream DOAM only takes 1.68 seconds for calculating azimuthally independent radiance of 3000 profiles in the hyper-spectral oxygen A-band (wavelength ranges from 0.757 µm to 0.775 µm), while the 4-stream DOAM takes 4.06 seconds and the 16-stream DOAM takes 45.93 seconds. The time of the 2-, 4- and 16- stream DOAM are 0.86 seconds, 1.09 seconds and 4.34 seconds for calculating azimuthally averaged radiance. DISORT with 16 streams takes 1521.56 seconds and 127.64 seconds under the same condition. As a new solver, DOAM has been integrated into ARMS and is used to simulate the brightness temperatures at MicroWave Humidity Sounder (MWHS) as well as MicroWave Radiation Imager (MWRI) frequencies. The simulations by DOAM are compared to those by Doubling Adding method and accuracy of both solvers shows a general agreement. All the results show that the DOAM is accurate and computational efficient for applications in NWP data assimilation and satellite remote sensing.

Efficient radiative transfer model for thermal infrared brightness temperature simulation in cloudy atmospheres.

An efficient radiative transfer model (ERTM) is developed to simulate thermal infrared brightness temperatures observed by the Advanced Himawari Imager (AHI) in this study. The ERTM contains an alternate mapping correlated k-distribution (AMCKD) scheme, a parameterization for cloud optical property, and a rapid infrared radiative transfer scheme. The AMCKD is employed to calculate the gaseous absorption in the inhomogeneous thermodynamic atmosphere. The optical properties of clouds are parameterized by the effective length for ice clouds based on the Voronoi model, and by the effective radius for water clouds based on the Lorenz-Mie theory. The adding method of four-stream discrete ordinates method (4DDA) is extended to be able to calculate the thermal infrared radiative intensity varying with the zenith angle in ERTM. The efficiency and accuracy of ERTM are evaluated by comparing with the benchmark model which is composed of discrete ordinate radiative transfer (DISORT) and line-by-line radiative transfer model (LBLRTM). Under the standard atmospheric profiles, the root mean square error (RMSE) of simulated brightness temperatures reaches a maximum of 0.21K at the B16 (13.28 µm) channel of AHI. The computational efficiency of ERTM is approximately five orders of magnitude higher than that of the benchmark model. Moreover, the simulated brightness temperatures by ERTM are highly consistent with the rigorous results and AHI observations in the application to the Typhoon Mujigae case.

Salvianolic acid B exerts a protective effect in acute liver injury by regulating the Nrf2/HO-1 signaling pathway.

Salvianolic acid B (Sal B) exerts strong antioxidant activity and eliminates the free radical effect. However, how it affects the antioxidant pathway is not very clear. The objective of this study was to investigate the underlying mechanism of Sal B in CCl4-induced acute liver injury, especially its effect on the Nrf2/HO-1 signaling pathway. For the in vivo experiment, an acute liver injury model was induced using CCl4 and treated with Sal B. For the in vitro experiment, an oxidative damage model was established followed by Sal B treatment. Serum biochemical indicators and reactive oxygen species activity were detected using corresponding kits. Oxidant/antioxidant status was determined based on the levels of malondialdehyde, glutathione, and superoxide dismutase. Nrf2 and HO-1 levels were analyzed by Western blotting and immunohistochemical staining. Sal B treatment improved liver histology, decreased the aminotransferase levels, and attenuated oxidative stress in the acute liver injury model. Nrf2 and HO-1 levels were increased both in vivo and in vitro. Sal B suppresses acute liver injury and Nrf2/HO-1 signaling plays a key role in this process.

Multi-layer solar radiative transfer considering the vertical variation of inherent microphysical properties of clouds.

A multi-layer solar radiative transfer (RT) scheme is proposed to deal with the vertical variation of inherent microphysical properties of clouds in this study. The exponential expressions are used to represent the vertical variation of optical properties caused by inhomogeneous microphysical properties. A perturbation method, coupled with the Eddington approximation, is used to solve the RT equation. In order to have a more accurate estimation of reflectance/transmittance for every single layer, the optical properties are adjusted following the theory of delta scaling in the proposed scheme. In addition, a modified adding method based on Chandrasekhar's invariance principle is introduced to solve the multi-layer RT. The accuracy of the proposed scheme is investigated by comparing the reflectance/absorptance to the benchmark for two double-layer cases, and each layer with vertically inhomogeneous optical properties. Results show that the bias related to vertically inhomogeneous optical properties reaches 13.8 % for reflectance and 29.2 % for absorptance while the bias of the proposed scheme is only -0.8 % for reflectance and 1.7 % for absorptance. We also apply the proposed scheme as well as the conventional Eddington approximation to the CanadianClimate Center RT model which handle RT in CanAM4. The calculations are performed in the following four solar wavenumber bands 2500-4200, 4200-8400, 8400-14500 and 14500-50000 cm -1. The result also shows that the proposed scheme also improved the accuracy in both flux and heating rate calculation by taking the vertical variation of inherent microphysical properties into account. The proposed scheme is approximately three times more computationally expensive compared to the Eddington approximation when we only consider the algorithm itself. The computational time is doubled compared to the Eddington approximation when we take the complete radiative transfer process into account. Due to its accuracy and efficiency, the proposed scheme is suitable to improve the RT calculations regarding the vertical variation of inherent microphysical properties in climate models.

A hierarchical architecture S/MWCNT nanomicrosphere with large pores for lithium sulfur batteries.

A hierarchical S/MWCNT nanomicrosphere for lithium/sulfur batteries with a high power and energy density as well as an excellent cycle life is introduced. Sulfur was uniformly coated on the surface of functional MWCNTs, which serves as a carbon matrix, to form a typical nanoscale core-shell structure with a sulfur layer of thickness 10-20 nm. Then the nanoscale sulfur intermediate composite was ball-milled to form interwoven and porous sphere architecture with large pores (around 1 µm to 5 µm). Different from most sulfur/carbon materials with micropore and mesopore structure, the micrometre scale S/MWCNT nanomicrosphere with a large pore structure could also exhibit high sulfur utilization and cycle retention. It could maintain a reversible capacity of 1000 mA h g(-1) after 100 cycles at 0.3 A g(-1) current density. And it even remained 780 mA h g(-1) after 200 cycles at 0.5 A g(-1) and 650 mA h g(-1) after 200 cycles at 1 A g(-1), showing a significant cyclability enhancement. It is believed that under the collective effect of hierarchical architecture, as well as the existence of carboxyl functional groups, sulfur/carbon materials with large pores could also exhibit an excellent electrochemical performance. The synthesis process introduced here is simple and broadly applicable, which would not only be beneficial to design new materials for lithium sulfur batteries but can also be extended to many different electrode materials for lithium ion batteries.