Modelling of Multi-Frequency Microwave Backscatter and Emission of Land Surface by a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP)

Emission and backscattering signals of land surfaces at different frequencies have distinctive responses to soil and vegetation physical states. The use of multi-frequency combined active and passive microwave signals provides complementary information to better understand and interpret the observed signals in relation to surface states and the underlying physical processes. Such a capability also improves our ability to retrieve surface parameters and states such as soil moisture, freeze-thaw dynamics and vegetation biomass and vegetation water content (VWC) for ecosystem monitoring. We present here a prototype Community Land Active Passive Microwave Radiative Transfer Modelling platform (CLAP) for simulating both backscatter (&sigma;0) and emission (TB) signals of land surfaces, in which the CLAP is backboned by an air-to-soil transition model (ATS) (accounting for surface dielectric roughness) integrated with the Advanced Integral Equation Model (AIEM) for modelling soil surface scattering, and the Tor Vergata model for modelling vegetation scattering and the interaction between vegetation and soil parts. The CLAP was used to simulate both ground-based and space-borne multi-frequency microwave measurements collected at the Maqu observatory on the eastern Tibetan plateau. The ground-based systems include a scatterometer system (1&ndash;10 GHz) and an L-band microwave radiometer. The space-borne measurements are obtained from the X-band and C-band Advanced Microwave Scanning Radiometer 2 (AMSR2) radiation observations. The impacts of different vegetation properties (i.e., structure, water and temperature dynamics) and soil conditions (i.e., different moisture and temperature profiles) on the microwave signals were investigated by CLAP simulation for understanding factors that can account for diurnal variations of the observed signals. The results show that the dynamic VWC partially accounts for the diurnal variation of the observed signal at the low frequencies (i.e., S- and L-bands), while the diurnal variation of the observed signals at high frequencies (i.e., X- and C-bands) is more due to vegetation temperature changing, which implies the necessity to first disentangle the impact of vegetation temperature for the use of high frequency microwave signals. The model derived vegetation optical depth &tau; differs in terms of frequencies and different model parameterizations, while its diurnal variation depends on the diurnal variation of VWC regardless of frequency. After normalizing &tau; at multi-frequency by wavenumber, difference is still observed among different frequencies. This indicates that &tau; is indeed frequency-dependent, and &tau; for each frequency is suggested to be applied in the retrieval of soil and vegetation parameters. Moreover, &tau; at different frequencies (e.g., X-band and L-band) cannot be simply combined for constructing accurate long time series microwave-based vegetation product. To this purpose, it is suggested to investigate the role of the leaf water potential in regulating plant water use and its impact on the normalized &tau; at multi-frequency. Overall, the CLAP is expected to improve our capability for understanding and applying current and future multi-frequency space-borne microwave systems (e.g. those from ROSE-L and CIMR) for vegetation monitoring.</p

Parameter Optimization of a Discrete Scattering Model by Integration of Global Sensitivity Analysis Using SMAP Active and Passive Observations

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for &#x03C3; HH&#x2070; , &#x03C3; VV&#x2070; , TBH, and TBV, respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data

An outlook to sophisticated technologies and novel developments for metabolic regulation in the Saccharomyces cerevisiae expression system

Saccharomyces cerevisiae is one of the most extensively used biosynthetic systems for the production of diverse bioproducts, especially biotherapeutics and recombinant proteins. Because the expression and insertion of foreign genes are always impaired by the endogenous factors of Saccharomyces cerevisiae and nonproductive procedures, various technologies have been developed to enhance the strength and efficiency of transcription and facilitate gene editing procedures. Thus, the limitations that block heterologous protein secretion have been overcome. Highly efficient promoters responsible for the initiation of transcription and the accurate regulation of expression have been developed that can be precisely regulated with synthetic promoters and double promoter expression systems. Appropriate codon optimization and harmonization for adaption to the genomic codon abundance of S. cerevisiae are expected to further improve the transcription and translation efficiency. Efficient and accurate translocation can be achieved by fusing a specifically designed signal peptide to an upstream foreign gene to facilitate the secretion of newly synthesized proteins. In addition to the widely applied promoter engineering technology and the clear mechanism of the endoplasmic reticulum secretory pathway, the innovative genome editing technique CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated system) and its derivative tools allow for more precise and efficient gene disruption, site-directed mutation, and foreign gene insertion. This review focuses on sophisticated engineering techniques and emerging genetic technologies developed for the accurate metabolic regulation of the S. cerevisiae expression system