Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

UV,five wavelengths fusion and electrochemical fingerprints combined with antioxidant activity for quality control of antiviral mixture

Aiming to ensure the consistency of quality control of Traditional Chinese Medicines(TCMs),a combination method of high-performance liquid chromatography(HPLC),ultraviolet(UV),electrochemical(EC)was developed in this study to comprehensively evaluate the quality of Antiviral Mixture(AM),and Comprehensive Linear Quantification Fingerprint Method(CLQFM)was used to process the data.Quantitative analysis of three active substances in TCM was conducted.A fivewavelength fusion fingerprint(FWFF)was developed,using second-order derivatives of UV spectral data to differentiate sample levels effectively.The combination of HPLC and UV spectrophotometry,along with electrochemical fingerprinting(ECFP),successfully evaluated total active substances.Ultimately,a multidimensional profiling analytical system for TCM was developed.

The Research on the Methods to Confirm the Key Control Points of the Internal Accounting Control

The control points are the key issue of the internal control, and the key control points mean the control joints that play an important part in the process of the operation. If these key control points are not well controlled, the process of the operation disposal will be mistaken and cannot reach the goal. However, for the confirmation of the control points, many studies only do qualitative research from the important aspect instead of quantificational research. They are devoid of a series of scientific methods. This paper advances quantificational methods to confirm the key control points from two aspects of job evaluation and mathematics model.

Establishment and application of an accurate identification method for fragrant soybeans

In order to screen the aroma characteristics of soybean,a new method was established which can quickly quantify the content of 2-acetyl-1pyrroline(2-AP),an important compound related to soybean aroma,using gas chromatography-mass spectrometry(GC-MS).Based on peak profile,total peak area and retention time as test indexes,an accurate identification method for fragrant soybeans was established.The optimum parameters of the protocol consisted of column temperature70℃,sample injector temperature 180℃,optimum extraction alcohol content 1 m L,Na Cl content 0.1 g,ultrasonication time10 min,and extraction time 1 h,which were established by using the orthogonal test of single factors and three factors with four levels(L_9(3)^4).2-AP content of leaves had significant correlations with seeds,which were easier to measure.The protocol was simple and easy to carry out,consumed only small amounts of reagents,and provided accurate and reliable results with good reproducibility.A total of 101 soybean genotypes from different geographical sources were analyzed using this protocol.The results showed that the average content of 2-AP was 0.29 mg L^(–1),ranging from 0.094 to 1.816 mg L^(–1),and the genetic diversity index was 0.54.Among all genotypes-tested,they were classified into three grades,including seven elite genotypes identified as"grade one fragrant soybeans",which were Zhonglong 608,Heinong 88,Ha13-2958,Hongmiandou,Heinong 82,Huangmaodou,and Jiyu 21.These results provide both an identification technique and several elite aroma genotypes for gene discovery and good quality breeding in soybean.

Harmoniousness analysis of total amount control of water use

Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this concept, the harmoniousness of total amount control of water use was analyzed in terms of the supply and demand of water resources, water resources management, water use benefits, and water-saving level. An evaluation index system of the degree of harmony of total amount control of water use was established, and a method for calculation of the degree of harmony of total amount control of water use was developed based on the analytic hierarchy process （AHP） and fuzzy comprehensive analysis （FCA） methods. The new evaluation index system was applied to a certain area in Jiangsu Province, China. The degree of harmony of total amount control of water use over this area was calculated for different years. Results indicate that the evaluation index system and calculation method proposed in this study are feasible, and such a harmoniousness analysis can provide scientific references for the strict water resources management system that will be implemented in China in the near future.

Quantifying the Cloud Water Resource:Methods Based on Observational Diagnosis and Cloud Model Simulation

Based on the concepts of cloud water resource(CWR)and related variables proposed in the first part of this study,this paper provides details of two methods to quantify the CWR.One is diagnostic quantification(CWR-DQ)based on satellite observations,precipitation products,and atmospheric reanalysis data;and the other is numerical quantification(CWR-NQ)based on a cloud resolving model developed at the Chinese Academy of Meteorological Sciences(CAMS).The two methods are applied to quantify the CWR in April and August 2017 over North China,and the results are evaluated against all available observations.Main results are as follows.(1)For the CWR-DQ approach,reference cloud profiles are firstly derived based on the Cloud Sat/CALIPSO joint satellite observations for 2007–2010.The NCEP/NCAR reanalysis data in 2000–2017 are then employed to produce three-dimensional cloud fields.The budget/balance equations of atmospheric water substance are lastly used,together with precipitation observations,to retrieve CWR and related variables.It is found that the distribution and vertical structure of clouds obtained by the diagnostic method are consistent with observations.(2)For the CWR-NQ approach,it assumes that the cloud resolving model is able to describe the cloud microphysical processes completely and precisely,from which four-dimensional distributions of atmospheric water vapor,hydrometeors,and wind fields can be obtained.The data are then employed to quantify the CWR and related terms/quantities.After one-month continuous integration,the mass of atmospheric water substance becomes conserved,and the tempospatial distributions of water vapor,hydrometeors/cloud water,and precipitation are consistent with observations.(3)Diagnostic values of the difference in the transition between hydrometeors and water vapor(Cvh-Chv)and the surface evaporation(Es)are well consistent with their numerical values.(4)Correlation and bias analyses show that the diagnostic CWR contributors are well correlated with observations,and match their numerical counterparts as well,indicating that the CWR-NQ and CWR-DQ methods are reasonable.(5)Underestimation of water vapor converted from hydrometeors(Chv)is a shortcoming of the CWR-DQ method,which may be rectified by numerical quantification results or by use of advanced observations on higher spatiotemporal resolutions.

Multiscale Hessian filter-based segmentation and quantification method for photoacoustic microangiography

The appearanee of blood vessels is an important biomarker to distinguish diseased from healthy tissues in several fields of medical applications. Photoacoustie microangiography has the advantage of directly visualizing blood vessel networks within mierocireulatory tissue. Usually these images are interpreted qualitatively. However, a quantitative analysis is needed to better describe the characteristics of the blood vessels. This Letter addresses this problem by leveraging an efficient multiscale Hessian filter-based segmentation method, and four measure- ment parameters are acquired. The feasibility of our approach is demonstrated on experimental data and we expect the proposed method to be beneficial for several microcireulatory disease studies.

Quantifying the Cloud Water Resource:Basic Concepts and Characteristics

The water in the air is composed of water vapor and hydrometeors,which are inseparable in the global atmosphere.Precipitation basically comes from hydrometeors instead of directly from water vapor,but hydrometeors are rarely focused on in previous studies.When assessing the maximum potential precipitation,it is necessary to quantify the total amount of hydrometeors present in the air within an area for a certain period of time.Those hydrometeors that have not participated in precipitation formation in the surface,suspending in the atmosphere to be exploited,are defined as the cloud water resource(CWR).Based on the water budget equations,we defined 16 terms(including 12 independent ones)respectively related to the hydrometeors,water vapor,and total water substance in the atmosphere,and 12 characteristic variables related to precipitation and CWR such as precipitation efficiency(PE)and renewal time(RT).Correspondingly,the CWR contributors are grouped into state terms,advection terms,and source/sink terms.Two methods are developed to quantify the CWR(details of which are presented in the companion paper)with satellite observations,atmospheric reanalysis data,precipitation products,and cloud resolving models.The CWR and related variables over North China in April and August 2017 are thus derived.The results show that CWR has the same order of magnitude as surface precipitation(Ps).The hydrometers converted from water vapor(Cvh)during the condensation process is the primary source of precipitation.It is highly correlated with Ps and contributes the most to the CWR over a large region.The state variables and advection terms of hydrometeors are two orders of magnitude lower than the corresponding terms of water vapor.The atmospheric hydrometeors can lead to higher PE than water vapor(several tens of percent versus a few percent),with a shorter RT(only a few hours versus several days).For daily CWR,the state terms are important,but for monthly and longer-time mean CWR,the source/sink terms(i.e.,cloud microphysical processes)contribute the largest;meanwhile,the advection terms contribute less for larger study areas.

An Efficient Spectral Method for Acoustic Scattering from Rough Surfaces

An efficient and accurate spectral method is presented for scattering problems with rough surfaces.A probabilistic framework is adopted by modeling the surface roughness as random process.An improved boundary perturbation technique is employed to transform the original Helmholtz equation in a random domain into a stochastic Helmholtz equation in a fixed domain.The generalized polynomial chaos(gPC)is then used to discretize the random space;and a Fourier-Legendre method to discretize the physical space.These result in a highly efficient and accurate spectral algorithm for acoustic scattering from rough surfaces.Numerical examples are presented to illustrate the accuracy and efficiency of the present algorithm.

Determination of Random Periodic Structures in Transverse Magnetic Polarization

Consider an inverse problem that aims to identify key statistical pro-perties of the profile for the unknown random perfectly conducting grating structure by boundary measurements of the diffracted fields in transverse mag-netic polarization.The method proposed in this paper is based on a novel combination of the Monte Carlo technique,a continuation method and the Karhunen-Loève expansion for the uncertainty quantification of the random structure.Numerical results are presented to demonstrate the effectiveness of the proposed method.