Browsing by Author "Zhou, Yan"
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Item Development of a Machine Learning-Based Radiometric Bias Correction for NOAA’s Microwave Integrated Retrieval System (MiRS)(MDPI, 2020-09-26) Zhou, Yan; Grassotti, ChristopherWe present the development of a dynamic over-ocean radiometric bias correction for the Microwave Integrated Retrieval System (MiRS) which accounts for spatial, temporal, spectral, and angular dependence of the systematic differences between observed and forward model-simulated radiances. The dynamic bias correction, which utilizes a deep neural network approach, is designed to incorporate dependence on the atmospheric and surface conditions that impact forward model biases. The approach utilizes collocations of observed Suomi National Polar-orbiting Partnership/Advanced Technology Microwave Sounder (SNPP/ATMS) radiances and European Centre for Medium-Range Weather Forecasts (ECMWF) model analyses which are used as input to the Community Radiative Transfer Model (CRTM) forward model to develop training data of radiometric biases. Analysis of the neural network performance indicates that in many channels, the dynamic bias is able to reproduce realistically both the spatial patterns of the original bias and its probability distribution function. Furthermore, retrieval impact experiments on independent data show that, compared with the baseline static bias correction, using the dynamic bias correction can improve temperature and water vapor profile retrievals, particularly in regions with higher Cloud Liquid Water (CLW) amounts. Ocean surface emissivity retrievals are also improved, for example at 23.8 GHz, showing an increase in correlation from 0.59 to 0.67 and a reduction of standard deviation from 0.035 to 0.026.Item Genome sequence of the insect pathogenic fungus Cordyceps militaris, a valued traditional chinese medicine(Springer Nature, 2011-11-23) Zheng, Peng; Xia, Yongliang; Xiao, Guohua; Xiong, Chenghui; Hu, Xiao; Zhang, Siwei; Zheng, Huajun; Huang, Yin; Zhou, Yan; Wang, Shengyue; Zhao, Guo-Ping; Liu, Xingzhong; St Leger, Raymond J; Wang, ChengshuSpecies in the ascomycete fungal genus Cordyceps have been proposed to be the teleomorphs of Metarhizium species. The latter have been widely used as insect biocontrol agents. Cordyceps species are highly prized for use in traditional Chinese medicines, but the genes responsible for biosynthesis of bioactive components, insect pathogenicity and the control of sexuality and fruiting have not been determined. Here, we report the genome sequence of the type species Cordyceps militaris. Phylogenomic analysis suggests that different species in the Cordyceps/Metarhizium genera have evolved into insect pathogens independently of each other, and that their similar large secretomes and gene family expansions are due to convergent evolution. However, relative to other fungi, including Metarhizium spp., many protein families are reduced in C. militaris, which suggests a more restricted ecology. Consistent with its long track record of safe usage as a medicine, the Cordyceps genome does not contain genes for known human mycotoxins. We establish that C. militaris is sexually heterothallic but, very unusually, fruiting can occur without an opposite mating-type partner. Transcriptional profiling indicates that fruiting involves induction of the Zn2Cys6-type transcription factors and MAPK pathway; unlike other fungi, however, the PKA pathway is not activated.Item MINIMIZING REANALYSIS JUMPS DUE TO NEW OBSERVING SYSTEMS(2014) Zhou, Yan; Kalnay, Eugenia; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A major problem with reanalyses has been the presence of jumps in the climatology associated with changes in the observing system. Such changes are common in reanalysis products. These jumps became especially obvious when satellites were first introduced in 1979. After 1979, however, during the "satellite era" jumps have continued to appear whenever a new observing system was introduced. To explore possible solutions to this problem, we develop and test new methodologies to minimize these reanalysis jumps in the reanalyses time series due to new observing systems. In the first part of this dissertation, we study a state-of-the-art reanalysis, NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA thereafter). Analysis increments from the MERRA and from one reanalysis without SSM/I observations (NoSSMI thereafter) are compared and their differences are defined as correction terms. The correction terms are then introduced into the tendency equation of the forecast model, i.e., GEOS-5. The debiased reanalysis without SSM/I observation shows improvements in almost all fields, even in the precipitation field, which is generally considered to be significantly uncertain on all time and space scales. However, the difference between the analysis increments of MERRA and NoSSMI is not just due to the assimilation of SSMI, but to the accumulated effect of the assimilation of previous SSMI observations. These produce a change in the model climatology and nonlinear interactions between the variables currently observed by SSM/I, and the variables that have been modified by previous assimilations of SSMI. The nonlinear interactions introduce an additional accumulated impact during the 2-year training period. In the second part of this dissertation, we test a new methodology in a simpler data assimilation system, SPEEDY-LETKF, because it would be unfeasible for our computational resources to apply this method to the complex MERRA system. The new method defines the correction terms by calculating the difference of analysis increments from the following two analyses, 1) assimilating both rawinsondes (RAOB) and AIRS observations, named RaobAirs, and 2) assimilating only RAOB but with its background coming from the RaobAirs analysis at every 6-hour analysis cycle. This new method limits the growth of nonlinear interactions between variables observed by AIRS and the variables that have been modified by previous assimilation of AIRS. The results show that the new method is significantly more effective in minimizing reanalysis "jumps" compared with the method applied to MERRA system. In the third part of this dissertation, we explore a spectral model instability problem. Imperfect SPEEDY-LETKF OSSEs are unstable when assimilating RAOB observations only. Data assimilation processes worsen this problem. We found two methods to stabilize the imperfect SPEEDY-LETKF OSSEs. Traces of the spectral waves are also clearly present in other spectral reanalyses such as the NCEP and the ERA15, but since their resolutions are higher than that of the SPEEDY model, their impact is smaller.