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Probabilistic Precipitation Forecasting Based on Ensemble Output Using generalized additive models and Bayesian model Averaging

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Acta meteorologica Sinica 2012年第1期26卷 1-12页

作者：杨赤严中伟邵月红 College of Global Change and Earth System Science Beijing Normal University Key Laboratory of Regional Climate-Environment Research for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of Sciences

A probabilistic precipitation forecasting model using generalized additive models （GAMs） and Bayesian model averaging （BMA） was proposed in this paper. GAMs were used to fit the spatial-temporal precipitation models to individual ensemble member forecasts. The distributions of the precipitation occurrence and the cumulative precipitation amount were represented simultaneously by a single Tweedie distribution. BMA was then used as a post-processing method to combine the individual models to form a more skillful probabilistic forecasting model. The mixing weights were estimated using the expectation-maximization algorithm. The residual diagnostics was used to examine if the fitted BMA forecasting model had fully captured the spatial and temporal variations of precipitation. The proposed method was applied to daily observations at the Yishusi River basin for July 2007 using the National Centers for Environmental Prediction ensemble forecasts. By applying scoring rules, the BMA forecasts were verified and showed better performances compared with the empirical probabilistic ensemble forecasts, particularly for extreme precipitation. Finally, possible improvements and a^plication of this method to the downscaling of climate change scenarios were discussed.

关键词： Bayesian model averaging generalized additive model probabilistic precipitation forecasting,TIGGE Tweedie distribution

modeling and Fault Monitoring of Bioprocess Using generalized additive models （GAMs） and Bootstrap

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Chinese Journal of Chemical Engineering 2012年第6期20卷 1180-1183页

作者：郑蓉建周林成潘丰 Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University Wuxi 214122 China Faculty of Electrical Engineering Huaiyin Institute of Technology Huai'an 223003 China

Fault monitoring of bioprocess is important to ensure safety of a reactor and maintain high quality of products. It is difficult to build an accurate mechanistic model for a bioprocess, so fault monitoring based on rich historical or online database is an effective way. A group of data based on bootstrap method could be resampling stochastically, improving generalization capability of model. In this paper, online fault monitoring of generalized additive models （GAMs） combining with bootstrap is proposed for glutamate fermentation process. GAMs and bootstrap are first used to decide confidence interval based on the online and off-line normal sampled data from glutamate fermentation experiments. Then GAMs are used to online fault monitoring for time, dissolved oxygen, oxygen uptake rate, and carbon dioxide evolution rate. The method can provide accurate fault alarm online and is helpful to provide useful information for removing fault and abnormal phenomena in the fermentation.

关键词： bioprocess fault monitoring generalized additive model glutamic acid fermentation bootstrap modeling

The effects of factor generalization scales on the reproduction of dynamic urban growth

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Geo-Spatial Information Science 2022年第3期25卷 457-475页

作者： Yongjiu Feng Peiqi Wu Xiaohua Tong Pengshuo Li Rong Wang Yilun Zhou Jiafeng Wang Jinyu Zhao College of Surveying&Geo-Informatics Tongji UniversityShanghaiChina The Shanghai Key Laboratory of Space Mapping and Remote Sensing for Planetary Exploration Tongji UniversityShanghaiChina

The production and selection of driving factors are essential to building a strong Cellular Automata(CA)model of dynamic urban growth simulation.A critical issue that should be addressed is how the spatial representation and the generalization scale of driving factors affect the CA modeling and the simulation *** is challenging to evaluate the effectiveness of the selected driving factors because they have no true *** explore the impacts of the generalization scales,we produced nine sets of driving factors at nine scales to calibrate the CA models based on the Particle Swarm Optimization(CAPSO)and applied them to simulate urban growth of Suzhou during *** results show that the driving factors at a smaller scale have much better performance in explaining urban growth simulations as inferred by the Explained Residual Deviance(ERD)of the generalized additive models(GAMs).Specifically,the ERD declined from 51.9%to 45.9%as the factor scale became larger during 2000-2020,but there was a peak value(52.2%)at *** all simulations during 2000-2020,the CAPSO models with larger-scale factors have slightly lower overall accuracy and Figure-of-Merit(FOM),which respectively decreased by 3.1%and 4.4%as compared to the CA models with scale-free *** concluded that the driving factors at a smaller scale(200~400 m for point-like facilities and 7~14 m for line-like facilities)can build more accurate CA models to simulate urban growth patterns,and the optimal scale for factors can be identified using the *** study contributes to the methods of evaluating the effectiveness of driving factor production and reveals the impacts of spatial representation of factors on the CA modeling and simulation considering the factor generalization scales.

关键词： Cellular automata urban growth driving factors scale effects generalized additive model

From furnace up to freezer:Elevational patterns of plant diversity in Mount Palvar,a semi-arid Irano-Turanian mountain range of southwest Asia

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Journal of Mountain Science 2024年第7期21卷 2236-2248页

作者： Atefeh GHORBANALIZADEH Moslem DOOSTMOHAMMADI Kerman *** Iran

Much of the world's biodiversity lies in heterogeneous mountain areas with their diverse *** an example,Iranian montane ranges are highly diverse,particularly in the Irano-Turanian phytogeographical *** plant diversity patterns with increasing elevation is of high significance,not least for conservation *** studied the pattern of species richness,Shannon diversity,endemic richness,endemics ratio,and richness of life forms along a 3900 m elevational transect in Mount Palvar,overlooking the Lut Desert in Southeast *** also analyzed the effect of environmental variables on species turnover along the vertical gradient.A total of 120 vegetation plots(10 m×10 m)were sampled along the elevational transect containing species and environmental *** discover plant diversity pattern along the elevational gradient,generalized additive model(GAM)was ***-metric multidimensional scaling(NMDS)was applied for illustrating the correlation between species composition and environmental *** found hump-shaped pattern for species richness,Shannon diversity,endemic richness,and species richness of different life forms,but a monotonic increasing pattern for ratio of endemic species from low to high *** study confirms the humped pattern of species richness peaking at intermediate elevations along a complete elevational gradient in a semi-arid *** monotonic increase of endemics ratio with elevation in our area as a case study is consistent with global increase of endemism with *** to our results,temperature and precipitation are two important climatic variables that drive elevational plant diversity,particularly in seasonally dry *** study suggests that effective conservation and management are needed for this low latitude mountain area along with calling for long-term monitoring for species redistribution.

关键词： Elevational gradient Biodiversity Endemic generalized additive model Hump-shaped pattern Irano-Turanian region

Long-term declining in carbon monoxide(CO)at a rural site of Beijing during 2006-2018 implies the improved combustion efficiency and effective emission control

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Journal of Environmental Sciences 2022年第5期34卷 432-442页

作者： Yingruo Li Zhiqiang Ma Tingting Han Weijun Quan Junxia Wang Huaigang Zhou Di He Fan Dong Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China Key Laboratory of Atmospheric Chemistry China Meteorological AdministrationBeijing 100081China Environmental Meteorology Forecast Center of Beijing-Tianjin-Hebei China Meteorological AdministrationBeijing 100089China College of Environmental Science and Engineering Peking UniversityBeijing 100871China

Carbon monoxide(CO)is primarily the result of incomplete combustion,which has impor-tant impacts on the atmospheric chemical cycle and *** quantitative char-acterization of long-term CO trends is important for both atmospheric modeling and the design and implementation of policies to efficiently control multiple *** to the limitations of high time-resolution and high-quality long-term observational data,studies on long-term trends in the CO concentration in China are quite *** this study,the observational data of the concentration of CO in a rural site of Beijing during 2006-2018 was used to analyze the long-term trend in CO concentration in *** Theil-Sen method and the generalized additive model(GAM)-based method,were used to conduct the trend estimation *** found that the concentration of CO at the Shangdianzi site showed a significant downward trend during 2006-2018,with a decline rate of 22.8±5.1 ppbV per *** declining trend in CO also showed phasic characteristics,with a fast decreasing rate during the period of 2006-2008,stable variations during the period of 2009-2013 and a continuous downward trend after *** declining trend in the CO concentration in the south to west(S-W)sectors where the polluted air masses come from is more rapid than that in the sectors where the clean air masses come *** declining trend in the CO concentration implies the improved combustion efficiency and the successful air pollution control policies in Beijing and the surrounding area.

关键词： Carbon monoxide Long-term trend Theil-Sen method generalized additive model (GAM)-based method Stratified analysis

Standardizing CPUE of Ommastrephes bartramii for Chinese squid-jigging fishery in Northwest Pacific Ocean

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Chinese Journal of Oceanology and Limnology 2009年第4期27卷 729-739页

作者：田思泉陈新军陈勇许柳雄戴小杰 College of Marine Sciences Shanghai Ocean University Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources Ministry of Education Key Laboratory of Shanghai Education Commission for Oceanic Fisheries Resources Exploitation School of Marine Sciences University of Maine

generalized linear models （GLM） and generalized additive models （GAM） were used to standardize catch per unit fishing effort （CPUE） of Ommastrephes bartramii for Chinese squid-jigging fishery in Northwest Pacific Ocean. Three groups of variables were considered in the standardization： spatial variables （longitude and latitude）, temporal variables （year and month） and environmental variables, including sea surface temperature （SST）, sea surface salinity （SSS） and sea level height （SLH）. CPUE was treated as the dependent variable and its error distribution was assumed to be log-normal in each model. The model selections of GLM and GAM were based on the finite sample-corrected Akaike information criterion （AICC） and pseudo-coefficient （Pcf） combined P-value, respectively. Both GAM and GLM analysis showed that the month was the most important variable affecting CPUE and could explain 21.3% of variability in CPUE while other variables only explained 8.66%. The interaction of spatial and temporal variables weakly influenced the CPUE. Moreover, spatio-temporal factors may be more important in influencing the CPUE of this squid than environmental variables. The standardized and nominal CPUEs were similar and had the same trends in spatio-temporal distribution, but the standardized CPUE values tended to be smaller than the nominal CPUE. The CPUE tended to have much higher monthly variation than annual variations and their values increased with month. The CPUE became higher with increasing latitude-high CPUE usually occurred in 145°E-148°E and 149°E-162°E. The CPUE was higher when SST was 14-21℃ and the SLH from -22 cm to -18 cm. In this study, GAM tended to be more suitable than GLM in analysis of CPUE.

关键词： Ommastrephes bartramii CPUE standardization generalized additive model generalizedlinear model Northwestern Pacific Ocean Chinese squid-jigging fishery

Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

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Acta Oceanologica Sinica 2020年第6期39卷 36-47页

作者： Yunlei Zhang Huaming Yu Haiqing Yu Binduo Xu Chongliang Zhang Yiping Ren Ying Xue Lili Xu College of Fisheries Ocean University of ChinaQingdao 266003China Laboratory for Marine Fisheries Science and Food Production Processes Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China College of Oceanic and Atmospheric Sciences Ocean University of ChinaQingdao 266100China Institute of Oceanology Chinese Academy of SciencesQingdao 266071China

Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine *** response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and ***,it is necessary to determine the optimal combination of environmental variables in HSI *** this study,generalized additive models(GAMs)were used to determine which environmental variables to be included in the HSI *** variables were retained and weighted in the HSI model according to their relative contribution(%)to the total deviation explained by the boosted regression tree(BRT).The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–*** and seasonal variations in HSI models of mantis shrimp were also *** the four models(non-optimized model,BRT informed HSI model,GAM informed HSI model,and both BRT and GAM informed HSI model),both BRT and GAM informed HSI model showed the best *** environmental variables(bottom temperature,depth,distance offshore and sediment type)were selected in the HSI models for four groups(spring-juvenile,spring-adult,falljuvenile and fall-adult)of mantis *** distribution of habitat suitability showed similar patterns between juveniles and adults,but obvious seasonal variations were *** study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models,and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.

关键词： habitat suitability index mantis shrimp generalized additive model boosted regression tree Haizhou Bay

The Potential Vertical Distribution of Bigeye Tuna (Thunnus obesus) and Its Influence on the Spatial Distribution of CPUEs in the Tropical Atlantic Ocean

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Journal of Ocean University of China 2020年第3期19卷 669-680页

作者： YANG Shenglong SONG Liming ZHANG Yu FAN Wei ZHANG Bianbian DAI Yang ZHANG Heng ZHANG Shengmao WU Yumei College of Marine Sciences Shanghai Ocean UniversityShanghai 201306China Key Laboratory of Oceanic and Polar Fisheries Ministry of AgricultureEast China Sea Fisheries Research InstituteChinese Academy of Fishery SciencesShanghai 200090China Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource East China Sea Fisheries Research InstituteChinese Academy of Fishery SciencesShanghai 200090China

Understanding the potential vertical distribution of bigeye tuna(Thunnus obesus) is necessary to understand the catch rate fluctuations and the stock assessment of bigeye tuna. To characterize the potential vertical distribution of this fish while foraging and determine the influences of the distribution on longline efficiency in the tropical Atlantic Ocean, the catch per unit effort(CPUE) data were compiled from the International Commission for the Conservation of Atlantic Tunas and the Argo buoy data were downloaded from the Argo data center. The raw Argo buoy data were processed by data mining methods. The CPUE was standardized by support vector machine before analysis. We assumed the depths with the upper and lower limits of the optimum water temperatures of 15℃ and 9℃ as the preferred swimming depth, while the lower limit of the temperature(12℃) associated with the highest hooking rate as the preferred foraging depth(D12) of bigeye tuna during the daytime in the Atlantic Ocean. The preferred swimming depth and foraging depth range in the daytime were assessed by plotting the isobath based on Argo buoy data. The preferred swimming depth and vertical structure of the water column were identified to investigate the spatial effects on the CPUE by using a generalized additive model(GAM). The empirical cumulative distribution function was used to assess the relationship between the spatial distribution of CPUE and the depth of 12℃ isolines and thermocline. The results indicate that 1) the preferred swimming depth of bigeye tuna in the tropical Atlantic is from 100 m to 400 m and displays spatial variation;2) the preferred foraging depth of bigeye tuna is between 190 and 300 m and below the thermocline;3) the number of CPUEs peaks at a relative depth of 30 –50 m(difference between the 12℃ isolines and the lower boundary of the thermocline);and 4) most CPUEs are within the lower depth boundary of the thermocline levels(LDBT) which is from 160 m to 230 m. GAM analysis i

关键词： CPUE Argo buoy data Thunnus obesus vertical distribution generalized additive model Atlantic Ocean

Growth and form of Quercus robur and Fraxinus excelsior respond distinctly different to initial growing space: results from 24-year-old Nelder experiments

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Journal of Forestry Research 2013年第1期24卷 1-14页

作者： Christian Kuehne Patrick Pyttel Edgar Kublin Jürgen Bauhus Institute of Silviculture University of FreiburgD-79085 Freiburg i.Br.Germany. Faculty of Forests and Forestry University of Applied Sciences Wei- henstephan-TriesdorfHans-Carl-von-Carlowitz-Platz 3D-85354 FreisingGermany Department of Biometry and Informatics Forest Research Station Baden-WürttembergPostfach 708D-79007 FreiburgGermany

Initial growing space is of critical importance to growth and quality development of individual trees. We investigated how mortality, growth （diameter at breast height, total height）, natural pruning （height to first dead and first live branch and branchiness） and stem and crown form of 24-year-old pedunculate oak （Quercus robur [L.]） and European ash （Fraxinus excelsior [L.]） were affected by initial spacing. Data were recorded from two replicate single-species Nelder wheels located in southern Germany with eight initial stocking regimes varying from 1,020 to 30,780 seedlings·ha？1. Mortality substantially decreased with increasing initial growing space but significantly differed among the two species, averaging 59% and 15% for oak and ash plots, respectively. In contrast to oak, the low self-thinning rate found in the ash plots over the investigated study period resulted in a high number of smaller intermediate or suppressed trees, eventually retarding individual tree as well as overall stand development. As a result, oak gained greater stem dimensions throughout all initial spacing regimes and the average height of ash significantly increased with initial growing space. The survival of lower crown class ashes also appeared to accelerate self-pruning dynamics. In comparison to oak, we observed less dead and live primary branches as well as a smaller number of epicormic shoots along the first 6 m of the lower stem of dominant and co-dominant ashes in all spacing regimes. Whereas stem form of both species was hardly affected by initial growing space, the percentage of brushy crowns significantly increased with initial spacing in oak and ash. Our findings suggest that initial stockings of ca. 12,000 seedlings per hectare in oak and 2,500 seedlings per hectare in ash will guarantee a sufficient number of at least 300 potential crop trees per hectare in pure oak and ash plantations at the end of the self-thinning phase, respectively. If the problem of epicormic shoots a

关键词： spacing trial stocking self-thinning intraspecific competition qualification spatially explicit modelling generalized additive model