Statistical downscaling of extreme daily precipitation,evaporation,and temperature and construction of
future scenarios
Tao Yang,1*,?Huihui Li,1Weiguang Wang,1Chong-Yu Xu 2and Zhongbo Yu 3
1
State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering,Hohai University,Nanjing 210098,China
2
Department of Geosciences,University of Oslo,P.O.Box 1047,Blindern,0316Oslo,Norway 3
Department of Geoscience,University of Nevada Las Vegas,Las Vegas,NV89154,USA
Abstract:
Generally,the statistical downscaling approaches work less perfectly in reproducing precipitation than temperatures,particularly for the extreme precipitation.This article aimed to testify the capability in downscaling the extreme temperature,evaporation,and precipitation in South China using the statistical downscaling method.Meanwhile,the linkages between the underlying driving forces and the incompetent skills in downscaling precipitation extremes over South China need to be extensively addressed.Toward this end,a statistical downscaling model (SDSM)was built up to construct future scenarios of extreme daily temperature,pan evaporation,and precipitation.The model was thereafter applied to project climate extremes in the Dongjiang River basin in the 21st century from the HadCM3(Hadley Centre Coupled Model version 3)model under A2and B2emission scenarios.The results showed that:(1)The SDSM generally performed fairly well in reproducing the extreme temperature.For the extreme precipitation,the performance of the model was less satisfactory than temperature and evaporation.(2)Both A2and B2scenarios projected increases in temperature extremes in all seasons;however,the projections of change in precipitation and evaporation extremes were not consistent with temperature extremes.(3)Skills of SDSM to reproduce the extreme precipitation were very limited.This was partly due to the high randomicity and nonlinearity dominated in extreme precipitation process over the Dongjiang River basin.In pre-?ood seasons (April to June),the mixing of the dry and cold air originated from northern China and the moist warm air releases excessive rainstorms to this basin,while in post-?ood seasons (July to October),the intensive rainstorms are triggered by the tropical system dominated in South China.These unique characteristics collectively account for the incompetent skills of SDSM in reproducing precipitation extremes in South China.Copyright ?2011John Wiley &Sons,Ltd.
KEY WORDS
climate extremes;statistical downscaling;climate change;projection;scenarios
Received 16August 2011;Accepted 10November 2011
INTRODUCTION
The frequent occurrence of extreme weather events such as heat waves and intense and persistent precipitation associated with subsequent ?ooding have raised concerns that human activity might have caused an alteration of the climate system (Yang et al .,2008),which is believed to be the culprit behind the severity of such events.There is also a widespread belief that the climate system will continue to change under the prevailing human activity and that humanity will be faced with more of these extreme events (Hundecha and Bardossy,2008;Yang et al .,2011).This leads to the growing concerns and studies on changes in frequency,intensity,and/or magnitude of such events in the past and for estimating climate that will occur in the future.
General circulation models (GCMs)and large-scale circulation predictors are the most important and effective tools and indicators for the climate impact study.These numerical coupled models represent various earth systems including the atmosphere,oceans,land surface,and sea-ice and offer considerable potential for the study of climate change and variability.Over the past decade,the sophistication of such models has increased,and their ability to simulate present and past global and continental scale climates has substantially improved.However,the resolution of GCMs remains relatively coarse and does not provide a direct estimation of hydrological responses to climate change.For example,the Hadley Centre ’s Hadcm3model is resolved at a spatial resolution of 2.5 latitude by 3.75 longitude,whereas a spatial resolution of 0.125 latitude and longitude is required by hydrologic simulations of monthly ?ow in mountainous catchment (Wilby et al .,2004).In other words,GCMs provide output at nodes of grid-boxes,which are tens of thousands of square kilometers in size,whereas the scale of interest to hydrologists is of the order of a few hundred square kilometers.Bridging the gap between the resolution of climate models and regional-and local-scale processes
*Correspondence to:Dr.Tao Yang,Professor,State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering,Hohai University,Nanjing 210098,The People ’s Republic of China.E-mail:yang.tao@https://www.doczj.com/doc/9c16626029.html, ?
Present address:State Key Laboratory of Desert and Oasis Ecology,Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi,China
HYDROLOGICAL PROCESSES Hydrol.Process.(2011)
Published online in Wiley Online Library
(https://www.doczj.com/doc/9c16626029.html,)DOI:10.1002/hyp.8427
represents a considerable problem for the climate change studies including the application of climate change scenarios to hydrological models.Thus,considerable effort in the climate community has focused on the development of techniques to bridge the gap,known as‘downscaling’.
More recently,downscaling has found wide application in hydroclimatology for scenario construction and simu-lation of(1)regional precipitation(Kim et al.,2004; Wang et al.,2011);(2)low-frequency rainfall events (Wilby,1998)(3)mean,minimum,and maximum air temperature(Kettle and Thompson,2004);(4)soil moisture(Jasper et al.,2004);(5)runoff(Arnell et al., 2003)and stream?ows(Cannon and Whit?eld,2002);
(6)ground water levels(Bouraoui et al.,1999);(7) transpiration(Misson et al.,2002),wind speed(Faucher et al.,1999),and potential evaporation rates(Weisse and Oestreicher,2001);(8)soil erosion and crop yield(Zhang et al.,2004);(9)landslide occurrence(Buma and Dehn, 2000),and(10)water quality(Hassan et al.,1998). Downscaling methods could be broadly classi?ed into two categories(Xu,1999):dynamic downscaling and statistical downscaling.Both techniques have their strengths and weaknesses.In dynamic downscaling,the GCM outputs are used as boundary conditions to drive a Regional Climate Model(RCM)or Limited Area Model and produce regional-scale information up to5–50km. This method has superior capability in complex terrain or with changed land cover.However,this method entails higher computation cost and relies strongly on the boundary conditions provided by GCMs with considerable uncertainties.In contrast,statistical downscaling gains local or station-scale meteorological time series(predictands)by appropriate statistical or empirical relationships with surface or troposphere atmospheric features.Generally,statistical downscaling methods can deliver ensembles of daily climate that evolve in line with the large-scale,transient changes of the host GCM.Moreover,given the advantages of being computationally inexpensive,statistical downscal-ing method can access?ner scales than dynamical methods and relatively easily applied to different GCMs,parameters and regions(Wilby et al.,2004).Therefore,it has been widely employed in climate impact studies.However, statistical downscaling approaches need much longer historical time series to build the appropriate statistical relationship.In addition,one of the assumptions of statistical downscaling is still valid in the future.This assumption cannot be testi?ed at present.The conclusion from the most recent studies is achieved in the statistical and regional dynamical downscaling of extremes project (STARDEX,https://www.doczj.com/doc/9c16626029.html,/projects/stardex) that both statistical and dynamical downscaling techniques are comparable for simulating current climate(Haylock et al.,2006;Schmidli et al.,2006).The statistical downscaling has been widely employed in climate change impact assessments(Wilby et al.,1999;Huth,2002; Tripathi et al.,2006;Ghosh and Mujumdar,2008),due to its low expenditure on usage and the equivalent power as dynamic downscaling.
In Wilby and Wigley’s study(2000),statistical downscaling techniques are described as three categories, namely:regression methods(e.g.Kim et al.,1984; Wigley et al.,1990;Storch et al.,1993);weather pattern-based approaches(https://www.doczj.com/doc/9c16626029.html,mb,1972;Hay et al.,1991; Bardossy and Plate,1992);and stochastic weather generators(Katz,1996).No matter whether the method is simple or complex,it is always based on some kind of a regression relationship.The statistical downscaling model(SDSM)is best described as a hybrid of stochastic weather generator and regression-based methods(Wilby et al.,2002).Many comparative studies(Wilby et al., 1998;Dibike and Coulibaly,2005)have shown that it has superior capability to capture local-scale climate variability and is,therefore,widely applied(Wilby and Harris,2006).
General practices in downscaling of monthly outputs from a full range of GCMs were presented as above in past years.However,research in constructing reliable scenarios of future climate extremes is still a challenge and inadequate so far(e.g.Wilby and Harris,2006). Moreover,SDSM normally works worse in subtropical and tropical regions than in inland regions for that precipitation in subtropical and tropical regions always presents more than one?ood season due to the effect of tropical cyclones,which are dif?cult to capture. Therefore,the main objective of the present study is to testify the capability of SDSM in downscaling extreme events in temperature,evaporation,and precipitation in the subtropical region in southern China and,if it is successful, to project their future patterns for the study region.This study strives to downscale extremes of temperature, evaporation,and precipitation in the study region,more importantly to identify the possible links between the underlying driving forces and skills in downscaling precipitation extremes in subtropical regions.It will contribute to promote current downscaling knowledge in similar subtropical regions of the world.
STUDY AREA AND DATA
Study area
Dongjiang River is located between114.0~116.5 E and22.5~25.5 N(Figure1).It has a562km long mainstream to the Boluo station with a drainage area of 25,555km2.The Dongjiang River is important not only for the local region but also for Hong Kong because about 80%of Hong Kong’s water supply comes from Dongjiang River through cross-basin water transfer.Three major reservoirs(i.e.Xingfengjiang Reservoir since1959, Fengshuba Reservoir since1973,and Baipenzhu Reservoir since1984)were built in the basin.
Annual average air temperature is about20.4 C.The precipitation of Dongjiang River demonstrates strong seasonality due to a subtropical monsoon climate.Owing to the in?uence of typhoons,precipitation exhibits strong variability in both spatial and temporal perspective.The annual precipitation varies between1500mm and2400mm.
T.YANG ET AL.
More than80%of the total annual precipitation falls in the ?ood seasons from April to September.
Data
Observed data sets.Measured daily maximum temperature,minimum temperature,pan evaporation,and precipitation were provided by China Meteorological Administration for41-year period1961–2001at?ve weather stations(Table I).The areal weights of?ve stations were calculated using the Thiessen polygons method(Figure2).
Reanalysis predictor sets used in calibration.Twenty-six different large-scale atmospheric variables derived from the daily reanalysis dataset of NCEP/NCAR in the period of1961–2001were used to calibrate and validate the SDSM model,which were downloaded freely from the internet sites at a scale of3.75?2.5 (http://www.cics. uvic.ca/scenarios/sdsm/select.cgi).The geographical extent(112.5–116.25 N,22.5–25 E)was chosen to cover the whole area with noticeable in?uence on the circulation patterns that govern the weather pattern observed over the Dongjiang River basin.
GCM predictor sets used in hindcast and projection.The validated SDSM was used to downscale the large-scale predictor variables derived from A2and B2scenarios of HadCM3(Hadley Centre Coupled Model version3)in the period of1961–2099.Both scenarios are characterized by a continuously increasing global population with a consequent increase in the emission of greenhouse gas and with a higher rate in A2than in B2.Maximum temperature,minimum temperature,pan evaporation, and precipitation were simulated during the following periods:the current(1961–2001),2020s(2010–2039), 2050s(2040–2069),and2080s(2070–2099).
METHODOLOGY
Downscaling method
The SDSM,developed by Wilby et al.(2002),is employed in this study to build statistical relationships between GCM predictors and local climate variables.The software tool for SDSM is available from the internet site:http://www.cisc.uvic.ca/scenarios/index.cgi?More_ Info-Downscaling-Tool.The regional climate variables conditioned by the large-scale state may be written as:
R?F LeT(1) in which R is the predictand(a local climate variable),L is the predictor(a set of large-scale climate variables),and F a deterministic/stochastic function conditioned by L and has to be estimated empirically from historical observations. Three implicit assumptions are made in order to use this kind of downscaling methods for assessing regional climate change:(1)the predictors are variables of relevance and are realistically simulated by the GCM;(2)the predictors employed fully represent the climate change signal;and(3)the relationship is valid also under altered climate condition.
Predictor selecting.The climate system is in?uenced by the combined action of multiple atmospheric variables in the wide tempo-spatial space.Therefore,any single circulation
Table I.Basic information of the?ve meteorological stations in
the study region
No ID Station Latitude(N)Longitude(E)Areal weight 159096Lianping24 22’114 29’0.215 259102Xunwu24 57’115 39’0.201 359293Heyuan23 48’114 44’0.332 459298Huiyang23 05’114 25’0.047 559493Shenzhen22 32’114 00’0.205Figure2.The study area divided by the method of Thiessen polygons
longtitude° (E)l a t i t u d e °( N )
Figure1.Map of Dongjiang river basin
STATISTICAL DOWNSCALING OF HYDROMETEOROLOGICAL EXTREMES
predictor and/or small tempo-spatial space are unlikely to be suf ?cient,as they fail to capture key precipitation mechan-isms based on thermodynamics and vapor content (Wilby,1998).Wilby and Wigley (2000)found that in many cases,maximum correlations between precipitation and the circulation predictors occurred away from the location of the grid-box of the downscaled station and suggested that selection of predictor domain was a critical factor affecting the realisation and stability of downscaling model.
The climate in many zones of China is strongly controlled by the East Asian monsoon,where the atmospheric circulation feature is quite different between winter and summer,and the scale of circulation pattern is large.Thus,it is a big challenge to choose predictors in the wide tempo-spatial space (Samel et al .1999).The procedure adopted in the study for selecting suitable predictors for each predictand is as follows:Table II
First,all of the 26atmospheric variables in each one of four grid-boxes (covering the whole study area and surrounding)were taken as potential predictors.Second,these variables were then screened by SDSM to determine what amount explained variance is when the predictand and predictor(s)were statistically compared.The user was required to select predictors that produce the highest explained variance (E)and lowest standard error (SE).Finally,the predictors identi ?ed in this study were summarized in Table III.It was shown that different atmospheric predictors control different local variables:the maximum and minimum temperature are more sensitive to mean temperature at 2m,and 850-hPa geopotential height,mean sea level pressure,and 500-hPa geopotential height are more sensitive predictors for the pan evaporation.For the daily precipitation,the relative humidity at 500hPa and surface relative humidity are the most sensitive factors.Calibration and validation of SDSM .Before downscal-ing of future climate with GCM predictors,the relation-ship between the selected predictors and precipitation in
all stations need to be calibrated by using NCEP/NCAR predictors.From the 41years of data representing present-day climate (1961–2001),the ?rst 30years (1961–1990)are used for calibrating the regression model,while the rest 11years of data (1991–2001)are used to validate the model.Measures of performance assessment
Four different measures were used to evaluate the performance of the model:the coef ?cient of ef ?ciency (Ens),coef ?cient of determination (R 2),ratio of simulated and observed standard deviation (RS),and model biases.
Table II.Extreme indices for temperature,pan evaporation,and precipitation
Precipitation-related indices Pav Mean of daily precipitation on all days [mm/day]Pnl90Number of events >long-term 90th percentile
Px1d The maximum of daily precipitation in given period [mm]
Px5d Maximum total precipitation from any consecutive 5days [mm]Pxcdd Maximum number of consecutive dry days [day]Pq90
Empirical 90%quantile of precipitation [mm]
Temperature-related indices Txx The maximum of daily maximum temperature [ C]Txn The minimum of daily maximum temperature [ C]
Txq90Empirical 90%quantile of the daily maximum temperature [ C]Tnx The maximum of daily minimum temperature [ C]Tnn The minimum of daily minimum temperature [ C]
Tnq10
Empirical 10%quantile of the daily minimum temperature [ C]Pan evaporation-related indices Ex1d The maximum of daily pan evaporation [mm]
Ex3d Maximum total evaporation from any consecutive 3days [mm]Ex5d Maximum total evaporation from any consecutive 5days [mm]Ex7d
Maximum total evaporation from any consecutive 7days [mm]
Table III.Selected predictor variables for Dongjiang river basin
downscaling
Predictors Predictands
Tmax Tmin Pcpn Eva 1.Mslp √√√
√2.p__u √√√3.p__v √√4.p__z √√5.p500√√√√6.p850√√7.temp √
√
√√8.p5zh √9.p5th √10.rhum √√11.shum √
12.r500√13.r850√14.p5_v √15.p5_z
√
Where:
mslp =mean sea level pressure;p__u =zonal velocity component @surface;p__v =meridional velocity component @surface;p__z =vorticity @surfacep500=500hPa geopotential height p850=850hPa geopotential height p5th =500hPa wind direction;rhum =surface relative humidity;shum =surface speci ?c humidity;r500=relative humidity at 500hPa;r850=relative humidity at 850hPa;p5_v =500hPa zonal wind;p5_z =Vorticity at 500hPa;Pcpn=daily precipitation;Eva =daily evaporation;Tmax-=daily maximumoftemperature;Tmin-=daily minimum of temperature
T.YANG ET AL .
The coef?cient of ef?ciency(Ens)describes how well the volume and timing of the calibrated predictand compares to the observed predictand and is de?ned by
E ns?1àP n
i?1
O iàS i
eT2
P n
i?1
O ià O
eT2
(2)
in which
O?1
n X n
i-1
O i(3)
Where n is the number of time steps,O i is the observed
predictand at time step i,and S i is the simulated
predictand at time step i.Coef?cient of determination
R2measures the amount of variation of a dependent
variable that is explained by variation in the independent.
The closer the values of Ens and R2equal to1,the more
successful the model calibration/validation is.
The ratio of standard deviation of the modelled and
observed indices describes the degree of dispersion of
variables(Hundecha and Bardossy,2008):
RS?
S sim
S obs
(4)
Where S sim is the standard deviation of the modeled
indices and S obs is the standard deviation of the observed
indices.Model bias describes the amount of system
deviation,which is de?ned by
bias?
1
n
X n
i?1
S iàO i
eT(5)
Table IV.Performance assessment for predictands in calibration
and validation
Items Periods Ens R2bias RS
Daily maximum temperature Calibration0.900.9000.93 Validation0.900.90à1.10.93
Daily minimum temperature Calibration0.940.9800.97 Validation0.940.94à0.120.98
Daily pan evaporation Calibration0.650.6500.77
Validation0.610.650.420.83
Daily precipitation Calibration0.500.500.390.67
Validation0.480.480.300.66
https://www.doczj.com/doc/9c16626029.html,parison of the indices of extreme temperature from observed data and simulated by SDSM driven by NCEP and H3A2and H3B2
scenarios in validation period
STATISTICAL DOWNSCALING OF HYDROMETEOROLOGICAL EXTREMES
Indices of extreme climate predictands
Changes in extremes of climate events have received increased attention in the last years(IPCC,2007).Since the early1990s,it has been known that the largest changes in the climate under enhanced greenhouse conditions were likely to be seen in changes of extremes (Gordon et al.,1992).Kunkel et al.(1999)reported that potential changes in extreme events can generate greater impact on human activities and natural environment than mean climate changes.
The select implementation of indices to describe extreme climate events should have several characteristics:relevant, easy to interpret,understandable for policy makers,and covering both frequency and intensity description of extreme processes comprehensively.The core indices of climate extremes recommended by STARDEX Project funded by the European Commission under the Fifth Framework Programme(FP5)(STARDEX,2001)were used in this study.These core indices were shown in Table II.It should be noted that index of mean precipitation is also included in the list.The indices were used to examine the skills of the downscaling method in constructing scenarios for both climate extremes and means.
RESULTS
Model calibration and validation
The calibration(1961–1990)and validation results (1991–2001)were shown in Table IV.It could be seen that both the simulated maximum and minimum tem-peratures were closely consistent with observations.R2, Ens,and RS between simulated and observed temperature exceeded or equaled to0.9in calibration and validation. The simulation of daily pan evaporation was less satisfactory(Ens and R2were between0.61and0.65). As for daily precipitation,Ens and R2values for the downscaled precipitation were about0.5,much lower than daily temperature and pan evaporation.The biases for the maximum temperature,minimum temperature,pan evap-oration,and precipitation wereà1.1C,à0.12C,0.42mm/ day,and0.39mm/day in validation.In summary,those biases were acceptable for practical uses.The statistical model built using SDSM is capable of reproducing daily climate variables.
Inter-comparison of extreme indices of downscaling for the calibration and validation period Temperature.Generally,the performance of a down-
scaling model in constructing temperature indices is better than the performance of precipitation indices.It was shown(Figure3)that the pattern of seasonal variations of temperature was well downscaled with all three datasets (NCEP/NCAR,H3A2,H3B2).In simulating the max-imum of daily maximum temperature(Txx)and empirical 90%quantile of the daily maximum temperature(Txq90), the results from NCEP/NCAR were systematically lower than observations in all seasons,while the simu-lations from the H3A2and H3B2were closer to observations.For the other four indices(the minimum of daily maximum temperature,Txn;maximum of daily minimum temperature,Tnx;minimum of daily minimum temperature,Tnn;and empirical10%quantile of the daily minimum temperature,Tnq10,Table II),the results from NCEP/NCAR were relatively satisfactory.Tnx was under-estimated in summer and winter;instead,the minimum of daily maximum temperature(Txn)from the H3A2and H3B2were6 C overestimated in summer.As for Tnq10, the results from all three datasets were consistent with the observations,while H3B2provided a worst performance for Tnn.Table V summarized the coef?cient of ef?ciency (Ens),coef?cient of determination(R2),ratio of standard deviation(RS),and biases between the16downscaled and observed indices.
Pan evaporation.The performance for pan evaporation downscaling was less satisfactory than daily temperature. The results for daily pan evaporation are provided by Figure4.It can be seen that in simulating these four indices (Ex1d,Ex3d,Ex5d and Ex7d,1Table II),all the simulated results were lower than observations in September.In general,the seasonal patterns were well simulated,while the simulated magnitude was less satisfactory.
Table https://www.doczj.com/doc/9c16626029.html,parison of the extreme indices between observed and simulated results during calibration(1961–1990)and
validation(1991–2001)periods based on NCEP predictors Indices Periods Ens R2bias RS
1.Txx Calibration0.810.93à1.25 1.08
Validation0.820.93à2.40 1.09 2.Txn Calibration0.880.94 1.70 1.03
Validation0.920.95 1.17 1.01 3.txq90Calibration0.910.96à0.98 1.04
Validation0.870.95à2.12 1.08 4.Tnx Calibration0.860.95à1.03 1.11
Validation0.850.93à1.04 1.08 5.Tnn Calibration0.960.970.77 1.02
Validation0.970.980.45 1.07 6.tnq10Calibration0.970.980.640.99
Validation0.970.980.52 1.00 7.Ex1d Calibration0.400.67à0.970.98
Validation0.690.74à0.23 1.00 8.Ex3d Calibration0.570.77à2.080.91
Validation0.760.77à0.290.95 9.Ex5d Calibration0.660.80à2.860.88
Validation0.790.79à0.180.93 10.Ex7d Calibration0.730.83à3.350.86
Validation0.810.810.240.92 11.Pav Calibration0.820.830.390.98
Validation0.810.820.290.89 12.pnl90Calibration0.490.71à0.03 1.32
Validation0.550.710.03 1.24 13.px1d Calibration0.20.47à13.450.61
Validation0.060.40à14.870.56 14.px5d Calibration0.620.67à12.850.76
Validation0.570.69à16.60.69 15.Pxcdd Calibration0.350.73à4.290.87
Validation0.120.61à3.54 1.03 16.pq90Calibration0.620.67à2.280.68
Validation0.670.75à2.510.68
T.YANG ET AL.
STATISTICAL DOWNSCALING OF HYDROMETEOROLOGICAL EXTREMES
https://www.doczj.com/doc/9c16626029.html,parison of the indices of extreme pan evaporation from observed data and simulated by SDSM driven by NCEP and H3A2and H3B2
scenarios in validation period
https://www.doczj.com/doc/9c16626029.html,parison of the indices of extreme precipitation from observed data and simulated by SDSM driven by NCEP and H3A2and H3B2
scenarios in validation period
Precipitation.Among the six indices in simulating precipitation extremes,four of them are associated with extreme wet events:90th percentile(pq90),maximum of daily precipitation(px1d),maximum5-day total(px5d),and number of heavy events(pnl90).The maximum number of consecutive dry days(pxcdd)describes very dry events,and mean of daily precipitation on all days(pav)describes changes of mean daily precipitation.The threshold of1mm was used for a wet day(Hennessy et al.,1999).A dry day was de?ned as having less than1-mm precipitation.
The calibration and validation results from NCEP/ NCAR were shown in Table V.It indicated that the indices were not equally well modeled.Pav has the highest performance(Ens>0.8),while px1d(Ens<0.3) and pxcdd(Ens<0.4)were the worst reproduced indices,implying that the model still cannot fully capture the true persistence of the precipitation occurrence process. Monthly precipitation can be better downscaled by SDSM than the extreme precipitation.In general,the model could simulate most indices well,but the capability in simulating heavy rainfall under abnormal climate and the persistence of the precipitation occurrence was still limited.
The inter-comparison between the simulated and observed six indices in the validation period was shown in Figure5.As for p90,px5d,and px1d,the simulations were generally underestimated,and the underestimation was rather obvious in summer under H3A2and H3B2scenarios.Underestimation of extremes to some extent can be attributed to the short validation period which is heavily in?uenced by some extreme events with very high return period.For instance,the underestimation of px1d and px5d in April was because Huiyang,Heyuan, and Shenzhen stations had recorded rain as high as146.7, 133.6,and344mm/day on14April2000.The return period of the rainfall total in April in Shenzhen was estimated to be100years approximately.Since the validation period only had10years,the simulation could not accurately capture some abnormal and extreme storms.Although the pxcdd was underestimated using the NCEP/NCAR in most seasons,the trend and variability were well simulated.It should be noted that the results from H3A2and H3B2were less satisfactory compared with the NCEP/NCAR data especially for px1d and pxcdd.In summary,the simulation results from NCEP/NCAR data were closer to the observations than the results from H3A2and H3B2.
Projected changes for future climate scenarios
1.Temperature
Changes in extreme temperature between the baseline period(1961–1990)and the future period(2011–2099) were shown in Figure6.Under the H3A2scenario,all six
Figure6.Changes(%)in extreme temperature between the period(1961–1990)and the period(2011–2099)under the H3A2and H3B2scenarios
T.YANG ET AL.
temperature indices will increase in future90years.Txx (6.2C)and Tnx(4.8C)showed the highest increase in summer,while Txn(5.5 C)and Tnn(4.9 C)increase most considerably in spring.Txq90and tnq10will increase with similar magnitude during different seasons.Under H3B2scenario,the projected Txx(in2020s and2050s)and Txn(in2050s)will decrease slightly in spring,while the other four indices(Txq90,Tnx,Tnn,and Tnq10)showed upward trends.Therefore,the extreme temperature events will be more frequent in the future.
2.Pan evaporation
Figure7showed that all the indices of pan evaporation in H3A2and H3B2scenario would increase by10%(in2020s) and40%(in2080s)in summer.However,the change trends of H3A2and H3B2projections are opposite in winter:the projections from H3A2scenario are decreasing while a slight increase was projected from H3B2scenario.Ex3d, Ex5d,and Ex7d would decrease in spring during2020s,but they would increase during2050s and2080s under H3A2 scenario.Under the H3B2scenario,they will decrease by 5%during2020s and2050s and increase by2%to12%in 2080s.
3.Precipitation
The projected changes of precipitation extremes(Figure8) were inconsistent with temperature extremes.It can be seen that under H3A2scenario,the pav and p90would decrease in winter and spring and increase in summer and autumn,while in H3B2,they showed decreasing trend only in winter.As for pnl90,the number of events higher than long-term90th percentile will decrease in winter and spring and increase in summer and autumn,and this is more obvious under H3A2scenario.Projection of pxcdd under H3A2scenario showed considerable increases only in winter.Under H3B2scenario,pxcdd showed increases in all seasons.For the px1d and px5d,the results of H3A2 had distinct change patterns in different seasons and periods.In the future,the maximum daily precipitation (px1d)and the cumulative5-day total precipitation(px5d) under H3B2scenario will increase.
DISCUSSION
In this section,we attempt to identify the linkages between the underlying driving forces and skill scores in downscaling precipitation extremes over the Dongjiang basin.During the calibration and validation of SDSM with the NCEP/NCAR reanalysis data,the temperature indices were downscaled rather perfectly,but SDSM was not very effective in downscaling precipitation extremes. This can be attributed to the reasons below. Dongjiang River basin located in southern China suffers frequent rainstorms,and the major driving forces are more complicated than in other inland regions
Figure6.(Continued)
STATISTICAL DOWNSCALING OF HYDROMETEOROLOGICAL EXTREMES
(See Fig.9).Hereby,the?ood season(April to October) was divided into pre-?ood and post-?ood seasons for sake of discussion.The pre-?ood season(April to June)in South China is composed of the frontal precipitation period and the summer monsoon precipitation period (Qiao et al.,2010).In pre-?ood season,the main atmospheric general circulation system dominated in middle high latitude of the Eurasia is two-trough and one-ridge,which help cold air move toward the South China.The Western Paci?c Subtropical High was stable at18 N,which creates favorable conditions for the prevailing of the southerly airstream in South China and coastal areas.Meanwhile,the active cold air in the southern Hemisphere and strengthening of the cross-equatorial?ow contributed to form and intensify low tropospheric jet in China and northern South China Sea.
A large amount of moisture and unstable air-mass with high humidity and temperature is transported to the upper level.In this favorable situation,along with the special topography and underlying surface,difference of sea land distribution,non-uniform heating,thermodynamic and dynamical processes in atmosphere and the interaction in different scales would release heavy rain to the South China.Besides,unbalance force of atmospheric motion and the coupling reaction among convective cloud cluster and moisture frontal zone and low level jet lead to the continuation of strong storm.In post-?ood season(July to October),the rainstorms are triggered by tropical system, such as tropical cyclone,inter-tropical convergence zone, and easterly wave.The tropical cyclone would not only bring tremendous moisture;they form big rainstorm directly due to the strong convergence and updraft.If combined with outside system(cold air and westerly belt system),it will bring more intense rainfall into the region.
Figure7.Changes(%)in extreme evaporation between the period(1961–1990)and the period(2011–2099)under the H3A2and H3B2scenarios
T.YANG ET AL.
For example,under the in?uence of the hitting of typhoon and the cold air traveling from the north and northwest China,a heavy rainstorm occurred in southern Guangdong providence on24September1979.The highest rainfall of Huiyang exceeded400mm.The monsoon trough is another important driving force compared with tropical cyclone.It brings persistent rainfall to South China.As for the precipitation in winter and spring,the anomalous vapor transport of the western Paci?c and the low level in the South China Sea were the main impact factors,which was caused by the ENSO teleconnection.The El Ni?o made the low-level anticyc-lone of the Philippine Sea abnormal,which offered favorable water vapor condition for the rainstorm.In addition,prevailing south wind contributed to the continuous water vapor convergence in south China. While in case of the La Ni?a,the opposite phenomenon occurs.Therefore,the complex precipitation processes in Dongjiang River basin increase the dif?culty in precipi-tation simulation.This explains why the indices that described very wet events(maximum of daily precipita-tion,maximum5-day total,number of heavy events)were not simulated well.
In addition,SDSM is not suf?ciently powerful to capture the features of extreme precipitation events similar with other SDSMs(e.g.Srikanthan and McMahon,2001).The defect of stochastic precipitation models need to be improved (Gregory et al.,1993).According to Wilby et al.(2004),this might attribute to the more stochastic nature of precipitation occurrence and magnitude,and the regression-based SDSMs often cannot explain entire variance of the down-scaled variable.Additionally,while there is a strong seasonal consistency between stations for a number of predictors(e.g.geopotential heights and humidity),the seasonal speci?c predictor also play an important role(e.g. surface divergence during the summer months,Fealy and Sweeney,2007).Hence,it is recommended the selected predictors at seasonal scale(or month scale)improve the downscaling performance to a certain degree.
CONCLUDING REMARKS
In this study,the large-scale atmospheric variables from GCMs output were downscaled to the regional scale in order to investigate the spatial-temporal changes in extreme precipitation,temperature,and pan evaporation over the Dongjiang River basin during2010–2099under H3A2and H3B2emission scenarios.It will improve current understanding on hydrological impacts under future climate change in the subtropical regions.The results for downscaling temperature under scenarios H3A2and H3B2showed that the temperature extreme events would be more signi?cant in the rest21st century (2010–2099).Despite the similar changes supplied by both scenarios,the magnitudes of the changes projected
A2 scenario B2 scenario
Figure8.Changes in extreme precipitation between the period(1961–1990)and the period(2011–2099)under the H3A2and H3B2scenarios STATISTICAL DOWNSCALING OF HYDROMETEOROLOGICAL EXTREMES
by the two scenarios are generally different.As to the pan evaporation,the predicted value from H3A2indicated that the maximum 1,3,5,and 7days evaporation will decrease in winter while increase in other three seasons in 2010–2099.For H3B2,a general upward trend was identi ?ed in future.However,the projected changes for precipitation-related indices are uncertain.
Although some preliminary results of changes in downscaled extreme indices are obtained in the present work,a number of uncertainties still exist in assessing the changes of regional-scale extreme indices.More research work in the future,particularly the ensemble projections by higher resolution GCMs or especially RCMs,as well as analyzing the uncertainties related to the model spread,
Figure 9.Conceptual diagram explained the heavy rain processes in South
China
Figure 8.(Continued )
T.YANG ET AL .
are needed for a more profound understanding of the futures changes in climate extremes.
ACKNOWLEDGEMENTS
The work was jointly supported by grants from the National Natural Science Foundation of China (40901016,40830639,40830640),a grant from the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(2009586612,2009585512),and the Fundamental Research Funds for the Central Universities(2010B00714),the Australian Endeavour Fellowship Program,and CSIRO Computational and Simulation Sciences Transformational Capability Plat-form.Finally,cordial thanks are also extended to the editor, Professor Malcolm G.Anderson and two anonymous referees for their valuable comments which greatly improved the quality of this paper.
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企业门户网站使用说明书 配置源程序 附加数据库MySQL （1）将TM\08\Database文件夹中db_database25.sql放入mysql目录下的bin 文件中，选择“开始”/“所有程序”/“MySQL”/“MySQL Command Line Client”命令， （2）将打开MySQL数据库的Command Line Client窗口，在该窗口中，输入密码并按下〈Enter〉键时，进入数据库在命令行输入source db_database25.sql。 发布与运行 （1）将光盘\TM\08\MedicineManager文件夹拷贝到MyEclipse的工作空间中。 （2）启动MyEclipse。 （3）选择“文件”/“导入”菜单项，展开“常规”节点，选择“现有项目到工作空间中”子节点，如图1所示。 图1 “导入”窗口 （4）单击【下一步】按钮，单击【浏览】按钮，选择程序所在目录，然后勾选“将项目复制到工作空间中”复选框，如图2所示。
图2 “导入”窗口 （5）单击【完成】按钮。 （6）参照第07章文档中的7.3.5节中的第5小节，为MyEclipse配置Tomcat服务器。 （8）添加MySQL驱动包。 （9）单击工具栏的“”按钮，将弹出如图3所示的对话框。这个对话框是项目发布对话框，在对话框的“Project”下拉选择框中选择本系统的项目名称“MedicineManager”，单击Add按钮进行项目发布的设置。 图3 MyEclipse项目发布对话框 （10）在弹出如图4所示的对话框中，选择“Server”下拉选择框中的“Tomcat 5”服务器，单击“完成”按钮程序将自动发布到服务器中。如果需要重新发布项目，可以单击Redeploy按钮。
档案管理操作手册 Document number【980KGB-6898YT-769T8CB-246UT-18GG08】
目录
档案管理 PowerOn图纸文档管理系统提供了从文件的产生，修改，批准到修订的系统管理，而本章节的档案管理则是文件的最终归档管理。为项目管理团队和项目各主要执行中心进行所有项目文件归档的系统管理，收集归档文档的相关信息，可以支持将来企业的运作及组织维护部门的需要。同时，档案管理中的文件及其原始数据有利于建立未来的项目生命周期和知识管理系统。 在实际项目中，许多信息是由档案管理系统给出。档案管理指的是对作为信息载体的资料进行有序的收集，加工，分解，编目，存档，并作为项目各参与方提供专用和常用的信息过程。前章图纸文档管理是本章档案管理的基础，是项目图纸文档被有效率使用的前提条件。 在【工程中心】中单击【档案管理】，或者在【工程中心】选择菜单【模块】=>【档案管理】，即可进入档案管理模块。 首先跳出的是档案库的选择窗口。
图17-1 档案库选择窗口 档案管理初始化 17.1.1 档案馆信息维护 用户选择【定义】=>【档案馆】菜单，系统弹出档案馆定义和维护窗口。用户可在当前窗口增加、删除和修改档案馆信息，默认档案馆不可删除。用户可指定一个档案馆，点击设置默认档案馆。系统将当前档案馆设置为默认档案馆。
图17-1-1 档案馆信息 17.1.2 定义ABS码 标准档案分类码在系统中简称ABS码。不同行业均有自己的行业标准档案分类码。所以，系统支持不同的档案库选择不同的标准档案分类码。 选择【定义】=>【标准档案类目（ABS）】菜单，进入ABS编辑的窗口。
思科交换机的基本配置命令学习 CISCO交换机基本配置：Console端口连接 用户模式hostname# ； 特权模式hostname(config)# ； 全局配置模式hostname(config-if)# ； 交换机口令设置： switch>enable ；进入特权模式 switch#config terminal ；进入全局配置模式 switch(config)#hostname csico ；设置交换机的主机名 switch(config)#enable secret csico1 ；设置特权加密口令 switch(config)#enable password csico8 ；设置特权非密口令 switch(config)#line console 0 ；进入控制台口 switch(config-line)#line vty 0 4 ；进入虚拟终端 switch(config-line)#login ；虚拟终端允许登录 switch(config-line)#password csico6 ；设置虚拟终端登录口令csico6 switch#exit ；返回命令 交换机VLAN创建，删除，端口属性的设置，配置trunk端口，将某端口加入vlan中，配置VTP：switch#vlan database ；进入VLAN设置 switch(vlan)#vlan 2 ；建VLAN 2 switch(vlan)#vlan 3 name vlan3 ；建VLAN 3并命名为vlan3 switch(vlan)#no vlan 2 ；删vlan 2 switch(config)#int f0/1 ；进入端口1 switch(config)#speed ? 查看speed命令的子命令 switch(config)#speed 100 设置该端口速率为100mb/s (10/auto) switch(config)#duplex ? 查看duplex的子命令 switch(config)#duplex full 设置该端口为全双工(auto/half) switch(config)#description TO_PC1 这是该端口描述为TO_PC1 switch(config-if)#switchport access vlan 2 ；当前端口加入vlan 2 switch(config-if)#switchport mode trunk ；设置为trunk模式(access模式) switch(config-if)#switchport trunk allowed vlan 1，2 ；设置允许的vlan switch(config-if)#switchport trunk encap dot1q ；设置vlan 中继 switch(config)#vtp domain vtpserver ；设置vtp域名相同 switch(config)#vtp password ；设置发vtp密码 switch(config)#vtp server ；设置vtp服务器模式 switch(config)#vtp client ；设置vtp客户机模式 交换机设置IP地址,默认网关，域名，域名服务器，配置和查看MAC地址表： switch(config)#interface vlan 1 ；进入vlan 1 switch(config-if)#ip address 192.168.1.1 255.255.255.0 ；设置IP地址 switch(config)#ip default-gateway 192.168.1.6 ；设置默认网关 switch(config)#ip domain-name https://www.doczj.com/doc/9c16626029.html, 设置域名 switch(config)#ip name-server 192.168.1.18 设置域名服务器 switch(config)#mac-address-table? 查看mac-address-table的子命令 switch(config)#mac-address-table aging-time 100 设置超时时间为100ms switch(config)#mac-address-table permanent 0000.0c01.bbcc f0/3 加入永久地址在f0/3端口 switch(config)#mac-address-table restricted static 0000.0c02.bbcc f0/6 f0/7 加入静态地址目标端口f0/6源端口f0/7 switch(config)#end
江苏电子税务局纳税人端用户操作手册
目录 1.1 功能概述 (3) 1.2 办税业务指引区 (3) 1.2.1功能概述 (3) 1.2.2操作步骤 (3) 1.2.3 注意事项 (4) 1.3 办税渠道区 (4) 1.3.1功能概述 (4) 1.3.2用户登陆注册 (4) 1.3.3纳税服务热线 (18) 1.3.4办税厅导航 (19) 1.3.5手机客户端、江苏国税官方微信 (20) 1.3.6邮递办税 (25) 1.4政策宣传发布区 (27) 1.4.1功能概述 (27) 1.4.2操作步骤 (27) 1.4.3 注意事项 (35) 1.5办税应用区 (35) 1.5.1功能概述 (35) 1.5.2操作步骤 (35) 1.5.3 注意事项 (37) 1.6视频辅导区 (37) 1.6.1功能概述 (37) 1.6.2注意事项 (38) 1.7在线帮助区 (38) 1.7.1功能概述 (38) 1.7.2征期日历 (38) 1.7.3 信息查询 (39) 1.7.4办税指南 (45) 1.7.5网上学堂 (45) 1.7.6在线帮助 (46) 1.7.7服务投诉 (46) 1.7.8涉税举报 (47) 1.7.9问卷调查 (47) 1.8其他 (48) 1.8.1功能概述 (48) 1.8.2下载中心 (48) 1.8.3 计算器 (49) 1.8.4 浏览器设置 (50)
首页各类功能区介绍及操作指引 1.1 功能概述 电子税务局门户首页包含7块区域，分别是A办税业务指引区、B办税渠道区、C政策宣传发布区、D办税应用区、E视频辅导区、F在线帮助区和G其他。页面如下： 1.2 办税业务指引区 1.2.1功能概述 本区域包含首页、税收优惠、申报及缴（退）税、发票使用、登记认定、税收证明和小微企业税银互动六个栏目，页面以若干常见问题问答的形式，系统友好地引导纳税人办理各类税收业务，并提供操作链接、办税指南、热点问题、视频学习，提高用户业务办理能力。 1.2.2操作步骤 点击进入各类模块即可查看。
实验四 三层交换机基本配置及利用三层交换机实现不同VLAN 间通信 一、实验名称 三层交换机基本配置及VLAN/802.1Q －VLAN 间通信实验。 二、实验目的 理解和掌握通过三层交换机的基本配置及实现VLAN 间相互通信的配置方法。 三、实验内容 若企业中有2个部门：销售部和技术部（2个部门PC 机IP 地址在不同网段），其中销售部的PC 机分散连接在2台交换机上，配置交换机使得销售部PC 能够实现相互通信，而且销售部和技术部之间也能相互通信。 在本实验中，我们将PC1和PC3分别连接到SwitchA （三层交换机）的F0/5端口和SwitchB 的F0/5端口并划入VLAN 10，将PC2连接到SwitchA （三层交换机）的F0/15端口并划入VLAN 20，SwitchA 和SwitchB 之间通过各自的F0/24端口连接。配置三层交换机使在不同VLAN 组中的PC1、PC2、PC3能相互通信。 三、实验拓扑 四、实验设备 S3550-24（三层交换机）1台、S2126交换机1台、PC 机3台。 五、实验步骤 VLAN/802.1Q －VLAN 间通信: 1．按实验拓扑连接设备，并按图中所示配置PC 机的IP 地址，PC1、PC3网段相同可以通信，但是PC1、PC3和PC2是不同网段的，所以PC2（技术部）不能和另外2台PC 机（销售部）通信。 2．在交换机SwitchA 上创建VLAN 10，并将0/5端口划入VLAN 10中。 SwitchA(config)#vlan 10 ！创建VLAN 10 SwitchA (config-vlan)#name sales ! 将VLAN 10 命名为sales SwitchA (config)#interface f0/5 ！进入F0/5接口配置模式 SwitchA (config-if)#switchport access vlan10 ！将F0/5端口划入VLAN 10 SwitchA #show vlan id 10 ！验证已创建了VLAN 10并已将F0/5端口划入VLAN 10中 PC2
附件2： 经销商门户系统操作手册 (V2.1) 四川沱牌舍得酒业股份有限公司 金蝶软件（中国）有限公司成都分公司 2015年09月
修改记录 更改记录 日期作者版本参考版本备注2015-8-6 谢松V1.0 2015-9-15 杜泽春V2.0 2015-10-8 杜泽春V2.1 添加了登录网址后缀 审校 日期作者版本参考版本备注
目录 修改记录 (2) 更改记录 (2) 审校 (2) 1 WEB端登录 (4) 1.1登录网址 (4) 1.2密码修改 (6) 2网上订货单制作 (6) 3渠道管理 (8) 3.1渠道网点建设单新增 (8) 3.2渠道网点建设单维护 (8) 4渠道库存导入单 (9) 5报表展示 (13) 5.1市场费用可用额度查询 (13) 5.2客户折扣对账表 (13)
本版本主要介绍经销商网上订货单制作、渠道网点建设制作、渠道库存导入单制作。 1 web端登录 1.1登录网址 1、输入网址：http://118.122.182.188:8888/K3WEB/login.aspx见如下界面 2、输入公司代号与密码：公司代号：06 密码：为空，不用输入任何文字 3、登录公司验证:点击确定则可，将出现如下界面。
4、公司验证通过后，选择命名用户登录 5、选择数据源：沱牌舍得业务账套 6、选择子系统：客户门户 7、输入用户名与密码（用户名系统唯一，客户首次登录须修改） 强恒用户名：13010303 密码：tpsd*2601 8、点击确定，则登录公司经销商门户系统。 注意事项： ①公司将为经销商在系统里建立1个唯一用户名。 ②系统将为经销商预设一个初始密码，第一次登录后，须更改密码，重新设置。 ③各经销商要妥善保管好用户名与密码，所有以自己用户名登录发生的经济业务自行承 担责任。
三层交换机与路由器的配置实例（图解） 目的：学会使用三层交换与路由器让处于不同网段的网络相互通信 实验步骤：一：二层交换机的配置： 在三个二层交换机上分别划出两VLAN，并将二层交换机上与三层交换或路由器上的接线设置为trunk接口 二：三层交换机的配置： 1：首先在三层交换上划出两个VLAN，并进入VLAN为其配置IP，此IP将作为与他相连PC的网关。 2：将与二层交换机相连的线同样设置为trunk接线，并将三层交换与路由器连接的线设置为路由接口（no switchsport） 3：将路由器和下面的交换机进行单臂路由的配置 实验最终结果：拓扑图下各个PC均能相互通信
交换机的配置命令： SW 0: Switch> Switch>en Switch#conf Configuring from terminal, memory, or network [terminal]? Enter configuration commands, one per line. End with CNTL/Z. Switch(config)#vlan 2 Switch(config-vlan)#exit Switch(config)#int f0/2 Switch(config-if)#switchport access vlan 2 Switch(config-if)#no shut Switch(config-if)#int f0/3 Switch(config-if)#switchport mode trunk %LINEPROTO-5-UPDOWN: Line protocol on Interface FastEthernet0/3, changed state to down %LINEPROTO-5-UPDOWN: Line protocol on Interface FastEthernet0/3, changed state to up Switch(config-if)#exit Switch(config)# SW 1: Switch>en Switch#conf Configuring from terminal, memory, or network [terminal]? Enter configuration commands, one per line. End with CNTL/Z. Switch(config)#int f0/2 Switch(config-if)#switchport access vlan 2 % Access VLAN does not exist. Creating vlan 2 Switch(config-if)#no shut Switch(config-if)#exit Switch(config)#int f0/3 Switch(config-if)#switchport mode trunk %LINEPROTO-5-UPDOWN: Line protocol on Interface FastEthernet0/3, changed state to down %LINEPROTO-5-UPDOWN: Line protocol on Interface FastEthernet0/3, changed state to up Switch(config-if)# SW 2: Switch>en Switch#conf Configuring from terminal, memory, or network [terminal]?
汾西矿业集团公司 档案（信息化）管理系统 用 户 操 作 手 册
1、系统应用价值 2、产品的特点 3、系统档案库结构 4、系统基本操作
1、系统应用价值 购买档案管理系统主要用来解决以下问题： 1.档案没有管理，档案散落在每个职工手里，没有档案管理部门，并且每年有200 份以上的文件产生。 2.有档案管理部门，但没有计算机管理，查询利用还是手工操作。 3.原始纸质档案占用大量的空间。在现在大城市空间紧张，房价越来越高的今天，，如何节省档案占 用的空间？ 4.档案的保管成为问题，南方太潮湿、北方干燥都成为档案管理的难题，如何能保证档案信息 不随着时间的流逝而消失。 5.有计算机管理档案，但没有实现联网，档案信息被困在“信息孤岛”中，无法得到有效利用。 6.有了计算机管理档案了，但系统维护非常困难，出现问题找开发厂商，几个月也没有回音。 7.上了计算机系统，但查询起来还是比较慢，不能达到预期的目的。 8.实现计算机联网了，但其它系统的数据无法与档案管理互通。造成数据的重复录入和查询利 用困难。 9.档案管理系统也联网了，与其它系统的数据也可以互通了，但档案的全面信息的保存没有实 现。如档案的产生过程（例如审批过程），并没有记录到档案中，而这些对于档案信息保持完整也 是必须的。 10. 上面的问题都解决了，是不是就没有问题了？也不一定！联网了、数据互通了，只是解决了档案的一般性管理。它并没有解决档案全部问题。如档案的保密特性，每个重要的单位都有非常保密的档案，和无法用价值衡量的珍贵档案，这些是在当前市场竞争中非常重要的“软实力” 了。怎样绝对的防止丢失和不能扩散，如果只是实现的一般意义上的权限管理及加密，显然是不够的。我们需要一个更加严密的监控系统监控整个单位的档案发生及保管过程。举一个例子：战场上侦查敌情，过去有飞机已经不错了，现在使用上了卫星，敌人的一举一动就一目了然，胜利就有了 每个职工手头的档案并没有随着一般的档案管理系统结合档案管理，可靠的保证！的使用得到严密的控制，丢失、泄密时有发生，而且不被人察觉，造成的损失是巨大的，有时是不可弥补的。 让客户明明我们都有对应的软件部件给予解决，对于以上问题的解决，并且量体裁衣，白白的上系统，实实在在的解决问题。2、产品特点:1. 数据库树形结构技术数据库树形结构技术是我们系统的独有优势，针对某一具体档案管理类型，树形扩展深度没有限制，提供了复杂文、档资料的管理平台。 理支持档案管类型深度扩充 档案管理中可能出现个性的地方均可灵活定制
实验四：交换机基本配置 一、实验项目名称：交换机基本配置。 二、实验环境：与Internet连接的局域网。 三、实验目的和要求： 1.清除交换机的现有配置； 2.检验默认交换机配置； 3.创建基本交换机配置； 4.管理MAC地址表； 5.配置端口安全性。 四、实验过程： 拓扑图 任务1：清除交换机的现有配置 步骤 1. 键入enable 命令进入特权执行模式。 enable 命令，进入特权执行模式。
步骤 2. 删除VLAN 数据库信息文件。 VLAN 数据库信息与配置文件分开存储，以vlan.dat 文件名存储在闪存中。要删除VLAN 文件，请发出命令delete flash:vlan.dat 步骤 3. 从NVRAM 删除交换机启动配置文件。 步骤 4. 确认VLAN 信息已删除。 使用show vlan 命令检查是否确实删除了VLAN 配置。 步骤 5. 重新加载交换机。 在特权执行模式提示符下，输入reload 命令开始这一过程。
任务2：检验默认交换机配置 步骤 1. 进入特权模式。 特权模式下，您可以使用全部交换机命令。不过，由于许多特权命令会配置操作参数，因此应使用口令对特权访问加以保护，防止未授权使用。特权命令集不仅包括用户执行模式所包含的那些命令，还包括configure 命令，通过该命令可以访问其余命令模式。 请注意特权执行模式下配置中提示符的变化。 步骤 2. 检查当前交换机配置。 发出show running-config 命令，检查当前的运行配置。
问题：1.交换机有多少个快速以太网接口？（24个）
2.交换机有多少个千兆以太网接口？（2个，分别是光纤上联接口，汇聚功能接口） 3.显示的vty 线路值范围是什么？（0-15） 发出show startup-config 命令，检查当前NVRAM 的内容。 问题：为什么交换机做出这样的响应？(因为启动配置文件不存在) 发出show interface vlan1 命令，检查虚拟接口VLAN1 的特征。 1.交换机上设置了IP 地址吗？（没有） 2.虚拟交换机接口的MAC 地址是什么？（00e0.b0d8.2421） 3.此接口打开了吗？(没有，administratively down 指端口被管理员关掉。) 现在使用show ip interface vlan1 命令查看接口的IP 属性。 你看到的输出是什么？ （指端口已被管理员关掉，“line protocol is down”可能是frame封装的问题。） 步骤 3. 显示Cisco IOS 信息。 使用show version 命令显示Cisco IOS 信息。
中国电信2013年 全国集中MSS外部门户系统
文档管理 文档信息 版本信息 批准 姓名: ____________________________ 日期: ___________ 姓名: ____________________________ 日期: ___________
目录 1文档说明 (4) 1.1编制说明 (4) 1.2项目背景 (4) 1.3文档目标 (4) 2供应商注册 (4) 2.1业务说明 (4) 2.2涉及角色 (5) 2.3操作流程 (5) 3登录系统 (14) 3.1用户登录 (14) 4系统功能 (16) 4.1系统功能模块 (16) 4.2角色简介 (16) 4.3常用操作 (17) 4.3.1常用操作 (17) 5日常业务 (17) 5.1系统主要业务功能简介 (17) 5.2日常业务操作 (19) 5.2.1采购协同 (36) 5.2.2付款协同 (39) 5.2.3可研协同 (46) 5.2.4设计协同 (51) 5.2.5施工协同 (59) 5.2.6监理委托 (66)
1 文档说明 1.1 编制说明 本操作手册适用于指导中国电信全国集中MSS项目外部门户系统的学习使用。 1.2 项目背景 通过集中MSS系统的建设，目标是在中国电信全国范围内建立一个集中、规范、统一的管理支撑系统的平台。通过数据规范的统一和数据透明促进企业内部数据和信息的共享，建立贯穿集团、省、地市的采购与库存管理体系一体化和标准化管理流程，提高采购执行效率、规范采购业务行为、规避采购风险，降低库存水平、提升供应链的总体运营效率；通过建立集团级企业管理信息数据仓库，为业务部门和管理层提供实时准确的业务管理和决策支持信息。 其次，通过建设集中MSS系统这样一个规范高度统一、业务高度集成的平台，为加强业务整合、统一业务模式、规范业务操作、优化业务流程、固化管理要求提供有效的管理手段和强有力的系统支撑。 总之，通过集中MSS系统的建设，将有效促进中国电信的纵向管理一体化和横向业务集成化进而达到集约高效，为中国电信进一步提高管理水平、保持可持续发展和实现精确管理搭建强大的技术和管理平台。 1.3 文档目标 2 供应商注册 2.1 业务说明 与电信合作单位需要在门户系统发起供应商注册申请，供应商注册审批通过后全国通用；
同济大学档案管理系统 操作手册 同济大学档案馆 二○○八年五月
目录 第一章系统简介 (1) 第二章档案管理 (3) 1．档案信息录入 (3) 2．档案查询与打印 (9) 3．文件调整 (11) 4．档案实体销毁 (12) 5．辅助立卷与批量修改 (12) 6．文件识别 (13) 7．邮件系统管理 (15) 第三章名词解释 (16)
第一章系统简介 本系统采用浏览器/服务器结构，具有维护方便，不需要安装客户端软件，客户端只需要一台联网（局域网、校园网、互联网）的计算机就可以应用，具有操作简单、维护方便、安全可靠、功能齐全等特点。 该系统包括档案管理(科技档案、文书档案、会计档案、声像档案、实物档案管理等)、收发文管理、全文自动著录与标引等子系统，其主要功能特点如下: 一、系统构架及运行平台 浏览器/服务器(B/S)结构作为客户机/服务器(C/S)的替代技术已经成为目前各类网络管理系统的主流技术。本系统正是基于浏览器/服务器(B/S)结构，具有易安装、易维护、易操作，与操作系统，后台数据库无关等特点。 二、系统主要功能 1. 全文自动著录与标引 系统设计了面向21世纪的办公自动化过程中形成电子文件全文自动采集，自动著录(即自动从电子文件全文提取各个著录项)，自动标引分类号、档号、主题词、保管期限与全文任意关键词自动检索。实现了档案文件的采集、著录与标引自动化和人工智能化，对办公自动化过程中形成的电子文件的利用十分方便，大大提高了档案工作效率和自动化程度。 2. 全文管理与全文检索 本系统的全文管理通过高效的全文检索算法，实现了全文的高速检索。系统还支持用户远程上载各种格式的电子文件全文、纸质文件扫描图像，从而实现了对档全文检索、打印、下载、上传、备份等的全方位管理。 3. 图像、录像、录音等多媒体档案管理 系统对扫描图像、录像、录音等多媒体档案进行统一管理，用户可以远程上载图像、多媒体文件到系统中，对于录音录像档案还可以进行在线点播。 4. 档案信息统计 系统可以对各类档案资料进行灵活的统计，并且可以绘出个直方图、统计表等各种统计图表。 5. 档案借阅利用 系统实现了档案管理借阅利用的网络化，用户只需要通过身边的计算机远程登录到系统中就可以查阅馆藏档案信息，确定所要借阅的档案实体，系统即可纪录完整的借阅利用信息，并可以进行借出档案实体的催还，借阅利用信息的统计等操作。
三层交换机基本配置 【实验名称】 三层交换机端口配置 【实验目的】 配置开启三层交换机的三层功能，实现路由作用。 【背景描述】 为了隔离广播域而划分了VLAN，但不同的VLAN之间需要通信，本实验将实现这一功能。即同一VLAN里的计算机能跨交换机通信，不同VLAN里的计算机系统也能互相通信。 【技术原理】 三层交换机是在二层交换的基础上实现了三层的路由功能。三层交换机基于“一次路由，多次交换”的特性，在局域网环境中转发性能远远高于路由器。而且三层交换机同时具备二层的功能，能和二层交换机进行很好的数据转发。三层交换机的以太网接口要比一般的路由器多很多，更加适合多个局域网段之间的互联。 三层交换机本身默认开启了路由功能，可利用IP Routing命令进行控制。 【实验设备】 S3350（一台），PC机（两台）。 【实验拓扑】
注意：先连线，在进行配置，注意连接线缆的接口编号。S3350为三层交换机。 【实验步骤】 步骤一 开启三层交换机的路由功能： Switch>enable //进程特权模式 Switch #configure terminal //进入全局模式 Switch (config)#hostname s3350-24 S3350-24 (config)#ip routing //开启三层交换机的路由功能 步骤二 配置三层交换机端口的路由功能： S3350-24>enable //进入特权模式 S3350-24#configure terminal //进入全局模式 S3350-241 (config)#interface fastethernet 0/2 //进入fa0/2端口 S3350-24 (config-if)#no switchport //开启端口的三层路由功能 S3350-24 (config-if)#ip address 192.168.5.254 255.255.255.0 //配置ip地址S3350-24 (config-if)#no shutdown //启用端口，使其转发数据
门户网站操作指南 哈尔滨市妇女联合会 2013年8月
目录 第一章门户网站简介 (2) 1.1 主要栏目 (2) 1.2 信息类型与表现形式 (3) 第二章门户网站后台管理 (5) 2.1 信息提交 (5) 2.1.1 图文结合类信息提交步骤 (5) 2.1.2 通知公告类信息提交步骤 (11) 2.1.4 视频类信息提交步骤 (14) 2.1.5 信息提交后的维护 (14) 2.2 审核发布 (14) 2.3 回收站 (15) 2.4 密码修改 (15) 附：信息编辑要求 (16) （供信息管理员使用）
第一章门户网站简介 哈尔滨市妇女联合会门户网站是以信息公开、在线办事、公众参与为主要内容的综合性网络平台，涉及我市妇女发展、维权、建设以及儿童家庭、社会服务等多方面内容，并将通过此平台为广大公众服务。这是加强妇女建设、提高办公效率、展示我市形象、建设阳光政府的有效途径，将为我市妇女及儿童教育的又好又快发展创造条件。 网站平台采用主/子网站模式构建，主要由首页、妇女工作、维权窗口、女性讲堂、巾帼志愿、爱心世界、家长网校、就业家政、妇儿规划、女性社区等子站组成。 1.1 主要栏目 【妇女工作】：为了宣传贯彻党的路线、方针、政策。教育、引导妇女成为有理想、有思想、有文化、有纪律的社会主义新女性，宣传、普及有关妇女儿童的法律和法规 知识，提高妇女儿童健康水平和家庭教育水平，维护社会稳定。 【维权窗口】：呼吁社会关注、推动有关部门解决侵害妇女儿童权益的热点、难点问题，进行男女平等基本国策、法律法规政策的宣传培训，开展婚姻家庭调适服务，举 办增强妇女能力、提高妇女素质相关内容的培训。 【女性讲堂】：进一步提高妇女和家庭的思想道德素质、科学文化素质、身心健康素质，促进女性、家庭和社会的和谐与幸福。 【巾帼志愿】：大力发展社会服务业，帮助更多的下岗失业妇女在社会中实现再就业；开展结对帮扶、扶贫济困和群众性互助服务活动。 【爱心世界】：致力公益慈善事业，关爱青少年成长，倡导企业公民责任，推动社会河蟹进步，通过互联网平台支持广泛的公益慈善事业。 【家长网校】：系统,科学,完整的帮助家长掌握好学习方法,提高学习效率和能力。 【就业家政】：通过就业培训扩大内需、服务民生、增加就业、构建和谐社会。 【妇儿规划】：深入贯彻落实科学发展观，宣传倡导全社会共同关注妇女儿童发展，并积极参与推动规划的实施，为妇女儿童创造良好的发展环境。 【女性社区】：围绕妇女学习、就业、婚恋、参与、维权等基本需求，不断加大服务力度，拓展女性服务领域。
三层交换机vlan配置 实验目的： 1.会使用三层交换机的路由功能。 2.会进行三层交换机与二层交换机之间的vlan配置。 实验步骤： 一、绘制实验拓扑如下： 二、配置S1、S2、S3间的Trunk（中继链路） S1(config)#int range f0/1 -2 S1(config-if-range)#sw mo trunk S2(config)#int f0/1 S2(config-if)#sw mo trunk S3(config)#int f0/1 S3(config-if)#sw mo trunk 三、配置VTP并创建vlan S1(config)#vtp mode server Device mode already VTP SERVER. S1(config)#vtp domain 123 S2(config)#vtp mode client Setting device to VTP CLIENT mode. S2(config)#vtp domain 123 S3(config)#vtp mode client Setting device to VTP CLIENT mode. S3(config)#vtp domain 123 //以上配置S1为VTP服务器模式，配置S2、S3为客户端模式S1(config)#vlan 2 S1(config)#vlan 3 //以上利用VTP在S1、S2、S3上创建vlan2、vlan3
四、配置三层交换机S1的路由功能下的vlan S1(config)#ip routing //打开三层交换机的路由功能 S1(config)#int vlan 2 S1(config-if)#ip add 192.168.2.1 255.255.255.0 S1(config-if)#no shut //启用vlan2 //以上为vlan2配置ip S1(config)#int vlan 3 S1(config-if)#ip add 192.168.3.1 255.255.255.0 S1(config-if)#no shut //启用vlan3 //以上为vlan3配置ip 五、配置S2、S3交换机的vlan接口 S2(config)#int f0/3 S2(config-if)#switchport access vlan 2 //端口f0/3划入vlan 2 S2(config)#int f0/4 S2(config-if)#switchport access vlan 3 //端口f0/4划入vlan 3 S3(config)#int f0/3 S3(config-if)#switchport access vlan 2 //端口f0/3划入vlan 2 S3(config)#int f0/4 S3(config-if)#switchport access vlan 3 //端口f0/4划入vlan3 六、主机配置 主机1、3分配192.168.2.0网段地址，网关为：192.168.2.1 主机2、4分配192.168.3.0网段地址，网关为：192.168.3.1 七、测试连通性 配置完成后，两个VLAN（VLAN2、VLAN3）就可以通过三层交换机进行通信了。 在分别属于不同VLAN的主机（1、2、3、4）之间使用ping命令测试VLAN间路由配置的正确性。能ping通即表示两个不同VLAN 之间实现通信。
BN市劳动保障 总集成及公共服务建设项目统一内部应用门户 用户操作手册 (V3.0)
目录 第一章系统介绍 (1) 1.1统一内部应用门户 (1) 1.2组织机构管理 (2) 1.3单点登录系统 (1) 第二章操作流程 (3) 2.1登陆流程 (3) 2.2个性化首页 (4) 2.3进入业务系统 (4) 第三章组织机构维护 (6) 3.1进入组织机构管理 (6) 3.2维护行政区划管理 (7) 3.3维护组织单元类型 (8) 3.4维护组织单元管理 (9) 3.5维护岗位管理 (13) 3.6维护用户管理 (15) 第四章配置管理 (18) 4.1系统管理 (18) 4.2菜单管理 (20) 4.3资源管理 (21) 第五章安全管理 (22) 5.1用户注册管理 (22) 5.2用户组织关系变更查询 (23) 5.3统一审计管理 (23) 5.4组织单元变更日志 (24) 5.5CA绑定管理 (24) 5.6访问策略管理 (25) 5.7用户信息查看 (26)
5.8在线用户查看 (27) 5.9帐号状态管理 (27) 5.10组织角色授权 (28) 5.11安全管理角色 (29) 5.12业务角色管理 (31) 5.13用户密码修改 (32) 第六章公共服务 (33) 6.1网站管理 (33) 6.1.1新建网站 (33) 6.1.2设为缺省网站 (35) 6.1.3更改网站名称 (36) 6.1.4委派网站管理员 (36) 6.1.5设定网站可访问人群 (38) 6.1.6网站导入 (39) 6.1.7网站导出 (41) 6.1.8网站删除 (42) 6.2页面管理 (42) 6.2.1新建页面 (43) 6.2.2创建链接 (44) 6.2.3编辑页面 (46) 6.2.4删除页面 (47) 6.2.5复制页面 (47) 6.2.6向上移动页面 (48) 6.2.7向下移动页面 (50) 6.2.8移动页面到 (51) 6.2.9配置模板 (51) 6.2.10手工编辑 (52) 6.2.11页面属性编辑（通用） (53) 6.3模板管理 (62) 6.3.1添加模板 (62)
信息门户使用指南 上海建桥学院信息门户为全校师生提供各种应用系统、数据资源和互联网资源的访问和查询,根据每个用户使用特点和角色的不同,形成个性化的应用界面，并通过对事件、消息的处理和传输把用户有机地联系在一起。 一、访问路径: 打开IE,输入 https://www.doczj.com/doc/9c16626029.html, 二、用户名、密码及登录方式： 1）本系统采用学校“统一身份认证系统”进行个人身份认证，用户名为您的职工号或是学号（本专科生、专升本）。 2）“统一身份认证”的密码为：如您未修改过密码，则初始密码规则为：身份证号码，取其最后六位作为初始密码。 3）登录成功后，进入“初始化个人资料”界面，初次登录需填写必要信息，（*为必填项目）。 三、信息门户“首页”介绍 此页面为系统登录成功后的“首页”。 1)个人信息 显示与个人相关的信息内容，可在“个人设置”中修改相关信息。 2)系统导航 点击导航图片可直接进入系统。 3)待办提醒 提示当前用户系统内站内信、工作区通知、邀请提
示、工作区讨论、图书借阅和校园一卡通余额情况。 4)待办事宜 该页面显示与当前用户相关的业务系统待办事项。5）我的日程 为用户进行日程的安排和管理，用户可以点击日历上的日期后添加事件。 6）图书借阅 整合图书管理系统中的当前借阅图书名、借阅日期以及应还日期等信息。 7）教师课表 与教务系统同步抽取，显示本学期的课程安排。8）内部公开信息 整合信息公开网站中的对校内员工公开的信息。9）建桥新闻 整合新闻网的建桥要文。 四、“个人主页”介绍 点击“个人主页”，页面会自动显示个人主页相关页面。 五、“综合应用”介绍 综合应用主要针对日常工作中所需要的应用，如我的日程，主要让用户维护自己的日程表；工作区主要让用户进行群组讨论、分享信息等；我的考勤记录主要让用户查看考勤信息。 例如“我的日程”操作
档案管理系统使用 说明
档案管理系统使用说明 系统运行环境： 显示器分分辨率在1024x768以上； windows 9x；windows xp；windows ；建议使用windows xp 效果最好。 excel.97及以上版本；word.97以上版本；建议使用word 及excel 系统使用： 只需将档案管理系统直接复制到硬盘上D盘根目录下（不能在其它位置，若在其它位置将出错）即可使用 特别注意：不能更改档案管理系统内任何文件夹内的文件结构，任何表格只能增减、修改记录。 一、系统登录： 打开D:\文书档案管理系统，将快捷图标复制到桌面上，双击打开。 初始用户名：123；密码：123
首次使用，将提示软件尚未注册，点击“是”打开注册界面，出现下图界面时请电话联系索取注册码。 二、系统使用方法： 注册成功后，再次登录出现如图主界面：
本系统可录入文书档案、教学档案、科技档案、声像档案、会计档案几类档案，请参照相关说明操作。 其中文书档案、教学档案、科技档案、声像档案操作方法完全相同，现以文书档案为例进行操作方法介绍。 点击“文书档案”按钮，出现以下界面： 文书档案分为文书档案收文簿、文书档案整理、文书档案归
档案、文书档案管理四个模块。完整规范的收集档案应按这四个模块的顺序进行，但也可直接在“文书档案管”理块中直接录入档案目录。 （一）文书档案收文簿 1.新增 点击“新增”按钮后在左边的输入框内输入相应内容 自动增加一条新记录并自动保存。 注意： （1）收文号与年度自动生成，一般不需改动。但年度发生变化时，请改动。 （2）收文月与收文日自动与上次输入的内容一致（避免同一天收文时重复输入收文月与收文日），若收文月与收文日与当前日期不一致，请修改。
知识库门户操作说明2016年10月
1 知识库专题门户 1.1功能描述 HSE信息系统知识库专题门户，用户可以通过本门户方便快捷查询自己的工作待办和工作提醒，查看企业通知公告。同时，能将共享知识进行发布、收藏、查询和订阅，并且能进行知识问答提问和回答。
1.2 操作角色 系统各级用户。二级单位和基层单位用户登录系统后默认显示知识库专题门户，企业及以上权限用户可以点击左侧信息共享-》知识库专题门户进入。 1.3 操作说明 1、工作提醒、工作待办 点击工作提醒-》提醒信息列和工作待办-》任务列蓝色链接，可以到HSE信息系统相应的提醒页面。 工作提醒与系统右上角红色字体“工作提醒”显示内容一致，来源于运维中心已编制提醒指标的模块，目前包括亡人事故等。 工作待办与系统左侧菜单“待办事项”显示内容一致，来源于环境统计报表管理、应急管理等模块需待办的事项。 2、企业通知公告 点击企业通知公告栏目标题名称可以查看本企业发布的通知公告。 通知公告可查看本企业发布的通知。企业通知由企业相关人员发布，通知公告发布菜单为：HSE信息系统-》综合管理-》管理维护-》企业基础配置-》通知公告管理。 3、我的知识库 我的知识库默认显示系统自定义的6个知识内容，点击订阅可以任意选择需要订阅的知识（最多6个栏目，最少3个栏目），点击确认即可。 点击“我的上传文件”后的个数和“我的收藏文件”后的个数，可以跳转到知识库页面查看我上传和我收藏的文件。
点击“文件上传”按钮，调转到知识库页面“我的主页”，点击“上传文件”，即可以共享文档。 （1）点击文件上传； （2）点击上传文件； （3）选择需要上传的文件，选择共享级别，优先级，选择知识分类，选择无误后激活“上传文件”按钮，点击上传。共享级别如果选择集团级和专业公司级，上传的文档需要进行两级审批（首先由企业级审批，然后由运维中心审批）；共享级别如果选择企业级，只需进行一级审批（企业级审批）。配置审批权限的用户（审批权限统一由运维中心配置）可在任务-》我的待办任务里进行审批，审批通过后的文件即可发布。 ①上传文件