博文
USE R: netCDF格式的通量数据的读取
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通量（涡度相关）数据，是分析生态系统水碳过程的常用数据。在Fluxnet可以免费申请到全球公开的通量数据。这些通量数据的格式多数是NetCDF。NetCDF可以储存观测站点和各观测项的元数据，在时间序列数据的存储和传播中使用广泛。这里介绍一下R里面的一个命令，可以方便读取Fluxnet的NetCDF格式的通量数据。
这里用到的读取命令readFLUXNETNcdf来自Jannis v. Buttlar开发的ncdf.tools包。这里用的数据DalyUncleared_2017_L3nc，是澳洲通量网的DalyRiverUncleared站点2017年的Level 3数据。感谢Jason Beringer公开了这一数据。无需注册即可下载，网址：
数据中的各个变量的意义和单位在网址提供的Metadata中可以查到。
以下为读取通量数据的代码，供参考。
| # install.packages("RNetCDF") # install.packages("cli","pillar") # install.packages('ncdf.tools', 'ggplot2') # if not installed, install please library(ncdf.tools) library(ggplot2) setwd("your working directory") # rewriten as your working directory # read nc data DaU2017 <- readFLUXNETNcdf(##title<< read data from FLUXNET NetCDF file. path = getwd() ##<< character string: path to the input file(s) , sites = 'DalyUncleared_2017_L3' ##<< character string: ids of the sites to extract , pars = 'all' ##<< character string: names of the variables to extract , time.ends = c(as.POSIXlt('2017-01-01 00:00:00'), as.POSIXlt('2017-12-31 23:30:00')) ##<< POSIXct object: start and end date of the period to extract. , dim.borders = list(1)##<< list: indices for other dimensions ) dim(DaU2017) # 1 251 17520 1 rownames(DaU2017[1,,,1]) # check the names of the variables # it will show names of 251 variables. # For the meanings and units of the variables, check the meta file in ozflux website. tmp = data.frame(matrix(nrow = 17520, ncol = 251)) for (i in 1:251) {tmp[,i] = as.numeric(DaU2017[1,i,,1]) } names(tmp) <- rownames(DaU2017[1,,,1]) DaU_2017 <- tmp DaU_2017$DT <- seq(as.POSIXct("2017-01-01 00:00:00", format = "%Y-%m-%d %H:%M:%S"), length.out=17520, by ='30 mins') DaU_2017$DT <- as.Date(DaU_2017$DT) # OK! Timeseries of flux data have been input. rownames(DaU2017[1,,,1]) # view the names of variables # [1] "AGC_7500" "AGC_7500_QCFlag" "Ah" "Ah_7500_Av" # [5] "Ah_7500_Av_QCFlag" "Ah_7500_Sd" "Ah_7500_Sd_QCFlag" "Ah_HMP_21m" # [9] "Ah_HMP_21m_QCFlag" "Ah_HMP_2m" "Ah_HMP_2m_QCFlag" "Ah_QCFlag" # [13] "AhAh" "AhAh_QCFlag" "Cc" "Cc_7500_Av" # [17] "Cc_7500_Av_QCFlag" "Cc_7500_Sd" "Cc_7500_Sd_QCFlag" "Cc_QCFlag" # [21] "CcCc" "CcCc_QCFlag" "co2_wpl_Fe" "co2_wpl_Fe_QCFlag" # [25] "co2_wpl_Fh" "co2_wpl_Fh_QCFlag" "Cpd" "Cpd_QCFlag" # [29] "Cpm" "Cpm_QCFlag" "Cpw" "Cpw_QCFlag" # [33] "crs" "Cs" "Cs_QCFlag" "Day" # [37] "Day_QCFlag" "Ddd" "Ddd_QCFlag" "Diag_7500" # [41] "Diag_7500_QCFlag" "Diag_CSAT" "Diag_CSAT_QCFlag" "Diag_IRGA" # [45] "Diag_IRGA_QCFlag" "Diag_SONIC" "Diag_SONIC_QCFlag" "dTs" # [49] "dTs_QCFlag" "e" "e_QCFlag" "esat" # [53] "esat_QCFlag" "eta" "eta_QCFlag" "Fa" # [57] "Fa_QCFlag" "Fc" "Fc_PFP" "Fc_PFP_QCFlag" # [61] "Fc_QCFlag" "Fc_single" "Fc_single_QCFlag" "Fe" # [65] "Fe_PFP" "Fe_PFP_QCFlag" "Fe_QCFlag" "Fe_raw" # [69] "Fe_raw_QCFlag" "Fg" "Fg_8cma" "Fg_8cma_QCFlag" # [73] "Fg_8cmb" "Fg_8cmb_QCFlag" "Fg_Av" "Fg_Av_QCFlag" # [77] "Fg_QCFlag" "Fh" "Fh_PFP" "Fh_PFP_QCFlag" # [81] "Fh_QCFlag" "Fhv" "Fhv_QCFlag" "Fld" # [85] "Fld_QCFlag" "Flu" "Flu_QCFlag" "Fm" # [89] "Fm_PFP" "Fm_PFP_QCFlag" "Fm_QCFlag" "Fn" # [93] "Fn_KZ" "Fn_KZ_QCFlag" "Fn_NR" "Fn_NR_QCFlag" # [97] "Fn_QCFlag" "Fsd" "Fsd_QCFlag" "Fsd_syn" # [101] "Fsd_syn_QCFlag" "Fsu" "Fsu_QCFlag" "H2O" # [105] "H2O_QCFlag" "Hdh" "Hdh_QCFlag" "Hour" # [109] "Hour_QCFlag" "L" "L_QCFlag" "Lv" # [113] "Lv_QCFlag" "Minute" "Minute_QCFlag" "Month" # [117] "Month_QCFlag" "Precip" "Precip_QCFlag" "ps" # [121] "ps_QCFlag" "q" "q_QCFlag" "RH" # [125] "RH_QCFlag" "RhoCp" "RhoCp_QCFlag" "rhod" # [129] "rhod_QCFlag" "rhom" "rhom_QCFlag" "rhow" # [133] "rhow_QCFlag" "S" "S_QCFlag" "Second" # [137] "Second_QCFlag" "SHD" "SHD_QCFlag" "solar_altitude" # [141] "solar_altitude_QCFlag" "Sws" "Sws_50cm" "Sws_50cm_QCFlag" # [145] "Sws_5cm" "Sws_5cm_QCFlag" "Sws_QCFlag" "Ta" # [149] "Ta_CSAT" "Ta_CSAT_QCFlag" "Ta_HMP_21m" "Ta_HMP_21m_QCFlag" # [153] "Ta_HMP_2m" "Ta_HMP_2m_QCFlag" "Ta_QCFlag" "theta" # [157] "theta_QCFlag" "Tpanel" "Tpanel_QCFlag" "Ts" # [161] "Ts_8cma" "Ts_8cma_QCFlag" "Ts_QCFlag" "Tv_CSAT" # [165] "Tv_CSAT_QCFlag" "u" "u_QCFlag" "ustar" # [169] "ustar_PFP" "ustar_PFP_QCFlag" "ustar_QCFlag" "uu" # [173] "uu_QCFlag" "uv" "uv_QCFlag" "uw" # [177] "uw_QCFlag" "Ux" "Ux_QCFlag" "Ux_Sd" # [181] "Ux_Sd_QCFlag" "UxA" "UxA_QCFlag" "UxC" # [185] "UxC_QCFlag" "UxT" "UxT_QCFlag" "UxUx" # [189] "UxUx_QCFlag" "UxUy" "UxUy_QCFlag" "UxUz" # [193] "UxUz_QCFlag" "Uy" "Uy_QCFlag" "Uy_Sd" # [197] "Uy_Sd_QCFlag" "UyA" "UyA_QCFlag" "UyC" # [201] "UyC_QCFlag" "UyT" "UyT_QCFlag" "UyUy" # [205] "UyUy_QCFlag" "UyUz" "UyUz_QCFlag" "Uz" # [209] "Uz_QCFlag" "Uz_Sd" "Uz_Sd_QCFlag" "UzA" # [213] "UzA_QCFlag" "UzC" "UzC_QCFlag" "UzT" # [217] "UzT_QCFlag" "UzUz" "UzUz_QCFlag" "v" # [221] "v_QCFlag" "Vbat" "Vbat_QCFlag" "VPD" # [225] "VPD_QCFlag" "vv" "vv_QCFlag" "vw" # [229] "vw_QCFlag" "w" "w_QCFlag" "wA" # [233] "wA_QCFlag" "wC" "wC_QCFlag" "Wd" # [237] "Wd_CSAT" "Wd_CSAT_QCFlag" "Wd_QCFlag" "Ws" # [241] "Ws_CSAT" "Ws_CSAT_QCFlag" "Ws_QCFlag" "wT" # [245] "wT_QCFlag" "ww" "ww_QCFlag" "xlDateTime" # [249] "xlDateTime_QCFlag" "Year" "Year_QCFlag" |
这里读取的是未经过插值的L3通量数据，有缺值。如果要分析水碳通量的年月日变化特征，需要进行插值。
插值的方法可以参考，澳洲通量数据的处理方法简介：
http://ozewex.org/ozfluxqc-flux-data-processing-tool/
| 代码原文下载链接： |
https://blog.sciencenet.cn/blog-526092-1128042.html
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