<div dir="ltr"><div>In my opinion, the source nc files are not well constructed. <br>---<br>NCL variables are data-structures. They contain the values and meta data: (a) long_name, (b) units; and (c) coordinate variables such as time, level/depth, lat/lon (rectilinear grids).<br><br>The 'coordinate variables' associated with each variable are assumed to follow the NUG netCDF rules:<br><br></div><div>(1) variable name and dimension name are the same; <br>(2) numeric; <br>(3) one-dimensional; <br>(4) monotonically increasing or decreasing<br></div><div><br>An issue:<br></div><div><br>Variable: u_wv</div><div>Dimensions and sizes: [initial_time0_hours | 648] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25] <==== GOOD monotonically decreasing<br></div><div> g0_lon_2: [250..30] <==== BAD for lon 'coordinate' variable<br><br></div><div> This is going: 250, ...,358.75?, 0, 1.25 ,....) *not* monotonically increasing<br></div><div><br>=====<br><br>One fix:<br><br> g0_lon_2 = a->g0_lon_2<br></div><div> g0_lon_2 = where(g0_lon_2.gt.180, g0_lon_2-360, g0_lon_2)<br></div><div> g0_lon_2&g0_lon_2 = g0_lon_2</div><div> printVarSummary(g0_lon_2)<br></div><div> <br><br></div> u_wv = a->UWV_GDS0_EATM_S123(1:648,:,<wbr>:) <br><div><div>Variable: u_wv</div><div>Type: float</div><div>Total Size: 15523488 bytes</div><div> 3880872 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 648] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]<br><br>===<br> u_wv&g0_lon_2 = g0_lon_2 ; replace with 'correct' ordering<br></div><br><div>Variable: u_wv</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [-110..30] ,=== monotonically increasing<br><br>Same for v_wv<br><br> v_wv&g0_lon_2 = g0_lon_2 <br><br>===<br></div><div>Any other variables also.<br><br></div><div>Good luck<br></div><div><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Mar 7, 2017 at 1:33 PM, MIRA BERDAHL <span dir="ltr"><<a href="mailto:mlosic@scarletmail.rutgers.edu" target="_blank">mlosic@scarletmail.rutgers.ed<wbr>u</a>></span> wrote:<br><blockquote style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex" class="gmail_quote"><div dir="ltr">Hi Mary,<div>Yes that is right, I have changed the script to use gsn_csm_vector_map and there is a map displayed now. Thank you! Trouble is, the longitude is still wrong, so it is plotting my subregion in the wrong place. The latitudes look good, but the range of longitudes should be -110/30 (or 250/30). I've attached my new plots so you can see where it is plotting them. </div><div>Any thoughts on why this would be shifted like this?</div><div>Thanks for any ideas,<br></div><div>Mira</div><div><br></div><div>I've copied my script and variable information below again:</div><div><br></div><div><br></div><div><br></div><div><div><div class="m_3459859790903531680gmail-m_6794290299911594193h5"><div><br></div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/gsn_code.ncl" </div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/gsn_csm.ncl" </div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/contributed.ncl" </div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/shea_util.ncl" </div><div>;*****************************<wbr>******************* </div><div>begin </div><div>;*****************************<wbr>******************* </div><div>; read in netCDF files</div><div>;*****************************<wbr>******************* </div><div>a = addfile("<a href="http://Uwv.mon.mean.nc" target="_blank">Uwv.mon.mean.nc</a>","r") ; u moisture transport</div><div>b = addfile("<a href="http://Vwv.mon.mean.nc" target="_blank">Vwv.mon.mean.nc</a>","r") ; v moisture transport</div><div><br></div><div>;*****************************<wbr>******************* </div><div>; read in zonal [u] and meridional [v] moisture transport (water vapor)</div><div>;*****************************<wbr>******************* </div><div><br></div><div>u_wv = a->UWV_GDS0_EATM_S123(1:648,:,<wbr>:) </div><div>v_wv = b->VWV_GDS0_EATM_S123(1:648,:,<wbr>:) ; </div><div><br></div><div>lat = a->g0_lat_1</div><div>lon = a->g0_lon_2</div><div><br></div><div>printVarSummary(lat)</div><div>printVarSummary(lon)</div><div><br></div><div>printVarSummary(u_wv)</div><div>printVarSummary(v_wv)</div><div><br></div><div><br></div><div>; Calculate the seasonal averages.</div><div>uwvDJF = month_to_season(u_wv, "DJF")</div><div>vwvDJF = month_to_season(v_wv, "DJF")</div><div><br></div><div><br></div><div>printVarSummary(uwvDJF)</div><div>printVarSummary(vwvDJF)</div><div><br></div><div><br></div><div>; from the matlab script i wrote: findExtremeYrs, i pulled out the extreme years (> or < 1std) that i want to average and plot here.</div><div><br></div><div><br></div><div>;ans = 7 (longitude of IL)</div><div>;We find the years where the Icelandic low is in an “extreme east” (high Long) position to be: 1966, 1968, 1969, 1974, 1983, 1984, 1994, 1995, 1999 and 2005. <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span></div><div>;The years with “extreme west” (low long) position of the Icelandic Low are: 1963, 1964, 1980, 1985, 1987, 1991, 1992, 1996, 2003 and 2006. <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span></div><div><br></div><div><br></div><div>; this data starts at 1958 (this is index 0), so 1963=5, 1973=15 etc.</div><div><br></div><div><br></div><div>uDJF_lon_hi = uwvDJF((/8,10,11,16,25,26,36,3<wbr>7,41,47/),:,:)</div><div>uDJF_lon_lo = uwvDJF((/5,6,22,27,29,33,34,38<wbr>,45,48/),:,:)</div><div><br></div><div>vDJF_lon_hi = vwvDJF((/8,10,11,16,25,26,36,3<wbr>7,41,47/),:,:)</div><div>vDJF_lon_lo = vwvDJF((/5,6,22,27,29,33,34,38<wbr>,45,48/),:,:)</div><div><br></div><div>uAvgTime_hi = dim_avg_n_Wrap(uDJF_lon_hi,0)</div><div>uAvgTime_lo = dim_avg_n_Wrap(uDJF_lon_lo,0)</div><div><br></div><div>printVarSummary(uAvgTime_hi)</div><div>printVarSummary(uAvgTime_lo)</div><div><br></div><div>vAvgTime_hi = dim_avg_n_Wrap(vDJF_lon_hi,0)</div><div>vAvgTime_lo = dim_avg_n_Wrap(vDJF_lon_lo,0)</div><div><br></div><div>printVarSummary(vAvgTime_hi)</div><div>printVarSummary(vAvgTime_lo)</div><div><br></div><div><br></div><div>; sneaky way to copy metadata over first.</div><div>diff_u = uAvgTime_hi;</div><div>diff_v = vAvgTime_hi;</div><div><br></div><div>diff_u = uAvgTime_lo - uAvgTime_hi</div><div>diff_v = vAvgTime_lo - vAvgTime_hi</div><div><br></div><div>printVarSummary(diff_u)</div><div>printVarSummary(diff_v)</div><div><br></div><div>;*****************************<wbr>******************* </div><div>; create plot </div><div>;*****************************<wbr>******************* </div><div>wks = gsn_open_wks("ps","Panel_lon_W<wbr>V") <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; open a ps file </div><div>gsn_define_colormap(wks,"temp1<wbr>")</div><div><br></div><div>plot = new(3,graphic)<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; create a plot array</div><div><br></div><div>;---- set common resources for all plots</div><div>res <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>= True</div><div>res@gsnDraw<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>= False <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; dont draw</div><div>res@gsnFrame<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>= False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; dont advance frame</div><div>res@cnInfoLabelOn<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>= False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; trn off cn info label</div><div>res@gsnAddCyclic = False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; has to do with wrapping the lonitude at 0/360</div><div>res@cnFillPalette = "matlab_jet"</div><div><br></div><div><br></div><div>;*****************************<wbr>******************</div><div>; ----wind vector plot</div><div>;*****************************<wbr>******************</div><div>vcres = res</div><div>vcres@vcRefAnnoOrthogonalPosF = -1.0 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; move ref vector up </div><div>vcres@vcRefMagnitudeF = 10.0 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; define vector ref mag </div><div>vcres@vcRefLengthF = 0.045 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; define length of vec ref</div><div>vcres@vcGlyphStyle = "CurlyVector" <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; turn on curly vectors </div><div>vcres@vcMinDistanceF = 0.017 </div><div>vcres@mpFillOn = False <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; turn off gray fill </div><div>vcres@mpOutlineBoundarySets = "National" <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; turn on country boundaries</div><div>;vcres@mpFillBoundarySets = AllBoundaries</div><div>vcres@mpGeophysicalLineColor = "Navy" <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; color of cont. outlines</div><div>vcres@mpGeophysicalLineThickne<wbr>ssF = 1.5 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; thickness of outlines </div><div>vcres@gsnRightString = ""<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; turn off thue units string</div><div><br></div></div></div><div>plot(0) = gsn_csm_vector_map(wks,uAvgTim<wbr>e_hi,vAvgTime_hi,vcres)</div><div>plot(1) = gsn_csm_vector_map(wks,uAvgTim<wbr>e_lo,vAvgTime_lo,vcres)</div><div>plot(2) = gsn_csm_vector_map(wks, diff_u, diff_v,vcres)</div><div><div class="m_3459859790903531680gmail-m_6794290299911594193h5"><div><br></div><div>;*****************************<wbr>*******************</div><div>; create panel</div><div>;*****************************<wbr>*******************</div><div>resP = False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; modify the panel plot</div><div>resP@txString = "lon - water vapor transport"</div><div>gsn_panel(wks,(/plot/),(/3,1/)<wbr>,resP)<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465gmail-Apple-tab-span"> </span>; now draw as one plot;</div><div> </div><div><br></div><div>end </div></div></div></div><div><div class="m_3459859790903531680gmail-m_6794290299911594193h5"><div><br></div><div><br></div><div><br></div><div><div style="font-size:12.8px">******************************<wbr>******************************<wbr>*******************</div><div style="font-size:12.8px"><div>Variable: lat</div><div>Type: float</div><div>Total Size: 212 bytes</div><div> 53 values</div><div>Number of Dimensions: 1</div><div>Dimensions and sizes: [g0_lat_1 | 53]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div>Number Of Attributes: 9</div><div> La1 : 90</div><div> Lo1 : 0</div><div> La2 : -90</div><div> Lo2 : -1.25</div><div> Di : 1.25</div><div> Dj : 1.25</div><div> units : degrees_north</div><div> GridType : Cylindrical Equidistant Projection Grid</div><div> long_name : latitude</div><div><br></div><div>Variable: lon</div><div>Type: float</div><div>Total Size: 452 bytes</div><div> 113 values</div><div>Number of Dimensions: 1</div><div>Dimensions and sizes: [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 9</div><div> La1 : 90</div><div> Lo1 : 0</div><div> La2 : -90</div><div> Lo2 : -1.25</div><div> Di : 1.25</div><div> Dj : 1.25</div><div> units : degrees_east</div><div> GridType : Cylindrical Equidistant Projection Grid</div><div> long_name : longitude</div><div><br></div><div>Variable: u_wv</div><div>Type: float</div><div>Total Size: 15523488 bytes</div><div> 3880872 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 648] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 15</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 157</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : kg/m/s</div><div> long_name : Zonal water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div><br></div><div>Variable: v_wv</div><div>Type: float</div><div>Total Size: 15523488 bytes</div><div> 3880872 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 648] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 15</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 152</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : Kg/m/s</div><div> long_name : Meridional water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div><br></div><div>Variable: uwvDJF</div><div>Type: float</div><div>Total Size: 1293624 bytes</div><div> 323406 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 54] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1850328]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 16</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 157</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : kg/m/s</div><div> long_name : DJF: Zonal water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div><div><br></div><div>Variable: vwvDJF</div><div>Type: float</div><div>Total Size: 1293624 bytes</div><div> 323406 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 54] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1850328]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 16</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 152</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : Kg/m/s</div><div> long_name : DJF: Meridional water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div><div><br></div><div>Variable: uAvgTime_hi</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Zonal water vapour flux</div><div> units : kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 157</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: uAvgTime_lo</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Zonal water vapour flux</div><div> units : kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 157</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: vAvgTime_hi</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Meridional water vapour flux</div><div> units : Kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 152</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: vAvgTime_lo</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Meridional water vapour flux</div><div> units : Kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 152</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: diff_u</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 157</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : kg/m/s</div><div> long_name : DJF: Zonal water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div><div><br></div><div>Variable: diff_v</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 152</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : Kg/m/s</div><div> long_name : DJF: Meridional water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div></div></div><div><br></div><div><br></div></div></div></div><div class="m_3459859790903531680gmail-m_6794290299911594193HOEnZb"><div class="m_3459859790903531680gmail-m_6794290299911594193h5"><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Mar 7, 2017 at 8:16 AM, Mary Haley <span dir="ltr"><<a href="mailto:haley@ucar.edu" target="_blank">haley@ucar.edu</a>></span> wrote:<br><blockquote style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex" class="gmail_quote"><div dir="ltr"><div style="font-size:small">Mira,</div><div style="font-size:small"><br></div><div style="font-size:small">In order to generate vectors over a map, you need to call gsn_csm_vector_map, and not gsn_csm_vector map.</div><div style="font-size:small"><br></div><div style="font-size:small">I think that's the only change you need to make to your script.</div><div style="font-size:small"><br></div><div style="font-size:small">--Mary</div><div style="font-size:small"><br></div></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465h5">On Mon, Mar 6, 2017 at 8:18 PM, MIRA BERDAHL <span dir="ltr"><<a href="mailto:mlosic@scarletmail.rutgers.edu" target="_blank">mlosic@scarletmail.rutgers.ed<wbr>u</a>></span> wrote:<br></div></div><blockquote style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex" class="gmail_quote"><div><div class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465h5"><div dir="ltr">Hi,<div><div>I'm trying to plot moisture transport from JRA55 output. I can generate figures, where the latitude looks correct, but my longitude is not correctly labelled. Also, there is no map generated, just the vector field. </div><div>Can anyone see what the problem is with my code? I also get the following error:</div><div><div>warning:VectorFieldSetValues: irregular coordinate array vfXArray non-monotonic: defaulting vfXArray</div></div><div>I've copied my code and the variable information below. I've attached the figure I can generate. <br></div><div>Thank you in advance, </div><div>Mira</div><div><br></div><div>******************************<wbr>******************************<wbr>******************</div><div><div><br></div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/gsn_code.ncl" </div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/gsn_csm.ncl" </div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/contributed.ncl" </div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/shea_util.ncl" </div><div>;*****************************<wbr>******************* </div><div>begin </div><div>;*****************************<wbr>******************* </div><div>; read in netCDF files</div><div>;*****************************<wbr>******************* </div><div>a = addfile("<a href="http://Uwv.mon.mean.nc" target="_blank">Uwv.mon.mean.nc</a>","r") ; u moisture transport</div><div>b = addfile("<a href="http://Vwv.mon.mean.nc" target="_blank">Vwv.mon.mean.nc</a>","r") ; v moisture transport</div><div><br></div><div>;*****************************<wbr>******************* </div><div>; read in zonal [u] and meridional [v] moisture transport (water vapor)</div><div>;*****************************<wbr>******************* </div><div><br></div><div>u_wv = a->UWV_GDS0_EATM_S123(1:648,:,<wbr>:) </div><div>v_wv = b->VWV_GDS0_EATM_S123(1:648,:,<wbr>:) ; </div><div><br></div><div>lat = a->g0_lat_1</div><div>lon = a->g0_lon_2</div><div><br></div><div>printVarSummary(lat)</div><div>printVarSummary(lon)</div><div><br></div><div>printVarSummary(u_wv)</div><div>printVarSummary(v_wv)</div><div><br></div><div><br></div><div>; Calculate the seasonal averages.</div><div>uwvDJF = month_to_season(u_wv, "DJF")</div><div>vwvDJF = month_to_season(v_wv, "DJF")</div><div><br></div><div><br></div><div>printVarSummary(uwvDJF)</div><div>printVarSummary(vwvDJF)</div><div><br></div><div><br></div><div>; from the matlab script i wrote: findExtremeYrs, i pulled out the extreme years (> or < 1std) that i want to average and plot here.</div><div><br></div><div><br></div><div>;ans = 7 (longitude of IL)</div><div>;We find the years where the Icelandic low is in an “extreme east” (high Long) position to be: 1966, 1968, 1969, 1974, 1983, 1984, 1994, 1995, 1999 and 2005. <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span></div><div>;The years with “extreme west” (low long) position of the Icelandic Low are: 1963, 1964, 1980, 1985, 1987, 1991, 1992, 1996, 2003 and 2006. <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span></div><div><br></div><div><br></div><div>; this data starts at 1958 (this is index 0), so 1963=5, 1973=15 etc.</div><div><br></div><div><br></div><div>uDJF_lon_hi = uwvDJF((/8,10,11,16,25,26,36,3<wbr>7,41,47/),:,:)</div><div>uDJF_lon_lo = uwvDJF((/5,6,22,27,29,33,34,38<wbr>,45,48/),:,:)</div><div><br></div><div>vDJF_lon_hi = vwvDJF((/8,10,11,16,25,26,36,3<wbr>7,41,47/),:,:)</div><div>vDJF_lon_lo = vwvDJF((/5,6,22,27,29,33,34,38<wbr>,45,48/),:,:)</div><div><br></div><div>uAvgTime_hi = dim_avg_n_Wrap(uDJF_lon_hi,0)</div><div>uAvgTime_lo = dim_avg_n_Wrap(uDJF_lon_lo,0)</div><div><br></div><div>printVarSummary(uAvgTime_hi)</div><div>printVarSummary(uAvgTime_lo)</div><div><br></div><div>vAvgTime_hi = dim_avg_n_Wrap(vDJF_lon_hi,0)</div><div>vAvgTime_lo = dim_avg_n_Wrap(vDJF_lon_lo,0)</div><div><br></div><div>printVarSummary(vAvgTime_hi)</div><div>printVarSummary(vAvgTime_lo)</div><div><br></div><div><br></div><div>; sneaky way to copy metadata over first.</div><div>diff_u = uAvgTime_hi;</div><div>diff_v = vAvgTime_hi;</div><div><br></div><div>diff_u = uAvgTime_lo - uAvgTime_hi</div><div>diff_v = vAvgTime_lo - vAvgTime_hi</div><div><br></div><div>printVarSummary(diff_u)</div><div>printVarSummary(diff_v)</div><div><br></div><div>;*****************************<wbr>******************* </div><div>; create plot </div><div>;*****************************<wbr>******************* </div><div>wks = gsn_open_wks("ps","Panel_lon_W<wbr>V") <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; open a ps file </div><div>gsn_define_colormap(wks,"temp1<wbr>")</div><div><br></div><div>plot = new(3,graphic)<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; create a plot array</div><div><br></div><div>;---- set common resources for all plots</div><div>res <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>= True</div><div>res@gsnDraw<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>= False <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; dont draw</div><div>res@gsnFrame<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>= False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; dont advance frame</div><div>res@cnInfoLabelOn<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>= False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; trn off cn info label</div><div>res@gsnAddCyclic = False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; has to do with wrapping the lonitude at 0/360</div><div>res@cnFillPalette = "matlab_jet"</div><div><br></div><div>;*****************************<wbr>******************</div><div>; ----wind vector plot</div><div>;*****************************<wbr>******************</div><div>vcres = res</div><div>vcres@vcRefAnnoOrthogonalPosF = -1.0 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; move ref vector up </div><div>vcres@vcRefMagnitudeF = 10.0 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; define vector ref mag </div><div>vcres@vcRefLengthF = 0.045 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; define length of vec ref</div><div>vcres@vcGlyphStyle = "CurlyVector" <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; turn on curly vectors </div><div>vcres@vcMinDistanceF = 0.017 </div><div>vcres@mpFillOn = False <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; turn off gray fill </div><div>vcres@mpOutlineBoundarySets = "National" <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; turn on country boundaries</div><div>;vcres@mpFillBoundarySets = AllBoundaries</div><div>vcres@mpGeophysicalLineColor = "Navy" <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; color of cont. outlines</div><div>vcres@mpGeophysicalLineThickne<wbr>ssF = 1.5 <span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; thickness of outlines </div><div>vcres@gsnRightString = ""<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; turn off thue units string</div><div><br></div><div>plot(0) = gsn_csm_vector(wks,uAvgTime_hi<wbr>,vAvgTime_hi,vcres)</div><div>plot(1) = gsn_csm_vector(wks,uAvgTime_lo<wbr>,vAvgTime_lo,vcres)</div><div>plot(2) = gsn_csm_vector(wks, diff_u, diff_v,vcres)</div><div><br></div><div>;*****************************<wbr>*******************</div><div>; create panel</div><div>;*****************************<wbr>*******************</div><div>resP = False<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; modify the panel plot</div><div>resP@txString = "lon - water vapor transport"</div><div>gsn_panel(wks,(/plot/),(/3,1/)<wbr>,resP)<span style="white-space:pre-wrap" class="m_3459859790903531680gmail-m_6794290299911594193m_-6911064360985668465m_6113662726990215349m_-1118452362477704329gmail-Apple-tab-span"> </span>; now draw as one plot;</div><div> </div><div><br></div><div>end </div></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div>******************************<wbr>******************************<wbr>*******************</div><div><div>Variable: lat</div><div>Type: float</div><div>Total Size: 212 bytes</div><div> 53 values</div><div>Number of Dimensions: 1</div><div>Dimensions and sizes: [g0_lat_1 | 53]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div>Number Of Attributes: 9</div><div> La1 : 90</div><div> Lo1 : 0</div><div> La2 : -90</div><div> Lo2 : -1.25</div><div> Di : 1.25</div><div> Dj : 1.25</div><div> units : degrees_north</div><div> GridType : Cylindrical Equidistant Projection Grid</div><div> long_name : latitude</div><div><br></div><div>Variable: lon</div><div>Type: float</div><div>Total Size: 452 bytes</div><div> 113 values</div><div>Number of Dimensions: 1</div><div>Dimensions and sizes: [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 9</div><div> La1 : 90</div><div> Lo1 : 0</div><div> La2 : -90</div><div> Lo2 : -1.25</div><div> Di : 1.25</div><div> Dj : 1.25</div><div> units : degrees_east</div><div> GridType : Cylindrical Equidistant Projection Grid</div><div> long_name : longitude</div><div><br></div><div>Variable: u_wv</div><div>Type: float</div><div>Total Size: 15523488 bytes</div><div> 3880872 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 648] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 15</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 157</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : kg/m/s</div><div> long_name : Zonal water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div><br></div><div>Variable: v_wv</div><div>Type: float</div><div>Total Size: 15523488 bytes</div><div> 3880872 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 648] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1858344]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 15</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 152</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : Kg/m/s</div><div> long_name : Meridional water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div><br></div><div>Variable: uwvDJF</div><div>Type: float</div><div>Total Size: 1293624 bytes</div><div> 323406 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 54] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1850328]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 16</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 157</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : kg/m/s</div><div> long_name : DJF: Zonal water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div><div><br></div><div>Variable: vwvDJF</div><div>Type: float</div><div>Total Size: 1293624 bytes</div><div> 323406 values</div><div>Number of Dimensions: 3</div><div>Dimensions and sizes: [initial_time0_hours | 54] x [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> initial_time0_hours: [1385736..1850328]</div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 16</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 152</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : Kg/m/s</div><div> long_name : DJF: Meridional water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div><div><br></div><div>Variable: uAvgTime_hi</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Zonal water vapour flux</div><div> units : kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 157</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: uAvgTime_lo</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Zonal water vapour flux</div><div> units : kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 157</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: vAvgTime_hi</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Meridional water vapour flux</div><div> units : Kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 152</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: vAvgTime_lo</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> NMO : 0</div><div> sub_center : 241</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> long_name : DJF: Meridional water vapour flux</div><div> units : Kg/m/s</div><div> _FillValue : 1e+20</div><div> level_indicator : 200</div><div> gds_grid_type : 0</div><div> parameter_table_version : 200</div><div> parameter_number : 152</div><div> level : 0</div><div> forecast_time : 0</div><div> forecast_time_units : hours</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> N : <ARRAY of 12 elements></div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div><br></div><div>Variable: diff_u</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 157</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : kg/m/s</div><div> long_name : DJF: Zonal water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div><div><br></div><div>Variable: diff_v</div><div>Type: float</div><div>Total Size: 23956 bytes</div><div> 5989 values</div><div>Number of Dimensions: 2</div><div>Dimensions and sizes: [g0_lat_1 | 53] x [g0_lon_2 | 113]</div><div>Coordinates: </div><div> g0_lat_1: [90..25]</div><div> g0_lon_2: [250..30]</div><div>Number Of Attributes: 17</div><div> average_op_ncl : dim_avg_n over dimension(s): initial_time0_hours</div><div> N : <ARRAY of 12 elements></div><div> statistical_process_duration : instantaneous (beginning at reference time at intervals of 6 hours)</div><div> statistical_process_descriptor : average of N uninitialized analyses</div><div> forecast_time_units : hours</div><div> forecast_time : 0</div><div> level : 0</div><div> parameter_number : 152</div><div> parameter_table_version : 200</div><div> gds_grid_type : 0</div><div> level_indicator : 200</div><div> _FillValue : 1e+20</div><div> units : Kg/m/s</div><div> long_name : DJF: Meridional water vapour flux</div><div> center : Japanese Meteorological Agency - Tokyo (RSMC)</div><div> sub_center : 241</div><div> NMO : 0</div></div><div><br></div></div></div>
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