Hi Jochen:
We call these "reduced grids" or "thin grids", their use is technically
independent of whether its a gaussian lat/lon (just means the lats are
spaced with a gaussian), although in practice they often go together
(perhaps always in the model - im just talking about the output files).
We probably stole the cubic spline code from GEMPAK/nawips which made
us think it was a reassonable thing to do.
IFAIU, cubic splines allow the interpolated numbers to be outside the
range of existing ones, so at this point i dont suspect an error.
You are right that we could use the actual min, max of the numbers to
clip the cubic spline results.
Not sure what the right thing to do here is. we could clip it based on
actual min/max (easy). We could try to make an option to allow linear
interpolation, which would prevent the interpolated numbers from
exceeding the min/max of existing numbers (harder). We could try to
allow user access to the original numbers (harder, need lower level
API). We could construct a quantity X conserving algorithm, which reads
the users' mind as to what X should be (requires faster than light
technology).
What does wgrib do?
Suggestions from anyone are welcome.
John
On 11/15/2013 6:04 AM, Jochen Kähler wrote:
Hi all,
we’re implementing some service that reads ECMWF 0.125° Grib files in
gaussian grid. The NetCDF-Library automatically interpolates the
gaussian grid to a regular lat/lon-grid. For the relative humidity we
found some strange values in output after that interpolation.
Using wgrib I’ve extracted some isobaric relative humidity record to a
single grib file called „dpd_test.grib“ (which i could send as well if
needed). According to wgrib, it is an gaussian grid and min and max
values are 0% and 100% - as I would expect them for a relative humidity
(see attached output).
Next I’ve written a small program which extracts that relative humidity
parameter via netcdf-java-lib and step thru all values to find minimum
and maximum in it. Source is also attached - just in case I did
something wrong there.
The output of that states the following...
2013-11-14 13:45:15,378 INFO : App -
dpd_test.grib/Relative_humidity_isobaric/850.0hPa:
min=-4.462653160095215 max=108.53846740722656
…indicating the minimum relative humidity is around -4.46% and the
maximum at 108.54%.
Browsing your code on Github I think you’re using cubic interpolation to
convert gaussian to regular grid, which might cause this problem.
https://github.com/Unidata/thredds/blob/6b1052455e597797f3a5980165a23292172920ce/grib/src/main/java/ucar/nc2/grib/QuasiRegular.java
Line
219 - 221:
outpt[oIdx] = (float) (a * inpt[iIdx + low] + b * inpt[iIdx + hi]
+ ((a * a * a - a) * y2d[low]
+ (b * b * b - b) * y2d[hi]) / 6.0);
Is the problem in the parametrization of this formula?
Is it possible to use Linear Interpolation here?
Kind Regards,
Jochen
— wgrib output ---------------
Losty-MacBook:Desktop jkaehler$ ~/wgrib/wgrib -V dpd_test.grib
rec 1:0:date 2013111300 R kpds5=157 kpds6=100 kpds7=850 levels=(3,82)
grid=255 850 mb 6hr fcst:
R=Relative humidity [%]
timerange 0 P1 6 P2 0 TimeU 1 nx -1 ny 800 GDS grid 4 num_in_ave 0
missing 0
center 98 subcenter 0 process 143 Table 128 scan: WE:NS winds(N/S)
thinned gaussian: lat 89.828000 to -89.828000
long 0.000000 to 359.900000, 843490 grid pts (-1 x 800)
scan 0 mode 0 bdsgrid 1
18 25 32 40 45 50 60 60 72 72 75 81 90
96 100
108 120 120 125 128 144 144 150 160 160 180 180 192
192 200
200 216 216 225 240 240 240 250 250 256 270 288 288
288 300
300 320 320 320 324 360 360 360 360 360 360 375 375
384 400
400 400 405 432 432 432 432 450 450 450 480 480 480
480 480
486 500 500 512 512 540 540 540 540 540 576 576 576
576 576
576 600 600 600 600 640 640 640 640 640 640 640 648
675 675
675 675 675 720 720 720 720 720 720 720 729 729 750
750 750
750 768 768 768 800 800 800 800 800 800 810 864 864
864 864
864 864 864 864 864 864 900 900 900 900 900 900 900
960 960
960 960 960 960 960 960 960 960 960 960 972 972 1000
1000 1000
1000 1000 1000 1024 1024 1024 1024 1024 1080 1080 1080 1080 1080
1080 1080
1080 1080 1080 1080 1125 1125 1125 1125 1125 1125 1125 1125 1125
1152 1152
1152 1152 1152 1152 1200 1200 1200 1200 1200 1200 1200 1200 1200
1200 1200
1215 1215 1215 1215 1280 1280 1280 1280 1280 1280 1280 1280 1280
1280 1280
1280 1280 1280 1280 1280 1296 1296 1296 1296 1350 1350 1350 1350
1350 1350
1350 1350 1350 1350 1350 1350 1350 1350 1350 1440 1440 1440 1440
1440 1440
1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440
1440 1440
1440 1440 1440 1440 1440 1440 1440 1458 1458 1458 1458 1458 1458
1458 1500
1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500
1500 1500
1500 1536 1536 1536 1536 1536 1536 1536 1536 1536 1536 1536 1536
1536 1536
1536 1536 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600
1600 1600
1600 1600 1600 1536 1536 1536 1536 1536 1536 1536 1536 1536 1536
1536 1536
1536 1536 1536 1536 1500 1500 1500 1500 1500 1500 1500 1500 1500
1500 1500
1500 1500 1500 1500 1500 1500 1458 1458 1458 1458 1458 1458 1458
1440 1440
1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440
1440 1440
1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1350 1350
1350 1350
1350 1350 1350 1350 1350 1350 1350 1350 1350 1350 1350 1296 1296
1296 1296
1280 1280 1280 1280 1280 1280 1280 1280 1280 1280 1280 1280 1280
1280 1280
1280 1215 1215 1215 1215 1200 1200 1200 1200 1200 1200 1200 1200
1200 1200
1200 1152 1152 1152 1152 1152 1152 1125 1125 1125 1125 1125 1125
1125 1125
1125 1080 1080 1080 1080 1080 1080 1080 1080 1080 1080 1080 1024
1024 1024
1024 1024 1000 1000 1000 1000 1000 1000 972 972 960 960 960
960 960
960 960 960 960 960 960 960 900 900 900 900 900 900
900 864
864 864 864 864 864 864 864 864 864 810 800 800 800
800 800
800 768 768 768 750 750 750 750 729 729 720 720 720
720 720
720 720 675 675 675 675 675 648 640 640 640 640 640
640 640
600 600 600 600 576 576 576 576 576 576 540 540 540
540 540
512 512 500 500 486 480 480 480 480 480 450 450 450
432 432
432 432 405 400 400 400 384 375 375 360 360 360 360
360 360
324 320 320 320 300 300 288 288 288 270 256 250 250
240 240
240 225 216 216 200 200 192 192 180 180 160 160 150
144 144
128 125 120 120 108 100 96 90 81 75 72 72 60
60 50
45 40 32 25 18
min/max data 0 100 num bits 8 BDS_Ref 0 DecScale 0 BinScale -1
——
— Java-Source ——
GridDataset dataset = GridDataset.open(gribFile.getAbsolutePath());
try {
GridDatatype grid = dataset.findGridDatatype("Relative_humidity_isobaric");
if(grid != null) {
CoordinateAxis1D isbl = grid.getCoordinateSystem().getVerticalAxis();
double[] isblValues = isbl.getCoordValues();
for (int isblIdx = 0; isblIdx < isblValues.length; isblIdx++) {
double[] data = (double[]) grid.readDataSlice(0, isblIdx, -1,
-1).get1DJavaArray(double.class);
double min = Double.MAX_VALUE;
double max = Double.MIN_VALUE;
for (double d : data) {
min = Math.min(min, d);
max = Math.max(max, d);
}
LOG.info("{}/{}/{}{}: min={} max={}", gribFile.getName(),
grid.getFullName(), isblValues[isblIdx], isbl.getUnitsString(), min, max);
}
}
} finally {
if (dataset != null) {
dataset.close();
}
}
--------
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