def calc_thetaOnEPV_column(data,time,hCell,nLevels):
#Ertel PV is (wLocal+wEarth).grad(tracer)/rho
#local and absolute vorticity
vort = calc_lstsq_vort_column(data, time, hCell, nLevels) #vort[l,dirs]
for l in xrange(nLevels):
vort[l,2] += 2.*omeg_e #absolute with earth
#gradient of tracer
theta_xyz = calc_lstsqDeriv_column(data, time, hCell, 'theta', nLevels) #coeffs[l,dirs]
#form epv
rho = data.variables['rho'][time,hCell,:]
epv = np.empty(nLevels)
for l in xrange(nLevels):
epv[l] = np.dot(vort[l,:],theta_xyz[l,:])/rho[l]
#looks like sign depends on hemisphere, but actually going by north/south is baffling about the equator
epv = abs(epv*1e6)
'''
#going by hemisphere is tricky since I'm not sure what to assign and sign(0)=0
sgn = np.sign(data.variables['zCell'][hCell])
if (sgn==0.0):#python treats 0==0.0 as True as well
sgn=1 #I'm not really sure what to do at equator!!!
epv *= sgn*1e6
'''
(l,dl) = output_data.calcIndexOfValue(2.0,epv, nLevels) #index on 2PVU surface
#print "For hcell {0}, dynamic tropopause at verticalIndex {1},{2}\n".format(hCell,l,dl)
theta = data.variables['theta'][time,hCell,:]
val = output_data.calcValueOfIndex(l,dl,theta)
return val
def calc_height_theta_2PVU(data, t0):
# vertical height of sign(lat)*2PVU surface.
# return height of cell center in column using interpolation from top
pvuTrop = 2.0
nCells = len(data.dimensions["nCells"])
nLevels = len(data.dimensions["nVertLevels"])
epv = data.variables["ertel_pv"][t0, :, :]
latCell = data.variables["latCell"][:]
zgrid = data.variables["zgrid"][:, :]
theta = data.variables["theta"][t0, :, :]
# hColumn = np.empty(nLevels,dtype='float')
epv_ht = np.empty(nCells, dtype="float")
theta_trop = np.empty(nCells, dtype="float")
for i in xrange(nCells):
# calc ht of cell centers
# for k in xrange(nLevels):
# hColumn[k] = .5*(zgrid[i,k]+zgrid[i,k+1])
hColumn = 0.5 * (zgrid[i, 0:nLevels] + zgrid[i, 1 : nLevels + 1])
pvuVal = pvuTrop
if latCell[i] < 0:
pvuVal = -pvuTrop
# don't really trust top and bottom levels so don't count those for interpolation
# interpLevs = range(0,nLevels); nInterpLevs = len(interpLevs)
interpLevs = range(1, nLevels - 1)
nInterpLevs = len(interpLevs)
(l, dl) = output_data.calcIndexOfValue(pvuVal, epv[i, interpLevs], nInterpLevs)
# (l,dl) = output_data.calcIndexOfValue_fromBottom(pvuVal,epv[i,interpLevs], nInterpLevs)
# (l,dl) = output_data.calcIndexOfValue(pvuTrop,np.abs(epv[i,interpLevs]), nInterpLevs)
# print "Cell {0} has l,dl = {1},{2}".format(i, l, dl)
epv_ht[i] = output_data.calcValueOfIndex(l, dl, hColumn[interpLevs])
theta_trop[i] = output_data.calcValueOfIndex(l, dl, theta[i, interpLevs])
return (epv_ht, theta_trop)
def derivedSfcs(ncfname, vtkfname):
#write some derived surfaces to file
data = output_data.open_netcdf_data(ncfname)
#header info
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
nLevels = len(data.dimensions['nVertLevels'])
#cell data
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
#geo for reference
output_data.write_vtk_staticGeoFields(f,data,nCells)
time = 0
#500 mb
output_data.write_vtk_pressureHeights(fvtk, data, nCells, time, vLevels, 50000.)
#theta on dynamic tropopause
pv = np.empty((nCells,nLevels), dtype=float)
for hcell in range(nCells):
for l in range(nLevels):
pv[hcell,l] = vars.calc_ertelPV(data, 'theta', time, hcell, l, nLevels)
#
pvuVal = 2.
thetaVal = np.empty(nCells)
for hcell in range(nCells):
(l,dl) = output_data.calcIndexOfValue(pvuVal,pv[hcell,:], nLevels)
thetaVal[hcell] = output_data.calcValueOfIndex(l,dl,data.variables['theta'][time,hcell,:])
output_data.write_levelData_float('theta_pv', fvtk, thetaVal, nCells)
#slp
slp = np.empty(nCells)
for hcell in range(nCells):
slp[hcell] = vars.calc_slp(data, hcell, nLevels, time)
output_data.write_levelData_float('slp', fvtk, slp, nCells)
#close da files
fvtk.close()
data.close()
def compare_mpas_pHgts():
f = '/arctic1/nick/cases/vduda/x4/x4.t.output.2006-08-01_00.00.00.nc'
data = netCDF4.Dataset(f,'r')
nLevels = len(data.dimensions['nVertLevels'])
nCells = len(data.dimensions['nCells'])
iTime = 0
hgt_mpas = data.variables['height_500hPa'][iTime,:]
zgrid = data.variables['zgrid'][:]
zMid = .5*(zgrid[:,0:-1]+zgrid[:,1:])
p = data.variables['pressure_p'][iTime,:,:]+data.variables['pressure_base'][iTime,:,:]
hgt_calc = np.empty(nCells,dtype=float)
pLev = 50000.
for iCell in xrange(nCells):
(l,dl) = output_data.calcIndexOfValue(pLev, p[iCell,:], nLevels)
z = output_data.calcValueOfIndex(l,dl,zMid[iCell,:])
hgt_calc[iCell] = z
diff = hgt_calc-hgt_mpas
return diff
def driver_arctic():
#plot epv on a polar cap
ncfname = '/arctic1/nick/cases/163842/testDuda/x1.163842.output.2006-07-15_00.00.00.nc'
#ncfname = '/arctic1/mduda/60km/x1.163842.output.2006-07-08_00.00.00.nc'
#ncfname = '/home/nickszap/research/mpas/output.2010-10-23_00:00:00.nc'
data = netCDF4.Dataset(ncfname,'r')
nCellsTotal = len(data.dimensions['nCells'])
nVerticesTotal = len(data.dimensions['nVertices']);
nLevels = len(data.dimensions['nVertLevels'])
nEdgesOnCell = data.variables['nEdgesOnCell'][:];
cellsOnCell = data.variables['cellsOnCell'][:]-1;
latThresh = 45.*np.pi/180.
#latThresh = 70.*np.pi/180.
latCell = data.variables['latCell'][:]
cells = conn.gatherArcticCells(latCell, nCellsTotal, latThresh)
nCells = len(cells)
#open the output vtk file and write header.
vtkfname = 'test.arctic.pv_approx.vtk'
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
#write nodes and cells
output_data.write_vtk_polyHorizConn_domain(data, fvtk, cells, nEdgesOnCell,nVerticesTotal)
#cell values and connectivity for this domain
haloCells = conn.get_arcticHalo(cells, latCell, latThresh, cellsOnCell, nEdgesOnCell)
g2lCell = conn.make_global2localMap(cells, haloCells, nCellsTotal)
c2c = conn.make_localDomainNbrs(nCells, cellsOnCell[cells,:], nEdgesOnCell[cells], g2lCell)
neededCells = cells.tolist(); neededCells.extend(haloCells) #has to be domain then halo (as in g2l map)
#I'm having memory errors.
#gc.collect()
#load data for domain and halo -----------------------------
timeInd = 0
print "Loading data for domain {0} with {1} cells\n".format('arctic', len(neededCells))
#print neededCells
state = loadFields(data, timeInd, neededCells, nLevels)
#compute derived variables -------------------------------
#theta on dynamic tropopause
pv = np.empty((nCells,nLevels), dtype=float)
#make_localDomainNbrs(nCells, cellsOnCell_local, nEdgesOnCell_local, g2lMap)
for hCell in xrange(nCells):
hNbrs = c2c[hCell,0:nEdgesOnCell[cells[hCell]]]
pvColumn = driverErtel(state, hCell, hNbrs, nLevels)
#pvColumn = driverErtel_column(state, hCell, hNbrs, nLevels)
for l in range(nLevels):
pv[hCell,l] = pvColumn[l]
#
pvuVal = 2.; #pv = np.abs(pv) #don't need questionable hack for southern hemisphere
thetaVal = np.empty(nCells)
for hCell in xrange(nCells):
(l,dl) = output_data.calcIndexOfValue(pvuVal,pv[hCell,:], nLevels)
thetaVal[hCell] = output_data.calcValueOfIndex(l,dl,state.theta[hCell,:])
#write some cell data ----------------
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
output_data.write_levelData_float('theta_2pvu', fvtk, thetaVal, nCells)
fvtk.close()
data.close()
def driver_domains(nSeeds):
#
ncfname = '/arctic1/mduda/60km/x1.163842.output.2006-07-09_12.00.00.nc'
#ncfname = '/home/nickszap/research/mpas/output.2010-10-23_00:00:00.nc'
data = netCDF4.Dataset(ncfname,'r')
nCellsTotal = len(data.dimensions['nCells'])
nVerticesTotal = len(data.dimensions['nVertices']);
nLevels = len(data.dimensions['nVertLevels'])
nEdgesOnCell = data.variables['nEdgesOnCell'][:];
cellsOnCell = data.variables['cellsOnCell'][:]-1;
seed0 = 0
#seed0 = np.argmax(data.variables['meshDensity'][:]) #seems like a decent heuristic
cell2Site,seeds = conn.partition_max(seed0, cellsOnCell, nEdgesOnCell,nCellsTotal, nSeeds)
for domainInd in xrange(nSeeds):
#output domain mesh ------------------------
cells = np.array(xrange(nCellsTotal))[cell2Site==seeds[domainInd]]
nCells = len(cells)
#open the output vtk file and write header.
vtkfname = 'test'+str(domainInd)+'.vtk'
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
#write nodes and cells
output_data.write_vtk_polyHorizConn_domain(data, fvtk, cells, nEdgesOnCell,nVerticesTotal)
#cell values and connectivity for this domain
haloCells = conn.getHalo(seeds[domainInd], cell2Site, cellsOnCell, nEdgesOnCell, nCellsTotal)
g2lCell = conn.make_global2localMap(cells, haloCells, nCellsTotal)
c2c = conn.make_localDomainNbrs(nCells, cellsOnCell[cells,:], nEdgesOnCell[cells], g2lCell)
neededCells = cells.tolist(); neededCells.extend(haloCells) #has to be domain then halo (as in g2l map)
#I'm having memory errors.
#gc.collect()
#load data for domain and halo -----------------------------
timeInd = 0
print "Loading data for domain {0} with {1} cells\n".format(domainInd, len(neededCells))
#print neededCells
state = loadFields(data, timeInd, neededCells, nLevels)
#compute derived variables -------------------------------
#theta on dynamic tropopause
pv = np.empty((nCells,nLevels), dtype=float)
#make_localDomainNbrs(nCells, cellsOnCell_local, nEdgesOnCell_local, g2lMap)
for hCell in xrange(nCells):
hNbrs = c2c[hCell,0:nEdgesOnCell[cells[hCell]]]
pvColumn = driverErtel(state, hCell, hNbrs, nLevels)
for l in range(nLevels):
pv[hCell,l] = pvColumn[l]
#
pvuVal = 2.; pv = np.abs(pv) #questionable hack for southern hemisphere
thetaVal = np.empty(nCells)
for hCell in range(nCells):
(l,dl) = output_data.calcIndexOfValue(pvuVal,pv[hCell,:], nLevels)
thetaVal[hCell] = output_data.calcValueOfIndex(l,dl,state.theta[hCell,:])
#write some cell data ----------------
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
output_data.write_levelData_float('theta_2pvu', fvtk, thetaVal, nCells)
fvtk.close()
data.close()
def calc_slp(data, hcell, nLevels, time):
#wrapper for calculating sea level (h=0m) pressure.
#Given (unjustified) assumptions on lapse rate, hydrostatic,
#the issue is how to find the pressure at below model levels. This boils down to
#what reference level to move down from.
#Following that described in slp_ben.m from Ryan Torn,
#T is moved from 2km above ground to the ground using the standard lapse rate.
#If surface cell is higher than 2km (eg Tibet), use that cell.
#Advantage of height is to alleviate diurnal effects (on temperature at surface, right???)
print "This might be buggy!!!"
refHt = 2000.; #2km
#get t and p at sfc
theta = data.variables['theta'][time,hcell,:]
#p = data.variables['pressure_base'][time,hcell,:]+data.variables['pressure_p'][time,hcell,:]
p = calcPressure_column(data,hcell,time,nLevels)
t = np.empty(nLevels)
for l in range(nLevels):
t[l] = calc_temperature(theta[l], p[l])
#
hg = .5*(data.variables['zgrid'][hcell,0]+data.variables['zgrid'][hcell,1])
#these values get changed below.
#here we're just setting them to my heart's content so they're in the proper scope
ph = 70000.; th = 280.; h = refHt;
if (hg>refHt):
#have to use cell as reference to move to sfc (could NaNs if slp not meaningful)
h = hg
#ph = p[0]
th = t[0]
else:
#interpolate to height
#zgrid is at faces of cells instead of midpts of layers.
#need to adjust index into centered arrays since cell_l0=layer_l0+.5
h = refHt
(l,dl) = output_data.calcIndexOfValue(refHt,data.variables['zgrid'][hcell,:], nLevels+1)
if (dl>=.5):
#same level, just shift
dl = dl-.5
else:
#have to shift into neighbor
l = l-1
dl = dl+.5
#account for indices out of bounds. this shouldn't happen w/ height at center.
#adjusting accounts for: vals[l+1]-vals[l] in calcValueOfIndex
if (l>nLevels-2):
#extrapolation up
dl = dl+(l-(nLevels-1))
l = nLevels-2;
elif (l<0):
#extrapolation down
dl = dl+(l-0)
l=0;
#interpolate to height
#ph = calcValueOfIndex(l,dl,p)
th = output_data.calcValueOfIndex(l,dl,t)
#
#move temperature to sfc and calc slp
tSurf = calc_temperatureFromLapse(th, hg-h)
pSurf = p[0] #could also data.variables['surface_pressure'][time,ncells]
tRef = calc_temperatureFromLapse(tSurf, -hg/2.) #half way between surface and sea level
slp = calc_pressureHypsometric(tRef, pSurf, -hg)
return slp
