3a03348288
Change-Id: I3656148f97b438b40fcd94fbd3fa1daa6b69e55e Former-commit-id: e3ac78fd1d9bcfc97cba82450c4e2a29998a8ac7
184 lines
6.5 KiB
Python
Executable file
184 lines
6.5 KiB
Python
Executable file
#
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from Init import *
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##--------------------------------------------------------------------------
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class HRRRForecaster(Forecaster):
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def __init__(self):
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Forecaster.__init__(self, "HRRR","HRRR")
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# def calcClgHgt(self, cc_CCL):
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# ceil = cc_CCL * .03280839
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# ceil[less_equal(ceil, 0.0)] = 250.0
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# return ceil
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def calcVis(self, vis_SFC):
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return (vis_SFC * 3.2808) / 5279.85564
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def calcT(self, t_FHAG2):
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return self.KtoF(t_FHAG2)
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def calcTd(self, dpt_FHAG2):
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return self.KtoF(dpt_FHAG2)
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##--------------------------------------------------------------------------
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## Returns the maximum of the specified MaxT and the T grids
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##--------------------------------------------------------------------------
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## def calcMaxT(self, T, MaxT):
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## if MaxT is None:
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## return T
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## return maximum(MaxT, T)
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##--------------------------------------------------------------------------
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## Returns the minimum of the specified MinT and T grids
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##--------------------------------------------------------------------------
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## def calcMinT(self, T, MinT):
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## if MinT is None:
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## return T
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## return minimum(MinT, T)
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def calcRH(self, T, Td):
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Tc = .556 * (T - 32.0)
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Tdc = .556 * (Td - 32.0)
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Vt = 6.11 * pow(10, (Tc * 7.5 / (Tc + 237.3)))
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Vd = 6.11 * pow(10, (Tdc * 7.5 / (Tdc + 237.3)))
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RH = (Vd / Vt) * 100.0
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# return the new value
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return RH
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def dewFromTandRH(self,T,RH):
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tc=(T-32.0)*(5.0/9.0)
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rh=clip(RH,0.001,99.999)/100.0
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x=(log(rh)/17.67)+(tc/(tc+243.5))
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tdc=(243.5*x)/(1.0-x)
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td=(tdc*9.0/5.0)+32.0
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return td
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##--------------------------------------------------------------------------
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# Calculates QPF from the total precip field out of the model
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##--------------------------------------------------------------------------
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def calcQPF(self, tp_SFC):
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return tp_SFC / 25.4 # convert from millimeters to inches
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def calcQPF6(self, QPF, QPF6):
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if QPF6 is None:
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QPF6=QPF
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else:
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QPF6=QPF6+QPF
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return QPF6
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def calcQPF12(self, QPF6, QPF12):
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if QPF12 is None:
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QPF12=QPF6
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else:
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QPF12=QPF12+QPF6
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return QPF12
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##--------------------------------------------------------------------------
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## Converts the lowest available wind level from m/s to knots
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##--------------------------------------------------------------------------
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def calcWind(self, wind_FHAG10):
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return (wind_FHAG10[0] * 1.94,clip(wind_FHAG10[1], 0, 359.5))
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#
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# Return the max of the max wind or wind gust
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#
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def calcWindGust(self, wgs_FHAG10, wgs1hr_FHAG10):
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return (maximum(wgs_FHAG10,wgs1hr_FHAG10) * 1.94)
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#=========================================================================
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# SnowAmt - simple snow ratio based on surface temperature - multiplied
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# times the model QPF amount
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#-------------------------------------------------------------------------
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def calcSnowAmt(self,T,QPF):
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m1=less(T,9.0)
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m2=greater_equal(T,30.0)
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snowr=(T*-0.5)+22.5
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snowr[m1] = 20
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snowr[m2] = 0
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snowamt=QPF*snowr
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return snowamt
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##--------------------------------------------------------------------------
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## Use cloud base and cloud top to get sky cover
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##--------------------------------------------------------------------------
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# def calcSky(self, gh_CBL, gh_CTL):
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# depth=gh_CTL-gh_CBL
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# c100=greater_equal(depth, 1000)
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# partialcloudy=depth/10
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# sky=0
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# sky=where(depth, c100, sky)
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## sky=where(depth, partialcloudy, sky)
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# return sky
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def calcSky(self,tcc_EA):
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return tcc_EA
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#--------------------------------------------------------------------------
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# PoP - based strongly on QPF (since when model has one inch of precip the
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# chance of getting 0.01 is pretty high). However, there is a big
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# difference between a place that model has 0.00 precip and is very
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# close to precipitating - and those where model has 0.00 and is a
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# thousand miles from the nearest cloud. Thus, uses the average
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#
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# Uses hyperbolic tangent of QPF, so that it rises quickly as model
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# QPF increases - but tapers out to nearly 100% as QPF gets high.
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#
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# Adjustable parameters:
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# topQPF is QPF amount that would give 75% PoP if nothing else
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# considered at half this amount, PoP is 45%, at double this
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# amount PoP is 96%. Default set at 0.40.
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#
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#--------------------------------------------------------------------------
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# def calcPoP(self, QPF12):
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#
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# topQPF=0.40 # QPF value where raw PoP would be 75%
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# factor=tanh(QPF12*(1.0/topQPF))
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# factor2=tanh(QPF12*(2.0/topQPF))
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# pop=(factor*100.0)+(factor2*100.0)
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# pop=clip(pop,0,100)
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# return pop
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##--------------------------------------------------------------------------
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## Use sky, reflecivity, qpf, vis, categoricals to get weather
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##--------------------------------------------------------------------------
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def calcWx(self, T, QPF, Vsby, crain_SFC, csnow_SFC, cicep_SFC, bli_BL0180, cfrzr_SFC, refc_EA):
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# Now apply a different algorithm for each type
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key = ['<NoCov>:<NoWx>:<NoInten>:<NoVis>:',
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"Wide:S:-:<NoVis>:", "Wide:R:-:<NoVis>:",
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"Wide:S:-:<NoVis>:^Wide:R:-:<NoVis>:",
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'Wide:ZR:-:<NoVis>:', 'Wide:IP:-:<NoVis>:',
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'Wide:ZR:-:<NoVis>:^Wide:IP:-:<NoVis>:',
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"Sct:SW:-:<NoVis>:", "Sct:RW:-:<NoVis>:",
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"Sct:SW:-:<NoVis>:^Sct:RW:-:<NoVis>:",
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"Chc:ZR:-:<NoVis>:", 'Chc:IP:-:<NoVis>:',
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'Chc:ZR:-:<NoVis>:^Chc:IP:-:<NoVis>:']
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wx = self.empty(int8)
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wx[logical_and(greater(QPF, 0.02), greater(T, 35))] = 2
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wx[equal(crain_SFC, 1)] = 2
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wx[equal(cfrzr_SFC, 1)] = 4
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wx[equal(cicep_SFC, 1)] = 5
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wx[equal(csnow_SFC, 1)] = 1
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# Make showers (scattered/Chc)
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convecMask = less(refc_EA, 35)
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wx[logical_and(not_equal(wx, 0), convecMask)] += 6
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# Thunder
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for i in xrange(len(key)):
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tcov = string.split(key[i], ":")[0]
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if tcov == "Chc" or tcov == "<NoCov>":
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tcov = "Sct"
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key.append(key[i] + "^" + tcov
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+ ":T:<NoInten>:<NoVis>:")
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wx[logical_and(greater_equal(bli_BL0180, -3), greater_equal(refc_EA, 35))] += 13
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# No wx where no qpf
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wx[less(QPF, 0.01)] = 0
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return(wx, key)
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def main():
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HRRRForecaster().run()
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