diff --git a/schainpy/model/proc/jroproc_parameters.py b/schainpy/model/proc/jroproc_parameters.py
index 61d2298..d51b16a 100644
--- a/schainpy/model/proc/jroproc_parameters.py
+++ b/schainpy/model/proc/jroproc_parameters.py
@@ -3976,8 +3976,8 @@ class WeatherRadar(Operation):
             data_param[:,0,:] = dataOut.data_POW/(factor)
             data_param[:,1,:] = dataOut.data_DOP
             data_param[:,2,:] = dataOut.data_WIDTH
-            data_param[:,3,:] = dataOut.data_SNR        
-        
+            data_param[:,3,:] = dataOut.data_SNR
+
         return data_param
 
     def getCoeficienteCorrelacionROhv_R(self,dataOut):
@@ -4041,9 +4041,9 @@ class WeatherRadar(Operation):
         #print("Pr last10",10*numpy.log10(Pr[0,-20:]))
         #print("LCTE",10*numpy.log10(self.lambda_**4/( numpy.pi**5 * self.Km**2)))
         if self.Pt<0.3:
-            factor=-20.0
+            factor=17
         else:
-            factor=0
+            factor=30
 
         dBZeh = 10*numpy.log10(Zeh) + factor
         if type=='N':
@@ -4068,7 +4068,7 @@ class WeatherRadar(Operation):
             self.setup(dataOut= dataOut,variableList=variableList,Pt=Pt,Gt=Gt,Gr=Gr,Glna=Glna,lambda_=lambda_, aL=aL,
                         tauW= tauW,thetaT=thetaT,thetaR=thetaR,Km =Km)
             self.isConfig = True
-        
+
         dataOut.data_param = self.setMoments(dataOut)
 
         for i in range(len(self.variableList)):
@@ -4175,7 +4175,7 @@ class PedestalInformation(Operation):
                 continue
           sigma_ele = numpy.nanstd(ele[start:start+sample_max])
           sigma_azi = numpy.nanstd(azi[start:start+sample_max])
-          
+
           if sigma_ele<.5 and sigma_azi<.5:
             if sigma_ele<sigma_azi:
               flag_mode = 'PPI'
@@ -4213,7 +4213,7 @@ class PedestalInformation(Operation):
                mode = self.find_mode(index)
             else:
                mode = self.mode
-            
+
             if mode is not None:
                 return self.fp['Data']['azi_pos'][index], self.fp['Data']['ele_pos'][index], mode
             else:
@@ -4309,8 +4309,8 @@ class Block360(Operation):
         '''
         Add a profile to he __buffer and increase in one the __profiel Index
         '''
-        tmp= getattr(data, attr)        
-        
+        tmp= getattr(data, attr)
+
         self.__buffer.append(tmp)
         self.__buffer2.append(data.azimuth)
         self.__buffer3.append(data.elevation)
@@ -4326,8 +4326,8 @@ class Block360(Operation):
         '''
         Return the PULSEPAIR and the profiles used in the operation
         Affected :  self.__profileIndex
-        '''  
-        
+        '''
+
         data_360 = numpy.array(self.__buffer).transpose(1, 0, 2)
         data_snr = numpy.array(self.__buffer4).transpose(1, 0, 2)
         data_p   = numpy.array(self.__buffer2)
@@ -4427,7 +4427,7 @@ class Block360(Operation):
         dataOut.attr_data = attr_data
         dataOut.runNextOp = runNextOp
         dataOut.flagAskMode = False
-        
+
         if dataOut.mode_op == 'PPI':
             dataOut.flagMode = 1
         elif dataOut.mode_op == 'RHI':
@@ -4445,7 +4445,7 @@ class Block360(Operation):
             setattr(dataOut, attr_data, data_360 )
             dataOut.data_snr = data_snr
             dataOut.data_azi  = data_p + 26.2
-            dataOut.data_azi[dataOut.data_azi>360] = dataOut.data_azi[dataOut.data_azi>360] - 360 
+            dataOut.data_azi[dataOut.data_azi>360] = dataOut.data_azi[dataOut.data_azi>360] - 360
             dataOut.data_ele  = data_e
             dataOut.utctime  = avgdatatime
             dataOut.flagNoData  = False
@@ -4525,15 +4525,14 @@ class MergeProc(ProcessingUnit):
 
             f = [getattr(data, attr_data) for data in data_inputs][0]
             g = [getattr(data, attr_data) for data in data_inputs][1]
-            data = numpy.concatenate((f,g),axis=2)            
+            data = numpy.concatenate((f,g),axis=2)
             setattr(self.dataOut, attr_data, data)
 
             # snr
             self.dataOut.data_snr = numpy.concatenate((data_inputs[0].data_snr, data_inputs[1].data_snr), axis=2)
-            
+
             # ranges
             dh = self.dataOut.heightList[1]-self.dataOut.heightList[0]
             heightList_2  = (self.dataOut.heightList[-1]+dh) + numpy.arange(g.shape[-1], dtype=numpy.float) * dh
 
             self.dataOut.heightList = numpy.concatenate((self.dataOut.heightList,heightList_2))
-