What would be the optimal way to address these arrays
You should almost never be using np.append, numpy arrays are designed to be used as fixed size arrays. np.append creates a whole new array each time and will thus fairly expensive. 

The first thing is that you should create the array at its full size. Then assign to the elements:

y = np.empty(10+len(wavelength)-2, int) # I don't know the type, guessing here
for i in xrange(10+len(wavelength)-2):#2 repeats
    y[i] = model[MN][i]


The second thing is that you should look for numpy operations to do the same thing your loop does. In this case, I can actually replace that code by:

y = model[MN, :10 + len(wavelength) - 2]


This assumes that model is a numpy array. If it is isn't, you should make it one.

Let's look at the code for fmod

for i in xrange(10,10+len(wavelength)-2): #2 repeats
     Alambda=Ak/wavelength[i-10]
     fmod=np.append(fmod,convertStr(y[i])*Fbol*scale*1e+023*1e+03/(c/wavelengthmodel[i-10]))
     if i== 11:
      fmod=np.append(fmod,convertStr(y[i])*Fbol*scale*1e+023*1e+03/(c/wavelengthmodel[i-10]))
     if i== 13:
      fmod=np.append(fmod,convertStr(y[i])*Fbol*scale*1e+023*1e+03/(c/wavelengthmodel[i-10]))


It is not as obvious how to vectorize this code. Firstly, we can clean up the code a bit. Eliminate the unused Alambda, eliminate duplicate pieces of code, and change the loop to start with zero. (When trying to vectorize you pretty much always want to start by changing your loops to start with 0).

for i in xrange(len(wavelength)-2): #2 repeats
     value = convertStr(y[i+ 10])*Fbol*scale*1e+023*1e+03/(c/wavelengthmodel[i])
     fmod=np.append(fmod, value)
     if i == 11 or i == 13:
          fmod = np.append(fmod, value)


It is still not clear how to break up this loop, so we apply a general strategy of breaking up a loop. If a loop does multiple things, we break the loop up so that the loop only does one thing. Here is the first loop.

value = numpy.empty( len(wavelength) - 2)
for i in xrange(len(wavelength) - 2):
    value[i] = convertStr(y[i+10])*Fbol*scale*1e+023*1e+03/(c/wavelengthmodel[i])


Once we have the loop down to the simple level of assigning to each element, we want to vectorize it. I don't know what convertStr does, but I'll assume it can be adapted to vectorize whatever I pass into it. So I can replace this loop by:

value = convertStr(y[10:])*Fbol*scale*1e+023*1e+03/(c/wavelengthmodel)


Let's move onto the second loop

for i in xrange(len(wavelength)-2): #2 repeats
     fmod=np.append(fmod, value[i])
     if i == 11 or i == 13:
          fmod = np.append(fmod, value[i])


This essentially copies value, but introduces repeats. There are  few ways this could be accomplished. Probability the simplest would be:

fmod = np.empty( len(wavelength), int)
fmod[0:11] = value[0:11]
fmod[11:13] = value[11]
fmod[13] = value[12]
fmod[14:17] = value[13]
fmod[17:] = value[14:]


Hopefully that gives you an idea of how to approach improving the performance.