我對編程相當陌生,我試圖在Python 2.7 IDLE中生成一個簡單的零維能量平衡模型,以計算地球表面溫度並增加了冰反照反饋,即如果模型的溫度輸出高於280K,則反照率保持在0.3(反射30%的能量),如果其低於250k,則反照率爲0.7(反射70%的能量,因爲其更冷卻器地球上有更大的冰蓋(白色)),以及溫度是否處於這兩者之間的範圍內;根據公式計算反照率。反照率的這個新值然後從模型返回,以提供更準確的溫度。Python:生成一個包含反饋機制的模塊的圖形
在我的模塊中,我已經定義了;
最後一個氣候模型 計算反照率 新敲定的氣候模型考慮到concideration新的反照率(S)
我想製作一個圖形的首個氣候模型的輸出與變化的比較太陽能輸入,但一致的反照率,第二輪輸出與不同的反照率和太陽能輸出。但不斷收到錯誤;
這是我爲我的圖形腳本:
import matplotlib.pyplot as plt
import numpy as np
from EBM_IceAlbFeedback import *
# q is for the Solar Constant
q=np.linspace(2.5e26,4.0e26,150)
# t= temperature derived from the final climate model
t= finalCM(Q=q)
plt.plot(q,t,'b-')
q=np.linspace(3.0e26,4.5e26,150)
# tb= is the second set of temperatures derived from the NEWfinalCM which contains an Ice Albedo Feedback
tb= NEWfinalCM(Q=q)
plt.plot(q,tb,'r-')
plt.show()
我的錯誤信息是:
Traceback (most recent call last):
File "K:/python/CompareCMsPlt2.py", line 13, in <module>
tb= NEWfinalCM(Q=q)
File "K:/python\EBM_IceAlbFeedback.py", line 228, in NEWfinalCM
NewAlb=NAlb(dist=dist, Q=Q, co2Emissions=co2Emissions, alpha=alpha, cCycleInt=cCycleInt, cCycleSlope=cCycleSlope)
File "K:/python\EBM_IceAlbFeedback.py", line 190, in NAlb
if ta>280.0:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
我相信這是我的模塊,這部分提到的東西:
def NAlb (dist=150e9, Alb=0.3, Q=3.87e26, co2Emissions=0.0, alpha=3.0, cCycleInt=0.4, cCycleSlope=0.0001):
'''
Readjusting Albedo to the output temperature
Arguments:
Q = solar ouput (W)
dist = distance from the sun (m)
co2Emissions = Cumulative CO2 emissions since 2010 (GtC)
alpha = climate sensitivity (K/2xCO2)
cCycleInt = Initial value of the airborne fraction (unitless)
cCycleSlope = Increment the airborne fraction per GtC (GtC^-1)
Return Value:
NewAlb= New Albedo (Unitless)
'''
# CALCULATE ABORTIVITY:
#Our model is baselined at an atmospheric CO2 concentration of 390 ppmv in 2010
baselineCO2=390.0
#The official IPCC figure for conversion of mass of emissions (GtC) top atmospheric concentration (ppmv)
IPCCmassToConc=2.12
#approximate correction for the carbon cycle:
cCycleAdjust=cCycleInt+cCycleSlope*co2Emissions
#convert GtC to CO2 conc in ppmv:
co2=co2Emissions*cCycleAdjust/IPCCmassToConc+baselineCO2
#calculate absorptivity
absrp=absrpFromCO2(CO2=co2, alpha=alpha)
#CALCULATE TEMPERATURE: using the same method as in the finalCM
ta=transATmCM (absrpt=absrp, dist=dist, Alb=0.3, Q=Q)
# define the thresholds for an ice free state.
if ta>280.0:
NewAlb=0.3
# define the threshold for a snow ball Earth state.
elif ta<250.0:
NewAlb=0.7# Calculate albedo for temperatures between 280k to 230k
elif 250.0<ta<280.0:
NewAlb=(0.3+(((0.7-0.3)/(280.0-250.0))*(280.0-ta)))
return NewAlb
def NEWfinalCM(co2Emissions=0.0, alpha=3., dist=150e9, Q=3.87e26, cCycleInt=0.4, cCycleSlope=0.0001):
'''
A New final Climate model which contains and Ice Albedo Feedback
Arguments:
Q = solar ouput (W)
dist = distance from the sun (m)
co2Emissions = Cumulative CO2 emissions since 2010 (GtC)
alpha = climate sensitivity (K/2xCO2)
cCycleInt = Initial value of the airborne fraction (unitless)
cCycleSlope = Increment the airborne fraction per GtC (GtC^-1)
Return Value:
tn = surface temperature (K)
'''
#Our model is baselined at an atmospheric CO2 concentration of 390 ppmv in 2010
baselineCO2=390.0
#The official IPCC figure for conversion of mass of emissions (GtC) top atmospheric concentration (ppmv)
IPCCmassToConc=2.12
#approximate correction for the carbon cycle:
cCycleAdjust=cCycleInt+cCycleSlope*co2Emissions
#convert GtC to CO2 conc in ppmv:
co2=co2Emissions*cCycleAdjust/IPCCmassToConc+baselineCO2
#calculate temperature
absrp=absrpFromCO2(CO2=co2, alpha=alpha)
NewAlb=NAlb(dist=dist, Q=Q, co2Emissions=co2Emissions, alpha=alpha, cCycleInt=cCycleInt, cCycleSlope=cCycleSlope)
tn=transATmCM(absrpt=absrp, dist=dist, Alb=NewAlb, Q=Q)
return tn
任何幫助表示讚賞
感謝
@cillosis - 爲什麼?科學家不是程序員......至於實際的錯誤,numpy數組(例如'x> 5')的條件返回布爾數組(例如'array([True,True,False])'而不是單個值。 – 2012-03-17 00:51:53