Question

我对编程很新，我正在尝试在Python 2.7 IDLE中创建一个简单的零维能量平衡模型，以计算地球的表面温度并添加了冰反照率反馈，即温度输出该模型高于280K，反照率保持在0.3（30％能量反射），如果低于250k反照率为0.7（70％能量反射，因为它的冷却器因此在地球上覆盖更大的冰（白色）），如果温度在这些之间的范围内;反照率用公式计算。然后从模型中回溯这个反照率的新值，以提供更准确的温度。

在我的模块中，我已定义;

最终的气候模型反照率的计算一个新的最终气候模型，其中新的反照率已被纳入考虑范围

我正在尝试制作一个图表来比较第一个气候模型的输出与不同的太阳能输入但是一致的反照率，以及具有变化的反照率和太阳能输出的第二次运行的输出。但不断得到错误;

这是我图表的脚本：

  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 ()

我的错误信息是：

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()

我相信这是我模块的这一部分：

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

感谢任何帮助

由于

Answer 1

上面的评论是正确的，并且不清楚您想要做什么，但如果您想检查数组中的所有元素是否验证了条件，那么您可以这样做：

if tb.all() > 280.0:

如果您对数组中是否存在满足它的值感兴趣，您可以这样做：

if tb.max() > 280.0:
    ...
elif tb.min() < 250.0:

上述两个示例都不应该只是第三个条件的简单else语句。

如果你想单独评估位置，你也可以，但我会选择以下内容：

tb_test = np.ones(tb.shape) * 3
tb_test[np.where(tb > 280)] = 1
tb_test[np.where(tb < 250)] = 2

这将使tb_test数组适用于第一个条件适用的位置，第二个条件适用于第二个条件，第三个适用于第三个条件。

当然，您可以直接插入计算，而不是上述不同条件适用的位置......

Python：生成包含反馈机制的模块图

1 个答案: