zzzJieHe-gradsresults

**Basic parts:** **1. Download and read...** My language code file for making the below figures is linked. I started from scratch.

 **2. Calculate zonally averaged P and v over longitude, and plot the resulting latitude-time series.**  Here is the latitude-time sections of P in the zonal mean:  and at 91.25W:  Notice that the mean precip peaks at the Equator and decrease pole ward. The ITCZ shifts northwards as the boreal summer comes Similarly the precip at 90W has a maximum during the summer at the Equator. However, a secondary maximum appears around Sep to the north of the Equator, probably as a result of hurricane activities.

Here is the latitude-time sections of v in the zonal mean:  and at 90W : The mean meridional wind field clearly shows the ITCZ and the subtropical divergence zone. The spatial distribution shifts with seasonal change, most apparently at the Equator. The meridional wind field at 90W shows similar patterns, but with larger magnitudes. Notice the maximum that occurs around later summer at the Equator, which is consistent with the precip.

 **3. Average air temperature over both lat and lon, to make a 12-month time series. Which season has the warmest global mean surface temperature? Can you understand why?**  <span style="font-family: Arial,serif;"> **4. Make a map of the temporal (i.e. seasonal) standard deviation of precipitation, expressed as a percentage of the annual mean precipitation. This might be one definition of a "monsoonal" climate.** <span style="font-family: Arial,serif;">Here is a map expressing the seasonality of precipitation: <span style="font-family: Arial,serif;"> Places with intensely seasonal rainfall tend to be the South and Northeast Asian Monsoon regions, the Saharan Desert, North American Monsoon region, and the El Nino 3 region. <span style="font-family: Arial,serif;"> **5. What is the space-time standard deviation of 'air' (temperature)?** <span style="font-family: Arial,serif;">The total space-time standard deviation of temperature is 15K <span style="font-family: Arial,serif;">__. The challenge of computing it is that we want area averages over the Earth, but we started with lat-lon grids. A simple call of stdev(air array) gives__ <span style="font-family: Arial,serif;">, which is too large because high latitude data are overweighed. Instead, we need to account for the fact that the earth is spherical.