..1 T-Mobile 00:25 100%- HW3 Paleoclimate.docX Background to the SPECMAP dataset
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..1 T-Mobile 00:25 100%- HW3 Paleoclimate.docX Background to the SPECMAP dataset We will be working with the SPECMAP dataset, which contains information about the volume of ice on land at various times in earth's history. These data are calculated from planktonic records collected from multiple sediment cores in the Atlantic Ocean. Background to the insolation dataset We will compare the SPECMAP dataset to insolation curves at 65°N latitude on the northern hemisphere summer solstice. Analytical Concepts In this homework, you will explore the relationship between the two above datasets. You will work with normalized versions of each dataset, and you will analyze correlations between the normalized variables as they change in time. Normalization A normalized dataset varies from roughly -1 to+ over time, and has no units. To calculate the normalized version of a specific dataset, one must use both the anomaly and the standard deviation. You are already familiar with anomaly: Anomaly-variable at a specific time-Reference quantity For the reference quantity, we have been using averages over a specific time interval (remember Homework 1, where the reference quantity was the average global temperature over 1951-1980). In this homework, we will use the average of each variable over the entire time series as our reference quantity Anomalies have units (e.g., °C, W/m, etc.) and often have specific and recognizable magnitudes (e.g., roughly 10-30°C for temperatures of the earth, roughly 200-500 W/m for radiation on earth). Normalized datasets do not have units, and their magnitudes vary from roughly -1 to . To generate a normalized dataset, we divide the anomaly by the standard deviation. The standard deviation is a statistical measure of how much a quantity varies. (In the above examples, the quantities vary by 20°C and by-300 W/m.) Normalized variable = Anomaly . Standard deviation In this homework, the time series of each variable will be provided to you in the spreadsheet. The time series of each normalized variable will also be calculated for you and provided Open With PrintExplanation / Answer
2)correlated. column normalised specmap d18O is negative value and it become more negative as we go down. which indicate that the presence of oxygen-18 is decreases or the oxygen-16 increased due to low evaporation, ie; less temperature. we can see that from the insolation data. even when the insolation is more than one the specmap d18O is going down it may be due to the precipitation due to increased temperature. generally the variables are in correlation.
4)Anti corrilated, as the solar insolation decreasesthe oxygen-18 is increasing or the oxygen-16 is decreasing the value becomes less negative. its opposit to the observable data.
5)at the time of 410 and 409kyr, the solar insolation is high but the specmap d18O is more negative it can be due to the melting of ice sheet which is rich in oxygen-16.
6)insolation high.
that relation can be due to the rate of change of ice sheets.
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