Antarctic Sea Ice

Quantitative description [A] The linear trend has an equation of y = x This means that, on average, the area of Antarctic sea ice is decreasing by million square km per quarter. OR On average, the area of Antarctic sea ice is decreasing by square km per quarter.

Antarctic Sea Ice Forecasts – Needed 2 correct out of the 3 [M] Forecast = Trend + ASE March 2007 period = 27 Forecast = x – 4.41 = million sq km June 2007 period = 28 Forecast = x – 1.50 = million sq km Sep 2007 period = 29 Forecast = x = million sq km Dec 2007 period = 30 Forecast = x = 4.65 million sq km Need a sentence for each forecast. E.g. The model predicts that the area of the Antarctic sea ice will be million square km in June 2007.

Antarctic Sea Ice Describe at least one further feature [E] – This time series shows a seasonal effect in which the largest area of sea ice occurs each Sept as the temperature is lower over this quarter (winter months) so the ice does not melt as quickly whereas March shows the lowest area as more ice has melted over the summer months. – The time series shows a ramp happening between Dec 2002 and Mar The ramp shows a huge decrease in the area of the sea ice. This could be due to human factors causing the breaking down of the ozone layer which leads to global warming, or due to natural weather factors such as an extremely warm year due to the El Nino effect.

Antarctic Sea Ice Describe at least one further feature [E] – Looking at the graph of the seasonally adjusted values, I can identify an outlier at June 2001 where the area of the sea ice is unusually low for that time of year. This could be due to an unusually warm autumn which caused the sea ice to melt.

Antarctic Sea Ice Relevance and usefulness of the forecasts [E] – The ability to make accurate forecasts about the area of sea ice in the Antarctic is relevant to scientists and environmental groups who are monitoring the sea level changes. The forecasts can give an indication of the effects of global warming and the rate at which it is progressing. Ultimately all of us should be concerned about this as the melting sea ice leads to rising sea levels which can lead to flooding in coastal areas which can have damaging effects to humans as well as plants and animals.

Antarctic Sea Ice Appropriateness of the model [E] – Overall, the linear model appears to be a reasonable fit for the data as the points of the CMM lie close the trendline and the R 2 of is fairly high. However, the linear model shows a decreasing trend that means that eventually all the sea ice will melt, and in fact predictions based on the model will eventually become negative which does not make sense. Additionally, it appears like the trend is changing so perhaps this linear model is not appropriate for making future predictions.

Antarctic Sea Ice Possible Improvements [E] – Looking at the graph of the CMM, it appears that there is a change in the trend so I decided to fit a piecewise model. If there has been a climate shift which has changed the rate of sea ice melting, then I would be able to make better forecasts using a trendline based on more recent data. The piecewise model has a recent trendline which indicates that the area of the sea ice is decreasing, but not as rapidly as it was.

Antarctic Sea Ice Possible Improvements (continued) – The R 2 for the recent trendline on the piecewise model is quite low at which indicates that this model may not be very appropriate for forecasting the area of the sea ice. With such a small amount of data, it is very hard to have an accurate model and we could be more certain about whether this new trendline was appropriate if we had more data. It may be that there is a shift in the trend, or perhaps this change is part of a longer cycle and the area of the sea ice will start decreasing at a faster rate again, or perhaps it will even start to increase in the future. More data should be gathered in order to for us to have a model which enables us to make better forecasts.

Antarctic Sea Ice Limitations of the Analysis [E] – As we do not have any information on how the data was collected on the area of the sea ice, we do not know how the area measurements were taken. Perhaps if the data was measured in only one area of the Antarctic, we would not see the same trend happening in another area. Therefore our forecasts would only apply in the area that the original data was collected in.

Antarctic Sea Ice Interpretation of the seasonally adjusted data [E] – The seasonally adjusted data shows a much lower than expected value for June 2001 and higher than expected values for Sept 2001 and June – As the seasonally adjusted data gets rid of cyclic effects, these values mean that something extreme happened at those times to cause a higher than expected area of sea ice (extremely cold weather) or lower than expected area of sea ice (extremely warm weather).