The component containing the overall upward or downward pattern of the data in an annual time series is: 

Key Points 

• The component containing the overall upward or downward pattern of the data in an annual time series is called the trend. The trend represents the long-term direction or movement in the data and helps identify whether the series is experiencing growth, decline, or remaining relatively stable over time. 
• It captures the underlying systematic and persistent changes in the time series data, filtering out shorter-term fluctuations and random variations. Analyzing the trend can provide insights into the overall behaviour and direction of the data, which can be useful for forecasting and decision-making purposes.
• The trend can take various forms, depending on the nature of the data. It can be a linear trend, indicating a steady and consistent increase or decrease over time. For example, a linear upward trend might suggest a series experiencing continuous growth, while a linear downward trend might indicate a decline. 
• The trend can also be nonlinear, exhibiting more complex patterns such as exponential growth or decay, cyclicality, or periodic fluctuations. Nonlinear trends may indicate seasonal or cyclical patterns within the data, where the series exhibits regular, repeating patterns over a specific period, such as monthly, quarterly, or annual cycles.
• Identifying and analyzing the trend is important in time series analysis and forecasting. It helps in understanding the overall behaviour and direction of the data, enabling the detection of long-term patterns, growth rates, and potential changes in the underlying dynamics.

Hence, the component containing the overall upward or downward pattern of the data in an annual time series is a trend.