Interpreting weather maps

Objective: Explain isobar and pressure gradient, distinguish their meanings, and apply them to a described case.

Isobar: An isobar connects locations of equal atmospheric pressure on a map. Pressure gradient: A pressure gradient describes pressure change over distance and helps drive wind. Weather observations are spatial samples of a changing system. Map contours help organize those samples but do not replace the underlying measurements. A strong pressure gradient is associated with wind-driving forces, while friction and Earth's rotation influence actual winds. Radar estimates precipitation from returned signals and has limitations. Forecasts combine observations and models, so communicating a probability or range is often more informative than claiming certainty. Application: A contour joins stations with the same pressure reading. This most directly illustrates isobar. Closely spaced isobars indicate a stronger pressure gradient. This most directly illustrates pressure gradient.

Objective: Explain station model and radar observation, distinguish their meanings, and apply them to a described case.

Station model: A station model summarizes weather observations at a location using standardized symbols. Radar observation: Weather radar measures returned signals used to estimate precipitation location and motion. Weather observations are spatial samples of a changing system. Map contours help organize those samples but do not replace the underlying measurements. A strong pressure gradient is associated with wind-driving forces, while friction and Earth's rotation influence actual winds. Radar estimates precipitation from returned signals and has limitations. Forecasts combine observations and models, so communicating a probability or range is often more informative than claiming certainty. Application: A map symbol shows temperature, wind, and cloud cover. This most directly illustrates station model. Successive radar images track an approaching rain band. This most directly illustrates radar observation.

Objective: Explain forecast uncertainty and weather versus climate, distinguish their meanings, and apply them to a described case.

Forecast uncertainty: Forecast uncertainty reflects limits in observations, models, and atmospheric predictability. Weather versus climate: Weather concerns short-term conditions; climate concerns statistical patterns over longer periods. Weather observations are spatial samples of a changing system. Map contours help organize those samples but do not replace the underlying measurements. A strong pressure gradient is associated with wind-driving forces, while friction and Earth's rotation influence actual winds. Radar estimates precipitation from returned signals and has limitations. Forecasts combine observations and models, so communicating a probability or range is often more informative than claiming certainty. Application: A longer-range forecast gives a broader range of outcomes. This most directly illustrates forecast uncertainty. A rainy afternoon is distinguished from a region's long-term rainfall distribution. This most directly illustrates weather versus climate.