explains trends, provides statistics, it sets a context for current data, allows the variability and occurrence of extremes to be quantified
real time data
current climate observations it helps with short term predictions of the consequences of specific weather events
climate forecast
predictions of climate. ranges from seasonal forecast to medium term forecast (10 - 30yrs) and long term climate data
6 ways to collect climate data
weather stations
satellites - remote sensing
ocean buoys - measure temperature, acidity and the currents of oceans
Oceanic research ship
ice cores and tree rings
Climate models (AI simulations)
Scientists take info from this data and make sure it is accurate (avoiding error of parallax) and reliable. good data is important but diversity of standards, inconsistency and missing data makes collecting climate data difficult - AI can assess the quality of data
quality control
spike
quality control
flatline - there isn't enough variability to be accurate
Quality control
outlier - extreme value that differs greatly from overall pattern of values
