Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is ev... more Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is evidence that predictability on subseasonal timescales comes from a combination of atmosphere, land, and ocean initial conditions. Predictability from the land is often attributed to slowly varying changes in soil moisture and snow pack, while predictability from the ocean is attributed to sources such as the El Niño Southern Oscillation. Here we use a unique set of subseasonal reforecast experiments to quantify the respective roles of atmosphere, land, and ocean initial conditions on subseasonal prediction skill over land. The majority of prediction skill for global surface temperature in weeks 3-4 comes from the atmosphere, while ocean initial conditions become important after week 4. In the CESM2 subseasonal prediction system, the land initial state does not contribute to surface temperature prediction skill in weeks 3-6 and climatological land conditions lead to higher skill, challenging our current understanding. However, land-atmosphere coupling is important in week 1. Results are similar over most land regions except South America, where ocean initialization is more important. Subseasonal precipitation prediction skill (weeks 3-6) also comes primarily from the atmosphere initial condition, except for a few regions for which the ocean state becomes important.
Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is ev... more Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is evidence that predictability on subseasonal timescales comes from a combination of atmosphere, land, and ocean initial conditions. Predictability from the land is often attributed to slowly varying changes in soil moisture and snow pack, while predictability from the ocean is attributed to sources such as the El Niño Southern Oscillation. Here we use a unique set of subseasonal reforecast experiments to quantify the respective roles of atmosphere, land, and ocean initial conditions on subseasonal prediction skill over land. The majority of prediction skill for global surface temperature in weeks 3-4 comes from the atmosphere, while ocean initial conditions become important after week 4. In the CESM2 subseasonal prediction system, the land initial state does not contribute to surface temperature prediction skill in weeks 3-6 and climatological land conditions lead to higher skill, challenging our current understanding. However, land-atmosphere coupling is important in week 1. Results are similar over most land regions except South America, where ocean initialization is more important. Subseasonal precipitation prediction skill (weeks 3-6) also comes primarily from the atmosphere initial condition, except for a few regions for which the ocean state becomes important.
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Papers by Julie Caron