the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Constraining ecosystem model with adaptive Metropolis algorithm using boreal forest site eddy covariance measurements
Jouni Susiluoto
Tiina Markkanen
Mika Aurela
Heikki Järvinen
Ivan Mammarella
Stefan Hagemann
Tuula Aalto
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Accurate national methane (CH4) emission estimates are essential for tracking progress towards climate goals. This study compares estimates from Finland, which use different methods and scales, and shows how well a global model estimates emissions within a country. The bottom-up estimates vary a lot, but constraining them with atmospheric CH4 measurements brought the estimates closer together. We also highlight the importance of quantifying natural emissions alongside anthropogenic emissions.
warmexperiment. The total number of cyclones did not change with warming and neither did the average strength, but there were more stronger and more weaker storms in the warm experiment. Precipitation associated with the most extreme mid-latitude cyclones increased by up to 50 % and occurred in a more poleward location in the warmer experiment.
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Using an operational numerical weather prediction framework, our numerical results show that TCI makes the system accurately generate new reflectivity cells and significantly improves the fractional skill score of forecasts over lead times of up to six hours by up to 10 %.
naturein a computational simulation. Idealized experiments with a low-order chaotic system show successful results by small control signals of only 3 % of the observation error. This is the first step toward realistic weather simulations.