The role of the Rocky Mountains in shaping the atmospheric mean state and the response to tropical forcing in idealised simulations.

Understanding the natural and forced variability of the atmospheric general circulation and its drivers is one of the grand challenges in climate science. It is of paramount importance to understand to what extent the systematic error of climate models affects the processes driving such variability. This is done by performing a set of simulations (ROCK experiments) with an intermediate complexity atmospheric model (SPEEDY), in which the Rocky Mountains orography is increased or decreased to influence the structure of the North Pacific jet stream. For each of these modified-orography experiments, the climatic response to idealized sea surface temperature anomalies of varying intensity in the El Niño Southern Oscillation (ENSO) region is studied. ROCK experiments are characterized by variations in the Pacific jet stream intensity whose extension encompasses the spread of the systematic error found in Coupled Model Intercomparison Project (CMIP6) models. When forced with ENSO-like idealised anomalies, they exhibit a non-negligible sensitivity in the response pattern over the Pacific North American region, indicating that the model mean state can affect the model response to ENSO. It is found that the classical Rossby wave train response to ENSO is more meridionally oriented when the Pacific jet stream is weaker and more zonally oriented with a stronger jet. Rossby wave linear theory suggests that a stronger jet implies a stronger waveguide, which traps Rossby waves at a lower latitude, favouring a zonal propagation of Rossby waves. The shape of the dynamical response to ENSO affects the ENSO impacts on surface temperature and precipitation over Central and North America. A comparison of the SPEEDY results with CMIP6 models suggests a wider applicability of the results to more resources-demanding climate general circulation models (GCMs), opening up to future works focusing on the relationship between Pacific jet misrepresentation and response to external forcing in fully-fledged GCMs.

Toward an understanding of the atmospheric forcing uncertainties in the Mediterranean Sea

The thesis has extensively investigated for the first time the statistical distributions of atmospheric surface variables and heat fluxes for the Mediterranean Sea. After retrieving a 30-year atmospheric analysis dataset, we have captured the spatial patterns of the probability distribution of the relevant atmospheric variables for ocean atmospheric forcing: wind components (U,V), wind amplitude, air temperature (T2M), dewpoint temperature (D2M) and mean sea-level pressure (MSL-P). The study reveals that a two-parameter PDF is not a good fit for T2M, D2M, MSL-P and wind components (U,V) and a three parameter skew-normal PDF is better suited. Such distribution captures properly the data asymmetric tails (skewness). After removing the large seasonal cycle, we show the quality of the fit and the geographic structure of the PDF parameters. It is found that the PDF parameters vary between different regions, in particular the shape (connected to the asymmetric tails) and the scale (connected to the spread of the distribution) parameters cluster around two or more values, probably connected to the different dynamics that produces the surface atmospheric fields in the Mediterranean basin. Moreover, using the atmospheric variables, we have computed the air-sea heat fluxes for a 20-years period and estimated the net heat budget over the Mediterranean Sea. Interestingly, the higher resolution analysis dataset provides a negative heat budget of –3 W/m2 which is within the acceptable range for the Mediterranean Sea heat budget closure. The lower resolution atmospheric reanalysis dataset(ERA5) does not satisfy the heat budget closure problem pointing out that a minimal resolution of the atmospheric forcing is crucial for the Mediterranean Sea dynamics. The PDF framework developed in this thesis will be the basis for a future ensemble forecasting system that will use the statistical distributions to create perturbations of the atmospheric ocean forcing.