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Michela Biasutti

Publications and source records attributed to Michela Biasutti.

5 recordsLinked to original sources

Accurate Column Moist Static Energy Budget in Climate Models. Part 1: Conservation Equation Formulation, Methodology, and Primary Results Demonstrated Using GISS ModelE3

Column-integrated moist static energy (MSE) budgets underpin theories of tropical convection and circulation, yet in reanalyses and climate models the budget rarely closes; residuals routinely match the leading terms and mask physical insights. This study derives an MSE conservation law that is strictly consistent with GISS ModelE3 and elucidates why conventional diagnostics fail. Multiple intertwined factors -- the breakdown of the product rule upon discretization, effects of mass-filtering, mismatched flux and advective forms, numerical noise in diagnosed vertical velocity, asynchronous model output timing, and postprocessing including vertical interpolation and temporal averaging -- leave significant residuals in both annual means and daily variability, even when raw 30-min model output is used. Residuals are even larger over land and along coastlines. To tackle this obstacle, this study implements the "process increment method," which accurately computes the column MSE flux divergence by calculating the change in column-integrated internal energy, geopotential energy, and latent heats before and after applying the dynamics scheme. Furthermore, the calculated column flux divergence is decomposed into horizontal and vertical advective components. The most crucial finding is that vertical interpolation into pressure coordinates can introduce errors substantial enough to reverse the sign of vertical MSE advection in the warm-pool regions. In ModelE3, native-grid values show MSE import via vertical circulations, while values after interpolation into pressure coordinates indicate export. This discrepancy may prompt a reevaluation of vertical advection as an exporting mechanism and underscores the importance of precise MSE budget calculations.

physics.ao-ph

More extreme Indian monsoon daily rainfall in El Niño summers

Extreme rainfall in the Indian summer monsoon can be destructive and deadly. Although El Niño/ events in the equatorial Pacific make dry days and whole summers more likely throughout India, their influence on daily extremes is not well established. Despite this summer-mean drying effect, we show using observational data spanning 1901-2020 that El Niño increases extreme rainfall likelihoods within monsoonal India, especially in the the summer's core rainy areas of central-eastern India and the narrow southwestern coastal band. Conversely, extremes are broadly suppressed in the drier southeast and far northwest, and more moderate accumulations are inhibited throughout the domain. These rainfall signals appear driven by corresponding ones in convective buoyancy, provided both the undilute instability of near-surface air and its dilution by mixing with drier air above are accounted for. When the summer ENSO state is predicted from a seasonal forecast ensemble initialized in May, the extreme rainfall patterns broadly persist, suggesting the potential for skillful seasonal forecasts. The framework of analyzing the full distributions of rainfall and convective buoyancy could be usefully applied to hourly extremes, other tropical regions under ENSO, other variability modes, and to trends in extreme rainfall under climate change.

physics.ao-ph

On the all-India rainfall index and sub-India rainfall heterogeneity

We revisit long-standing controversies regarding relationships among the all-India rainfall index (AIRI), sub-India summer rainfall variations, El Niño-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD) using 120-year sea surface temperature and high-resolution rainfall datasets. AIRI closely tracks with the spatial extent of wet anomalies and with the average across gridpoints in rainy day count. The leading rainfall variability mode is a monopole associated primarily with rainy day count and ENSO. The second mode is a tripole with same-signed loadings in the high-rainfall Western Ghats and Central Monsoon Zone regions and opposite-signed loadings in Southeastern India between. The IOD projects onto this tripole and, as such, is weakly correlated with AIRI. However, when the linear influence of ENSO is removed, the IOD rainfall regressions become quasi-homogeneously more positive, making the ENSO-residual IOD and AIRI timeseries significantly correlated.

physics.ao-ph

Sources of inter-model scatter in TRACMIP, the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project

We analyze the source of inter-model scatter in the surface temperature response to quadrupling CO2 in two sets of GCM simulations from the Tropical Rain Belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP; Voigt et al, 2016). TRACMIP provides simulations of idealized climates that allow for studying the fundamental dynamics of tropical rainfall and its response to climate change. One configuration is an aquaplanet atmosphere (i.e., with zonally-symmetric boundary conditions) coupled to a slab ocean (AquaCTL and Aqua4x). The other includes an equatorial continent represented by a thin slab ocean with increased surface albedo and decreased evaporation (LandCTL and Land4x).

physics.ao-ph

Delayed Seasonal Cycle and African Monsoon in a Warmer Climate

Increasing greenhouse gases will change many aspects of the Earth's climate, from its annual mean to the frequency of extremes such as heat waves and droughts. Here we report that the current generation of climate models predicts a delay in the seasonal cycle of global rainfall and ocean temperature in response to increasing greenhouse gases, with important implications for the regional monsoons. In particular, the rainy season of the semi-arid African Sahel is projected to start later and become shorter: an undesirable change for local rainfed agriculture and pastoralism. Previous work has highlighted the uncertainty in this region's response to anthropogenic global warming: summer rainfall is predicted either to decrease or increase by up to 30% depending which model is used. The robust agreement across models on the seasonal distribution of rainfall changes signifies that the onset date and length of the rainy season should be more predictable than annual mean anomalies.

physics.ao-ph