Search

We propose a strategy to couple a stochastic lattice gas model of a cloud system to a rather general class of convective parametrization schemes. As proposed in similar models recently presented in the literature, a cloud system in a grid box of a general circulation model (GCM) is modelled as a subgrid lattice of N elements that can be in one of S states, each corresponding to a different convective regime. The time evolution of each element of the lattice is represented as a Markov process characterized by transition rates dependent on large-scale fields and/or local interactions. In order to make application to GCMs computationally feasible, we propose a reduction method leading to a system of S - 1 stochastic differential equations with multiplicative noise. The accuracy of the reduction method is tested in a minimal version of the model. The coupling to a convective scheme is performed in such a way that, in the limit of space- and time-scale separation, the modified stochastic parametrization converges to the original deterministic version of the host scheme. Experiments with a real GCM are then performed, coupling the minimal version of the stochastic model to the Betts-Miller scheme in an aquaplanet version of the Planet Simulator. In this configuration, the stochastic extension of the parametrization keeps the climatology of its deterministic limit but strongly impacts the statistics of the extremes of daily convective precipitation. © 2014 Royal Meteorological Society.

A general circulation model of intermediate complexity with an idealized Earth-like aquaplanet setup is used to study the impact of changes in the oceanic heat transport on the global atmospheric circulation. Focus is on the atmospheric mean meridional circulation and global thermodynamic properties. The atmosphere counterbalances to a large extent the imposed changes in the oceanic heat transport, but, nonetheless, significant modifications to the atmospheric general circulation are found. Increasing the strength of the oceanic heat transport up to 2.5 PW leads to an increase in the global mean near-surface temperature and to a decrease in its equator-to-pole gradient. For stronger transports, the gradient is reduced further, but the global mean remains approximately constant. This is linked to a cooling and a reversal of the temperature gradient in the tropics. Additionally, a stronger oceanic heat transport leads to a decline in the intensity and a poleward shift of the maxima of both the Hadley and Ferrel cells. Changes in zonal mean diabatic heating and friction impact the properties of the Hadley cell, while the behavior of the Ferrel cell is mostly controlled by friction. The efficiency of the climate machine, the intensity of the Lorenz energy cycle and the material entropy production of the system decline with increased oceanic heat transport. This suggests that the climate system becomes less efficient and turns into a state of reduced entropy production as the enhanced oceanic transport performs a stronger large-scale mixing between geophysical fluids with different temperatures, thus reducing the available energy in the climate system and bringing it closer to a state of thermal equilibrium.

Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

A tangent linear adjoint for a low-resolution dynamical model of the atmosphere is used to derive the optimal forcing perturbations for all state variables such that after a specified lead time the model response has a given projection, in terms of an energy norm, on the pattern associated with the 51-yr trend in the Northern Hemisphere winter tropospheric circulation, 1948/49–1998/99. A feature of the derived forcing sensitivity is a Rossby wave–like feature that emanates from the western tropical Pacific and is associated with the deepening of the Aleutian low, whereas an annular pattern in the forcing sensitivity in the uppermost model level is shown to be associated with the pattern of the trend over the Euro-Atlantic/Asian sectors, including the upward trend in the North Atlantic Oscillation index. The authors argue that the Rossby wave–type feature is consistent with studies that have argued a role for the upward trend in tropical sea surface temperature during the 51-yr period. On the other hand, the authors interpret the annular pattern in the forcing sensitivity as being consistent with studies that have argued that the trend over the Euro-Atlantic sector was associated with influences from the stratosphere. In particular, a nonlinear model driven by the optimal forcing perturbation applied only to the top model level is successful at reproducing the trend pattern with the correct amplitude in the Euro-Atlantic sector, but implies a trend over the North Pacific toward a weaker Aleutian low, contrary to what was observed but similar to the spatial pattern associated with the northern annular mode. These results show that the adjoint approach can shed light on previous apparently different interpretations of the trend. The study also presents a successful application of a tangent linear adjoint model to a climate problem.

An analysis of the dynamic mechanisms relevant for the North Atlantic Oscillation (NAO) is performed based on the NCAR-NCEP Reanalysis data set. The NAO is mainly driven by transient fluxes, whereby growth and decay of the NAO-cycle are caused by synoptic waves, which break anticyclonically in the positive phase (negative ano - maly at Iceland) and cyclonically in the negative phase. The NAO-pattern as well as further teleconnections can be simulated with a dynamic atmospheric model. Reanalysis data (ERA40) show that the daily NAO variability is rela ted to the stratospheric circulation.

A detailed description of the third-generation atmospheric general circulation model ECHAM is presen- ted. The climatology of ECHAM3, as simulated at low and high resolution (T21 and T42, respectively), is compared with ECMWF analyses (1981-1990) and also with the climatology of two earlier low reso- lution versions ECHAM 1 and ECHAM2. At low resolution, the impact of the improved model physics is evident primarily in the simulated time- mean state which is more successfully reproduced by the more recent model versions, particularly by ECHAM3. The impact of increased horizontal resolution can be identified not on] v by a generally impro- ved time-mean circulation, particularly in the Southern Hemisphere, but mosbsignificantly by the incre- ased level of high-frequency variability. In the low-frequency range, however, the impact of increased horizontal resolution is modest, and all models fail to reproduce the observed level of low-frequency intraseasonal variability