Such principles have recently been taken to efficiently model motion of water in the ocean and specifically predict sea surface tem-peratures. Here, the motion field was learned via a deep neural network, and then used to update the heat content and temperatures via phys-ically modelling the movement implied by the motion field

the physical processes actively contributing to the formation of the kinetic energy spectrum are as follows

Interestingly the dry experiment in their study maintains the steep −3 slope all the way to the mesoscale in the upper troposphere. This result emphasizes the critical role of moist convection in the creation of the shallower −5/3 slope.

Small, but unavoidable, relative errors on the largest scales at which the background kinetic energy spectrum follows a λ5/3 slope (100–400 km) can rapidly propagate downscale to the smallest resolved features in operational weather forecasts

The growth of the KE spectra shown in Fig. 4 is certainly due to deep moist convection, but its detailed evolution does not particularly resemble a cascade in which energy spreads either upscale or downscale through progressive exchanges with nearby scales.

Nevertheless, comparing both panels of Fig. 1, it is evident that butterflies will never be of practical importance because trivial relative errors in the large scales will overwhelm 100% relative errors on the very small scales.

One important limitation on the accuracy of weather forecasts is imposed by unavoidable errors in the specification of the atmosphere’s initial state.

convective

the areal fraction of convective

Time evolution of the simulated (a) MSLP and (b) radius of the azimuthal-mean hurricane-force surface wind

These terms are engineered to drive the mean vertical profile of virtual temperature toward a specified reference profile. This relaxation may be visualized as being the result of a mean vertical velocity profile which produces cooling via upward advection of potential temperature so as to counter the heating associated with condensation and radiation in the model.

The level of nondivergence separates vertically the inflow from the outflow, and its level strongly influences the values of sin and sout in these currents, and hence the value of δs.

We used δθ = ±0.5, 1.0, and 2.0 K, where the “+” corresponds to warming in the upper troposphere, the “−” indicates cooling at lower levels.

temperature itself,

the predictability of water is compromised severely

There can be no radiative-convective equilibrium unless /3 = 1, which in most implementations of Kuo-type schemes requires large-scale saturation through the entire column

Observations show that latent heating is positively correlated with temperature in disturbances found in the tropical western Pacific (i.e. they are not moist convectively damped)

CISK more broadly interpreted has long acknowledged the important role of surface fluxes

considering the limit in which clouds are exactly neutrally buoyant with respect to their environment.

Arakawa and Schubert [1974] in which it is argued that moist convection constrains the “cloud work‐function” (a plume‐based counterpart to CAPE that considers entrainment) to be close to zero.

Nine simulations are conducted, each with a different imposed CO2concentration in the range 1–1280 ppmv and a corresponding SST between 286 and 309 K

(3)

The particularnature of that moist adiabat is determined by the bulk properties of updrafts (includingthe microphysics of freezing and precipitation within them), and of downdrafts driven bythe evaporation of precipitation.

Fig. 1b

Three main features are seen in Fig. 2: a single-signed warming of the whole tropo-sphere, associated with a phase speed c ~ 50 m/s;

The cross-isentropic flow - that is, the heating of the atmosphere by convection

The cloud-resolving model (CRM) simulations wereperformed using the anelastic System for AtmosphericModeling (SAM), version 6.8.2 (Khairoutdinov andRandall 2003), for a radiative–convective equilibrium(RCE) state over an ocean surface with a sea surfacetemperature of 301.15 K

To reduce thiscomplication, we prescribed time-invariant temperatureand moisture tendencies to substantially reduce the driftin the large-scale basic state (seeappendix A). We takethe view that the prescribed tendencies affect convec-tion indirectly through their effects on the (horizontalmean) temperature and humidity profiles, and theseprofiles uniquely determine the convective statistics.

This is achieved by tracking a total of approximately30 million Lagrangian particles/parcels (or eight per gridbox on average) embedded in the CRM

buoyancy acceleration,

n empirical formula was proposed to relate thefractional entrainment rate to the product of the verticalvelocity and cloud radius, and a nearly constant co-efficientawas identified within the bulk of the cloudlayer («5a/wd, wherewis the vertical velocity,dis thedistance to cloud edge, anda’0.23 m s21).

fractional entrainment rate

A buoyancybarrier created by a warm anomaly will more easilyeliminate parcels with smaller vertical velocity from thecloudy updrafts, resulting in more mass flux reduction inresponse to a lower-tropospheric warm anomaly.

Observed diabatic heating anomaly profiles regressed against MJO-filtered outgoing longwave radiation during TOGA-COARE as a function of time relative to the MJO peak.

shallow and midlevel-top (“congestus”) convective clouds that heat and moisten the lower troposphere are most common. As the atmosphere humidifies and destabilizes, deep convection is eventually triggered

The lack of sensitivity can be traced in part to underestimated entrainment of environmental air into rising convective clouds and insufficient evaporation of rain into the environment. As a result, the parameterizations produce deep convection too easily while stabilizing the environment too quickly to allow the effects of convective mesoscale organization to occur.

The spurious double intertropical convergence zone (ITCZ) is a systematic bias affecting state-of-the-art coupled general circulation models (GCMs).

Fig. 2. The 1979–99 mean DJFM precipitation (mm day−1) from (a) GPCP, (b)–(d) AMIP, and (e)–(g) CMIP sensitivity experiments.

Fig. 1. The 1979–99 mean JJAS precipitation (mm day−1) from (a) GPCP, (b)–(d) AMIP, and (e)–(g) CMIP sensitivity experiments.

The presence of dry midtropospheric air may thus serve to help permit the buildup of buoyant energy for subsequent episodes of deep convection, such as associated with the onset of the Madden–Julian oscillation.

The entrainment of drier air results in a 37% reduction in rainfall when the dry layer extends from the 600-hPa level to the model top. Tests show that entrainment of dry air at mid levels has a major impact in suppressing precipitation production due to cold rain processes.