Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z_e > 45 dBZ) than observed but a much narrower stratiform area. The magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speed are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Z_e in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low‐level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low‐level vertical wind shear, and rear‐inflow jets. Updraft velocity variability between schemes is mainly controlled by differences in simulated ice‐related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no‐ice simulations mainly because of scheme differences in collision‐coalescence parameterizations.

Ten 3‐D cloud‐resolving model simulations and four 3‐D limited area model simulations of an intense mesoscale convective system observed on 23–24 January 2006 during the Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE) are compared with each other and with observed radar reflectivity fields and dual‐Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high‐bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias. Making snow mass more realistically proportional to D² rather than D³ eliminates unrealistically large snow reflectivities over 40 dBZ in some simulations. Graupel, unlike snow, produces high biased reflectivity in all simulations, which is partly a result of parameterized microphysics but also partly a result of overly intense simulated updrafts. Peak vertical velocities in deep convective updrafts are greater than dual‐Doppler‐retrieved values, especially in the upper troposphere. Freezing of liquid condensate, often rain, lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. The strongest simulated updraft cores are nearly undiluted, with some of the strongest showing supercell characteristics during the multicellular (presquall) stage of the event. Decreasing horizontal grid spacing from 900 to 100 m slightly weakens deep updraft vertical velocity and moderately decreases the amount of condensate aloft but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may additionally be a product of unrealistic interactions between convective dynamics, parameterized microphysics, and large‐scale model forcing that promote different convective strengths than observed.

Observations made during the TWP‐ICE campaign are used to drive and evaluate thirteen cloud‐resolving model simulations with periodic lateral boundary conditions. The simulations employ 2D and 3D dynamics, one‐ and two‐moment microphysics, several variations on large‐scale forcing, and the use of observationally derived aerosol properties to prognose droplet numbers. When domain means are averaged over a 6‐day active monsoon period, all simulations reproduce observed surface precipitation rate but not its structural distribution. Simulated fractional areas covered by convective and stratiform rain are uncorrelated with one another, and are both variably overpredicted by up to a factor of ∼2. Stratiform area fractions are strongly anticorrelated with outgoing longwave radiation (OLR) but are negligibly correlated with ice water path (IWP), indicating that ice spatial distribution controls OLR more than mean IWP. Overpredictions of OLR tend to be accompanied by underpredictions of reflected shortwave radiation (RSR). When there are two simulations differing only in microphysics scheme or large‐scale forcing, the one with smaller stratiform area tends to exhibit greater OLR and lesser RSR by similar amounts. After ∼10 days, simulations reach a suppressed monsoon period with a wide range of mean precipitable water vapor, attributable in part to varying overprediction of cloud‐modulated radiative flux divergence compared with observationally derived values. Differences across the simulation ensemble arise from multiple sources, including dynamics, microphysics, and radiation treatments. Close agreement of spatial and temporal averages with observations may not be expected, but the wide spreads of predicted stratiform fraction and anticorrelated OLR indicate a need for more rigorous observation‐based evaluation of the underlying micro‐ and macrophysical properties of convective and stratiform structures.

Deep convective updraft invigoration via indirect effects of increased aerosol number concentration on cloud microphysics is frequently cited as a driver of correlations between aerosol and deep convection properties. Here, we critically evaluate the theoretical, modeling, and observational evidence for warm- and cold-phase invigoration pathways. Though warm-phase invigoration is plausible and theoretically supported via lowering of the supersaturation with increased cloud droplet concentration in polluted conditions, the significance of this effect depends on substantial supersaturation changes in real-world convective clouds that have not been observed. Much of the theoretical support for cold-phase invigoration depends on unrealistic assumptions of instantaneous freezing and unloading of condensate in growing, isolated updrafts. When applying more realistic assumptions, impacts on buoyancy from enhanced latent heating via fusion in polluted conditions are largely canceled by greater condensate loading. Many foundational observational studies supporting invigoration have several fundamental methodological flaws that render their findings incorrect or highly questionable. Thus, much of the evidence for invigoration has come from numerical modeling, but different models and setups have produced a vast range of results. Furthermore, modeled aerosol impacts on deep convection are rarely tested for robustness, and microphysical biases relative to observations persist, rendering many results unreliable for application to the real world. Without clear theoretical, modeling, or observational support, and given that enervation rather than invigoration may occur for some deep convective regimes and environments, it is entirely possible that the overall impact of cold-phase invigoration is negligible. Substantial mesoscale variability of dominant thermodynamic controls on convective updraft strength coupled with substantial updraft and aerosol variability in any given event are poorly quantified by observations and present further challenges to isolating aerosol effects. Observational isolation and quantification of convective invigoration by aerosols is also complicated by limitations of available cloud condensation nuclei and updraft speed proxies, aerosol correlations with meteorological conditions, and cloud impacts on aerosols. Furthermore, many cloud processes, such as entrainment and condensate fallout, modulate updraft strength and aerosol–cloud interactions, varying with cloud life cycle and organization, but these processes remain poorly characterized. Considering these challenges, recommendations for future observational and modeling research related to aerosol invigoration of deep convection are provided.