ALBERT

Description: We present non-rotating simulations with the Goddard Earth Observing System (GEOS) atmospheric general circulation model (AGCM) in a square limited area domain over uniform sea surface temperature. As in previous studies, convection spontaneously aggregates into humid clusters, driven by a combination of radiative and moisture-convective feedbacks. The aggregation is qualitatively independent of resolution, with horizontal grid spacing from 3 km to 110 km, with both explicit and parameterized deep convection. A budget for the spatial variance of column moist static energy suggests that longwave radiative and surface flux feedbacks help establish aggregation, while the shortwave feedback contributes to its maintenance. Mechanism denial experiments confirm that aggregation does not occur without interactive longwave radiation. Ice cloud radiative effects help support the humid convecting regions, but are not essential for aggregation, while liquid clouds have a negligible effect. Removing the dependence of parameterized convection on tropospheric humidity reduces the intensity of aggregation, but does not prevent the formation of dry regions. In domain sizes less than (5000 km)2, the aggregation forms a single cluster, while larger domains develop multiple clusters. Larger domains initialized with a single large cluster are unable to maintain them, suggesting an upper size limit. Surface windspeed increases with domain size, implying that maintenance of the boundary layer winds may limit cluster size. As cluster size increases, large boundary layer temperature anomalies develop to maintain the surface pressure gradient, leading to an increase in the depth of parameterized convective heating and an increase in gross moist stability.

Description: The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10 – 35% for typical grid sizes (Δ = 12.5 – 100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of 7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

Description: Several improvements are implemented in the Zhang-McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST) and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long-standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.

Description: Reliable estimates of historical and current biogeochemistry are essential for understanding past ecosystem variability and predicting future changes. Efforts to translate improved physical ocean state estimates into improved biogeochemical estimates, however, are hindered by high biogeochemical sensitivity to transient momentum imbalances that arise during physical data assimilation. Most notably, the breakdown of geostrophic constraints on data assimilation in equatorial regions can lead to spurious upwelling, resulting in excessive equatorial productivity and biogeochemical fluxes. This hampers efforts to understand and predict the biogeochemical consequences of El Niño and La Niña. We develop a strategy to robustly integrate an ocean biogeochemical model with an ensemble coupled-climate data assimilation system used for seasonal to decadal global climate prediction. Addressing spurious vertical velocities requires two steps. First, we find that tightening constraints on atmospheric data assimilation maintains a better equatorial wind stress and pressure gradient balance. This reduces spurious vertical velocities, but those remaining still produce substantial biogeochemical biases. The remainder is addressed by imposing stricter fidelity to model dynamics over data constraints near the equator. We determine an optimal choice of model-data weights that removed spurious biogeochemical signals while benefitting from off-equatorial constraints that still substantially improve equatorial physical ocean simulations. Compared to the unconstrained control run, the optimally constrained model reduces equatorial biogeochemical biases and markedly improves the equatorial subsurface nitrate concentrations and hypoxic area. The pragmatic approach described herein offers a means of advancing earth system prediction in parallel with continued data assimilation advances aimed at fully considering equatorial data constraints.

Description: Precipitation is an important climate quantity that is critically relevant to society. In spite of intense efforts, significant precipitation biases remain in most climate models. One pervasive and persistent bias found in many general circulation models occurs in the Tropical West Pacific where northern hemisphere summer-time precipitation is often underestimated compared to observations. Using the DOE-E3SM model, the inclusion of a missing process, convective gustiness, is shown to reduce those biases through a net increase in surface evaporation. Gustiness in surface wind fields is assumed to arise empirically in proportion to the intensity of convective precipitation. The increased evaporation can be treated as an increase in the moist static energy forcing into the atmosphere. A Normalized Gross Moist Stability (NGMS) framework (which characterizes the relationship between convective forcing and convective response) is used to explore the processes responsible for the precipitation bias, and the impact of the gustiness parameterization in reducing that bias. Because the NGMS of the Tropical West Pacific is less than unity in the E3SMv1 model, the increase in energy forcing amplifies the increase in precipitation to exceed that of the evaporative flux. Convective gustiness favors increased precipitation in regions where the resolved surface winds are weak and convection is present.

Description: A homogenization algorithm for randomly distributed microstructures is applied to develop a mass diffusion model for dry snow. Homogenization is a multi-scale approach linking constituent behavior at the microscopic level—amongst ice and air—to the macroscopic material—snow. Principles of continuum mechanics at the microscopic scale describe water vapor diffusion across an ice grain's surface to the air-filled pore space. Volume averaging and a localization assumption scale up and down, respectively, between microscopic and macroscopic scales. The model yields a mass diffusivity expression at the macroscopic scale that is, in general, a 2 nd order tensor parameterized by both bulk and microstructural variables. The model predicts a mass diffusivity of water vapor through snow that is less than that through air. Mass diffusivity is expected to decrease linearly with ice volume fraction. Potential anisotropy in snow's mass diffusivity is captured due to the tensor representation. The tensor is built from directional data assigned to specific, idealized microstructural features. Such anisotropy has been observed in the field and laboratories in snow morphologies of interest such as weak layers of depth hoar and near-surface facets.

Description: Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Description: By extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

Description: Ocean-Waves-Atmosphere (OWA) exchanges are not well represented in current Numerical Weather Prediction (NWP) systems, which can lead to large uncertainties in tropical cyclone track and intensity forecasts. In order to explore and better understand the impact of OWA interactions on tropical cyclone modelling, a fully coupled OWA system based on the atmospheric model Meso-NH, the oceanic model CROCO and the wave model WW3 and called MSWC was designed and applied to the case of tropical cyclone Bejisa (2013-2014). The fully coupled OWA simulation shows good agreement with the literature and available observations. In particular, simulated significant wave height is within 30 cm of measurements made with buoys and altimeters. Short-term (〈 2 days) sensitivity experiments used to highlight the effect of oceanic waves coupling showlimited impact on the track, the intensity evolution and the turbulent surface fluxes of the tropical cyclone. However, it is also shown that using a fully coupled OWA system is essential to obtain consistent sea salt emissions. Spatial and temporal coherence of the sea state with the 10m-wind speed are necessary to produce sea salt aerosol emissions in the right place (in the eyewall of the tropical cyclone) and with the right size distribution, which is critical for cloud microphysics.