CLASI: coordinating innovative observations and modeling to improve coastal environmental prediction systems

The Coastal Land-Air-Sea-Interaction (CLASI) project aims to develop new “coast-aware” atmospheric boundary and surface layer parameterizations that represent the complex land-sea transition region through innovative observational and numerical modeling studies. The CLASI field effort will involve an extensive array of more than 40 land- and ocean-based moorings and towers deployed within varying coastal domains, including sandy, rocky, urban, and mountainous shorelines. Eight Air-Sea Interaction Spar (ASIS) buoys are positioned within the coastal and nearshore zone, the largest and most concentrated deployment of this unique, established measurement platform. Additionally, an array of novel nearshore buoys, and a network of land-based surface flux towers are complimented by spatial sampling from aircraft, shore-based radars, drones and satellites. CLASI also incorporates unique electromagnetic wave (EM) propagation measurements using coherent transmitter/receiver arrays to understand evaporation duct variability in the coastal zone. The goal of CLASI is to provide a rich dataset for validation of coupled, data assimilating large eddy simulations (LES) and the Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®). CLASI observes four distinct coastal regimes within Monterey Bay, California (MB). By coordinating observations with COAMPS and LES simulations, the CLASI efforts will result in enhanced understanding of coastal physical processes and their representation in numerical weather prediction (NWP) models tailored to the coastal transition region. CLASI will also render a rich dataset for model evaluation and testing in support of future improvements to operational forecast models.

Understanding model spread in sea ice volume by attribution of model differences in seasonal ice growth and melt

Arctic sea ice is declining rapidly, but predictions of its future loss are made difficult by the large spread both in present-day and in future sea ice area and volume; hence, there is a need to better understand the drivers of model spread in sea ice state. Here we present a framework for understanding differences between modelled sea ice simulations based on attributing seasonal ice growth and melt differences. In the method presented, the net downward surface flux is treated as the principal driver of seasonal sea ice growth and melt. A system of simple models is used to estimate the pointwise effect of model differences in key Arctic climate variables on this surface flux, and hence on seasonal sea ice growth and melt. We compare three models with very different historical sea ice simulations: HadGEM2-ES, HadGEM3-GC3.1 and UKESM1.0. The largest driver of differences in ice growth / melt between these models is shown to be the ice area in summer (representing the surface albedo feedback) and the ice thickness distribution in winter (the thickness-growth feedback). Differences in snow and melt-pond cover during the early summer exert a smaller effect on the seasonal growth and melt, hence representing the drivers of model differences in both this and in the sea ice volume. In particular, the direct impacts on sea ice growth / melt of differing model parameterisations of snow area and of melt-ponds are shown to be small but non-negligible.

Proximal-Sensing-Powered Modelling of Energy-Water Fluxes in a Vineyard: A Spatial Resolution Analysis

Spatial resolution is a key parameter in energy–water surface flux modelling. In this research, scale effects are analyzed on fluxes modelled with the FEST-EWB model, by upscaling both its inputs and outputs separately. The main questions are: (a) if high-resolution remote sensing images are necessary to accurately model a heterogeneous area; and (b) whether and to what extent low-resolution modelling provides worse/better results than the upscaled results of high-resolution modelling. The study area is an experimental vineyard field where proximal sensing images were obtained by an airborne platform and verification fluxes were measured via a flux tower. Modelled fluxes are in line with those from alternative energy-balance models, and quite accurate (NSE = 0.78) with respect to those measured in situ. Field-scale evapotranspiration has resulted in both the tested upscaling approaches (with relative error within ±30%), although fewer pixels available for low-resolution calibration may produce some differences. When working at low resolutions, the model has produced higher relative errors (20% on average), but is still within acceptable bounds. This means that the model can produce high-quality results, partially compensating for the loss in spatial heterogeneity associated with low-resolution images.

Spontaneous Cyclogenesis without Radiative and Surface-Flux Feedbacks

Tropical cyclones (TCs) are among the most intense and feared storms in the world. What physical processes lead to cyclogenesis remains the most mysterious aspect of TC physics. Here, we study spontaneous TC genesis in rotating radiative-convective equilibrium using cloud-resolving simulations over an f-plane with constant sea-surface temperature. Previous studies proposed that spontaneous TC genesis requires either radiative or surface-flux feedbacks. To test this hypothesis, we perform mechanism-denial experiments, in which we switch off both feedback processes in numerical simulations. We find that TCs can self-emerge even without radiative and surface-flux feedbacks. Although these feedbacks accelerate the genesis and impact the size of the TCs, TCs in the experiments without them can reach similar intensities as those in the control experiment. We show that TC genesis is associated with an increase in the Available Potential Energy (APE); and that convective heating dominates the APE production. Our result suggests that spontaneous TC genesis may result from a cooperative interaction between convection and circulation, and that radiative and surface-flux feedbacks accelerate the process. Furthermore, we find that increasing the planetary rotation favors spontaneous TC genesis.

Radiative Energy Flux Variation from 2001–2020

Radiative energy flux data, downloaded from CERES, are evaluated with respect to their variations from 2001 to 2020. We found the declining outgoing shortwave radiation to be the most important contributor for a positive TOA (top of the atmosphere) net flux of 0.8 W/m2 in this time frame. We compare clear sky with cloudy areas and find that changes in the cloud structure should be the root cause for the shortwave trend. The radiative flux data are compared with ocean heat content data and analyzed in the context of a longer-term climate system enthalpy estimation going back to the year 1750. We also report differences in the trends for the Northern and Southern hemisphere. The radiative data indicate more variability in the North and higher stability in the South. The drop of cloudiness around the millennium by about 1.5% has certainly fostered the positive net radiative flux. The declining TOA SW (out) is the major heating cause (+1.42 W/m2 from 2001 to 2020). It is almost compensated by the growing chilling TOA LW (out) (−1.1 W/m2). This leads together with a reduced incoming solar of −0.17 W/m2 to a small growth of imbalance of 0.15 W/m2. We further present surface flux data which support the strong influence of the cloud cover on the radiative budget.

Environment Effect Treatments in PWR Whole-Core Pin-by-Pin Calculation

The environment effect arises when pin-cell homogenized parameters are generated with reflective boundary conditions. To treat it in whore-core pin-by-pin calculation, two works are summarized in this article. Firstly, by analyzing the relative errors of pin-cell homogenized group constants and the relative importance of pin-cell discontinuity factors (PDF) in each group, the importance of correcting the PDF of the thermal group is recognized. Secondly, the least-squares method for a multivariate polynomial is utilized to functionalize the relation of the thermal group PDF and the core parameters, including diffusion coefficient, removal cross-section, neutron source, and normalized surface flux. The C5G7 and KAIST benchmarks are employed to evaluate the performance of the PDF predication. Numerical results indicate its effectiveness in reducing the errors of eigenvalue and pin power, especially for the cases with the fuel pins located near the interface between different assemblies.