Numerical simulation of planetary boundary-layer evolution and mesoscale flow over irregular terrain under daytime heating conditions

The influence of irregular terrain on the evolution of the daytime planetary boundary layer (PBL) and meso-β scale dry circulations is studied using two three-dimensional hydrostatic σ-coordinate models with different approaches for the PBL parameterizations; the 4-layer model uses the mixed-layer (bulk-layer) approach, while the 7-layer model adopts the eddy-diffusivity (multi-layer) approach. Numerical experiments are carried out under the conditions of a dry, sunny summer day with moderate prevailing westerly winds blowing over gently sloping idealized hills in a domain of 150 km on a side. The results from the two models are compared and their performances are evaluated. The behaviors of the mean PBL depth and inversion strength are analytically described using a simple one-point mixed-layer model. Counterclockwise rotation of the mean PBL winds with time observed in both model results can be explained only when the non-zero momentum flux at the PBL top is taken into account. However, stresses associated with entrainment at the PBL top are not sufficient to pull the cold air out of the valleys so as to result in breakup of the early morning stable layer, as is suggested in a previous study. The regions of weak winds that persist in the morning PBL are attributed largely to the baroclinic effect of horizontal variations of potential temperature θ in the PBL, while the effect of surface drag is quite small in these areas. Significant differences in the flow patterns near the surface in two results suggest the importance of the local pressure gradient force associated with terrain irregularities. The effect of horizontal θ advection is also significant in helping reduce the PBL θ anomalies and promote breakup of the stable layer. The well-mixed assumption generally applies quite well to the development of the θ profiles, while for momentum it seems valid only during the peak of convective mixing and the eddy-diffusivity approach is probably preferable for a better description of the low-level flows. The fields of the PBL top height obtained using different procedures in the two models are found to correspond fairly well to each other. Mass-flux convergence associated with terrain irregularities and resulting changes in the wind fields are shown to play a key role in the midday PBL height patterns. The development of the PBL structure as revealed by the θ cross sections obtained from either model corresponds favorably to that indicated by idealized cross sections previously constructed from observed data. The formation of a region of mass-flux convergence and accompanying updrafts near the surface on the leeward side of a mountain, processes which are likely to be important in terrain-induced cloud initiations, seem to be simulated

A preliminary description of climatology in the western United States

We describe the climatology of the western United States as seen from two 1-month perspectives, January and July 1988, of the National Meteorological Center large-scale global analysis, the Colorado State University Regional Atmospheric Modeling System (RAMS), and various station observation sets. An advantage of the NMC analysis and the RAMS is that they provide a continuous field interpolation of the meteorological variables. It is more difficult to describe spatial meteorological fields from the available sparse station networks. We assess accuracy of the NMC analysis and RAMS by finding differences between the analysis, the model, and station values at the stations. From these comparisons, we find that RAMS has much more well-developed mesoscale circulation, especially in the surface wind field. However, RAMS climatological and transient fields do not appear to be substantially closer than the larger-scale analysis to the station observations. The RAMS model does provide other meteorological variables, such as precipitation, which are not readily available from the archives of the global analysis. Thus, RAMS could, at the least, be a tool to augment the NMC large-scale analyses

Hurricane-driven alteration in plankton community size structure in the Gulf of Mexico: A modeling study

This was the first study to analyze phytoplankton and zooplankton community size structure during hurricane passage. A three-dimensional biophysical model was used to assess ecosystem dynamics, plankton biomass, and plankton distribution in the Gulf of Mexico during Hurricane Katrina (2005). Model simulations revealed that large phytoplankton were most responsive to hurricane-induced turbulent mixing and nutrient injection, with increases in biomass along the hurricane track. Small phytoplankton, microzooplankton, and mesozooplankton biomass primarily shifted in location and increased in spatial extent as a result of Hurricane Katrina. Hurricane passage disrupted the distribution of plankton biomass associated with mesoscale eddies. Biomass minimums and maximums that resided in the center of warm- and cold-core eddies and along eddy peripheries prior to hurricane passage were displaced during Hurricane Katrina

Regional-scale simulations of the western United States climate

Mesoscale models can provide a sufficiently detailed regional climatology. From these pioneering studies, we were inspired to begin to develop regional climatologies with the Colorado State University Regional Atmospheric Modeling System (CSU-RAMS). Our major goal is to develop a better understanding of the hydrologic cycle in the mountainous, arid west. An advantage of using the RAMS code is that we can generate detailed descriptions of precipitation processes, which will hopefully translate into realistic surface yields of both rain and snow. In the ensuing sections, we first describe the model and its microphysics parameterizations, then continue with our methodology for incorporating large-scale data into the model grid. Preliminary results demonstrating the mesoscale variation of precipitation over the mountainous western US are then presented. The model framework for the present study incorporates a three-dimensional, terrain-following non-hydrostatic version of the code. The simulation includes topography derived from a 5-minute global data set with a silhouette averaging scheme that preserves realistic topography heights. This height data is then interpolated to the model grid. 13 refs., 8 figs

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

The article of record as published may be found at http://dx.doi.org/10.1002/2016JC011993Upon publication, the in situ data will be available for academic purposes through the NASA SeaWiFS Bio-optical Archive and Storage System (http:// seabass.gsfc.nasa.gov/), including NPP, NO3, and Zeu.The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.National Aeronautics and Space Agency (NASA)Ocean Biology and Biogeochemistry (OBB)The project ‘‘Green Mercator’’National Program CNRS/LEFE/INSU.NSF Office of Polar ProgramsFP7 MyOcean2PAVE (Polish-Norwegian Research Program)Norwegian Supercomputing Project (NOTUR2)Research Council of Norway funded project ORGANICNASA Cryosphere programCNRM-CM climate modelMétéo-France/DSI supercomputingOcean Biology and Biogeochemistry (OBB) NNX13AE81GNSF Office of Polar Programs PLR- 1417925NSF Office of Polar Programs PLR-1416920FP7 MyOcean2 (project number 283367)Research Council of Norway funded project ORGANIC (239965/RU)NASA Cryosphere program (NNX15AG68G)