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J. Ching, R. Rotunno, M. LeMone, A. Martilli, B. Kosovic, P. A. Jimenez, and J. Dudhia

Abstract

Mesoscale numerical weather prediction models using fine-grid [O(1) km] meshes for weather forecasting, environmental assessment, and other applications capture aspects of larger-than-grid-mesh size, convectively induced secondary circulations (CISCs) such as cells and rolls that occur in the convective planetary boundary layer (PBL). However, 1-km grid spacing is too large for the simulation of the interaction of CISCs with smaller-scale turbulence. The existence of CISCs also violates the neglect of horizontal gradients of turbulent quantities in current PBL schemes. Both aspects—poorly resolved CISCs and a violation of the assumptions behind PBL schemes—are examples of what occurs in Wyngaard’s “terra incognita,” where horizontal grid spacing is comparable to the scale of the simulated motions. Thus, model CISCs (M-CISCs) cannot be simulated reliably. This paper describes how the superadiabatic layer in the lower convective PBL together with increased horizontal resolution allow the critical Rayleigh number to be exceeded and thus allow generation of M-CISCs like those in nature; and how the M-CISCs eventually neutralize the virtual temperature stratification, lowering the Rayleigh number and stopping their growth. Two options for removing M-CISCs while retaining their fluxes are 1) introducing nonlocal closure schemes for more effective removal of heat from the surface and 2) restricting the effective Rayleigh number to remain subcritical. It is demonstrated that CISCs are correctly handled by large-eddy simulation (LES) and thus may provide a way to improve representation of them or their effects. For some applications, it may suffice to allow M-CISCs to develop, but account for their shortcomings during interpretation.

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Raquel Lorente-Plazas, Pedro A. Jiménez, Jimy Dudhia, and Juan P. Montávez

Abstract

This study assesses the impact of the atmospheric stability on the turbulent orographic form drag (TOFD) generated by unresolved small-scale orography (SSO) focusing on surface winds. With this aim, several experiments are conducted with the Weather Research and Forecasting (WRF) Model and they are evaluated over a large number of stations (318 at 2-m height) in the Iberian Peninsula with a year of data. In WRF, Jiménez and Dudhia resolved the SSO by including a factor in the momentum equation, which is a function of the orographic variability inside a grid cell. It is found that this scheme can improve the simulated surface winds, especially at night, but it can underestimate the winds during daytime. This suggests that TOFD can be dependent on the PBL’s stability. To inspect and overcome this limitation, the stability conditions are included in the SSO parameterization to maintain the intensity of the drag during stable conditions while attenuating it during unstable conditions. The numerical experiments demonstrate that the inclusion of stability effects on the SSO drag parameterization improves the simulated surface winds at diurnal, monthly, and annual scales by reducing the systematic daytime underestimation of the original scheme. The correction is especially beneficial when both the convective velocity and the boundary layer height are used to characterize the unstable conditions.

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Pedro A. Jiménez, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, and Elena García-Bustamante

Abstract

Meteorological data of good quality are important for understanding both global and regional climates. In this respect, great efforts have been made to evaluate temperature- and precipitation-related records. This study summarizes the evaluations made to date of the quality of wind speed and direction records acquired at 41 automated weather stations in the northeast of the Iberian Peninsula. Observations were acquired from 1992 to 2005 at a temporal resolution of 10 and 30 min. A quality assurance system was imposed to screen the records for 1) manipulation errors associated with storage and management of the data, 2) consistency limits to ensure that observations are within their natural limits of variation, and 3) temporal consistency to assess abnormally low/high variations in the individual time series. In addition, the most important biases of the dataset are analyzed and corrected wherever possible. A total of 1.8% wind speed and 3.7% wind direction records was assumed invalid, pointing to specific problems in wind measurement. The study not only tries to contribute to the science with the creation of a wind dataset of improved quality, but it also reports on potential errors that could be present in other wind datasets.

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P. A. Jiménez, E. García-Bustamante, J. F. González-Rouco, F. Valero, J. P. Montávez, and J. Navarro

Abstract

Daily wind variability in the Comunidad Foral de Navarra in northern Spain was studied using wind observations at 35 locations to derive subregions with homogeneous temporal variability. Two different methodologies based on principal component analysis were used to regionalize: 1) cluster analysis and 2) the rotation of the selected principal components. Both methodologies produce similar results and lead to regions that are in general agreement with the topographic features of the terrain. The meridional wind variability is similar in all subregions, whereas zonal wind variability is responsible for differences between them. The spectral analysis of wind variability within each subregion reveals a dominant annual cycle and the varying presence of higher-frequency contributions in the subregions. The valley subregions tend to present more variability at high frequencies than do higher-altitude sites. Last, the influence of large-scale dynamics on regional wind variability is explored by studying connections between wind in each subregion and sea level pressure fields. The results of this work contribute to the characterization of wind variability in a complex terrain region and constitute a framework for the validation of mesoscale model wind simulations over the region.

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Pedro A. Jiménez, Jimy Dudhia, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, and Elena García-Bustamante

Abstract

This study summarizes the revision performed on the surface layer formulation of the Weather Research and Forecasting (WRF) model. A first set of modifications are introduced to provide more suitable similarity functions to simulate the surface layer evolution under strong stable/unstable conditions. A second set of changes are incorporated to reduce or suppress the limits that are imposed on certain variables in order to avoid undesired effects (e.g., a lower limit in u *). The changes introduced lead to a more consistent surface layer formulation that covers the full range of atmospheric stabilities. The turbulent fluxes are more (less) efficient during the day (night) in the revised scheme and produce a sharper afternoon transition that shows the largest impacts in the planetary boundary layer meteorological variables. The most important impacts in the near-surface diagnostic variables are analyzed and compared with observations from a mesoscale network.

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Pedro A. Jimenez, Joshua P. Hacker, Jimy Dudhia, Sue Ellen Haupt, Jose A. Ruiz-Arias, Chris A. Gueymard, Gregory Thompson, Trude Eidhammer, and Aijun Deng

Abstract

WRF-Solar is a specific configuration and augmentation of the Weather Research and Forecasting (WRF) Model designed for solar energy applications. Recent upgrades to the WRF Model contribute to making the model appropriate for solar power forecasting and comprise 1) developments to diagnose internally relevant atmospheric parameters required by the solar industry, 2) improved representation of aerosol–radiation feedback, 3) incorporation of cloud–aerosol interactions, and 4) improved cloud–radiation feedback. The WRF-Solar developments are presented together with a comprehensive characterization of the model performance for forecasting during clear skies. Performance is evaluated with numerical experiments using a range of different external and internal treatment of the atmospheric aerosols, including both a model-derived climatology of aerosol optical depth and temporally evolving aerosol optical properties from reanalysis products. The necessity of incorporating the influence of atmospheric aerosols to obtain accurate estimations of the surface shortwave irradiance components in clear-sky conditions is evident. Improvements of up to 58%, 76%, and 83% are found in global horizontal irradiance, direct normal irradiance, and diffuse irradiance, respectively, compared to a standard version of the WRF Model. Results demonstrate that the WRF-Solar model is an improved numerical tool for research and applications in support of solar energy.

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Pedro A. Jiménez, J. Fidel González-Rouco, Elena García-Bustamante, Jorge Navarro, Juan P. Montávez, Jordi Vilà-Guerau de Arellano, Jimy Dudhia, and Antonio Muñoz-Roldan

Abstract

This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the performance of the simulation to reproduce the wind variability within subregions identified from observations over the 1999–2002 period in a previous study. By comparing with wind observations, the model results show the ability of the WRF dynamical downscaling over a region of complex terrain. The higher spatiotemporal resolution of the WRF simulation is used to evaluate the extent to which the length of the observational period and the limited spatial coverage of observations condition one’s understanding of the wind variability over the area. The subregions identified with the simulation during the 1992–2005 period are similar to those identified with observations (1999–2002). In addition, the reduced number of stations reasonably represents the spatial wind variability over the area. However, the analysis of the full spatial dimension simulated by the model suggests that observational coverage could be improved in some subregions. The approach adopted here can have a direct application to the design of observational networks.

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Pedro A. Jiménez, Jordi Vilà-Guerau de Arellano, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, Elena García-Bustamante, and Jimy Dudhia

Abstract

Variations in the diurnal wind pattern associated with heat waves and drought conditions are investigated climatologically at a regional level (northeast of the Iberian Peninsula). The study, based on high-density observational evidence and fine spatial-scale mesoscale modeling for the 1992–2004 period, shows that wind speed can decrease up to 22% under situations characterized by extremely high temperatures and severe drought, such as the European summer of 2003. By examining the role of the different atmospheric scales of motion that determine the wind diurnal variability, it is found that the 2003 synoptic conditions are the main driver for changes in the wind speed field. In turn, these changes are modulated by mesoscale circulations influenced by the soil moisture availability. The results have implications for broad regional modeling studies of current climate and climate change simulations in as much as the study demonstrates that a correct representation of local soil moisture conditions impacts atmospheric circulation and therefore the regional climate state.

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Thomas W. N. Haine, Renske Gelderloos, Miguel A. Jimenez-Urias, Ali H. Siddiqui, Gerard Lemson, Dimitri Medvedev, Alex Szalay, Ryan P. Abernathey, Mattia Almansi, and Christopher N. Hill

Abstract

Computational Oceanography is the study of ocean phenomena by numerical simulation, especially dynamical and physical phenomena. Progress in information technology has driven exponential growth in the number of global ocean observations and the fidelity of numerical simulations of the ocean in the past few decades. The growth has been exponentially faster for ocean simulations, however. We argue that this faster growth is shifting the importance of field measurements and numerical simulations for oceanographic research. It is leading to the maturation of Computational Oceanography as a branch of marine science on par with observational oceanography. One implication is that ultra-resolved ocean simulations are only loosely constrained by observations. Another implication is that barriers to analyzing the output of such simulations should be removed. Although some specific limits and challenges exist, many opportunities are identified for the future of Computational Oceanography. Most important is the prospect of hybrid computational and observational approaches to advance understanding of the ocean.

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C. L. Reddington, K. S. Carslaw, P. Stier, N. Schutgens, H. Coe, D. Liu, J. Allan, J. Browse, K. J. Pringle, L. A. Lee, M. Yoshioka, J. S. Johnson, L. A. Regayre, D. V. Spracklen, G. W. Mann, A. Clarke, M. Hermann, S. Henning, H. Wex, T. B. Kristensen, W. R. Leaitch, U. Pöschl, D. Rose, M. O. Andreae, J. Schmale, Y. Kondo, N. Oshima, J. P. Schwarz, A. Nenes, B. Anderson, G. C. Roberts, J. R. Snider, C. Leck, P. K. Quinn, X. Chi, A. Ding, J. L. Jimenez, and Q. Zhang

Abstract

The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.

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