The purpose of this work is to investigate the physical mechanisms of formation of the OLLJ by performing a dynamical downscaling of the large-scale atmospheric conditions provided by the Global Forecast System (GFS) analysis data, and a momentum balance evaluation similar to that used by Doyle & Warner (1993), Rife et al. (2010), Du et al. (2014); Du, Chen, et al. (2015); Du, Rotunno, et al. (2015); and He et al. (2016). The dynamical downscaling provides greater detail than in previous studies about the OLLJ structure and evolution (Jiménez-Sánchez et al., 2019), and the momentum balance analysis is used to determine the forcings for the wind acceleration responsible for the OLLJ.
The findings suggest that the OLLJ is the result of several mesoscale mechanisms acting together to accelerate the wind, and because of its proximity to the equator, existing theories explaining the behavior of higher-latitude LLJs apply only partially to the OLLJ formation.
The next section describes the model configuration and momentum-balance analysis method. Section 3 analyzes the results and discusses the mechanisms of OLLJ formation. Finally, a summary and conclusions are presented.
2 Data and methods
To characterize the behavior of the OLLJ and the complex topography surrounding the Orinoco River basin, the nonhydrostatic version 3.4.1 of the Advanced Research-WRF model (WRF-ARW; Skamarock & Klemp, 2008) is used to perform a dynamical downscaling of the large-scale atmospheric conditions. This modeling technique enables finer spatial and temporal resolutions than in previous studies. Figure 1 shows the limits of the model domain, which is centered at 7ºN and 68.5ºW, and the main topographic features along the OLLJ corridor.
The WRF-ARW physical parameterization schemes/models, the initial and boundary conditions, as well as the spatial and temporal resolutions are the same described in Jiménez-Sánchez et al.(2019), where the period of study (November 2013–March 2014) provides the opportunity to analyze the OLLJ isolating the wind variability produced by El Niño-Southern Oscillation (ENSO). The model simulations were validated using NCEP FNL Operational Global Analysis and GFS Analysis files, which evidenced good agreement with the model (not shown).
Modifications to the WRF-ARW dynamical solver (Moisseeva & Steyn, 2014) allows the extraction of the individual tendency terms from the horizontal momentum equations so that the contribution of each forcing to the total acceleration of the wind can be assessed. After the extraction, a streamwise (s ) and a crosswise (n ) coordinate system is constructed applying the dot product of the wind direction unit vector and the Coriolis force direction unit vector, respectively, to each tendency term. The final momentum equations characterizing the streamwise and crosswise components of the flow are:
\begin{equation} \frac{\partial V_{s}}{\partial t}={-\frac{\partial\Phi}{\partial s}+\left(-\mathrm{V\ \bullet\ }\mathbf{\nabla}\mathrm{V}\right)}_{s}-fV_{n}+\text{Res}\nonumber \\ \end{equation}
and
\begin{equation} \frac{\partial V_{n}}{\partial t}={-\frac{\partial\Phi}{\partial n}+\left(-\mathrm{V\ \bullet\ }\mathbf{\nabla}\mathrm{V}\right)}_{n}+fV_{s}+\text{Res}\nonumber \\ \end{equation}
Eqs. (1) and (2) imply that the local acceleration of the horizontal wind (LHS), along the streamwise and crosswise axes respectively, is balanced by the sum of the horizontal PGF, horizontal advection, Coriolis force, and Residual term. The residual includes accelerations due to the vertical momentum advection, map projection, model diffusion, and physical parameterizations, as well as errors in the calculation of the other terms. In the boundary layer, the residual is dominated by the effects of surface friction.
3 OLLJ conceptual model
As shown by Jiménez-Sánchez et al. (2019), the OLLJ is a single stream tube (2000 km long \(\times\) 300 km wide \(\times\) 3 km deep, approximately) over Colombia and Venezuela, with mean wind speeds greater than 8 m s‑1. It is an austral summer phenomenon that exhibits its seasonal maximum wind speed and largest spatial extent (2100 km × 450 km) in January (Fig. 2). The OLLJ’s interaction with the surrounding topography produces four localized cores of higher wind speeds (C1–C4; Fig. 2) along its curved axis of propagation, whose mean heights above the terrain increase in the streamwise direction (~500 m, 700 m, 700 m, and 1250 m, respectively; Fig. 3).