Comparison of Volume Velocity Processing (VVP) and 3DVAR+DIV Algorithms for Deriving 3D Wind Fields in the Mesosphere and Lower Thermosphere with Meteor Radar Observations.

Accurate estimation of three-dimensional wind fields in the mesosphere and lower thermosphere (MLT) is crucial for understanding atmospheric dynamics and variability, however, it has been a longstanding challenge in atmospheric science. Particularly, the retrieval of vertical wind, due to the inherent biases in meteor radar observations resulting from geometric and observational limitations. This challenge has to be addressed as the vertical wind plays a key role in the dynamical processes in the global atmosphere, such as the vertical transport of momentum and energy which incorporates the global meridional circulation. Volume Velocity Processing (VVP) and the 3DVar+DIV algorithms are two advanced retrieval methodologies which have been applied to estimate vertical winds and their variabilities, mitigating the biases and improving the accuracy of wind estimations. These approaches have recently demonstrated significant progress in overcoming the longstanding challenge.
The VVP method derives three-dimensional winds by employing coordinate transformations and nonlinear constraints on the observed radial velocities of the meteor radars. Its design is emphasized on high spatial resolution, making it particularly effective for localized studies of wind variability. The 3DVAR+DIV algorithm integrates radial velocity data into a variational framework that minimizes a cost function while adhering to physical constraints such as the continuity equation. This approach ensures a physically consistent wind field and allows for the calculation of additional atmospheric diagnostics, including horizontal divergence and vorticity. While both methods provide robust solutions for addressing vertical wind biases, their respective implementations capabilities offer unique advantages.
This study seeks to compares these two cutting-edge methodologies; VVP and the 3D-Var+DIV algorithms using data the Nordic Meteor Radar Cluster (NORDIC), a dense multistatic radar network in the Northern Hemisphere, to uncover their ability to estimate 3D wind fields and mitigate vertical wind biases in MLT as well as their potential in advancing understanding of atmospheric dynamics. Algorithm implementation and testing are being conducted to ensure both methods operate optimally within the same dataset, enabling a fair and direct comparison. Key aspects of the comparison will include vertical wind retrieval accuracy, spatial resolution, diagnostic capabilities, and computational efficiency. The anticipated outcomes of this study will provide valuable insights into the relative strengths and weaknesses of the VVP and 3DVAR+DIV methods. While the VVP method is expected to excel in capturing spatially detailed wind patterns, the 3DVAR+DIV algorithm may offer enhanced physical consistency and diagnostic functionality. This study aims to contribute to advancing retrieval techniques and enhance the accuracy of atmospheric models and improve our understanding of MLT dynamics. Such advancements are crucial for refining predictions of global weather and climate systems, particularly in the context of long-term atmospheric monitoring and modeling.