Evaluating and Improving Parameterizations of the Variance of Temperature Fluctuations Over Heterogeneous Landscapes for Surface Boundary Conditions in Atmospheric Models

Author(s):  
Tyler Waterman ◽  
Gabriel Katul ◽  
Andy Bragg ◽  
Nathaniel Chaney

<p>The implementation of higher-order turbulence closure schemes in Earth system models (e.g., the Cloud Layers Unified by Binormals; CLUBB) aims to improve the modeling of convection and radiative transfer in numerical weather prediction and climate models. However, the added value of these schemes is constrained by the specification of boundary conditions on higher-order statistics. At the land surface, many of the higher order turbulence statistics that are required as boundary conditions are parameterized using formulations more appropriate for stationary and planar-homogeneous flow in the absence of subsidence. A case in point is the variance of the potential temperature fluctuations.  Because of the additive nature of variances arising from non-uniformity in surface heating, current parameterizations are not readily generalizable. The current scheme used in CLUBB, as well as other models, relies on limited studies over uniform terrain, with the variance entirely determined by local sensible heat flux, friction velocity, and the Obukhov stability parameter without regard to local site characteristics. This presentation aims to address this weakness by leveraging the National Ecological Observation Network (NEON) network of eddy covariance towers to validate the current parameterization scheme for potential temperature variance, as well as propose improvements for more heterogeneous terrain.</p><p>The turbulence fluctuations of temperature at 39 NEON sites are processed and quality controlled, removing points occurring at night, while precipitation is falling, and with sub-zero temperatures. Results overall indicate the current scheme performs well, especially over flat homogeneous terrain where local flux relationships dominate. When there is sufficiently heterogeneous, rough terrain or non-closure of the local energy balance, however, existing schemes fail to accurately estimate the variances in temperature. In these cases, the parameterization needs to be modified, and initial results suggest simple adjustments can yield improvements and reduce error close to that of the uniform sites with local energy balance closure. The successful improvement of the temperature variance parameterization scheme implies high potential for similar, new, empirically derived parameterizations for the surface boundaries for other higher order turbulent statistics (e.g. temperature skewness) in atmospheric turbulence models.</p>

2017 ◽  
Vol 24 (3) ◽  
pp. 351-366 ◽  
Author(s):  
Geoffrey Gebbie ◽  
Tsung-Lin Hsieh

Abstract. The Lagrange multiplier method for combining observations and models (i.e., the adjoint method or 4D-VAR) has been avoided or approximated when the numerical model is highly nonlinear or chaotic. This approach has been adopted primarily due to difficulties in the initialization of low-dimensional chaotic models, where the search for optimal initial conditions by gradient-descent algorithms is hampered by multiple local minima. Although initialization is an important task for numerical weather prediction, ocean state estimation usually demands an additional task – a solution of the time-dependent surface boundary conditions that result from atmosphere–ocean interaction. Here, we apply the Lagrange multiplier method to an analogous boundary control problem, tracking the trajectory of the forced chaotic pendulum. Contrary to previous assertions, it is demonstrated that the Lagrange multiplier method can track multiple chaotic transitions through time, so long as the boundary conditions render the system controllable. Thus, the nonlinear timescale poses no limit to the time interval for successful Lagrange multiplier-based estimation. That the key criterion is controllability, not a pure measure of dynamical stability or chaos, illustrates the similarities between the Lagrange multiplier method and other state estimation methods. The results with the chaotic pendulum suggest that nonlinearity should not be a fundamental obstacle to ocean state estimation with eddy-resolving models, especially when using an improved first-guess trajectory.


2016 ◽  
Author(s):  
Geoffrey Gebbie ◽  
Tsung-Lin Hsieh

Abstract. The Lagrange multiplier method for combining observations and models (i.e., the adjoint method or "4D-VAR") has been avoided or approximated when the numerical model is highly nonlinear or chaotic. This approach has been adopted primarily due to difficulties in the initialization of low-dimensional chaotic models, where the search for optimal initial conditions by gradient descent algorithm is hampered by multiple local minima. Although initialization is an important task for numerical weather prediction, ocean state estimation usually demands an additional task – solution of the time-dependent surface boundary conditions that result from atmosphere–ocean interaction. Here, we apply the Lagrange multiplier method to an analogous boundary control problem, tracking the trajectory of the forced chaotic pendulum. Contrary to previous assertions, it is demonstrated that the Lagrange multiplier method can track multiple chaotic transitions through time, so long as the boundary conditions render the system controllable. Thus, the nonlinear timescale poses no limit to the time interval for successful Lagrange multiplier-based estimation. That the key criterion is controllability, not a pure measure of dynamical stability or chaos, illustrates the similarities between the Lagrange multiplier method and other state estimation methods. The results with the chaotic pendulum suggest that there is no fundamental obstacle to ocean state estimation with eddy-resolving, highly-nonlinear models, especially when using an improved first-guess trajectory.


2008 ◽  
Vol 47 (10) ◽  
pp. 2627-2644 ◽  
Author(s):  
R. Hamdi ◽  
V. Masson

Abstract The Town Energy Balance module bridges the micro- and mesoscale and simulates local-scale urban surface energy balance for use in mesoscale meteorological models. Previous offline evaluations show that this urban module is able to simulate in good behavior road, wall, and roof temperatures and to correctly partition radiation forcing into turbulent and storage heat fluxes. However, to improve prediction of the meteorological fields inside the street canyon, a new version has been developed, following the methodology described in a companion paper by Masson and Seity. It resolves the surface boundary layer inside and above urban canopy by introducing a drag force approach to account for the vertical effects of buildings. This new version is tested offline, with one-dimensional simulation, in a street canyon using atmospheric and radiation data recorded at the top of a 30-m-high tower as the upper boundary conditions. Results are compared with simulations using the original single-layer version of the Town Energy Balance module on one hand and with measurements within and above a street canyon on the other hand. Measurements were obtained during the intensive observation period of the Basel Urban Boundary Layer Experiment. Results show that this new version produces profiles of wind speed, friction velocity, turbulent kinetic energy, turbulent heat flux, and potential temperature that are more consistent with observations than with the single-layer version. Furthermore, this new version can still be easily coupled to mesoscale meteorological models.


2006 ◽  
Vol 77 (10) ◽  
pp. 10F302
Author(s):  
T. Numakura ◽  
T. Cho ◽  
J. Kohagura ◽  
M. Hirata ◽  
R. Minami ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document