Real-time numerical simulation of tropical cyclone Nilam with WRF: experiments with different initial conditions, 3D-Var and Ocean Mixed Layer Model

2015 ◽  
Vol 77 (2) ◽  
pp. 597-624 ◽  
Author(s):  
Greeshma M. Mohan ◽  
C. V. Srinivas ◽  
C. V. Naidu ◽  
R. Baskaran ◽  
B. Venkatraman
Keyword(s):  
Numerical Simulation ◽  
Tropical Cyclone ◽  
Real Time ◽  
Mixed Layer ◽  
Initial Conditions ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Mixed Layer Model

scholarly journals A multilevel ocean mixed layer model resolving the diurnal cycle: Development and validation

2015 ◽  
Vol 7 (4) ◽  
pp. 1680-1692 ◽  
Author(s):  
Tiejun Ling ◽  
Min Xu ◽  
Xin-Zhong Liang ◽  
Julian X. L. Wang ◽  
Yign Noh
Keyword(s):  
Mixed Layer ◽  
Diurnal Cycle ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Development And Validation ◽  
Mixed Layer Model

scholarly journals Use of a Mixed-Layer Model to Investigate Problems in Operational Prediction of Return Flow

2007 ◽  
Vol 135 (7) ◽  
pp. 2610-2628 ◽  
Author(s):  
John M. Lewis
Keyword(s):  
Sensitivity Analysis ◽  
Gulf Of Mexico ◽  
Boundary Conditions ◽  
Mixed Layer ◽  
Initial Conditions ◽  
Sea Surface ◽  
Return Flow ◽  
Control Vector ◽  
Layer Model ◽  
Mixed Layer Model

Abstract Inaccuracy in the numerical prediction of the moisture content of return-flow air over the Gulf of Mexico continues to plague operational forecasters. At the Environmental Modeling Center/National Centers for Environmental Prediction in the United States, the prediction errors have exhibited bias—typically too dry in the early 1990s and too moist from the mid-1990s to present. This research explores the possible sources of bias by using a Lagrangian formulation of the classic mixed-layer model. Justification for use of this low-order model rests on careful examination of the upper-air thermodynamic structure in a well-observed event during the Gulf of Mexico Experiment. The mixed-layer constraints are shown to be appropriate for the first phase of return flow, namely, the northerly-flow or outflow phase. The theme of the research is estimation of sensitivity—change in the model output (at termination of outflow) in response to inaccuracies or uncertainties in the elements of the control vector (the initial conditions, the boundary conditions, and the physical and empirical parameters). The first stage of research explores this sensitivity through a known analytic solution to a reduced form of the mixed-layer equations. Numerically calculated sensitivity (via Runge–Kutta integration of the equations) is compared to the exact values and found to be most credible. Further, because the first- and second-order terms in the solution about the base state can be found exactly for the analytic case, the degree of nonlinearity in the dynamical system can be determined. It is found that the system is “weakly nonlinear”; that is, solutions that result from perturbations to the control vector are well approximated by the first-order terms in the Taylor series expansion. This bodes well for the sensitivity analysis. The second stage of research examines sensitivity for the general case that includes moisture and imposed subsidence. Results indicate that uncertainties in the initial conditions are significant, yet they are secondary to uncertainties in the boundary conditions and physical/empirical parameters. The sea surface temperatures and associated parameters, the saturation mixing ratio at the sea surface and the turbulent transfer coefficient, exert the most influence on the moisture forecast. Uncertainty in the surface wind speed is also shown to be a major source of systematic error in the forecast. By assuming errors in the elements of the control vector that reflect observational error and uncertainties in the parameters, the bias error in the moisture forecast is estimated. These bias errors are significantly greater than random errors as explored through Monte Carlo experiments. Bias errors of 1–2 g kg−1 in the moisture forecast are possible through a variety of systematic errors in the control vector. The sensitivity analysis also makes it clear that judiciously chosen incorrect specifications of the elements can offset each other and lead to a good moisture forecast. The paper ends with a discussion of research approaches that hold promise for improved operational forecasts of moisture in return-flow events.

scholarly journals Simulation of More Realistic Upper-Ocean Processes from an OGCM with a New Ocean Mixed Layer Model

2002 ◽  
Vol 32 (5) ◽  
pp. 1284-1307 ◽  
Author(s):  
Yign Noh ◽  
Chan Joo Jang ◽  
Toshio Yamagata ◽  
Peter C. Chu ◽  
Cheol-Ho Kim
Keyword(s):  
Mixed Layer ◽  
Upper Ocean ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Mixed Layer Model ◽  
Ocean Processes

scholarly journals Parameterization of Langmuir Circulation in the Ocean Mixed Layer Model Using LES and Its Application to the OGCM

2016 ◽  
Vol 46 (1) ◽  
pp. 57-78 ◽  
Author(s):  
Yign Noh ◽  
Hyejin Ok ◽  
Eunjeong Lee ◽  
Takahiro Toyoda ◽  
Naoki Hirose
Keyword(s):  
Mixed Layer ◽  
High Latitude ◽  
General Circulation ◽  
Circulation Model ◽  
Langmuir Circulation ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Tropical Ocean ◽  
Common Error ◽  
Mixed Layer Model

AbstractThe effect of Langmuir circulation (LC) on vertical mixing is parameterized in the ocean mixed layer model (OMLM), based on the analysis of large-eddy simulation (LES) results. Parameterization of LC effects is carried out in terms of the modifications of the mixing length scale as well as the inclusion of the contribution from the Stokes force in momentum and TKE equations. The performance of the new OMLM is examined by comparing with LES results, together with sensitivity tests for empirical constants used in the parameterization. The new OMLM is then applied to the ocean general circulation model (OGCM) Meteorological Research Institute Community Ocean Model (MRI.COM), and its effect is investigated. The new OMLM helps to correct too shallow mixed layer depths (MLDs) in the high-latitude ocean, which has been a common error in most OGCMs, without making the thermocline in the tropical ocean more diffused. The parameterization of LC effects is found to affect mainly the high-latitude ocean, in which the MLD is shallow in summer and stratification is weak in winter.

scholarly journals A New Ocean Mixed-Layer Model Coupled into WRF

2012 ◽  
Vol 5 (3) ◽  
pp. 170-175 ◽  
Author(s):  
Wang Zi-Qian ◽  
Duan An-Min
Keyword(s):  
Mixed Layer ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Mixed Layer Model

A 31-year Global Diurnal Sea Surface Temperature Dataset Created by an Ocean Mixed-Layer Model

2018 ◽  
Vol 35 (12) ◽  
pp. 1443-1454 ◽  
Author(s):  
Xiang Li ◽  
Tiejun Ling ◽  
Yunfei Zhang ◽  
Qian Zhou
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Sea Surface ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Mixed Layer Model
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