Center for Ocean-Atmospheric Prediction Studies

Abstract: A composite study is presented analyzing the influence of upper-tropospheric troughs on the evolution of precipitation in twelve Atlantic tropical cyclones (TCs) between the years 2000 � 2005. The TRMM Multi-Satellite Precipitation Analysis (TMPA) is used to examine the enhancement of precipitation within a 24 h window centered on trough interaction (TI) time in a shear-vector relative coordinate system. Eddy angular momentum flux convergence (EFC) computed from European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses is employed to objectively determine the initiation of a TI while adding insight, along with vertical wind shear, into the intensification of TC vortices. The relative roles of the dynamics (EFC and vertical wind shear) and thermodynamics (moist static energy potential) in TIs are outlined in the context of precipitation enhancement that provides quantitative insight into the “good trough”/“bad trough” paradigm. The largest precipitation rates and enhancements are found in the down-shear left quadrant of the storm, consistent with previous studies of convective asymmetries. Maximum mean enhancement values of 1.4 mm/h are found at the 200 km radius in the down-shear left quadrant. Results indicate that the largest precipitation enhancements occur with “medium” TIs; comprised of EFC values between 17 � 22 (m/s)/day and vertical wind shear Sensitivity tests on the upper vertical wind shear boundary reveal the importance of using the tropopause for wind shear computations when a TC enters mid-latitude regions. Changes in radial mean precipitation ranging from 29 � 40 % across all storm quadrants are found when using the tropopause as the upper boundary on the shear vector. Tests on the lower boundary using QuikSCAT ocean surface wind vectors expose large sensitivities on the precipitation ranging from 42 � 60 % indicating that the standard level of 850 hPa, outside of the boundary layer in most storms, is more physically reliable for computing vertical wind shear. These results should help to improve TC quantitative precipitation forecasting (QPF) as operational forecasters routinely rely on crude statistical methods and rules of thumb for forecasting TC precipitation.

Abstract: Gridded QuikSCAT data has been used to show that a strong confluence zone of the Southeast Pacific Intertropical Convergence Zone (SITCZ) existed in 2000 � 2002 during boreal spring, and the Panama wind jet contributes to its variability. Time series analysis of winds off the Gulf of Panama and convergence advection into the Southern Hemisphere (from 80W to 95W) show these winds kept the SE Trades out of the Northern Hemisphere and created a confluent zone in the Southern Hemisphere. A monthly averaged SITCZ is maintained by the deceleration of the SE Trades that flow from warm water toward the equatorial cold tongue, creating a speed convergent zone south of the equator. Images of wind trajectories show zonally orientated SE Trade winds that were deflected from a divergent zone parallel to the coast of South America converge with more meridional Trades over warm waters. Panamanian winds crossed into the Southern Hemisphere to contribute to this convergence. It is hypothesized that this confluent zone can be intensified by the Panamanian winds. In 2002, the SITCZ confluent zone occurred with more intense Panamanian gap flow than the previous two years. Cross equatorial SE Trades wrapped anti-cyclonically around a divergent pocket in the Northern Hemisphere and became southward winds, which allowed the Panamanian winds to enter the Southern Hemisphere and intensify the SITCZ. Variability in the Panamanian winds makes a substantial contribution to the evolution of the SITCZ.

Abstract: Scatterometer observations of vector winds are used to examine the amplitudes of synoptic and diurnal cycles. Scatterometers have the advantage of providing global coverage over water; however, irregular temporal sampling complicates the analyses. A least squares technique is used in determination of the amplitudes and phases of the diurnal and synoptic cycles on spatial scales of 5°, 15°, and 30°. In open ocean areas and regions with sufficient open water, the magnitudes of the diurnal and synoptic cycles are 1.0 ms-1 and 3.5ms-1, respectively. Diurnal amplitudes are highest in the polar regions and close to land surfaces due to sea breeze effects. The fraction of variance explained by the diurnal cycle is greatest near the equator. Synoptic amplitudes are consistently larger downwind of land from storm tracks and in the southern polar region as the time analyzed is during the southern winter season.

Abstract: State of the art fully three-dimensional ocean models are very computationally expensive and their adjoints are even more resource intensive. However, many features of interest are approximated by the first baroclinic mode over much of the ocean, especially in the lower and mid latitude regions. Based on this dynamical feature, a new type of data assimilation scheme to assimilate sea surface height (SSH) data, a reduced-space adjoint technique, is developed and implemented with a three-dimensional model using vertical normal mode decomposition. The technique is tested with the Navy Coastal Ocean Model (NCOM) configured to simulate the Gulf of Mexico. The assimilation procedure works by minimizing the cost function, which generalizes the misfit between the observations and their counterpart model variables. The “forward” model is integrated for the period during which the data are assimilated. Vertical normal mode decomposition retrieves the first baroclinic mode, and the data misfit between the model outputs and observations is calculated. Adjoint equations based on a one-active-layer reduced gravity model, which approximates the first baroclinic mode, are integrated backward in time to get the gradient of the cost function with respect to the control variables (velocity and SSH of the first baroclinic mode). The gradient is input to an optimization algorithm (the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used for the cases presented here) to determine the new first baroclinic mode velocity and SSH fields, which are used to update the forward model variables at the initial time. Two main issues in the area of ocean data assimilation are addressed: 1. How can information provided only at the sea surface be transferred dynamically into deep layers? 2. How can information provided only locally, in limited oceanic regions, be horizontally transferred to ocean areas far away from the data-dense regions, but dynamically connected to it? The first problem is solved by the use of vertical normal mode decomposition, through which the vertical dependence of model variables is obtained. Analyses show that the first baroclinic mode SSH represents the full SSH field very closely in the model test domain, with a correlation of 93% in one of the experiments. One common way to solve the second issue is to lengthen the assimilation window in order to allow the dynamic model to propagate information to the data-sparse regions. However, this dramatically increases the computational cost, since many oceanic features move very slowly. An alternative solution to this is developed using a mapping method based on complex empirical orthogonal functions (EOF), which utilizes data from a much longer period than the assimilation cycle and deals with the information in space and time simultaneously. This method is applied to map satellite altimeter data from the ground track observation locations and times onto a regular spatial and temporal grid. Three different experiments are designed for testing the assimilation technique: two experiments assimilate SSH data produced from a model run to evaluate the method, and in the last experiment the technique is applied to TOPEX/Poseidon and Jason-1 altimeter data. The assimilation procedure converges in all experiments and reduces the error in the model fields. Since the adjoint, or “backward”, model is two-dimensional, the method is much more computationally efficient than if it were to use a fully three-dimensional backward model.