Climate Variability Diagnosed from the Spherical Coordinates
The spherical coordinates are commonly used in oceanography; in particular, most climate studies and datasets are based on the z-coordinate. Therefore, in the first part of this chapter we examine the climate variability using the z-coordinate; at the end
- PDF / 16,200,733 Bytes
- 43 Pages / 504.567 x 720 pts Page_size
- 94 Downloads / 195 Views
Climate Variability Diagnosed from the Spherical Coordinates
The spherical coordinates are commonly used in oceanography; in particular, most climate studies and datasets are based on the z-coordinate. Therefore, in the first part of this chapter we examine the climate variability using the z-coordinate; at the end of this chapter, we will also explore using longitudinal and latitudinal coordinates to diagnose the climate variability. In these coordinates climate signals can be separated into the external and internal modes. The external modes indicate the net change of heat content (or salt/density content) integrated over the world oceans; these modes are directly linked to anomalies in net external forcing, such as heat flux (or freshwater/density flux). On the other hand, the internal modes represent the internal exchanges of heat, salt and density between different layers (latitude/longitude bands). These processes may involve internal diabatic components, which give rise to changes of heat (salt/density) in individual layers; however, the global net contribution of these internal diabatic processes must be zero by definition. Therefore, separating the climate signals into external and internal modes in these coordinates may reveal interesting phenomena hidden in climate changes. The dynamical/thermodynamic processes leading to such internal modes of variability may take place primarily within isopycnal layers, which are slanted in the traditional spherical coordinates. Hence, to explore the cause of climate variability observed in the ocean, one should also look at climate variability from
different angles. Isopycnal/isothermal analysis is one of such tools, and it will be examined in details in this book. Although most studies of climate changes are focused on the upper ocean, with the limited information available about the deep ocean, one can also infer the climate variability in the deep ocean, from climate datasets generated from either observations or numerical simulations. Due to the server limits of data availability for the deep ocean, any result related to the deep ocean is at best speculation only. Nevertheless, such studies may reveal some important dynamics related to climate changes. Our discussion below is based on the GODAS data (Behringer and Xue 2004).
2.1
Climate Variability Diagnosed in the z-Coordinate
In the following discussion, we calculate the total heat content anomaly for the world oceans, with the mean annual cycle removed. Note that the GODAS data is a monthly mean climatology which began in 1980. The horizontal resolution is 1 0:333 ; there are 40 non-uniform layers in the vertical direction, and the center of the lowest layer is at the depth of 4478 m. Since the vertical grid in the GODAS data is non-uniform, we will use heat content per unit thickness, in units of J/m. In addition, figures are plotted in a
© Higher Education Press and Springer Nature Singapore Pte Ltd. 2020 R. X. Huang, Heaving, Stretching and Spicing Modes, https://doi.org/10.1007/978-981-15-2941-2_2
1
Data Loading...
