Sonification -- the mapping of data to non-speech audio -- offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870--2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two-dimensional acoustic phase space. Recurrence-based diagnostics, convex hull geometry, and coupling analysis reveal that the sonification pipeline preserves key dynamical signatures: alternating modes produce the highest trajectory recurrence rates, echoing ENSO's quasi-periodicity; layered polyphonic modes explore the broadest phase space regions; and the two scale families induce qualitatively distinct coupling regimes between spectral brightness and energy -- predominantly anti-phase in pelog but near-independent in slendro. Phase space trajectory analysis provides a rigorous geometric framework for comparing sonification designs within a complex systems context. Perceptual validation remains necessary; we contribute the dynamical systems methodology for evaluating such mappings.

翻译：可听化——将数据映射为非语音音频——为表示复杂动力系统提供了一个尚未充分探索的通道。我们将厄尔尼诺-南方涛动（ENSO）这一低维气候混沌的典型范例作为测试案例，通过复杂系统诊断方法评估文化情境下的可听化效果。利用Niño 3.4海表温度异常指数（1870–2024）的参数映射可听化技术，我们将ENSO变率编码到两种传统爪哇甘美兰五声音阶系统（pelog与slendro）中，并采用四种作曲策略，随后将生成的音频作为二维声学相空间中的轨迹进行分析。基于递归的诊断、凸包几何分析及耦合分析表明，该可听化流程保留了关键动力学特征：交替模式产生最高的轨迹递归率，呼应了ENSO的准周期性；分层复调模式探索了最广阔的相空间区域；两种音阶体系在频谱亮度与能量之间引发了性质迥异的耦合机制——pelog主要表现为反相位耦合，而slendro则呈现近独立状态。相空间轨迹分析为在复杂系统背景下比较不同可听化设计提供了严谨的几何框架。感知验证仍有待进行；我们提出的动力系统方法论为评估此类映射关系提供了理论工具。