THE INFLUENCE OF COLD SURGE (CS) AND CROSSEQUATORIAL NORTHERLY SURGE (CENS) ON NET SURFACE HEAT FLUX (NSHF) AND WAVE HEIGHT IN THE INNER WATERS OF INDONESIA (CASE STUDY: WESTERN INDONESIA) - Agdialta, Rezfiko
On Java Island, the phenomena of the Cold Surge (CS) and Cross-Equatorial Northerly Surge (CENS) are usually connected with more rainfall. Still not fully understood, though, are the basic effects of CS and CENS on other parameters including Wind Speed (WS), Net Surface Heat Flux (NSHF), Shortwave Radiation (SWR), Longwave Radiation (LWR), Surface Latent Heat Flux (LHF), Surface Sensible Heat Flux (SHF), Rate of SST Change (dSST/dt), and Significant Wave Height (SWH). Richening the scientific literature requires a better knowledge of the effects of CS and CENS on many criteria. The objective of this work is to investigate on WS, NSHF, SWR, LWR, LHF, SHF, dSST/dt, and SWH the effects of CS and CENS events. The nCS-nCENS (neutral circumstances without CS and CENS), nCS-CENS (CENS events not induced by CS), CS-nCENS (CS events without producing CENS), and CS-CENS (simultaneous occurrence of CS and CENS) phases were investigated in the waters of Western Indonesia. For data screening, this study employs Oceanic Nino Index (ONI), Dipole Mode Index (D MI), and Madden-Julian Oscillation (MJO) Index from 2000 to 2023. Dates with neutral conditions free from El Niño-Southern Oscillation (ENSO), Dipole Mode (DM), and MJO phases 3, 4, and 5 were sought by means of this data filtering technique. To identify CS episodes the study additionally employs Mean Sea Level Pressure (MSLP) data and wind speed data at the 850 hPa level. CENS incidents were noted using surface layer meridional wind speed data. NSHF was computed using SWR, LWR, LHF, and SHF data; the anomalies of these parameters were examined versus neutral conditions. The rate of SST change over time was computed using SST data then examined against neutral conditions. Furthermore required for analysis of the deviations of this parameter against neutral conditions were SWH data. In this work, the deviations of these parameters during the nCS-CENS, CSnCENS, and CS-CENS phases were investigated and matched with neutral conditions. Results of the composite anomaly show that increases in WS and SWH are strongly influenced by CS-CENS occurrences. 0.83 m/s, 0.61 m/s, and 2.08 m/s were the average WS in the research region for the nCS-CENS, CS-nCENS, and CS-CENS phases respectively. This indicates that the CS-CENS phase produces the most wind speed deviations. With a cosine similarity value of 0.91, one can deduce from the cosine similarity results obtained from the angle between two eigenvectors from the Principal Component Analysis (PCA) biplot diagram that the rise in WS iv anomalies during the CS-CENS phase has a positive linear relationship with SWH anomalies. Consequently, a rise in WS might cause SWH to rise as well. Reflecting the maximum SWH also occurring during the CS-CENS phase, the average SWH anomaly during the nCS-CENS, CS-nCENS, and CS-CENS phases was 0.06 m, 0.14 m, and 0.37 m correspondingly. By contrast, with a cosine similarity value of -1, the rise in WS throughout the CS-CENS period shows a negative linear connection with LHF. This suggests that a rise in WS anomalies may cause LHF to drop in the negative direction from the sea to the atmosphere. -17.36 W/m², -10.88 W/m², and -29.04 W/m² were the average LHF anomalies for the nCS-CENS, CS-nCENS, and CS-CENS phases respectively. This also suggests that during the CS-CENS phase the LHF is transferred from the sea to the atmosphere more extensively. A loss of heat at the sea surface can result from this more LHF movement from the water to the atmosphere.