SUBSEASONAL PREDICTION CROSS-EQUATORIAL NORTHERLY SURGE (CASE STUDY: DECEMBER 31, 2019)

• Main Author: Wulan Safitri, Dinda
• Format: Final Project
• Language: Indonesia
• Subjects: Geologi, hidrologi & meteorologi
• Online Access: https://digilib.itb.ac.id/gdl/view/76097
• Institution: Institut Teknologi Bandung

Weather and seasonal predictions have gaps between them. Subseasonal prediction is a prediction period to close the gap between daily weather forecasts and seasonal climate predictions. One of the subseasonal scale phenomena on December 31, 2019–January 1, 2020 is the cross-equatorial northerly surge which affects weather conditions and supports increased rainfall in parts of Indonesia. Subseasonal predictions can be used to analyze atmospheric conditions during subseasonal scale phenomena that cannot be fulfilled by daily weather predictions. Therefore, accurate subseasonal predictions are needed to assess subseasonal scale phenomena. This research uses WRF-ARW model simulations for subseasonal predictions on December 15, 2019-January 15, 2020. The identification of the cold surge phenomenon uses a 5-day pattern and looks at the similarity of the pattern with the ERA5 reference data. The pattern is 5 days before the event (December 26–30, 2019), 5 days of the event (December 31, 2019–January 4, 2020), and 5 days after the event (January 5–9, 2020). As a result of the pattern identification, probabilistic calculations were performed on all four cycles to estimate the uncertainty of the prediction results. Overall, the subseasonal prediction results are able to simulate the cold surge phenomenon. The parameters studied such as relative humidity, surface temperature, meridional wind speed, and moisture transport can identify the occurrence of cold surge in a particular cycle. The relative humidity and surface temperature parameters are identified in cycle 18, while the meridional wind speed and moisture transport parameters are identified in cycle 00. From the cycle 18 simulation results, the cold surge phenomenon is characterized by an increase in dry air mass towards the south and a decrease in surface temperature by 4 °C towards the south to warmer regions. The strengthening of meridional winds and moisture transport towards the south along its movement path, which are the main characteristics of the cold surge phenomenon, are identified in cycle 00. This shows that accurate subseasonal predictions require probabilistic predictions because the simulation results of one cycle cannot fully represent the cold surge signal.