Fast Storm Surge Ensemble Prediction using Searching Optimization of a Numerical Scenario Database

Accurate storm surge forecasts provided rapidly could support timely decision-making with consideration of tropical cyclone (TC) forecasting error. This study developed a fast storm surge ensemble prediction method based on TC track probability forecasting and searching optimization of a numerical scenario database (SONSD). In a case study of the Fujian Province coast (China), a storm surge scenario database was established using numerical simulations generated by 93,150 hypothetical TCs. In a GIS-based visualization system, a single surge forecast representing 2562 distinct typhoon tracks and the occurrence probability of overflow of seawalls along the coast could be achieved in 1–2 min. Application to the cases of Typhoon Soudelor (2015) and Typhoon Maria (2018) demonstrated that the proposed method is feasible and effective. Storm surge calculated by SONSD had excellent agreement with numerical model results (i.e., mean MAE/RMSE: 7.1/10.7 cm, correlation coefficient: >0.9). Tide prediction also performed well with MAE/RMSE of 9.7/11.6 cm versus the harmonic tide, and MAE/RMSE of phase prediction for all high waters of 0.25/0.31 h versus observations. The predicted high-water level was satisfactory (MAE of 10.8 cm versus observations) when the forecasted and actual positions of the typhoon were close. When the forecasted typhoon position error was large, the ensemble surge prediction effectively reduced prediction error (i.e., the negative bias of −58.5 cm reduced to −5.2 cm versus observations), which helped avoid missed alert warnings. The proposed method could be applied in other regions to provide rapid and accurate decision-making support for government departments.

Quantifying non-CO2 contributions to remaining carbon budgets

<p>The IPCC Special Report on 1.5°C concluded that the maximum level of anthropogenic global warming is “determined by cumulative net global anthropogenic CO2 emissions up to the time of net zero CO2 emissions and the level of non-CO2 radiative forcing” in the decades prior to the time of peak warming. Here we quantify this statement, using CO2-forcing-equivalent (CO2-fe) emissions to calculate remaining carbon budgets without treating available mitigation scenarios as a representative sample of possible futures.</p><p>CO2-fe emissions are used to calculate an observationally-constrained estimate of the Transient Climate Response to cumulative Emissions (TCRE) using a large ensemble of historical radaitve forcing timeseries. This observationally-constrained TCRE is used to calculate remaining total CO2-fe budgets from 2018 to 1.5°C, which we compare with results discussed in Chapter 2, SR15. We consider contributions to this total remaining budget from CO2 and non-CO2 sources using both historical observations and the available mitigation scenarios in the IAMC scenario database.</p><p>We calculate remaining CO2 budgets for a 33, 50 or 66% chance of limiting peak warming to 1.5°C and use these to assess the extent to which scenarios in the IAMC scenario database are consistent with ambitious mitigation as outlined in the Paris Agreement. We argue that, assuming no change in the definition of observed global warming and no increase in TCRE due to non-linear feedbacks, scenarios currently classified as “lower 2°C-compatible” are consistent with a best-estimate peak warming of 1.5°C.</p>

Tectonic Origin Tsunami Scenario Database for the Marmara Region

This study presents the first tsunami scenario database in Marmara Sea, Turkey referring to 30 different earthquake scenarios obtained with the combinations of 32 possible fault segments. The fault mechanisms in Marmara Sea have been studied in detail within FP-7 MARSite project, which were derived from various databases and literature review. Tsunami simulations have been performed according to these defined 30 earthquake scenarios by tsunami numerical code NAMI DANCE (NAMIDANCE, 2011) which solves Nonlinear Shallow Water Equations (NLSWE) using leap-frog scheme. For each earthquake scenario, tsunami hydrodynamic parameters, mainly maximum water surface elevations, arrival time of first wave and maximum wave, and water level fluctuations were calculated at 1333 synthetic gauge points meticulously selected along the coasts of Marmara Sea. The overall simulation results indicate that maximum expected wave heights due to these earthquake scenarios are between 1 m and 2 m and even more than 2 m at some locations along Marmara coasts, such as Kadikoy, Halic and Silivri coasts in Istanbul and Bayramdere and Kursunlu districts along the coasts of Bursa province. The estimated maximum water levels at Bostanci, Pendik and Buyukada coasts in Istanbul, Cinarcik and Bandirma towns and at the entrance of Izmit Bay would reach up to 2 m. Tekirdag coasts and Buyuk Cekmece and Bakirkoy coasts in Istanbul and Yalova coasts would experience maximum tsunami wave amplitudes around 1.5 m. The waves reach up to 1 m at Izmit and Gemlik Bays, Erdek Peninsula and Marmara Island. The overwiew of the results reveal that higher historical tsunami wave heights observed in Marmara Sea cannot be explained by only earthquake-generated tsunamis. Therefore, there is strong agreement on considering submarine landslides as the primary tsunami hazard component in the Marmara Sea as experienced during history and expected in the future.