Kulp, S.A., Strauss, B.H. New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding. Nat Commun 10, 4844 (2019) https://www.nature.com/articles/s41467-019-12808-z
As a part of the natural cycle, sea-levels have increased or decreased throughout our planet’s history. Water frozen in ice caps would melt during the hotter periods, contributing to the sea level rise. This was usually a gradual process spread over thousands of years. But over the recent decades of unabated CO2 emissions, we seem to have accelerated the sea-level rise and the flooding events along the coasts. Higher temperatures resulting from the CO2 emissions affect the sea-level in two important ways, the rapid melting of glaciers and as the water gets warmer it expands occupying more space. Under the accelerated warming scenario, the accurate estimates of sea-level projection are very important for coastal planning and safeguarding a large number of people.
Previous estimates suggest that the global mean sea level is likely to rise by 20-30 cm by 2050. By the end of this century, a 50-70 cm increase under moderate CO2 emissions and 70-100 cm under high CO2 emissions is expected. More recent projections take Antarctic ice sheet melting into account which further pushes up the estimated values. Such estimates require accurate data on land topography and elevation. And that is where the difficulties arise. High accuracy elevation data from airborne light detection and ranging system is only available for the coastal US, much of coastal Australia and parts of Europe. For other parts of the world, scientists have to depend on easily accessible and widely available satellite-based data that is prone to large errors particularly in densely vegetated or populated areas. In their recent study Kulp et al., have attempted to develop a new coastal elevation model by reducing the error in the satellite data. The satellite data capture the upper surface, which includes the high rise buildings and the vegetation rather than the bare Earth and hence the large errors.
Getting to know the new model better
To put it very simply, the authors of the study first looked at the locations where both the satellite (low accuracy) and airborne (high accuracy) datasets were available. Contribution from the various factors (vegetation, buildings, population density) that lead to the differences in the two datasets were identified at these locations. At the new locations, the dominant factors were identified and their contributions were added or subtracted from the already available satellite data.
Major lessons from the new model
There are three major lessons that we can draw from the recent study. First, the new model suggests that currently, 250 million people are living below the annual flood line. This is about four times higher than previously estimated by the satellite data and this number is expected to increase to 300 million by 2050 and 480 million by the end of this century. Secondly, the scientists noted that change in the sea-level is not the straightforward addition of the effects of CO2 emissions, Antarctic ice melting, flooding, and other conditions. It, in fact, is a complex interaction of these conditions which exceeds simple addition. Finally, and probably the most important, irrespective of satellite or the new model data, the developing countries across Asia and the small island developing states will be the worst hit by the coastal flooding and permanent inundation. China, Bangladesh, India, Vietnam, Indonesia, Thailand, the Philippines, and Japan account for 70 % of the population threatened by coastal inundation. Bangladesh, India, Indonesia, and the Philippines see a predicted 5 to 10-fold increase in the estimates. Unfortunately, the model suggests that even with deep cuts in CO2 emissions about 20% of the population of some Asian countries would permanently fall below the high tide line.
Limitations of the new model
Despite several advances, there are some limitations to the study. In the dense cities and areas with exceptionally tall buildings, the errors are still high. Another limitation comes from the unavailability of a very accurate population count; the current study utilizes the 2010 population density. These factors might lead to an underestimation of the number of people exposed to the rising seas. At the same time absence of data on sea walls, levees and other defenses in various countries might result in an overestimation. Even in light of these limitations, the most optimistic sea levels projected by this model are much higher than the most pessimistic projections with the satellite data.
Hi, I am a Ph.D. student at the National Institute of Oceanography, India. I am currently studying the particulate and dissolved organic matter dynamics in the central and eastern Arabian Sea. I am also interested in the effects of climate change on marine systems, as well as outreach and science communication. My interest in science communication stems from the lack of effective scientific outreach in my country and I wish to contribute to improving that. In my spare time, I like to read non-fiction and learn about things I didn’t know existed.