National Research Council of Science & Technology:
Forecasting flash floods an hour in advance
Korea has recently seen a surge in localized torrential rain and floods due to global warming. Frequent flash floods are hard to forecast and, when forecast, the accuracy is low. This often leads to major disasters that take hundreds of lives, as seen in Germany and China (Henan) in July 2021. Floods are one of the deadliest types of natural disasters, but climate change has made the forecasting of them even more challenging.
Researchers at the Korea Institute of Civil Engineering and Building Technology (KICT) have developed a system that can forecast flash floods one hour in advance.
A flash flood is caused by a rapid rise of water flowing into adjacent streams or rivers because of intense rainfall concentrated in small areas and occurs in a fairly short period of time. In low-lying urban areas such as Gangnam in Seoul and in mountainous areas, the speeds of water surge and flow are much faster than in other areas with the same amounts of rainfall. The current heavy rain alert (forecasting based on a certain level of rainfall) is a far cry from actual, perceived risk of flooding. It falls far short of efficiently communicating the risk of flash floods that abruptly hit cities, mountainous areas, or regions along small rivers.
The research team at the KICT, led by Dr. Hwang Seokhwan, developed a system for these regions that forecasts abrupt flash floods based on the rainfall radar data from the Ministry of Environment with regional flood characteristics taken into account. This system will begin to provide forecasting services by the Korean government this year.
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Dam construction mitigates methane emissions along river-estuary continuum of Yangtze River, finds study
Methane (CH4) is the second most important greenhouse gas. Despite occupying only 0.58% of Earth’s non-glaciated land surface, rivers play a critical role in carbon delivery and transformation within aquatic networks, rendering them a significant contributor of CH4 to the atmosphere.
Dam construction has increased since the mid-20th century driven by the growing utilization of hydropower. However, they have a potential to impede carbon transport and impact the biogeochemical cycling of CH4, leading to an uncertainty in riverine CH4 emissions.
Researchers led by Dr. Li Biao and Prof. Wu Qinglong from the Nanjing Institute of Geography and Limnology of the Chinese Academy of Sciences (NIGLAS), along with their collaborators, have carried out an extensive examination of CH4 dynamics along the river-estuary continuum of the Yangtze River.
Their findings were published in Water Research on May 20.
The stable carbon isotope signature (δ13C-CH4) along the river-estuary continuum of the Yangtze River strongly supports the persistence of hydrogenotrophic methanogenesis as the primary pathway within the study area. In order to provide further validation for this hypothesis, the researchers conducted comprehensive tests involving methanogenic community composition and substrate amendment, and ultimately confirmed the prevailing role of hydrogenotrophic methanogenesis along the river-estuary continuum of the Yangtze River.
Through field investigations, the researchers identified a robust correlation between dissolved carbon dioxide (CO2) and dissolved CH4. Based on the established predominance of hydrogenotrophic methanogenesis, they developed a process-based model. Historical CO2 data were further employed to retrospectively examine the historical fluctuations in CH4, uncovering a substantial reduction of 82.5% in CH4 emissions after the construction of the Three Gorges Dam.
“Our study provides new insights from a microbial perspective on CH4 cycling, and it is necessary to take the methanogenic pathway into account when predicting CH4 emissions from inland waters in the future,” said Dr. Li.
Paper: Biao Li et al, Hydrogenotrophic pathway dominates methanogenesis along the river-estuary continuum of the Yangtze River, Water Research (2023). DOI: 10.1016/j.watres.2023.120096
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A multi-model prediction system for ENSO
A multi-model ensemble (MME) prediction system has been recently developed by a team led by Dr. Dake Chen. This prediction system consists of five dynamical coupled models with various complexities, parameterizations, resolutions, initializations, and ensemble strategies, to address various possible uncertainties of ENSO prediction.
One long term (1880-2017) ensemble hindcast demonstrated the superiority of the MME over individual models, evaluated by both deterministic and probabilistic skills, and it suffered less from the spring predictability barrier. Comparison with the North American Multi-Model Ensemble reveals that this MME prediction system can compete with, or even exceed, the counterparts of pioneering prediction models in this world.
Since 2020, the MME system has been issuing the real-time ENSO prediction, which has successfully captured the latest successive triple La Niña events six months ahead including the occurrence of a third-year La Niña event. This MME prediction has been regularly collected by the National Marine Environmental Forecasting Center, used as a consultant advice for national operational prediction.
The research is published in the journal Science China Earth Sciences.
Paper: Ting Liu et al, A multi-model prediction system for ENSO, Science China Earth Sciences (2023). DOI: 10.1007/s11430-022-1094-0
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Hakon Karlsen auf Judith Curry’s Climate Etc.:
How much warming can we expect in the 21st century?
A comprehensive explainer of climate sensitivity to CO2
Short summary
According to the Intergovernmental Panel on Climate Change (IPCC), the atmosphere’s climate sensitivity to CO2is likely between 2.5 and 4.0°C. Simply put, this means that (in the very long term) Earth’s temperature will rise between 2.5 and 4.0°C when the amount of CO2 in the atmosphere doubles.
A 2020 study (Sherwood20) greatly influenced how the IPCC calculated the climate sensitivity. Sherwood20 has been “extremely influential, including in informing the assessment of equilibrium climate sensitivity (ECS) in the 2021 IPCC Sixth Assessment Scientific Report (AR6); it was cited over twenty times in the relevant AR6 chapter“, according to Nic Lewis. A Comment in Nature confirmed this view.1)
Nic Lewis took a closer look at this study, and in September 2022, he published his own study (Lewis22) that criticizes Sherwood20. By correcting errors and using more recent data, including from AR6, Lewis22 found that the climate sensitivity may be about 30% lower than what Sherwood20 had found.
If we know what the climate sensitivity is, and if we also know approximately the amount of greenhouse gases that will be emitted going forward, then the amount of future warming that’s caused by greenhouse gases can also be estimated.
In terms of future emissions, a 2022 study (Pielke22) found that something called RCP3.4 is the most plausible emissions scenario. Traditionally, another scenario (RCP8.5), has been used as a business-as-usual scenario, but this is now widely regarded as an extremely unlikely scenario, with unrealistically high emissions.
Assuming that the climate sensitivity from Lewis22 is correct and that RCP3.4 is the most appropriate emissions scenario, then we find that global temperatures will rise by less than 1°C from 2023 to 2100 (not accounting for natural variability).
How much the Earth’s surface air temperature will rise this century depends, among other things, on how sensitive the atmosphere is to greenhouse gases such as CO2, the amount of greenhouse gases that are emitted, and natural variations. It’s hard to predict natural variations, so the focus here will be on climate sensitivity and greenhouse gas emissions (in particular CO2).
Climate sensitivity
Climate sensitivity is the amount of warming that can be expected in the Earth’s surface air temperature if the amount of CO2 in the atmosphere doubles. So if the climate sensitivity is 3°C, and the amount of CO2 in the atmosphere quickly doubles and stays at that level, then the Earth’s surface air temperature will – in the long term – rise by 3°C.2) In the long term, in this case, is more than 1000 years, but most of the temperature increase happens relatively fast.
The exact value for the climate sensitivity isn’t known, and the uncertainty range has traditionally been very large. In 1979, the so-called Charney report found the climate sensitivity to be between 1.5 and 4.5°C. 34 years later, in 2013, the IPCC reached the exact same conclusion – that it’s likely (66% probability) that the climate sensitivity is between 1.5 and 4.5°C. However, the uncertainty in the Charney report may have been underestimated. So even though the official climate sensitivity estimate didn’t change, it wouldn’t be correct to say that no progress was made during those 34 years.
In climate science, there are several different types of climate sensitivity. I won’t go into detail about the various types just yet, but I’ll have something to say about some of them later in the article – when it becomes relevant. The type of climate sensitivity referred to above – in the Charney report and by the IPCC – is called equilibrium climate sensitivity (ECS).
Why so much uncertainty? (Feedback effects)
There’s broad agreement that without so-called feedback effects, the equilibrium climate sensitivity (ECS) would be close to 1.2°C 3), which is quite low and not particularly dangerous. The reason for the great uncertainty comes from how feedback effects affect the temperature.
A feedback effect can be either positive or negative. A positive feedback effect amplifies warming, contributing to a higher climate sensitivity. A negative feedback dampens warming and contributes to a lower climate sensitivity.
The strengths of feedback effects can vary based on the atmosphere’s temperature and composition, and how much of the Earth is covered by ice and vegetation, among other things. Earth’s climate sensitivity is thus not a constant. And for this reason, the equilibrium climate sensitivity, ECS, has been defined as the long-term increase in temperature as a result of a doubling of CO2 from pre-industrial levels (which was about 284 parts per million (ppm)).
Atmospheric CO2 concentration currently stands at approximately 420 ppm, which means there’s been a near 50% increase since the second half of the 19th century.4) Since the concentration of CO2 hasn’t yet doubled (and also since the long term is a long way away), the temperature has risen less than than the magnitude of the equilibrium climate sensitivity. To be more precise, the temperature increase has been approximately 1.2°C over the past 150 years.
Types of feedback mechanisms
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Reconstructing land temperature changes of the past 2,500 years using speleothems from Pyrenean caves (NE Spain)
Reconstructing of past temperatures at regional scales during the Common Era is necessary to place the current warming in the context of natural climate variability. Here we present a composite record of oxygen isotope variations during last 2500 years based on eight stalagmites from four caves in the central Pyrenees (NE Spain) dominated by temperature variations, with precipitation playing a minor role. The dataset is compared with other Iberian reconstructions that show a high degree of internal coherence with respect to variability at the centennial scale. The Roman Period (especially 0–200 AD), the Medieval Climate Anomaly, and part of the Little Ice Age represent the warmest periods, while the coldest decades occurred during the Dark Ages and most of the Little Ice Age intervals (e.g., 520–550 AD and 1800–1850 AD). Importantly, the LIA cooling or the MCA warming were not continuous or uniform and exhibited high decadal variability. The Industrial Era shows an overall warming trend although with marked cycles and partial stabilization during the last two decades (1990–2010). The strong coherence between the speleothem data, European temperature reconstructions and global tree-ring data informs about the regional representativeness of this new record as Pyrenean past temperature variations. Solar variability and major volcanic eruptions appear to be the two main drivers of climate in southwestern Europe during the past 2.5 millennia.