Extreme Warm Land Temperature in Spring 2024 in Tibetan Plateau and Subsequent June Catastrophic Flood in Southern Yangtze River and Drought to the North - a Typical GEWEX/LS4P Scenario under Warm Climate

This presentation introduces a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over high mountains, especially the Tibetan Plateau (TP) and Rocky Mountains (RM) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. It is well-known that the root cause of extreme hydroclimate events under climate change is in the variability of precipitation at subseasonal to seasonal (S2S) time scales. Yet, the skill of S2S precipitation prediction has remained poor to date. The S2S precipitation predictability has been mainly attributed to sea surface temperature (SST) variability. However, observational data analyses and modeling studies have consistently shown that SST alone can only partially explain the phenomena of S2S predictability. The GEWEX/LS4P (Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction) is the first international effort to explore the possibility that spring LST/SUBT over high mountain areas is a crucial factor that can lead to significant improvement in S2S precipitation prediction through the remote effects of land/atmosphere interactions. The LS4P experiment focused on whether the TP LST/SUBT anomaly provides an additional source for subseasonal-to-seasonal (S2S) predictability. In the LS4P Phase I, a cold 2003 TP case was investigated, while LS4P Phase II focuses on TP warm case, which is particularly relevant under current global warming situation.

Observational evidence revealed the land memory and statistically significant lag relationship between spring TP/RM LST and summer precipitation in downstream regions. Based on observation and prototype modeling studies, LS4P has proposed that warm (cold) TP spring contributes summer flood (drought) in the southern Yangtze River basin, and opposite anomaly to the north. With the newly developed LS4P initialization method for TP land temperature, the observed cold spring 2003 surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature and also consistent with observation. Among 8 hotspots, six are along the Tibetan-Rocky Mountain Circumglobal wave train path (TRC). Consideration of the TP LST/SUBT effect has produced about 25%-50% of observed precipitation anomalies in most hotspot regions. For comparison, the global SST effect has also been tested and 6 hotspot regions with significant SST effects were identified in the 2003 case, explaining about 25-50% of precipitation anomalies over most of these regions.

With the completion of the LS4P-I, the LS4P-II has been launched, which focuses on the 1998 case, when the spring was very warm (cold) in TP (RM) and the Yangtze River (Southern Great Plains) had severe summer flood (drought), respectively. However, since the TP spring and summer situation in 2024 is very similar to what happened in 1998, we will present our latest study on the 2024 case. In June 2024, Southern Yangtze River area have been battered by devastating heavy rainfall, causing catastrophic floods there and drought (heat) to the north. Spring 2024 had an extremely warm TP land temperature, 2.56°C above climatology, in May, much warmer than May 1998 (1.35°C). As such the severe flood in June 2024 is a typical LS4P scenario, consistent with the LS4P hypothesis. We have designed a series of experiments, following the LS4P-II protocol, to test the spring 2024 TP LST/SUBT effect and compare this effect with the SST forcing. The NCEP Global Forecast System was coupled with a land model, SSiB, to conduct numerical experiments. The results indicated that after reproducing 70% of observed TP T2m anomaly, about 50% of the heavy precipitation anomaly was predicted. This presentation will present the LS4P hypothesis and approach, and the observational and modeling results demonstrating that the spring 2024 TP LST/SUBT anomaly was one of the major factors that produced summer catastrophic flood in eastern China and relevant mechanism.