The Tibetan Plateau's Role in the 2003 European Summer Heatwave: A Key to Improving Climate Predictions

A new study reveals a key link between spring snow cover anomalies on the Tibetan Plateau and the 2003 European heatwave. The Tibetan Plateau influenced atmospheric circulation and sea surface temperatures, playing a key role in this event and highlighting its importance in climate predictability.
Published in Earth & Environment and Mathematics
The Tibetan Plateau's Role in the 2003 European Summer Heatwave: A Key to Improving Climate Predictions
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Extreme weather events like heatwaves have captured global attention in recent years due to their devastating effects on human health, agriculture, and the environment. One of the most notorious examples is the 2003 European summer heatwave, which caused widespread fatalities, economic damage, and long-term ecological impacts. While such heatwaves are often attributed to local atmospheric conditions, our research uncovers the surprising interannual predictability of this event and its attribution to the Tibetan Plateau (TP).

Known as the "Third Pole", the TP plays a significant role in shaping global weather patterns through its unique geographic and atmospheric characteristics. Acting as a massive heat source, the TP influences the large-scale circulation patterns in the atmosphere, particularly during boreal summer. The plateau’s ability to generate Rossby waves—large atmospheric waves that propagate across continents—connects the TP with distant regions, including Europe. Our study uncovers how TP land conditions, especially its snow cover, contributed to the interannual predictability of the 2003 European heatwave.

Using a newly developed weakly coupled land data assimilation system, we incorporated land observations only over the TP into the coupled climate model. Remarkably, our model simulations show substantial skill in predicting the 2003 European heatwave two years in advance, reproducing the large-scale temperature anomalies and high-pressure systems over Europe during that summer (Figure 1). This underscores the TP’s significant influence on the atmospheric circulation patterns that drove the heatwave and demonstrates how local land data from the TP can enhance the predictability of such extreme events.

In our analysis, we found that the key mechanism linking the TP to the 2003 European heatwave lies in the snow cover anomalies over the TP (Figure 2). A reduction in spring snow cover over the TP in 2003 led to increased surface heating, which initiated a distinct Rossby wave train. This wave train propagated across Eurasia, ultimately generating high-pressure anomalies over Europe during the summer. The high-pressure system reduced cloud cover and increased net surface radiation, contributing to the extreme temperatures experienced during the heatwave. This physical process demonstrates the far-reaching impact of the TP’s land conditions on European climate, creating a favorable environment for extreme weather events.

Beyond its influence on atmospheric circulation, the TP also played a significant role in modulating ocean conditions during this period. The TP's land states affected sea surface temperatures (SST) in both the Atlantic and Pacific Oceans, further enhancing the predictability of extreme events like the 2003 European heatwave. Figure 3 shows improved initial SST anomalies in January 2001 due to the TP's remote influence. By incorporating TP land data into our climate model, we were able to better simulate the cooling over the tropical Atlantic and tropical eastern Pacific, demonstrating the TP’s broader influence on oceanic and atmospheric systems.

Our findings not only enable a better understanding of the past—they have important implications for the future of climate prediction. By incorporating data from the TP into climate models, we can potentially improve predictions of extreme weather events, not only in Europe but in other regions connected to the TP through atmospheric teleconnections. This research paves the way for improving subseasonal-to-decadal climate forecast foundational to developing better early warning systems that can give communities more time to prepare for extreme heat events, potentially saving lives and reducing economic losses.

Anomalies of the June-August 2003 European heatwave event for (a) surface air temperature (shaded, units: ℃) and 500-hPa geopotential height (contour, units: gpm), (b) soil moisture (shaded, units: kg m-2) and sensible heat flux (contour, units: W m-2), (c) net radiation flux at surface (shaded, units: W m-2). The control simulation (CTRL) is a free running coupled simulation. The HCAST experiments are initialized between April 2000 and January 2001 from the assimilation run incorporating monthly mean GLDAS data only over the Tibetan Plateau. The red boxes show the Europe (10°W-20°E, 35°-55°N) region.

Figure 1. Land and atmosphere anomaly patterns during the 2003 European heatwave. Anomalies of the June-August 2003 European heatwave event for (a) surface air temperature (shaded, units: °C) and 500-hPa geopotential height (contour, units: gpm), (b) soil moisture (shaded, units: kg m-2) and sensible heat flux (contour, units: W m-2), (c) net radiation flux at surface (shaded, units: W m-2). The control simulation (CTRL) is a free running coupled simulation. The HCAST experiments are initialized between April 2000 and January 2001 from the assimilation run incorporating monthly mean GLDAS data only over the Tibetan Plateau. The red boxes show the Europe (10°W-20°E, 35°-55°N) region.

Differences between SNS2_ALO (Tibetan Plateau land states initialized with observed data) and SNS1_AO (no Tibetan Plateau land initialization) of (a) snow cover fraction (shaded, units: %) in spring 2003, (b) surface air temperature (shaded, units: ℃) and 500-hPa geopotential height (contour, units: gpm), (c) low cloud cover (shaded, units: %), and (d) net radiation flux (shaded, units: W m-2) in the summer of 2003. The boundary of the Tibetan Plateau is demarcated by the magenta contour line in (a) and (b) for surface elevation at 3000 m. The orange box in (b), (c), and (d) defines the Europe region (10°W-20°E, 35°-55°N).

Figure 2. Processes connecting the Tibetan Plateau snow cover anomaly with the surface air temperature anomaly in Europe. Differences between SNS2_ALO (Tibetan Plateau land states initialized with observed data) and SNS1_AO (no Tibetan Plateau land initialization) of (a) snow cover fraction (shaded, units: %) in spring 2003, (b) surface air temperature (shaded, units: °C) and 500-hPa geopotential height (contour, units: gpm), (c) low cloud cover (shaded, units: %), and (d) net radiation flux (shaded, units: W m-2) in the summer of 2003. The boundary of the Tibetan Plateau is demarcated by the magenta contour line in (a) and (b) for surface elevation at 3000 m. The orange box in (b), (c), and (d) defines the Europe region (10°W-20°E, 35°-55°N).

Sea surface temperature (SST) anomalies in January 2001 for (a) OBS, (b) SNS3_L with the ocean state from the control simulation, and (c) SNS4_LO with the ocean state initialized from assimilation of Tibetan Plateau observed data, and the differences between SNS3_L and OBS (d) and between SNS4_LO and SNS3_L (e). The Pearson Correlation Coefficient (PCC) of the spatial pattern between observed and SST anomalies in SNS3_L and SNS4_LO over global ocean are given at the top right corner for (b) and (c). The observed and simulated SST anomalies are calculated relative to the 1996-2010 climatology of the observations and simulations, respectively.

Figure 3. Improved simulation of sea surface temperature anomalies in January 2001. Sea surface temperature (SST) anomalies in January 2001 for (a) OBS, (b) SNS3_L with the ocean state from the control simulation, and (c) SNS4_LO with the ocean state initialized from assimilation of Tibetan Plateau observed data, and the differences between SNS3_L and OBS (d) and between SNS4_LO and SNS3_L (e). The Pearson Correlation Coefficient (PCC) of the spatial pattern between observed and SST anomalies in SNS3_L and SNS4_LO over global ocean are given at the top right corner for (b) and (c). The observed and simulated SST anomalies are calculated relative to the 1996-2010 climatology of the observations and simulations, respectively.

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Atmospheric Science
Physical Sciences > Earth and Environmental Sciences > Earth Sciences > Atmospheric Science
Climate and Earth System Modelling
Mathematics and Computing > Mathematics > Applications of Mathematics > Mathematics of Planet Earth > Climate and Earth System Modelling

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