大規模気候変動が地域気象システムに与える影響(Footprint of Large-Scale Climate Variabilities on Regional Weather Systems)

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2024-02-22 パシフィック・ノースウェスト国立研究所(PNNL)

研究者たちは、Puget Sound地域の冬の気象データを使用して、12種類の異なる冬の気象システムを特定しました。これらのシステムは、大規模な気候変動と地域の水文過程に影響を与える降水と気温の反応に違いがあります。大規模な気象ドライバーと地域の水文条件を関連付けることで、2種類の洪水を引き起こす気象条件が浮かび上がりました。一つは過剰な降水を引き起こし、もう一つは暖かい気温下で強い降水と激しい雪解けをもたらします。これらの気象システムは、ENSOやMJOなどの大規模気候変動の影響を反映し、地域の水文過程を理解するための新しい手法を提供します

<関連情報>

気候変動様式と水文気候の地域的極端さをつなぐ気象システム Weather Systems Connecting Modes of Climate Variability to Regional Hydroclimate Extremes

Xiaodong Chen, L. Ruby Leung, Ning Sun
Geophysical Research Letters  Published: 12 December 2023
DOI:https://doi.org/10.1029/2023GL105530

大規模気候変動が地域気象システムに与える影響(Footprint of Large-Scale Climate Variabilities on Regional Weather Systems)

Abstract

Weather system clustering provides a high-level summary of regional meteorological conditions. Most quantitative clustering schemes focus on precipitation alone, which does not sufficiently describe the meteorological conditions driving hydroclimate variability. This study presents the Weather Anomaly Clustering (WAC-hydro), which extends the existing capability of predicting weather systems to predicting hydroclimate variability. Focusing on both precipitation and temperature predictions, WAC-hydro identifies 12 clusters of daily weather anomaly modes in the US Pacific Northwest Puget Sound region during 1981–2020. The influence of El Niño-Southern Oscillation and Madden-Julian Oscillation on regional precipitation can be well approximated by their modulation on the weather clusters. Within each weather cluster, local factors such as topography only play a secondary role in the hydrologic variability. The weather clusters highlight two types of flood-inducing regional weather conditions, one causing floods by inducing positive precipitation anomalies and the other causing floods through combined precipitation and temperature-induced rain-on-snow effect.

Key Points

  • A new weather system clustering model is developed specifically for hydroclimate analysis and prediction
  • Twelve weather systems in the Puget Sound region connect the regional hydroclimate to major modes of climate variability
  • Regional cold season floods are tied to two weather systems, each highlighting unique flood mechanisms

Plain Language Summary

Weather systems clustering (WSC) provides a high-level summary of regional weather conditions, and they have wide applications in weather forecasting, climate analysis, disaster preparation and travel planning. Although many WSC algorithms have been developed, most focus on either phenomenological tagging (i.e., tagging each day as sunny/rainy/snow/fog/etc. type) or predicting a single meteorological variable (usually precipitation P) when optimized toward surface meteorological conditions. Given the importance of both P and temperature (T2) in driving land hydroclimatic variability and extreme, a WSC is developed and optimized for concurrent P and T2 prediction. The system (Weather Anomaly Clustering or WAC-hydro) is demonstrated in a US Pacific Northwest watershed and identified 12 different daily weather clusters during the cold season from 1981 to 2020. These weather clusters feature unique combinations of P/T2 conditions, causing differing regional snowpack and runoff responses: one cluster causes more floods by enhancing P, while another causes floods through a combination of enhanced P and warm temperature induced rain-on-snow. Additionally, the weather clusters can link the regional P to well-known modes of climate variability, suggesting that their modulations on regional hydroclimate variability can be estimated using their modulations on the weather systems. Therefore, WAC-hydro can bridge large-scale climate conditions to regional/local hydroclimatic conditions.

1702地球物理及び地球化学
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