TY  - JOUR
A1  - Steirou, Eva
A1  - Gerlitz, Lars
A1  - Apel, Heiko
A1  - Sun, Xun
A1  - Merz, Bruno
T1  - Climate influences on flood probabilities across Europe
JF  - Hydrology and earth system sciences : HESS
N2  - The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods.
Y1  - 2019
U6  - https://doi.org/10.5194/hess-23-1305-2019
SN  - 1027-5606
SN  - 1607-7938
VL  - 23
IS  - 3
SP  - 1305
EP  - 1322
PB  - Copernicus
CY  - Göttingen
ER  - 
TY  - JOUR
A1  - Gerlitz, Lars
A1  - Steirou, Eva
A1  - Schneider, Christoph
A1  - Moron, Vincent
A1  - Vorogushyn, Sergiy
A1  - Merz, Bruno
T1  - Variability of the Cold Season Climate in Central Asia. Part II: Hydroclimatic Predictability
JF  - Journal of climate
N2  - Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November-March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Nino. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.
KW  - Asia
KW  - Climate prediction
KW  - Seasonal forecasting
KW  - North Atlantic Oscillation
KW  - Southern Oscillation
Y1  - 2019
U6  - https://doi.org/10.1175/JCLI-D-18-0892.1
SN  - 0894-8755
SN  - 1520-0442
VL  - 32
IS  - 18
SP  - 6015
EP  - 6033
PB  - American Meteorological Soc.
CY  - Boston
ER  -