Large scale circulation patterns associated to seasonal dry and wet conditions over the Czech Republic

Transcription

1 Large scale circulation patterns associated to seasonal dry and wet conditions over the Czech Republic C. BORONEANT, V. POTOP, M. MOZNÝ3, P. ŠTEPÁNEK3, P. SKALÁK3 Center for Climate Change, Geography Dept., University Rovira I Virgili, Tortosa, Spain Czech University of Life Sciences Prague, Dept.of Agroecology and Biometeorology, Czech Republic 3 Czech Hydrometeorological Institute, Prague, Czech Republic

2 Outline Motivation Objectives Data & Methods Results Summary & concluding remarks

3 Motivation Recent studies based on long term observations () point out on significant trends toward dry conditions in the Czech Republic (Trnka et al. and Brázdil et al. ). The intensity and frequency of drought in the region were shown to be due to changes in near surfaces temperature rather than changes in precipitation. To our knowledge, relatively few studies have dealt so far with the connection between drought in the Central Europe and its large scale driving factors. What are the large scale factors associated to seasonal moisture variability over the Czech Republic based on station observations?

4 Objectives To investigate the relationship between moisture indicators (SPEI drought index) and the large scale patterns (MSLP, PWC, SST) associated to seasonal dry and wet conditions in the Czech Republic

5 Data Monthly temperature means and total precipitation from 4 climatological stations uniformly covering the Czech Republic Global gridded data ( x ) Monthly Sea Level Pressure (MSLP) and Precipitable water content (PWC) (Compo et al., ; Whitaker et al. 4), and Sea Surface Temperature (SST) from NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b Period of analysis: -

6 Methods Standardized Precipitation-Evapotranspiration Index - SPEI (Vicente-Serrano, ) EOF Analysis (Preisendorfer, von Storch 5) Composite maps ( MSLP, PWC,SST vs +/-.5 stdv PC of seasonal SPEI mo lag)

7 Results

8 Climate of the Czech Republic Climatic classification according to Quitt () cold on the borderline between temperate continental and oceanic; relatively hot summers and cold, cloudy and snowy winters. The temperature difference between summer and winter is relatively high, due to the landlocked geographical position Continentality increases from W to E and is greater in the lowlands than at higher locations warm moderate warm Continenta lity

9 Temporal evolution of seasonal SPEI at month lag averaged over all 4 stations.5 SPEI_ avg all_4 st winter SPEI_ avg_all 4 st summer SPEI_ avg all_4 st spring SPEI_ avg_all 4 st autumn

10 The explained variance of the first three EOFs of seasonal SPEI at month lag Explained variance (%) wi sp su au SPEI_ EOF EOF EOF

11 5 4 3 Longitude ( E) 4 5 EOF summer Longitude ( E) 4 5 EOF.. -. summer Latitude ( N) 5 Latitude ( N) Latitude ( N) The spatial patterns of the first three EOFs of summer SPEI at month lag over the Czech Republic (upper panel) and the corresponding temporal PC series normalized by its standard deviation (lower panel) Longitude ( E) 4 5 EOF summer

12 The wettest and driest years (standardized amplitude of PC >.5 and < -.5, respectively) used to build the composite maps Season Winter Spring Summer Autumn Wet years,,,, 3,,, 4, 5,,, 5,,,, 4, 5,,,, 5,, 4,,, 5,,,,, 5, 4,,,,, 3,,, Dry years 4,,, 3, 4,,,,,,, 4,,,, 3,,,, 3,,, 3,, 3,,, 4, 3,, 3,,, 3, 5,,

13 Composite maps of anomalies ( maps) Mean Sea Level Pressure Precipitable Water Content SST & >+.5 std of winter PC SPEI_ mo

14 Composite maps of anomalies ( maps) Mean Sea Level Pressure Precipitable Water Content SST & > +.5 std spring PC SPEI_ mo

15 Composite maps of anomalies ( maps) Mean Sea Level Pressure Precipitable Water Content SST & >+.5 std summer PC SPEI_ mo

16 Composite maps of anomalies ( maps) Mean Sea Level Pressure Precipitable Water Content SST & >+.5 std autumn PC SPEI_ mo

17 Composite maps of anomalies ( maps) Mean sea Level pressure Precipitable Water content SST & <-.5std winter PC SPEI_ mo lag

18 Composite maps of anomalies ( maps) Mean sea Level pressure Precipitable Water content SST & <-.5std spring PC SPEI_ mo lag

19 Composite maps of anomalies ( maps) Mean sea Level pressure Precipitable Water content SST & <-.5std summer PC SPEI_ mo lag

20 Composite maps of anomalies ( maps) Mean sea Level pressure Precipitable Water content SST & <-.5std autumn PC SPEI_ mo lag

21 Summary & concluding remarks seasonal modes of variability of the SPEI at mo lag at 4 stations of the Czech Republic have been analized the explained variance of EOF ranges between 5% (winter) and % (autumn); spatial coefficients have positive loadings at all stations; the EOF pattern point out on the climate influences (oceanic and continental) the seasonal composite maps of MSLP, PWC and SST anomalies built on selected standardized values of PC of SPEI- (higher/lover than ±.5 std of the series) point out on large scale driving mechanisms: - negative/positive AO phase associated with La Niña/El Niño years which may induce wet/dry conditions over the Czech Republic

22 Gracias por su attention!

23 Iberian Peninsula seasonal EOFs SPEI_3 4 Explained variance & patterns SPEI_3 SPEI_ SPEI_ SPEI_4 wi_eof wi_eof wi_eof sp_eof sp_eof sp_eof su_eof su_eof su_eof au_eof au_eof au_eof Boroneant et al, WCRP OSC, Denver, USA

24 Boroneant et al, WCRP OSC, Denver, USA

25 Boroneant et al, WCRP OSC, Denver, USA