Precipitation and temperature variability during Heinrich event 4 and Dansgaard/Oeschger interstadial 8 events from western Mediterranean high resolution pollen data

2012 ◽  
Vol 279-280 ◽  
pp. 96
Author(s):  
Nathalie Combourieu Nebout
Keyword(s):  
High Resolution ◽  
Western Mediterranean ◽  
Temperature Variability ◽  
Pollen Data ◽  
Heinrich Event ◽  
Precipitation And Temperature

scholarly journals Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean

2016 ◽  
Vol 20 (3) ◽  
pp. 1031-1047 ◽  
Author(s):  
Benjamin Grouillet ◽  
Denis Ruelland ◽  
Pradeebane Vaittinada Ayar ◽  
Mathieu Vrac
Keyword(s):  
High Resolution ◽  
Statistical Downscaling ◽  
General Circulation ◽  
Hydrological Model ◽  
General Circulation Models ◽  
Western Mediterranean ◽  
Cumulative Distribution ◽  
Time Step ◽  
Stochastic Weather Generator ◽  
Precipitation And Temperature

Abstract. This paper analyzes the sensitivity of a hydrological model to different methods to statistically downscale climate precipitation and temperature over four western Mediterranean basins illustrative of different hydro-meteorological situations. The comparison was conducted over a common 20-year period (1986&ndsh;2005) to capture different climatic conditions in the basins. The daily GR4j conceptual model was used to simulate streamflow that was eventually evaluated at a 10-day time step. Cross-validation showed that this model is able to correctly reproduce runoff in both dry and wet years when high-resolution observed climate forcings are used as inputs. These simulations can thus be used as a benchmark to test the ability of different statistically downscaled data sets to reproduce various aspects of the hydrograph. Three different statistical downscaling models were tested: an analog method (ANALOG), a stochastic weather generator (SWG) and the cumulative distribution function–transform approach (CDFt). We used the models to downscale precipitation and temperature data from NCEP/NCAR reanalyses as well as outputs from two general circulation models (GCMs) (CNRM-CM5 and IPSL-CM5A-MR) over the reference period. We then analyzed the sensitivity of the hydrological model to the various downscaled data via five hydrological indicators representing the main features of the hydrograph. Our results confirm that using high-resolution downscaled climate values leads to a major improvement in runoff simulations in comparison to the use of low-resolution raw inputs from reanalyses or climate models. The results also demonstrate that the ANALOG and CDFt methods generally perform much better than SWG in reproducing mean seasonal streamflow, interannual runoff volumes as well as low/high flow distribution. More generally, our approach provides a guideline to help choose the appropriate statistical downscaling models to be used in climate change impact studies to minimize the range of uncertainty associated with such downscaling methods.

scholarly journals Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean

2015 ◽  
Vol 12 (10) ◽  
pp. 10067-10108 ◽  
Author(s):  
B. Grouillet ◽  
D. Ruelland ◽  
P. V. Ayar ◽  
M. Vrac
Keyword(s):  
High Resolution ◽  
Statistical Downscaling ◽  
Climate Models ◽  
Hydrological Model ◽  
Flow Distribution ◽  
Western Mediterranean ◽  
Climatic Conditions ◽  
Cumulative Distribution ◽  
Stochastic Weather Generator ◽  
Precipitation And Temperature

Abstract. This paper analyzes the sensitivity of a hydrological model to different methods to statistically downscale climate precipitation and temperature over four western Mediterranean basins illustrative of different hydro-meteorological situations. The comparison was conducted over a common 20 year period (1986–2005) to capture different climatic conditions in the basins. Streamflow was simulated using the GR4j conceptual model. Cross-validation showed that this model is able to correctly reproduce runoff in both dry and wet years when high-resolution observed climate forcings are used as inputs. These simulations can thus be used as a benchmark to test the ability of different statistically downscaled datasets to reproduce various aspects of the hydrograph. Three different statistical downscaling models were tested: an analog method (ANALOG), a stochastic weather generator (SWG) and the "cumulative distribution function – transform" approach (CDFt). We used the models to downscale precipitation and temperature data from NCEP/NCAR reanalyses as well as outputs from two GCMs (CNRM-CM5 and IPSL-CM5A-MR) over the reference period. We then analyzed the sensitivity of the hydrological model to the various downscaled data via five hydrological indicators representing the main features of the hydrograph. Our results confirm that using high-resolution downscaled climate values leads to a major improvement of runoff simulations in comparison to the use of low-resolution raw inputs from reanalyses or climate models. The results also demonstrate that the ANALOG and CDFt methods generally perform much better than SWG in reproducing mean seasonal streamflow, interannual runoff volumes as well as low/high flow distribution. More generally, our approach provides a guideline to help choose the appropriate statistical downscaling models to be used in climate change impact studies to minimize the range of uncertainty associated with such downscaling methods.

scholarly journals High-resolution monthly precipitation and temperature time series from 2006 to 2100

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Dirk Nikolaus Karger ◽  
Dirk R. Schmatz ◽  
Gabriel Dettling ◽  
Niklaus E. Zimmermann
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Temperature Time Series ◽  
Monthly Precipitation ◽  
Temperature Time ◽  
Precipitation And Temperature

scholarly journals Temperature variability and moisture synergistically interact to exacerbate an epizootic disease

2015 ◽  
Vol 282 (1801) ◽  
pp. 20142039 ◽  
Author(s):  
Thomas R. Raffel ◽  
Neal T. Halstead ◽  
Taegan A. McMahon ◽  
Andrew K. Davis ◽  
Jason R. Rohr
Keyword(s):  
Climate Change ◽  
Batrachochytrium Dendrobatidis ◽  
Temperature Variability ◽  
Parasitic Diseases ◽  
Notophthalmus Viridescens ◽  
Increased Temperature ◽  
Constant Versus ◽  
Global Patterns ◽  
Epizootic Disease ◽  
Precipitation And Temperature

Climate change is altering global patterns of precipitation and temperature variability, with implications for parasitic diseases of humans and wildlife. A recent study confirmed predictions that increased temperature variability could exacerbate disease, because of lags in host acclimation following temperature shifts. However, the generality of these host acclimation effects and the potential for them to interact with other factors have yet to be tested. Here, we report similar effects of host thermal acclimation (constant versus shifted temperatures) on chytridiomycosis in red-spotted newts ( Notophthalmus viridescens ). Batrachochytrium dendrobatidis ( Bd ) growth on newts was greater following a shift to a new temperature, relative to newts already acclimated to this temperature (15°C versus 25°C). However, these acclimation effects depended on soil moisture (10, 16 and 21% water) and were only observed at the highest moisture level, which induced greatly increased Bd growth and infection-induced mortality. Acclimation effects were also greater following a decrease rather than an increase in temperature. The results are consistent with previous findings that chytridiomycosis is associated with precipitation, lower temperatures and increased temperature variability. This study highlights host acclimation as a potentially general mediator of climate–disease interactions, and the need to account for context-dependencies when testing for acclimation effects on disease.

Heinrich event 4 and Dansgaard/Oeschger events 5–10 recorded by high-resolution speleothem oxygen isotope data from central China

2014 ◽  
Vol 82 (2) ◽  
pp. 394-404 ◽  
Author(s):  
Houyun Zhou ◽  
Jian-xin Zhao ◽  
Yuexing Feng ◽  
Qiong Chen ◽  
Xiaojian Mi ◽  
...  
Keyword(s):  
High Resolution ◽  
Oxygen Isotope ◽  
High Precision ◽  
High Latitude ◽  
Southwest China ◽  
Asian Summer Monsoon ◽  
Central China ◽  
Temperature Changes ◽  
Heinrich Event ◽  
Asian Summer

AbstractA 50-yr resolution reconstruction of climate and environment variability during the period 43–14 ka was developed using 26 high-precision U/Th dates and 390 oxygen isotope (δ18O) data of a stalagmite (SJ1) collected from Songjia Cave in central China, which is close to the northwestern boundary of the Asian summer monsoon (ASM). The δ18O record in SJ1 displays significant millennial-scale changes that correlate well in timing and duration with Dansgaard/Oeschger (D/O) events 5–10 and Heinrich event 4 (H4) identified in high-latitude regions of the Northern Hemisphere. Four 230Th dates constrain the H4 event precisely to the period of 39.7 to 38.3 ka. Notable centennial variations of the ASM activity could be observed within the H4 event. The magnitude and duration of D/O event 4.1 recorded in SJ1 are similar to those archived in east China but different from those documented in southwest China, suggesting that the manifestation of this event may be regionally different. The timing, duration and structure of D/O events 5–10 and Heinrich event 4 suggest that temperature changes in both hemispheres have exerted significant influences on the ASM variations in central China.

scholarly journals Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

2016 ◽  
Vol 12 (3) ◽  
pp. 635-662 ◽  
Author(s):  
Laurie Caillouet ◽  
Jean-Philippe Vidal ◽  
Eric Sauquet ◽  
Benjamin Graff
Keyword(s):  
Climate Change ◽  
Twentieth Century ◽  
High Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Precipitation Forecast ◽  
Seasonal Temperature ◽  
Downscaling Method ◽  
Quantitative Precipitation Forecast ◽  
Precipitation And Temperature

Abstract. This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (T). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. The probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.

High resolution climate and environmental changes of the northern Japan (East) Sea for the last 40kyr inferred from sedimentary geochemical and pollen data

2014 ◽  
Vol 414 ◽  
pp. 260-272 ◽  
Author(s):  
Sergey A. Gorbarenko ◽  
Seung-Il Nam ◽  
Yulia V. Rybiakova ◽  
Xuefa Shi ◽  
Yanguang Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Environmental Changes ◽  
East Sea ◽  
Pollen Data ◽  
Northern Japan
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