Seasonal Temperature and Precipitation Fluctuations in Selected Parts of Europe During the Sixteenth Century

Author(s):  
Rüdiger Glaser ◽  
Rudolf Brázdil ◽  
Christian Pfister ◽  
Petr Dobrovolný ◽  
Mariano Barriendos Vallvé ◽  
...  
Geosciences ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 160 ◽  
Author(s):  
Ennio Ferrari ◽  
Roberto Coscarelli ◽  
Beniamino Sirangelo

2020 ◽  
Vol 287 (1929) ◽  
pp. 20200358
Author(s):  
Junfeng Tang ◽  
Ronald R. Swaisgood ◽  
Megan A. Owen ◽  
Xuzhe Zhao ◽  
Wei Wei ◽  
...  

Climate change is one of the most pervasive threats to biodiversity globally, yet the influence of climate relative to other drivers of species depletion and range contraction remain difficult to disentangle. Here, we examine climatic and non-climatic correlates of giant panda ( Ailuropoda melanoleuca ) distribution using a large-scale 30 year dataset to evaluate whether a changing climate has already influenced panda distribution. We document several climatic patterns, including increasing temperatures, and alterations to seasonal temperature and precipitation. We found that while climatic factors were the most influential predictors of panda distribution, their importance diminished over time, while landscape variables have become relatively more influential. We conclude that the panda's distribution has been influenced by changing climate, but conservation intervention to manage habitat is working to increasingly offset these negative consequences.


2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.


2019 ◽  
Vol 32 (16) ◽  
pp. 4919-4941 ◽  
Author(s):  
Simon McGree ◽  
Nicholas Herold ◽  
Lisa Alexander ◽  
Sergei Schreider ◽  
Yuriy Kuleshov ◽  
...  

Abstract Trends in mean and extreme annual and seasonal temperature and precipitation over the 1951–2015 period were calculated for 57 stations in 20 western Pacific Ocean island countries and territories. The extremes indices are those of the World Meteorological Organization Expert Team on Sector-Specific Climate Indices. The purpose of the expert team and indices is to promote the use of globally consistent climate indices to highlight variability and trends in climate extremes that are of particular interest to socioeconomic sectors and to help to characterize the climate sensitivity of various sectors. Prior to the calculation of the monthly means and indices, the data underwent quality control and homogeneity assessment. A rise in mean temperature occurred at most stations, in all seasons, and in both halves of the study period. The temperature indices also showed strong warming, which for the majority was strongest in December–February and weakest in June–August. The absolute and percentile-based indices show the greatest warming at the upper end of the distribution. While changes in precipitation were less consistent and trends were generally weak at most locations, declines in both total and extreme precipitation were found in southwestern French Polynesia and the southern subtropics. There was a decrease in moderate- to high-intensity precipitation events, especially those experienced over multiple days, in southwestern French Polynesia from December to February. Strong drying trends have also been identified in the low- to moderate-extreme indices in the June–August and September–November periods. These negative trends contributed to an increase in the magnitude of meteorological drought in both subregions.


2003 ◽  
Vol 84 (12) ◽  
pp. 1761-1782 ◽  
Author(s):  
L. Goddard ◽  
A. G. Barnston ◽  
S. J. Mason

The International Research Institute for Climate Prediction (IRI) net assessment seasonal temperature and precipitation forecasts are evaluated for the 4-yr period from October–December 1997 to October–December 2001. These probabilistic forecasts represent the human distillation of seasonal climate predictions from various sources. The ranked probability skill score (RPSS) serves as the verification measure. The evaluation is offered as time-averaged spatial maps of the RPSS as well as area-averaged time series. A key element of this evaluation is the examination of the extent to which the consolidation of several predictions, accomplished here subjectively by the forecasters, contributes to or detracts from the forecast skill possible from any individual prediction tool. Overall, the skills of the net assessment forecasts for both temperature and precipitation are positive throughout the 1997–2001 period. The skill may have been enhanced during the peak of the 1997/98 El Niño, particularly for tropical precipitation, although widespread positive skill exists even at times of weak forcing from the tropical Pacific. The temporally averaged RPSS for the net assessment temperature forecasts appears lower than that for the AGCMs. Over time, however, the IRI forecast skill is more consistently positive than that of the AGCMs. The IRI precipitation forecasts generally have lower skill than the temperature forecasts, but the forecast probabilities for precipitation are found to be appropriate to the frequency of the observed outcomes, and thus reliable. Over many regions where the precipitation variability is known to be potentially predictable, the net assessment precipitation forecasts exhibit more spatially coherent areas of positive skill than most, if not all, prediction tools. On average, the IRI net assessment forecasts appear to perform better than any of the individual objective prediction tools.


Author(s):  
Anfeng Qiang ◽  
Ni Wang ◽  
Jiancang Xie ◽  
Jiahua Wei ◽  
Xia Wei

The variance tendency of climatic and spatial-temporal equilibrium characteristics of major cities along the SREB were systematically described through moving mean method, Kriging interpolation method, Bernaola-Galvan algorithm and correlation analysis based on monthly scale data of global weather stations released by the National Climatic Data Center website since 1951. Some conclusions cloud be drawn: (1) The precipitation showed a downward trend in other districts with significant seasonal differences except the Europe. The annual precipitation was “N” type distribution in Central Asia, while showed an “inverted V” and a “positive V” distribution in the East Asia and West Asia respectively, and the precipitation change was relatively gentle in Europe. The dominant factors affecting climate were different in different districts. (2) The temperature continued to increase in all districts and the seasonal temperature presented unimodal distribution, the alternation of drying and wetting was obvious in each districts as well as the temperature was complex and changeable in Europe. (3) The mutation point of temperature was detected by using Bernaola-Galvan algorithm in all districts, but the timing of the mutation was not synchronous and the mutation point of precipitation was not detected except in Europe. (4) The precipitation was decreasing from west to east in space, and the temperature showed the morphological distribution characteristics of of low in the middle but high on both sides. (5) The change of temperature were more sensitive than precipitation, the precipitation in Central Asia was inversely correlated with other districts, however, there was a high positive correlation between temperature in all districts. The inversely correlation between temperature and precipitation was the most significant in Central Asia.


2008 ◽  
Vol 45 (11) ◽  
pp. 1435-1453 ◽  
Author(s):  
A. E. Viau ◽  
K. Gajewski ◽  
M. C. Sawada ◽  
J. Bunbury

We present new temperature and precipitation reconstructions for the past 25 000 cal. years BP from across eastern Beringia based on a network of pollen diagrams, an updated modern pollen calibration database, and an improved methodology using the modern analogue technique (MAT). Time series show July temperatures were around 4 °C lower during full glacial and January temperatures were about 2 °C lower than present. Annual temperatures rose beginning around 16 000 cal. years BP, reaching a maximum around 12 000 cal. year BP. The warming was more rapid in southern Beringia. Annual precipitation varied by 250 mm during the past 25 000 cal. years BP. Maps of reconstructed precipitation patterns show increasingly drier conditions since 12 000 cal. years BP. that vary regionally, suggesting Holocene atmospheric circulation changes at multiple time and space scales. Orbitally forced seasonality changes during the late glacial and early Holocene resulted in reversed seasonal temperature reconstructions due to methodological constraints using the MAT and (or) non-analogue conditions. The magnitude of millennial-scale climate variability in this region was greater during the last glacial and late glacial periods than during the past 8000 years.


2020 ◽  
Author(s):  
Daniel Schönbein ◽  
Luzia Keupp ◽  
Felix Pollinger ◽  
Heiko Paeth

<p>Within the frame of BigData@Geo, a collaborative EFRE-funded project between the University of Würzburg and several medium-sized companies in regional pomi- and viticulture, a webportal similar to a climate-atlas is built. An Ensemble of six RCM/GCM-Couples from EURO-CORDEX with EUR-11 resolution is therefore retrieved. After a Nearest-Neighbour-Remap onto a 1x1km-grid within Lower Franconia (Bavaria, Germany), a linear bias-correction of air-temperature and precipitation is executed. The applied method calibrates mean seasonal cycles for the reference period 1970-1999 using gridded observation data from the German Weather Service. Subsequently, climatic tendecies of seasonal temperature and precipitation as well as various derived indizes (e.g. frostdays, hot days, tropical nights, vegetation period, huglin index) are evaluated along emission pathways rcp45 and rcp85 during the 21st century.</p>


1997 ◽  
Vol 43 (143) ◽  
pp. 152-164 ◽  
Author(s):  
M. J. Schmeits ◽  
J. Oerlemans

AbstractThe historical length variations in Unterer Grindelwaldgletscher have been simulated by coupling a numerical mass-balance model to a dynamic ice-flow model. As forcing functions, we used (partly reconstructed) local climatic records, which were transformed by the mass-balance model into a mass-balance history. The ice-flow model then computes the length variations that have occurred over the course of time.In a model run from AD 1530 to the present, with both seasonal temperature and precipitation variations as forcing functions, the observed maximum length of the glacier around AD 1860 and the subsequent retreat are simulated. The observed AD 1600 maximum, however, does not show up in the simulation. This is probably due to an incorrect reconstruction of the mass balance for this period, as detailed climatic data are available only since 1865. The root-mean-square difference between the simulated and the observed front positions is 0.28 km. The simulated glacier geometry for 1987 fits the observed geometry for that year reasonably well.Because of the success of the historical simulation, an attempt is made to predict future glacier retreat on the basis of two different greenhouse-gas scenarios. For a Business-as-Usual scenario, only 29% of the 1990 volume would remain in AD 2100.


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