Recent trends in daily temperature extremes over the central Adriatic region of Italy in a Mediterranean climatic context

2018 ◽  
Vol 38 ◽  
pp. e741-e757 ◽  
Author(s):  
Anna R. Scorzini ◽  
Mario Di Bacco ◽  
Maurizio Leopardi
Keyword(s):  
Daily Temperature ◽  
Temperature Extremes ◽  
Recent Trends ◽  
Adriatic Region

scholarly journals Recent trends in pre-monsoon daily temperature extremes over India

2010 ◽  
Vol 119 (1) ◽  
pp. 51-65 ◽  
Author(s):  
D R Kothawale ◽  
J V Revadekar ◽  
K Rupa Kumar
Keyword(s):  
Daily Temperature ◽  
Temperature Extremes ◽  
Recent Trends

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

scholarly journals Recent trends in daily temperature extremes over northeastern Spain (1960–2006)

2011 ◽  
Vol 11 (9) ◽  
pp. 2583-2603 ◽  
Author(s):  
A. El Kenawy ◽  
J. I. López-Moreno ◽  
S. M. Vicente-Serrano
Keyword(s):  
Land Use Planning ◽  
Crop Yields ◽  
Extreme Temperature ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Growing Season Length ◽  
Cold Extremes

Abstract. Spatial and temporal characteristics of extreme temperature events in northeastern Spain have been investigated. The analysis is based on long-term, high-quality, and homogenous daily maximum and minimum temperature of 128 observatories spanning the period from 1960 to 2006. A total of 21 indices were used to assess changes in both the cold and hot tails of the daily temperature distributions. The presence of trends in temperature extremes was assessed by means of the Mann-Kendall test. However, the autocorrelation function (ACF) and a bootstrap methodology were used to account for the influence of serial correlation and cross-correlation on the trend assessment. In general, the observed changes are more prevalent in hot extremes than in cold extremes. This finding can largely be linked to the increase found in the mean maximum temperature during the last few decades. The results indicate a significant increase in the frequency and intensity of most of the hot temperature extremes. An increase in warm nights (TN90p: 3.3 days decade−1), warm days (TX90p: 2.7 days decade−1), tropical nights (TR20: 0.6 days decade−1) and the annual high maximum temperature (TXx: 0.27 °C decade−1) was detected in the 47-yr period. In contrast, most of the indices related to cold temperature extremes (e.g. cold days (TX10p), cold nights (TN10p), very cold days (TN1p), and frost days (FD0)) demonstrated a decreasing but statistically insignificant trend. Although there is no evidence of a long-term trend in cold extremes, significant interdecadal variations were noted. Almost no significant trends in temperature variability indices (e.g. diurnal temperature range (DTR) and growing season length (GSL)) are detected. Spatially, the coastal areas along the Mediterranean Sea and the Cantabrian Sea experienced stronger warming compared with mainland areas. Given that only few earlier studies analyzed observed changes in temperature extremes at fine spatial resolution across the Iberian Peninsula, the results of this work can improve our understanding of climatology of temperature extremes. Also, these findings can have different hydrological, ecological and agricultural implications (e.g. crop yields, energy consumption, land use planning and water resources management).

Estimating missing daily temperature extremes using an optimized regression approach

2001 ◽  
Vol 21 (11) ◽  
pp. 1305-1319 ◽  
Author(s):  
Robert J. Allen ◽  
Arthur T. DeGaetano
Keyword(s):  
Daily Temperature ◽  
Temperature Extremes ◽  
Regression Approach

scholarly journals Estimates of daily global solar radiation based on the daily temperature extremes and precipitation sums

2004 ◽  
Vol 52 (5) ◽  
pp. 13-28
Author(s):  
Miroslav Trnka
Keyword(s):  
Solar Radiation ◽  
Sunshine Duration ◽  
Regression Line ◽  
Global Solar Radiation ◽  
Daily Temperature ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Daily Maximum ◽  
Bias Error ◽  
Temperature Extremes

Two methods for estimating daily global solar radiation (RG) based on the daily temperature extremes and precipitation sum are compared in the study. All parameters necessary for application of both methods were derived either from literature or from climatic characteristics easily available at the given meteorological stations excluding need for measured RG data. The performance of both methods was assessed with a help of meteorological database including 4 stations in the Czech Republic (data were provided by the Czech Hydrometeorological Institute) and 6 in Austria (data provided by the Austrian Weather Service) containing in total 41 640 observational day. For each day in the database observed daily sum of RG, daily maximum and minimum temperatures and precipitation sum were available. Coefficient of determination, slope of regression line forced through origin, mean bias error (MBE) and root mean square error (RMSE) were used as performance indicators. The first method proposed by Winslow et al. (2001) – Eq. (1) is capable to explain 86% of daily RG variability, with systematic error represented by MBE equaling to 0.19 MJ.m–2.day-1 and random error indicated by RMSE reaching up to 3.09. The second method published by Thornton and Running (1999)-Eq. (2) was found to be in almost all parameters inferior to the Eq. (1) and thus the Eq. (1) is recommended to be used in the Central European region (up to 600 m above the sea level). This method might be recommended for stations where neither measured RG or sunshine duration hours exist. However, one should take into consideration that relative MBE and RMSE are in some months higher than 10% and 30% respectively, which may compromise results of subsequent calculations made with use of estimated solar radiation data and alter the order of the method suitability.

Modelling daily temperature extremes: recent climate and future changes over Europe

2007 ◽  
Vol 81 (S1) ◽  
pp. 249-265 ◽  
Author(s):  
Erik Kjellström ◽  
Lars Bärring ◽  
Daniela Jacob ◽  
Richard Jones ◽  
Geert Lenderink ◽  
...  
Keyword(s):  
Daily Temperature ◽  
Temperature Extremes ◽  
Recent Climate

Evaluation of systematic biases and skill of summer subseasonal forecasts in the ECMWF system

2020 ◽  
Author(s):  
Frederico Johannsen ◽  
Emanuel Dutra ◽  
Linus Magnusson
Keyword(s):  
Northern Hemisphere ◽  
Lead Time ◽  
Model Error ◽  
Forecast Skill ◽  
Daily Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Error Growth ◽  
Weather Forecasts ◽  
Systematic Biases

<p>Subseasonal forecasts (ranging between 2 weeks and 2 months) have been the subject of attention in many operational weather forecasts centers and by the research community in recent years. This growing attention stems from the value of these forecasts for society and from the scientific challenges involved. The scientific challenges of capturing and representing key processes and teleconnections which are relevant at these scales are significant. One example is temperature extremes associated with weather extremes like heatwaves and droughts that can have severe consequences in nature and human health, among others. Some of the limitations in forecast skill arise from the limits of predictability of the chaotic earth system. Model error is also likely to play a relevant role. In this study, we investigate systematic model biases, their evolution with lead time and potential links with forecast skill.</p><p>This study assessed the skill and biases of the European Centre for Medium-Range Weather Forecasts (ECMWF) subseasonal forecast in predicting the daily temperature extremes in the Northern Hemisphere. These forecasts are from an experimental setup of ECMWF extended-range forecast system. The forecasts compromise 11 ensemble members with weekly starting dates between 9 April to 30 July extending up to 6 weeks lead with a 20-years hindcast period (1998-2017). The forecasts were performed by the coupled ECMWF systems with TcO199 horizontal resolution (about 50km) in the atmosphere and 1x1 degree ocean. A particular focus is given to Europe and to two other regions that were identified with large systematic errors. The data used in this work consisted of the daily maximum and minimum two-meter temperature, precipitation and other surface fluxes that are aggregated into weekly means and verified against ERA5. </p><p>The evaluation of systematic biases in daily temperature extremes shows a clear increase with lead time, which is widespread on a hemispheric scale. The spatial patterns of model error growth with lead time are reasonably similar between daily maximum and minimum temperatures. However, the amplitude of the errors is remarkably different with general cold bias of daily maximum and warm bias of daily minimum that consistently grow with forecast lead time. Despite the consistent error growth with lead time, there are clear differences between the forecasts initialized in late Spring (April-May) and those in Summer (June-July). These biases are not fully collocated in two regions in the Northern Hemisphere showing the largest warm temperature biases: Central US and East of Caspian Sea. The warm biases are consistent with an underestimation of precipitation and dry soil moisture, compared to ERA5, but only over the East Caspian region.  Forecasts skill assessed via the anomaly correlation shows that the temperature forecasts are skillful up to week 2, with a drop in skill from week 3 onwards. This drop in skill is consistent over all the European domain. Similar results are found for precipitation, but with ACC at week 2 comparable with those of temperature at week 3. </p>

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