Long term water temperature trends in Austrian rivers

1995 ◽  
Vol 40 (1) ◽  
pp. 83-96 ◽  
Author(s):  
B. W. WEBB ◽  
F. NOBILIS
Keyword(s):  
Water Temperature ◽  
Temperature Trends

Long-term water temperature trends of the Warta River in the years 1960–2009

2019 ◽  
Vol 19 (3) ◽  
pp. 441-451 ◽  
Author(s):  
Mariusz Ptak ◽  
Mariusz Sojka ◽  
Tomasz Kałuża ◽  
Adam Choiński ◽  
Bogumił Nowak
Keyword(s):  
Water Temperature ◽  
Temperature Trends

scholarly journals The effect of wind on long-term summer water temperature trends in Tokyo Bay, Japan

2015 ◽  
Vol 65 (6) ◽  
pp. 919-930 ◽  
Author(s):  
Li-Feng Lu ◽  
Ryo Onishi ◽  
Keiko Takahashi
Keyword(s):  
Water Temperature ◽  
Tokyo Bay ◽  
Temperature Trends

scholarly journals Special Issue on Climate Migration

2021 ◽  
pp. 1-3
Author(s):  
Anda David ◽  
Frédéric Docquier
Keyword(s):  
Climate Change ◽  
Human Mobility ◽  
Economic Research ◽  
Special Issue ◽  
Low Latitude ◽  
Weather Shocks ◽  
Temperature Trends ◽  
Agricultural Areas ◽  
Slow Onset

How do weather shocks influence human mobility and poverty, and how will long-term climate change affect future migration over the course of the 21st century? These questions have gained unprecedented attention in public debates as global warming is already having severe impacts around the world, and prospects for the coming decades get worse. Low-latitude countries in general, and their agricultural areas in particular, have contributed the least to climate change but are the most adversely affected. The effect on people's voluntary and forced displacements is of major concern for both developed and developing countries. On 18 October 2019, Agence Française de Développement (AFD) and Luxembourg Institute of Socio-Economic Research (LISER) organized a workshop on Climate Migration with the aim of uncovering the mechanisms through which fast-onset variables (such as weather anomalies, storms, hurricanes, torrential rains, floods, landslides, etc.) and slow-onset variables (such as temperature trends, desertification, rising sea level, coastal erosion, etc.) influence both people's incentives to move and mobility constraints. This special issue gathers five papers prepared for this workshop, which shed light on (or predict) the effect of extreme weather shocks and long-term climate change on human mobility, and stress the implications for the development community.

scholarly journals Surface Water Temperature Predictions at a Mid-Latitude Reservoir under Long-Term Climate Change Impacts Using a Deep Neural Network Coupled with a Transfer Learning Approach

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Transfer Learning ◽  
Air Temperature ◽  
Climate Models ◽  
Temporal Variations ◽  
Training Data ◽  
Surface Water Temperature

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.

scholarly journals Two decades of in-situ temperature measurements in the upper troposphere and lowermost stratosphere from IAGOS long-term routine observation

2017 ◽  
Author(s):  
Florian Berkes ◽  
Patrick Neis ◽  
Martin G. Schultz ◽  
Ulrich Bundke ◽  
Susanne Rohs ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Global Scale ◽  
Temperature Trend ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
Temperature Trends ◽  
Geographical Regions

Abstract. Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.

scholarly journals Exploring and Quantifying River Thermal Response to Heatwaves

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1098 ◽  
Author(s):  
Sebastiano Piccolroaz ◽  
Marco Toffolon ◽  
Christopher Robinson ◽  
Annunziato Siviglia
Keyword(s):  
Water Temperature ◽  
River Water ◽  
Thermal Response ◽  
Hydrological Regime ◽  
Management Policy ◽  
Extreme Weather Events ◽  
Thermal Dynamics ◽  
Depth Analysis ◽  
River Water Temperature

Most of the existing literature on river water temperature focuseds on river thermal sensitivity to long-term trends of climate variables, whereas how river water temperature responds to extreme weather events, such as heatwaves, still requires in-depth analysis. Research in this direction is particularly relevant in that heatwaves are expected to increase in intensity, frequency, and duration in the coming decades, with likely consequences on river thermal regimes and ecology. In this study we analyzed the long-term temperature and streamflow series of 19 Swiss rivers with different hydrological regime (regulated, low-land, and snow-fed), and characterized how concurrent changes in air temperature and streamflow concurred to affect their thermal dynamics. We focused on quantifying the thermal response to the three most significant heatwave events that occurred in Central Europe since 1950 (July–August 2003, July 2006, and July 2015). We found that the thermal response of the analyzed rivers contrasted strongly depending on the river hydrological regime, confirming the behavior observed under typical weather conditions. Low-land rivers were extremely sensitive to heatwaves. In sharp contrast, high-altitude snow-fed rivers and regulated rivers receiving cold water from higher altitude hydropower reservoirs or diversions showed a damped thermal response. The results presented in this study suggest that water resource managers should be aware of the multiple consequences of heatwave events on river water temperature and incorporate expected thermal responses in adaptive management policy. In this respect, additional efforts and dedicated studies are required to deepen our knowledge on how extreme heatwave events can affect river ecosystems.

scholarly journals Is the Water Temperature of the Danube River at Bratislava, Slovakia, Rising?

2008 ◽  
Vol 9 (5) ◽  
pp. 1115-1122 ◽  
Author(s):  
Pavla Pekarova ◽  
Dana Halmova ◽  
Pavol Miklanek ◽  
Milan Onderka ◽  
Jan Pekar ◽  
...  
Keyword(s):  
Time Series ◽  
Water Temperature ◽  
Heat Load ◽  
Empirical Relationship ◽  
Danube River ◽  
Average Heat ◽  
The Danube River ◽  
Average Temperature ◽  
Monthly Discharge

Abstract This paper aims to reveal the annual regime, time series, and long-term water temperature trends of the Danube River at Bratislava, Slovakia, between the years 1926 and 2005. First, the main factors affecting the river’s water temperature were identified. Using multiple regression techniques, an empirical relationship is derived between monthly water temperatures and monthly atmospheric temperatures at Vienna (Hohe Warte), Austria, monthly discharge of the Danube, and some other factors as well. In the second part of the study, the long-term trends in the annual time series of water temperature were identified. The following series were evaluated: 1) The average annual water temperature (To) (determined as an arithmetic average of daily temperatures in the Danube at Bratislava), 2) the weighted annual average temperature values (Toυ) (determined from the daily temperatures weighted by the daily discharge rates at Bratislava), and 3) the average heat load (Zt) at the Bratislava station. In the long run, the To series is rising; however, the trend of the weighted long-term average temperature values, Toυ, is near zero. This result indicates that the average heat load of the Danube water did not change during the selected period of 80 yr. What did change is the interannual distribution of the average monthly discharge. Over the past 25 yr, an elevated runoff of “cold” water (increase of the December–April runoff) and a lower runoff of “warm” water (decrease of the river runoff during the summer months of June–August) were observed.

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