scholarly journals THE EFFECT OF CLIMATE CHANGE ON THE THERMAL REGIME IN THE RYBINSK RESERVOIR

2021 ◽  
pp. 7-16
Author(s):  
A. Zakonnova
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Water Temperature ◽  
Air Temperature ◽  
Rybinsk Reservoir ◽  
Surface Air Temperature ◽  
Average Water Temperature ◽  
Maximum Increase ◽  
Modern Period ◽  
The Rybinsk Reservoir

According to the data of the Rybinsk Hydrometeorological Observatory (HMO) and archival data of the Laboratory of Hydrology, Papanin Institute for Biology of Inland Waters, Russian Academy of Sciences, the seasonal variability of the main climate parameters, air temperature (Rybinsk HMO) and water temperature in the Rybinsk Reservoir have been studied at the modern stage of global warming (2001–2019). Over the period of 1976–2019, the rate of an increase in the average annual air temperature was 0.50°C /10 years in the littoral zone of the Rybinsk Reservoir. Changes in the timing of the onset and end of the climatic seasons of the year and an increase in their duration have been determined. It is found that during the modern period the average surface air temperature was higher than the climatic norm in all months of the year (1960–1990). During the growing season (conventionally May–October), its maximum increase was recorded in July, 1.5°C, May and September, 1.2°C. It is shown during the modern period of intensive global warming the average decadal water temperature in the spring, summer, and autumn seasons increased compared to the norm. The maximum positive anomalies were recorded in the second-third decade of May, 2.8–2.3°C and July, 2.0°C. According to observations at the standard stations, significant differences were recorded in water mass heating: in July in anomalously warm summer of 2010 the average water temperature was 27°C in the surface layer and 18.5°C in the near bottom layer; in the cold summer of 2017, the temperature was 18.5 and 16.0°C, respectively. The monitoring data on the water temperature in the reservoir indicate an increase in the number of years with anomalous thermal conditions as a result of climate change. The earlier temperature stratification of water masses (the end of May) and decrease in the difference in the temperature between the surface and near-bottom water layers have been observed.

scholarly journals Non-Stationary Frequency Analysis and Uncertainty of Heat Wave Events

2021 ◽  
Vol 21 (1) ◽  
pp. 301-310
Author(s):  
Jiyu Seo ◽  
Jeongeun Won ◽  
Jeonghyeon Choi ◽  
Okjeong Lee ◽  
Sangdan Kim
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Global Warming ◽  
Energy Management ◽  
Heat Wave ◽  
Air Temperature ◽  
Frequency Analysis ◽  
Heat Waves ◽  
Surface Air Temperature ◽  
Return Periods

Due to global warming, there is an increasing concern regarding persistent and severe heat waves. The maximum daily surface air temperature observations show strong non-stationary features, and the increased intensity and persistence of heat wave events have been observed in many regions. The heat wave persistence day frequency (HPF) curve, which correlates the intensity of a heat wave persistence event for days with return periods, can be a useful tool to analyze the frequency of heat wave events. In this study, non-stationary HPF curves are developed to explain the trend in the increase of the surface air temperature due to climate change, and their uncertainty is analyzed. The non-stationary HPF model can be used in climate change adaptation management such as public health, public safety, and energy management.

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 Tropopause height at 78° N 16° E: average seasonal variation 2007–2010

2011 ◽  
Vol 11 (1) ◽  
pp. 39-52
Author(s):  
C. M. Hall ◽  
G. Hansen ◽  
F. Sigernes ◽  
K. M. Kuyeng Ruiz
Keyword(s):  
Climate Change ◽  
Seasonal Variation ◽  
Air Temperature ◽  
High Latitude ◽  
Column Density ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Tropopause Height ◽  
Vhf Radar ◽  
Ozone Column

Abstract. We present a seasonal climatology of tropopause altitude for 78° N 16° E derived from observations 2007–2010 by the SOUSY VHF radar on Svalbard. The spring minimum occurs one month later than that of surface air temperature and instead coincides with the maximum in ozone column density. This confirms similar studies based on radiosonde measurements in the arctic and demonstrates downward control by the stratosphere. If one is to exploit the potential of tropopause height as a metric for climate change at high latitude and elsewhere, it is imperative to observe and understand the processes which establish the tropopause – an understanding to which this study contributes.

scholarly journals Evaluation of CLDAS and GLDAS Datasets for Near-Surface Air Temperature over Major Land Areas of China

2020 ◽  
Vol 12 (10) ◽  
pp. 4311
Author(s):  
Shuai Han ◽  
Buchun Liu ◽  
Chunxiang Shi ◽  
Yuan Liu ◽  
Meijuan Qiu ◽  
...  
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Data Assimilation ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Assimilation System

As one of the most principal meteorological factors to affect global climate change and human sustainable development, temperature plays an important role in biogeochemical and hydrosphere cycle. To date, there are a wide range of temperature data sources and only a detailed understanding of the reliability of these datasets can help us carry out related research. In this study, the hourly and daily near-surface air temperature observations collected at national automatic weather stations (NAWS) in China were used to compare with the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the Global Land Data Assimilation System (GLDAS), both of which were developed by using the advanced multi-source data fusion technology. Results are as follows. (1) The spatial and temporal variations of the near-surface air temperature agree well between CLDAS and GLDAS over major land of China, except that spatial details in high mountainous areas were not sufficiently displayed in GLDAS; (2) The near-surface air temperature of CLDAS were more significantly correlated with observations than that of GLDAS, but more caution is necessary when using the data in mountain areas as the accuracy of the datasets gradually decreases with increasing altitude; (3) CLDAS can better illustrate the distribution of areas of daily maximum above 35 °C and help to monitor high temperature weather. The main conclusion of this study is that CLDAS near-surface air temperature has a higher reliability in China, which is very important for the study of climate change and sustainable development in East Asia.

scholarly journals An Integrated Procedure to Determine a Reference Station Network for Evaluating and Adjusting Urban Bias in Surface Air Temperature Data

2015 ◽  
Vol 54 (6) ◽  
pp. 1248-1266 ◽  
Author(s):  
Guoyu Ren ◽  
Jiao Li ◽  
Yuyu Ren ◽  
Ziying Chu ◽  
Aiying Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Historical Data ◽  
Spatial Scales ◽  
Mainland China ◽  
Surface Air Temperature ◽  
Reference Station ◽  
Reference Network ◽  
Station Network

AbstractTrends in surface air temperature (SAT) are a critical indicator for climate change at varied spatial scales. Because of urbanization effects, however, the current SAT records of many urban stations can hardly meet the demands of the studies. Evaluation and adjustment of the urbanization effects on the SAT trends are needed, which requires an objective selection of reference (rural) stations. Based on the station history information from all meteorological stations with long-term records in mainland China, an integrated procedure for determining the reference SAT stations has been developed and is applied in forming a network of reference SAT stations. Historical data from the network are used to assess the urbanization effects on the long-term SAT trends of the stations of the national Reference Climate Network and Basic Meteorological Network (RCN+BMN or national stations), which had been used most frequently in studies of regional climate change throughout the country. This paper describes in detail the integrated procedure and the assessment results of urbanization effects on the SAT trends of the national stations applying the data from the reference station network determined using the procedure. The results showed a highly significant urbanization effect of 0.074°C (10 yr)−1 and urbanization contribution of 24.9% for the national stations of mainland China during the time period 1961–2004, which compared well to results that were reported in previous studies by the authors using the predecessor of the present reference network and the reference stations selected but when applying other methods. The authors are thus confident that the SAT data from the updated China reference station network as reported in this paper best represented the baseline SAT trends nationwide and could be used for evaluating and adjusting the urban biases in the historical data series of the SAT from different observational networks.

The Global Warming By Using The Experimental Methods Within Project-Based Learning Approach

2020 ◽  
Author(s):  
Gulperi Selcan Öncü
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Greenhouse Gases ◽  
Water Temperature ◽  
Forest Fires ◽  
Experimental Methods ◽  
Project Based Learning ◽  
Control Group ◽  
Learning Approaches ◽  
The Impact

<div> <p>In recent times we have often received news such as about melting glaciers, sudden and torrential rain, storms, increased atmospheric temperatures, and forest fires. We have also observed some of these phenomena in our immediate vicinity. There is a frequently used expression among the public, 'the seasons are shifting'. </p> <p>Students have asked the reasons why these changes have been occurring and what about changes between the past and present. In order to understand these changes we all know that they need to understand global warming in the first place. To help them with this as an science teacher I have guided them to be capable of using experimental methods within project-based learning approaches. First they did preliminary literature surveys and then they designed an experiment. In the experiment, they tested the hypothesis that the water inside the bell JAR, which is coated with black cardboard, heats up more than the transparent one. In this way they began to investigate climate change due to greenhouse gases. </p> <p>In the experiment, two bell glasses were used to represent the atmosphere layers. One was intermittently covered with pieces cut out of black cardboard. Black cardboard was used to represent the greenhouse gas due since the black colour absorbs light. Two beakers of the same size were used, filled with water. A thermometer was placed inside and bell jars were turned upside down and put over the beakers. The two thermometers were used to measure the water temperature inside the beakers. </p> <p>The first apparatus is the control group (inside uncovered). The second apparatus is the experimental group (covered with independent black cardboard). In the experimental and observation stage, the independent variable is the bell jar; the dependent variable is the water temperature. The constant variables are the size of the jar, the size of the beaker, the amount of water and the ambient conditions. </p> <p>Having set up the apparatus, the initial temperature of water was measured and recorded. Students carried out the experiment on a sunny day by placing the apparatus in a sun-covered field. They recorded the data in the tables they completed periodically. Then they shared the results with participants at the science festival. </p> <p>In this way they began to investigate the impact of greenhouse gases on climate change.</p> </div>

Sign in / Sign up

Export Citation Format

Share Document