scholarly journals Relative impacts of increases of solar radiation and air temperature on the temperature of surface water in a shallow, eutrophic lake

2021 ◽  
Author(s):  
Ryuichiro Shinohara ◽  
Yoji Tanaka ◽  
Ariyo Kanno ◽  
Kazuo Matsushige
Keyword(s):  
Heat Flux ◽  
Surface Water ◽  
Solar Radiation ◽  
Water Temperature ◽  
Air Temperature ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Surface Water Temperature ◽  
Lake Kasumigaura ◽  
Lake Surface

Abstract We monitored lake surface water temperatures from 1992 to 2019 in Lake Kasumigaura, a shallow lake in Japan. We hypothesized that increases of shortwave radiation had increased surface water temperatures and heat fluxes more than had the increases of air temperature. We used the heat flux analyses and the sensitivity analyses to test the hypothesis. The fluxes of solar radiation gradually increased during the study period in a manner consistent with the phenomenon of global brightening. The increase was especially apparent in the spring. The rate of increase of surface water temperature was especially significant in May. Air temperature did not significantly increase in May, but it increased significantly in June (0.40 °C decade−1). A sensitivity analysis of the heat fluxes at the lake surface (shortwave radiation, longwave radiation, latent heat flux, and sensible heat flux) revealed that surface water temperature was more sensitive to changes of shortwave radiation than to air temperature during the spring. Although other factors such as inflows of groundwater and river water may also have impacted surface water temperatures, the increase of solar radiation appeared to be the major factor responsible for the increase of surface water temperature during the spring in Lake Kasumigaura.

scholarly journals The impact of global warming on lake surface water temperature in Poland - the application of empirical-statistical downscaling, 1971-2100

2018 ◽  
Vol 77 (2) ◽  
Author(s):  
Bartosz Czernecki ◽  
Mariusz Ptak
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Water Temperature ◽  
Air Temperature ◽  
Statistical Downscaling ◽  
Surface Water Temperature ◽  
Lake Surface ◽  
The Future ◽  
Rcp 8.5 ◽  
The Impact

The paper presents historical (1971-2015) and scenario-based (2006-2100) changes in surface water temperatures in 10 lakes of Poland. The analysis of historical measurement (1971-2015) showed that mean annual lake surface water temperature (LSWT) was characterised by an increasing tendency by 0.37°C∙dec-1 on average, and was higher by 0.01°C∙dec-1 than air temperature in the analogical period. The highest increase in LSWT was recorded in spring months (April, May) and in summer (July). The future changes in LSWT was based on simulations of 33 AOGCMs available in the scope of CMIP5 project for RCPs: 2.6, 4.5, 6.0, and 8.5. The developed empirical-statistical downscaling models (ESD) use the air temperature field as predictors, with consideration of autocorrelation for two preceding months. ESD models are characterised by high quality of reconstruction of water temperatures in the historical period, with correlation from 0.82 (December, February) to 0.93 (July). The future CMIP5 scenarios for the period 2006-2100 assume an increase in air temperature at the end of the 21st century from +1.8°C (RCP 2.6) to +5.1°C (RCP 8.5) in reference to the period 1971-2005. According to the downscaling models, this corresponds to an increase in water temperature in the analysed lakes ranging from +1.4°C (RCP 2.6) to +4.2°C (RCP 8.5) in the years 2081-2100, respectively, with evident variability between the adopted emission paths beginning from the period 2041-2060. At a monthly scale, water temperature will increase the slowest in February (2081-2100: RCP 2.6 = +0.5°C, RCP 8.5 = +1.8°C). The highest increase in temperature will occur from May to August (RCP 8.5 = +6°C in June).Substantial effects of transformations of the thermal regime are already observed today, e,g. in the reduction of the ice season length. According to developed scenarios, a further considerable increase in water temperature will be the primary factor determining the transformation of lake ecosystems. The obtained results provide a theoretical basis for further research conducted in the scope of many disciplines, among others hydrology, hydrobiology, ecology, water management, energy production, etc. In the case of Poland, issues related to low water resources per capita are particularly important. Contemporary studies concerning changes in water resources showed that the natural factor playing the key role in their reduction is temperature increase and therefore it should constitute for the possibly fast development of multidisciplinary concepts of mitigation policy to potential impact of climate change. 

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 Comparison of Methods to Estimate Lake-Surface-Water Temperature Using Landsat 7 ETM+ and MODIS Imagery: Case Study of a Large Shallow Subtropical Lake in Southern Brazil

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 168 ◽  
Author(s):  
Matheus Tavares ◽  
Augusto Cunha ◽  
David Motta-Marques ◽  
Anderson Ruhoff ◽  
J. Cavalcanti ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
Single Channel ◽  
Atmospheric Correction ◽  
Ecological Status ◽  
Surface Water Temperature ◽  
Lake Surface ◽  
Subtropical Lake ◽  
Landsat 7 ◽  
The Impact

Water temperature regulates many processes in lakes; therefore, evaluating it is essential to understand its ecological status and functioning, and to comprehend the impact of climate change. Although few studies assessed the accuracy of individual sensors in estimating lake-surface-water temperature (LSWT), comparative analysis considering different sensors is still needed. This study evaluated the performance of two thermal sensors, MODIS and Landsat 7 ETM+, and used Landsat methods to estimate the SWT of a large subtropical lake. MODIS products MOD11 LST and MOD28 SST were used for comparison. For the Landsat images, the radiative transfer equation (RTE), using NASA’s Atmospheric Correction Parameter Calculator (AtmCorr) parameters, was compared with the single-channel algorithm in different approaches. Our results showed that MOD11 obtained the highest accuracy (RMSE of 1.05 ° C), and is the recommended product for LSWT studies. For Landsat-derived SWT, AtmCorr obtained the highest accuracy (RMSE of 1.07 ° C) and is the recommended method for small lakes. Sensitivity analysis showed that Landsat-derived LSWT using the RTE is very sensitive to atmospheric parameters and emissivity. A discussion of the main error sources was conducted. We recommend that similar tests be applied for Landsat imagery on different lakes, further studies on algorithms to correct the cool-skin effect in inland waters, and tests of different emissivity values to verify if it can compensate for this effect, in an effort to improve the accuracy of these estimates.

scholarly journals On Recent Trends in Atmospheric and Limnological Variables in Lake Ontario

2012 ◽  
Vol 25 (17) ◽  
pp. 5807-5816 ◽  
Author(s):  
Anning Huang ◽  
Yerubandi R. Rao ◽  
Weitao Zhang
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
Air Temperature ◽  
Surface Wind ◽  
Lake Ontario ◽  
Surface Wind Speed ◽  
Surface Mixed Layer ◽  
Surface Water Temperature ◽  
Recent Trends ◽  
Annual Time

Abstract The surface air and water temperatures increased at all seasonal and annual time scales during the last 40 yr in Lake Ontario. The annual mean air and surface water temperatures have increased by 1.43° ±0.39° and 1.26° ±0.32°C, respectively, over 1970–2009. The air temperature increased at a faster rate than the surface water temperature in winter and autumn, whereas in spring and summer the surface water temperature warmed faster than the air temperature. The length of summer stratified season has increased by 12 ± 2 days since the early 1970s due to the increase in water temperature. The decline of surface wind speed over Lake Ontario resulted in a shallower surface mixed layer and enhanced the summer thermal stratification, which increased the summer surface water temperature more rapidly than the air temperature.

scholarly journals Irregular changes in lake surface water temperature and ice cover in subalpine Lake Lunz, Austria

Inland Waters ◽  
2017 ◽  
Vol 7 (1) ◽  
pp. 27-33 ◽  
Author(s):  
Martin J. Kainz ◽  
Robert Ptacnik ◽  
Serena Rasconi ◽  
Hannes H. Hager
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
Ice Cover ◽  
Surface Water Temperature ◽  
Lake Surface ◽  
Subalpine Lake
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