Impacts of rainfall and air temperature variations due to climate change upon hydrological characteristics: a case study

2015 ◽  
Vol 6 (4) ◽  
pp. 865-879 ◽  
Author(s):  
Ying Ouyang ◽  
Jia-En Zhang ◽  
Yide Li ◽  
Prem Parajuli ◽  
Gary Feng
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Driving Forces ◽  
Water Discharge ◽  
Future Climate Change ◽  
Temperature Variations ◽  
Study Results ◽  
Evaporative Loss ◽  
Water Outflow ◽  
Air Temperature Variations

Rainfall and air temperature variations resulting from climate change are important driving forces to change hydrologic processes in watershed ecosystems. This study investigated the impacts of past and future rainfall and air temperature variations upon water discharge, water outflow (from the watershed outlet), and evaporative loss in the Lower Yazoo River Watershed (LYRW), Mississippi, USA using the Hydrological Simulation Program-Fortran (HSPF) model. Four future climate change (i.e., rainfall and air temperature change) scenarios, namely the CSIROMK35A1B, HADCM3B2, CSIROMK2B2, and MIROC32A1B scenarios, were used as input data to perform simulations in this study. Results showed that monthly variations of water discharge, evaporative loss, and water outflow were primarily due to the monthly fluctuations of rainfall rather than air temperature. On average, for all of the four scenarios, a 6.4% decrease in rainfall amount resulted in, respectively, 11.8 and 10.3% decreases in water outflow and evaporative loss. Our study demonstrated that rainfall had profound impacts upon water outflow and evaporative loss. In light of this predicted future decrease in water outflow, water resource conservation practices such as reducing ground and surface water usages that help to prevent streams from drying are vitally important in mitigating climate change impacts on stream flow in the LYRW.

scholarly journals Current and future occurrences of health-relevant, compound heat and ozone pollution events in six European ozone-temperature regions 

2021 ◽  
Author(s):  
Sally Jahn ◽  
Elke Hertig
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Large Scale ◽  
Coupled Model ◽  
Ground Level ◽  
Future Climate Change ◽  
Ozone Pollution ◽  
Ground Level Ozone ◽  
Ozone Concentrations ◽  
Elevated Ozone

<p>Air pollution and heat events present two major health risks, both already independently posing a significant threat to human health and life. High levels of ground-level ozone (O<sub>3</sub>) and air temperature often coincide due to the underlying physical relationships between both variables. The most severe health outcome is in general associated with the co-occurrence of both hazards (e.g. Hertig et al. 2020), since concurrent elevated levels of temperature and ozone concentrations represent a twofold exposure and can lead to a risk beyond the sum of the individual effects. Consequently, in the current contribution, a compound approach considering both hazards simultaneously as so-called ozone-temperature (o-t-)events is chosen by jointly analyzing elevated ground-level ozone concentrations and air temperature levels in Europe.</p><p>Previous studies already point to the fact that the relationship of underlying synoptic and meteorological drivers with one or both of these health stressors as well as the correlation between both variables vary with the location of sites and seasons (e.g. Otero et al. 2016; Jahn, Hertig 2020). Therefore, a hierarchical clustering analysis is applied to objectively divide the study domain in regions of homogeneous, similar ground-level ozone and temperature characteristics (o-t-regions). Statistical models to assess the synoptic and large-scale meteorological mechanisms which represent main drivers of concurrent o-t-events are developed for each identified o-t-region.</p><p>Compound elevated ozone concentration and air temperature events are expected to become more frequent due to climate change in many parts of Europe (e.g. Jahn, Hertig 2020; Hertig 2020). Statistical projections of potential frequency shifts of compound o-t-events until the end of the twenty-first century are assessed using the output of Earth System Models (ESMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6).</p><p><em>Hertig, E. (2020) Health-relevant ground-level ozone and temperature events under future climate change using the example of Bavaria, Southern Germany. Air Qual. Atmos. Health. doi: 10.1007/s11869-020-00811-z</em></p><p><em>Hertig, E., Russo, A., Trigo, R. (2020) Heat and ozone pollution waves in Central and South Europe- characteristics, weather types, and association with mortality. Atmosphere. doi: 10.3390/atmos11121271</em></p><p><em>Jahn, S., Hertig, E. (2020) Modeling and projecting health‐relevant combined ozone and temperature events in present and future Central European climate. Air Qual. Atmos. Health. doi: 10.1007/s11869‐020‐009610</em></p><p><em>Otero N., Sillmann J., Schnell J.L., Rust H.W., Butler T. (2016) Synoptic and meteorological drivers of extreme ozone concentrations over Europe. Environ Res Lett. doi: 10.1088/ 1748-9326/11/2/024005</em></p>

scholarly journals Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon

2019 ◽  
Vol 11 (9) ◽  
pp. 2480 ◽  
Author(s):  
Cláudia Reis ◽  
António Lopes
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Urban Climate ◽  
Green Spaces ◽  
Reference Station ◽  
Future Climate Change ◽  
Measuring Point ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Human Thermal Comfort

The increase and optimization of urban vegetation has been considered an effective mitigation measure of an urban heat island (UHI), with positive effects on human thermal comfort. In this study, the cooling potential of all green spaces in Lisbon was estimated. For that, several mobile measurements of air temperature data were made in a single park (Gulbenkian’s Garden). These measurements were used for the interpolation of air temperature. Furthermore, urban biomass was estimated using remote sensing products, namely Landsat satellite images. Ultimately, a linear regression model was built from the relation between vegetation density and air temperature. Results regarding the estimation of biomass (AGB) in the city of Lisbon were higher in winter than in summer. The urban green spaces cooling potential model showed that for every decrease of 1 °C in air temperature between a measuring point and a reference station we need to increase the area covered by vegetation by 50 m2 (planar measure). This methodology can be applied in other urban areas for the quantification of the cooling effect provided by vegetation in order to improve urban climate thermal conditions and human well-being and, consequently, to mitigate some consequences of future climate change.

scholarly journals A novel method for assessing climate change impacts in ecotron experiments

2020 ◽  
Vol 64 (10) ◽  
pp. 1709-1727
Author(s):  
Inne Vanderkelen ◽  
Jakob Zscheischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Air Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Forcing ◽  
Future Climate Change ◽  
Ecosystem Responses ◽  
Model Projection ◽  
Global Mean

Abstract Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change.

Land surface air temperature variations over Eurasia and possible causes in the past century

2017 ◽  
Vol 38 (4) ◽  
pp. 1925-1937 ◽  
Author(s):  
Zhiyan Zuo ◽  
Song Yang ◽  
Kang Xu ◽  
Renhe Zhang ◽  
Qiong He ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Past Century ◽  
Temperature Variations ◽  
The Past ◽  
Air Temperature Variations

scholarly journals Observed groundwater temperature response to recent climate change

2014 ◽  
Vol 18 (11) ◽  
pp. 4453-4466 ◽  
Author(s):  
K. Menberg ◽  
P. Blum ◽  
B. L. Kurylyk ◽  
P. Bayer
Keyword(s):  
Climate Change ◽  
Heat Transfer ◽  
Air Temperature ◽  
Shallow Groundwater ◽  
Regime Shifts ◽  
Future Climate Change ◽  
Groundwater Temperature ◽  
Recent Climate Change ◽  
Recent Climate ◽  
Groundwater Dependent Ecosystems

Abstract. Climate change is known to have a considerable influence on many components of the hydrological cycle. Yet, the implications for groundwater temperature, as an important driver for groundwater quality, thermal use and storage, are not yet comprehensively understood. Furthermore, few studies have examined the implications of climate-change-induced groundwater temperature rise for groundwater-dependent ecosystems. Here, we examine the coupling of atmospheric and groundwater warming by employing stochastic and deterministic models. Firstly, several decades of temperature time series are statistically analyzed with regard to climate regime shifts (CRSs) in the long-term mean. The observed increases in shallow groundwater temperatures can be associated with preceding positive shifts in regional surface air temperatures, which are in turn linked to global air temperature changes. The temperature data are also analyzed with an analytical solution to the conduction–advection heat transfer equation to investigate how subsurface heat transfer processes control the propagation of the surface temperature signals into the subsurface. In three of the four monitoring wells, the predicted groundwater temperature increases driven by the regime shifts at the surface boundary condition generally concur with the observed groundwater temperature trends. Due to complex interactions at the ground surface and the heat capacity of the unsaturated zone, the thermal signals from distinct changes in air temperature are damped and delayed in the subsurface, causing a more gradual increase in groundwater temperatures. These signals can have a significant impact on large-scale groundwater temperatures in shallow and economically important aquifers. These findings demonstrate that shallow groundwater temperatures have responded rapidly to recent climate change and thus provide insight into the vulnerability of aquifers and groundwater-dependent ecosystems to future climate change.

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