scholarly journals Analysis of climate change effects on evapotranspiration in the watershed Uhlířská in the Jizera Mountains

2010 ◽  
Vol 5 (No. 1) ◽  
pp. 28-38 ◽  
Author(s):  
M. Remrová ◽  
M. Císlerová
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Water Movement ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climatic Conditions ◽  
Weather Data ◽  
Atmospheric Conditions

This study has been conducted with the aim to analyse the hydrology balance in the experimental watershed Uhlířská under the actual atmospheric conditions and expected climate changes in the upcoming years. The main accent is put on the water availability for the water root uptake by the dominant grass vegetation (Calamagrostis villosa). Special attention is paid to the seasonal potential evapotranspiration estimation under mountain climatic conditions. Three methods for the potential evapotranspiration quantification are analysed in order to find out the most acceptable approach for future periods for which no adequate weather data are available. The future precipitation and temperature data are simulated by the regional climate model HIRHAM which is driven by global climate model HadCM3. The data are simulated for the period from 2071 to 2100. The modelling of the soil water movement (using S1D model) is carried out on selected 18 years from the period of 1961–2005 and on selected 10 climate-change-affected years with extremely low precipitations high temperatures. The results of the scenario presented do not indicate that the climatic changes should significantly affect the hydrological balance in the studied area in terms of evapotranspiration up to the year 2100. Due to the lower seasonal precipitation and higher air the temperature, was increased in the results of simulations under the defined approach, however, the local vegetation cover did not suffer from insufficient water supply. These considerations are close to the simulation models used.

scholarly journals Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

2013 ◽  
Vol 6 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Conditions ◽  
Southeastern Us ◽  
The Us ◽  
Ozone Levels

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF) model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM) to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

scholarly journals Brief Communication: An update of the article "Modelling flood damages under climate change conditions – a case study for Germany"

2016 ◽  
Vol 16 (7) ◽  
pp. 1617-1622 ◽  
Author(s):  
Fred Fokko Hattermann ◽  
Shaochun Huang ◽  
Olaf Burghoff ◽  
Peter Hoffmann ◽  
Zbigniew W. Kundzewicz
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Considerable Increase ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Impact Modelling ◽  
Flood Damages

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood-related losses can be expected in a future warmer climate. However, the general significance of the study was limited by the fact that outcome of only one global climate model (GCM) was used as a large-scale climate driver, while many studies report that GCMs are often the largest source of uncertainty in impact modelling. Here we show that a much broader set of global and regional climate model combinations as climate drivers show trends which are in line with the original results and even give a stronger increase of damages.

scholarly journals Quantification of the Expected Changes in Annual Maximum Daily Precipitation Quantiles under Climate Change in the Iberian Peninsula

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
The Future

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.

scholarly journals Brief Communication: An update of the article "Modeling flood damages under climate change conditions – a case study for Germany"

2015 ◽  
Vol 3 (12) ◽  
pp. 7231-7245
Author(s):  
F. F. Hattermann ◽  
S. Huang ◽  
O. Burghoff ◽  
P. Hoffmann ◽  
Z. W. Kundzewicz
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Large Scale ◽  
Considerable Increase ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Flood Damages

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood related losses can be expected in future, warmer, climate. However, the general significance of the study was limited by the fact that outcome of only one Global Climate Model (GCM) was used as large scale climate driver, while many studies report that GCM models are often the largest source of uncertainty in impact modeling. Here we show that a much broader set of global and regional climate model combinations as climate driver shows trends which are in line with the original results and even give a stronger increase of damages.

scholarly journals Downscaling a global climate model to simulate climate change impacts on US regional and urban air quality

2013 ◽  
Vol 6 (2) ◽  
pp. 2517-2549 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Climate Conditions ◽  
Southeastern Us ◽  
The Us

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (Western US, Texas, Northeastern, and Southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (northeast). We also find that daily peak temperatures tend to increase in most major cities in the US which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

scholarly journals Climate Data to Undertake Hygrothermal and Whole Building Simulations Under Projected Climate Change Influences for 11 Canadian Cities

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 72 ◽  
Author(s):  
Abhishek Gaur ◽  
Michael Lacasse ◽  
Marianne Armstrong
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Internal Variability ◽  
Climatic Conditions ◽  
Climate Data ◽  
Wide Range ◽  
The Future

Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance over current and projected future climates. Hygrothermal and whole building simulation models, which are important tools for assessing performance, require continuous climate records at high temporal frequencies of a wide range of climate variables for input into the kinds of models that relate to solar radiation, cloud-cover, wind, humidity, rainfall, temperature, and snow-cover. In this study, climate data that can be used to assess the performance of building envelopes under current and projected future climates, concurrent with 2 °C and 3.5 °C increases in global temperatures, are generated for 11 major Canadian cities. The datasets capture the internal variability of the climate as they are comprised of 15 realizations of the future climate generated by dynamically downscaling future projections from the CanESM2 global climate model and thereafter bias-corrected with reference to observations. An assessment of the bias-corrected projections suggests, as a consequence of global warming, future increases in the temperatures and precipitation, and decreases in the snow-cover and wind-speed for all cities.

Building synergies in regional climate services for Southeast Asia: The ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series.

2020 ◽  
Author(s):  
Gerald Lim ◽  
Aurel Moise ◽  
Raizan Rahmat ◽  
Bertrand Timbal
Keyword(s):  
Climate Change ◽  
Data Analysis ◽  
Southeast Asia ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Early Warning Systems ◽  
Climate Data ◽  
Climate Services

<p>Southeast Asia (SEA) is a rapidly developing and densely populated region that is home to over 600 million people. This, together with the region’s high sensitivity, exposure and low adaptive capacities, makes it particularly vulnerable to climate change and extremes such as floods, droughts and tropical cyclones. While the last decade saw some countries in SEA develop their own climate change projections, studies were largely uncoordinated and most countries still lack the capability to independently produce robust future climate information. Following a proposal from the World Meteorological Organisation (WMO) Regional Association (RA) V working group on climate services, the ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series was conceived in 2017 to bridge these gaps in regional synergies. The ARCDAP series has been organised annually since 2018 by the ASEAN Specialised Meteorological Centre (hosted by Meteorological Service Singapore) with support from WMO through the Canada-funded Climate Risk and Early Warning Systems (Canada-CREWS) initiative.</p><p>This presentation will cover the activities and outcomes from the first two workshops, as well as the third which will be held in February 2020. The ARCDAP series has so far brought together representatives from ASEAN National Meteorological and Hydrological Services (NMHSs), climate scientists and end-users from policy-making and a variety of vulnerability and impact assessment (VIA) sectors, to discuss and identify best practices regarding the delivery of climate change information, data usage and management, advancing the science etc. Notable outputs include two comprehensive workshop reports and a significant regional contribution to the HadEX3 global land in-situ-based dataset of temperature and precipitation extremes, motivated by work done with the ClimPACT2 software.</p><p>The upcoming third workshop will endeavour to encourage the uptake of the latest ensemble of climate simulations from the Coupled Model Intercomparison Project (CMIP6) using CMIP-endorsed tools such as ESMValTool. This will address the need for ASEAN climate change practitioners to upgrade their knowledge of the latest global climate model database. It is anticipated that with continued support from WMO, the series will continue with the Fourth workshop targeting the assessment of downscaling experiments in 2021.</p>

Future storylines of the 2012 soybean failure event

2021 ◽  
Author(s):  
Henrique Moreno Dumont Goulart ◽  
Bart van den Hurk ◽  
Karin van der Wiel
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Random Forest ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climatic Conditions ◽  
Soybean Production ◽  
Weather Events ◽  
Failure Event

<p>Weather events are a common cause for crop failures all over the world. Whilst extreme weather conditions may cause extreme impacts, the most common type of failure-inducing weather events are compounded. For these cases, explaining which conditions triggered a failure event is a complex task, as the links connecting climate and crop yield can be multiple and non-linear. On top of that, the climate change is likely to perturb the interface between climate and agriculture, possibly altering the occurrences or the drivers of crop failures, or generating new types of extreme impacts. In this context, the goal of this study is to demonstrate how global warming can affect the climate-crop connection. For that, we use a storyline approach and focus on an observed failure event, the extreme low soybean production during the 2012 season in hotspots regions, such as the Midwest US, Brazil and Argentina. The scale of this event drove the global soybean prices to the highest values ever recorded. We set out to quantify the change in occurrence of similar events in a warmer scenario. The storylines allow for event attribution, where a given impact can be examined and its causes disentangled. Here, four hotspots of soybean production are examined to contemplate the local consequences of climate change. The study is divided in two parts. We first link climatic features with soybean yields. For each hotspot region, a random forest classifier model is used to establish which meteorological variables are most important and how they are correlated with low soybean yields. With the model trained, we identify the climatic conditions that lead to the 2012 event. Second, we explore the influence of global warming on crop failures. Three large ensembles of simulated weather are obtained from the EC-Earth global climate model, one relating to the present-day period (including the 2012 event) and two relating to future periods with different levels of future warming . We apply the random forest model to these data, and obtain failure statistics for both present and future conditions, isolating the influence of climate change on the soybean failure.  </p>

scholarly journals The surface climatology of the eastern Mediterranean region obtained in a three-member ensemble climate change simulation experiment

2007 ◽  
Vol 12 ◽  
pp. 67-80 ◽  
Author(s):  
S. O. Krichak ◽  
P. Alpert ◽  
K. Bassat ◽  
P. Kunin
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Eastern Mediterranean ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Eastern Mediterranean Region ◽  
Climate Change Simulation ◽  
Precipitation Increase ◽  
Major Factors

Abstract. Two configurations of RegCM3 regional climate model (RCM) have been used to downscale results of two atmosphere-ocean global climate model (AOGCM) simulations of the current (1961–1990) and future climates (2071–2100) over the eastern Mediterranean (EM) region. The RCM domain covering the EM region from northern Africa to central part of Asia Minor with grid spacing of 50 km was used. Three sets of RCM simulations were completed. Results of the RCM experiment support earlier projections of a temperature (annual precipitation) increase (decrease) to the end of 21st century over the EM. The roles of several major factors in controlling uncertainty of the climate change estimates are evaluated. The main uncertainty factors appear to be associated with possible inadequacies in RCM description of the EM-climate-controlling developments over remotely located areas as well as those in the simulations of the global climate and its trends by the AOGCMs.

Sign in / Sign up

Export Citation Format

Share Document