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>

scholarly journals Assessing mean climate change signals in the global CORDEX-CORE ensemble

2020 ◽  
Author(s):  
Claas Teichmann ◽  
Daniela Jacob ◽  
Armelle Reca Remedio ◽  
Thomas Remke ◽  
Lars Buntemeyer ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Future Climate Change ◽  
Climate Services ◽  
Climate Change Information ◽  
Mean Climate

<p>The Coordinated Output for Regional Evaluations (CORE) simulation ensemble is an effort of the WCRP CORDEX community to provide high resolution regional climate change information for the major inhabited areas of the world and thus to generate the solid scientific basis for further research related to vulnerability, impact, adaptation and climate services (VIACS). This is especially important in those areas in which so far only few high-resolution simulations or only global comparatively coarse simulations were available. The driving simulations were selected to cover the spread of high, medium and low climate sensitivity at a global scale. Initially, the two RCMs REMO and RegCM4 were used to downscale these data global climate model output to a resolution of 0.22° (about 25km) while it is intended that the CORDEX CORE ensemble can then be extended by additional regional simulations to further increase the ensemble size and thus the representation of possible future climate change pathways.</p> <p>The aim of this study is to investigate and document the climate change information provided by the current CORDEX CORE ensemble with respect to mean climate change in different regions and in comparison to previously existing global climate information, especially those global climate simulations used as boundary forcing for CORDEX CORE, but also in comparison to the entire AR5-GCM ensemble. The analysis focuses on the representation of the AR5-GCM range of climate change signals by the CORDEX CORE ensemble with respect to mean temperature and precipitation changes and corresponding shifts in the annual cycles in the new AR6 IPCC physical reference regions. This also provides an indication for CORDEX CORE suitability for VIACS applications in each region.</p>

scholarly journals Early emergence in a butterfly causally linked to anthropogenic warming

2010 ◽  
Vol 6 (5) ◽  
pp. 674-677 ◽  
Author(s):  
Michael R. Kearney ◽  
Natalie J. Briscoe ◽  
David J. Karoly ◽  
Warren P. Porter ◽  
Melanie Norgate ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Change ◽  
Future Climate Change ◽  
Climate Data ◽  
Regional Warming

There is strong correlative evidence that human-induced climate warming is contributing to changes in the timing of natural events. Firm attribution, however, requires cause-and-effect links between observed climate change and altered phenology, together with statistical confidence that observed regional climate change is anthropogenic. We provide evidence for phenological shifts in the butterfly Heteronympha merope in response to regional warming in the southeast Australian city of Melbourne. The mean emergence date for H. merope has shifted −1.5 days per decade over a 65-year period with a concurrent increase in local air temperatures of approximately 0.16°C per decade. We used a physiologically based model of climatic influences on development, together with statistical analyses of climate data and global climate model projections, to attribute the response of H. merope to anthropogenic warming. Such mechanistic analyses of phenological responses to climate improve our ability to forecast future climate change impacts on biodiversity.

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.

Climate Change Explorer: Extracting localized data for developing Climate Services

2021 ◽  
Author(s):  
Christine Nam ◽  
Bente Tiedje ◽  
Susanne Pfeifer ◽  
Diana Rechid ◽  
Daniel Eggert
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Climate Projections ◽  
Climate Data ◽  
Climate Services ◽  
Mitigation And Adaptation ◽  
Data Formats

<p>Everyone, politicians, public administrations, business owners, and citizens want to know how climate changes will affect them locally. Having such knowledge offers everyone the opportunity to make informed choices and take action towards mitigation and adaptation.</p><p> </p><p>In order to develop locally relevant climate service products and climate advisory services, as we do at GERICS, we must extract localized climate change information from Regional Climate Model ensemble simulations.</p><p> </p><p>Common challenges associated with developing such services include the transformation of petabytes of data from physical quantities such as precipitation, temperature, or wind, into user-applicable quantities such as return periods of heavy precipitation, e.g. for legislative or construction design frequency. Other challenges include the technical and physical barriers in the use and interpretation of climate data, due to large data volume, unfamiliar software and data formats, or limited technical infrastructure. The interpretation of climate data also requires scientific background knowledge, which limit or influence the interpretation of results.</p><p> </p><p>These barriers hinder the efficient and effective transformation of big data into user relevant information in a timely and reliable manner. To enable our society to adapt and become more resilient to climate change, we must overcome these barriers. In the Helmholtz funded Digital Earth project we are tackling these challenges by developing a Climate Change Workflow.</p><p> </p><p>In the scope of this Workflow, the user can <span>easily define a region of interest and extract </span><span>the</span><span> relevant </span><span>climate data </span><span>from the simulations available </span><span>at</span><span> the Earth System Grid Federation (ESGF). Following which, </span><span>a general overview of the projected changes, in precipitation </span><span>for example, for multiple climate projections is presented</span><span>. It conveys the bandwidth, </span><span>i.e. </span><span>the minimum/maximum range by an ensemble of regional climate model projections. </span><span>We implemented the sketched workflow in a web-based tool called </span><span>The Climate Change Explorer. </span><span>It</span> addresses barriers associated with extracting locally relevant climate data from petabytes of data, in unfamilar data formats, and deals with interpolation issues, using a more intuitive and user-friendly web interface.</p><p> </p><p>Ultimately, the Climate Change Explorer provides concise information on the magnitude of projected climate change and the range of these changes for individually defined regions, such as found in GERICS ‘Climate Fact Sheets’. This tool has the capacity to also improve other workflows of climate services, allowing them to dedicate more time in deriving user relevant climate indicies; enabling politicians, public administrations, and businesses to take action.</p>

scholarly journals Impacts of climate and catastrophic forest changes on streamflow and water balance in a mountainous headwater stream in Southern Alberta

2013 ◽  
Vol 17 (12) ◽  
pp. 4941-4956 ◽  
Author(s):  
V. Mahat ◽  
A. Anderson
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Similar Amount ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Stochastic Weather Generator ◽  
Precipitation Decrease ◽  
Southern Alberta

Abstract. Rivers in Southern Alberta are vulnerable to climate change because much of the river water originates as snow in the eastern slopes of the Rocky Mountains. Changes in likelihood of forest disturbance (wildfire, insects, logging, etc.) may also have impacts that are compounded by climate change. This study evaluates the impacts of climate and forest changes on streamflow in the upper parts of the Oldman River in Southern Alberta using a conceptual hydrological model, HBV-EC (Hydrologiska Byråns attenbalansavdelning, Environment Canada), in combination with a stochastic weather generator (LARS-WG) driven by GCM (global climate model) output climate data. Three climate change scenarios (A1B, A2 and B1) are selected to cover the range of possible future climate conditions (2020s, 2050s, and 2080s). The GCM projected less than a 10% increase in precipitation in winter and a similar amount of precipitation decrease in summer. These changes in projected precipitation resulted in up to a 200% (9.3 mm) increase in winter streamflow in February and up to a 63% (31.2 mm) decrease in summer flow in June. Flow also decreased in July and August, when irrigation is important; these reduced river flows during this season could impact agriculture production. The amplification in the streamflow is mostly driven by the projected increase in temperature that is predicted to melt winter snow earlier, resulting in lower water availability during the summer. Uncertainty analysis was completed using a guided GLUE (generalized likelihood uncertainty estimation) approach to obtain the best 100 parameter sets and associated ranges of streamflows. The impacts of uncertainty in streamflows were higher in spring and summer than in winter and fall. Forest change compounded the climate change impact by increasing the winter flow; however, it did not reduce the summer flow.

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