scholarly journals Contructing Climate Change Scenarios for Ho Chi Minh City

Author(s):  
Mai Van Khiem

Abstract: This article presents the results of constructing climate change scenarios for Ho Chi Minh City (HCMC)based on the climate change scenarios of Vietnam published in 2016 by the Ministry of Natural Resources and Environment. Four high- resolution regional climate models include CCAM, clWRF, PRECIS, RegCM were used to downscale results of global climate models. The results show that the annual average temperature in HCMC tends to increase in the future compared to the baseline period 1986-2005, the increase depends on each RCP scenario. By the end of the century, the annual average temperature in HCMC had an increase of about 1.7÷1.9°C under the RCP4.5 scenario and 3.2÷3.6°C under RCP8.5.Meanwhile, annual rainfall in HCMC tends to increase in most periods under both of RCP scenarios. By the end of the century, annual rainfall in HCMC increases from 15% to 25% in the RCP4.5 scenario and 20-25% in the RCP8.5 scenario. Annual rainfall in coastal areas increases more than inland areas. Keyword: Climate change scenarios, Ho Chi Minh city

2022 ◽  
Vol 964 (1) ◽  
pp. 012009
Author(s):  
Anh Ngoc Le ◽  
Thi Nguyen Vo ◽  
Van Hong Nguyen ◽  
Dang Mau Nguyen

Abstract This paper reviews the trends of climate and climate change scenarios in Ho Chi Minh City (HCMC). The linear regression method is used to determine the trend and variation of past climate (1980-2019) at Tan Son Hoa station. The annual average temperature tends to increase about 0.024°C/year (r2=0.54) and the rainfall tends to increase about 6.03 mm/year (r2=0.67). For temperature scenario, by 2030 the annual average temperature in the whole city will increase from 0.80- 0.81°C (RCP4.5) and 0.92-0.98°C (RCP8.5). By 2050, it will increase 1.23-1.33°C (RCP4.5) and 1.55-1.68°C (RCP8.5). By 2100, it will increase 1.75-1.88°C (RCP4.5) and 3.20-3.55°C (RCP8.5) compared to the base period. Regarding rainfall scenario, in 2030, the city-wide average rainfall will increase by 12-21% (RCP4.5) and by 12-17% (RCP8.5). By 2050, the average rainfall is likely to increase by 13-15% (RCP4.5) and 15-17% (RCP8.5). By 2100, the average rainfall is likely to increase by 18-22% (RCP4.5) and 20-21% (RCP8.5) compared to the base period.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.


2011 ◽  
Vol 137 ◽  
pp. 286-290 ◽  
Author(s):  
Xi Chun ◽  
Mei Jie Zhang ◽  
Mei Ping Liu

The objective of this study is to analyse the climate changing patterns chronologically for exposing the coincident relationships between the lake area fluctuation and the climate change in Qehan lake of Abaga county of Inner Mongolia. The results show that there’s highly interrelation between the changes of the lake area and the climatic factors here, the annual average temperature and annual evaporation are negatively interrelate to the lake area fluctuation, and the annual precipitation interrelate to it is positive. The lake area has descended about 75 km2 during the nearly past 40 years. There were about two considerable lake expansions in 1973, 1998 through the generally lake area descending process.


2020 ◽  
Author(s):  
James Murphy

<p>The challenge of combining initialised and uninitialised decadal projections</p><p>James Murphy, Robin Clark, Nick Dunstone, Glen Harris, Leon Hermanson and Doug Smith</p><p>During the past 10 years or so, exploratory work in initialised decadal climate prediction, using global climate models started from recent analyses of observations, has grown into a coordinated international programme that contributes to IPCC assessments. At the same time, countries have continued to develop and update their national climate change scenarios.  These typically cover the full 21<sup>st</sup> century, including the initial decade that overlaps with the latest initialised forecasts. To date, however, national scenarios continue to be based exclusively on long-term (uninitialised) climate change simulations, with initialised information regarded as a separate stream of information.</p><p>We will use early results from the latest UK national scenarios (UKCP), and the latest CMIP6 initialised predictions, to illustrate the potential and challenges associated with the notion of combining both streams of information. This involves assessing the effects of initialisation on predictability and uncertainty (as indicated, for example, by the skill of ensemble-mean forecasts and the spread amongst constituent ensemble members). Here, a particular challenge involves interpretation of the “signal-to-noise” problem, in which ensemble-mean skill can sometimes be found which is larger than would be expected on the basis of the ensemble spread. In addition to initialisation, we will also emphasise the importance of understanding how the assessment of climate risks depends on other features of prediction system design, including the sampling of model uncertainties and the simulation of internal climate variability.</p>


Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1803
Author(s):  
Inmaculada C. Jiménez-Navarro ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Julio Pérez-Sánchez ◽  
Javier Senent-Aparicio

Precipitation and temperature around the world are expected to be altered by climate change. This will cause regional alterations to the hydrological cycle. For proper water management, anticipating these changes is necessary. In this study, the basin of Lake Erken (Sweden) was simulated with the recently released software SWAT+ to study such alterations in a short (2026–2050), medium (2051–2075) and long (2076–2100) period, under two different climate change scenarios (SSP2-45 and SSP5-85). Seven global climate models from the latest projections of future climates that are available (CIMP 6) were compared and ensembled. A bias-correction of the models’ data was performed with five different methods to select the most appropriate one. Results showed that the temperature is expected to increase in the future from 2 to 4 °C, and precipitation from 6% to 20%, depending on the scenario. As a result, water discharge would also increase by about 18% in the best-case scenario and by 50% in the worst-case scenario, and the surface runoff would increase between 5% and 30%. The floods and torrential precipitations would also increase in the basin. This trend could lead to soil impoverishment and reduced water availability in the basin, which could damage the watershed’s forests. In addition, rising temperatures would result in a 65% reduction in the snow water equivalent at best and 92% at worst.


Author(s):  
Jayne F. Knott ◽  
Jo E. Sias ◽  
Eshan V. Dave ◽  
Jennifer M. Jacobs

Pavements are vulnerable to reduced life with climate-change-induced temperature rise. Greenhouse gas emissions have caused an increase in global temperatures since the mid-20th century and the warming is projected to accelerate. Many studies have characterized this risk with a top-down approach in which climate-change scenarios are chosen and applied to predict pavement-life reduction. This approach is useful in identifying possible pavement futures but may miss short-term or seasonal pavement-response trends that are essential for adaptation planning. A bottom-up approach focuses on a pavement’s response to incremental temperature change resulting in a more complete understanding of temperature-induced pavement damage. In this study, a hybrid bottom-up/top-down approach was used to quantify the impact of changing pavement seasons and temperatures on pavement life with incremental temperature rise from 0 to 5°C at a site in coastal New Hampshire. Changes in season length, seasonal average temperatures, and temperature-dependent resilient modulus were used in layered-elastic analysis to simulate the pavement’s response to temperature rise. Projected temperature rise from downscaled global climate models was then superimposed on the results to determine the timing of the effects. The winter pavement season is projected to end by mid-century, replaced by a lengthening fall season. Seasonal pavement damage, currently dominated by the late spring and summer seasons, is projected to be distributed more evenly throughout the year as temperatures rise. A 7% to 32% increase in the asphalt-layer thickness is recommended to protect the base and subgrade with rising temperatures from early century to late-mid-century.


2021 ◽  
Author(s):  
Yusuke Satoh ◽  
Hideo Shiogama ◽  
Naota Hanasaki ◽  
Yadu Pokhrel ◽  
Julien Boulange ◽  
...  

<p>Droughts are anticipated to intensify or become more frequent in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought definition, makes it difficult to compare drought projections and hampers overviewing future changes in drought. This issue is widely known and underscored in recent reports of the Intergovernmental Panel on Climate Change, but the relative importance of the issue and its spatial distribution have never been quantitatively evaluated compared to other sources of uncertainty.</p><p>Here, using a multi-scenario and multi-model dataset with combinations of three climate change scenarios, four global climate models and seven global water models, we evaluated changes in the frequency of three categories of drought (meteorological, agricultural, and hydrological droughts) by a consistent standardized approach with four different temporal scales of accumulation periods to show how differences among the drought definitions could result in critical uncertainties. For simplicity, this study focuses on one drought index per drought category. Firstly we investigated the disagreement in the sign of changes between definitions, and then we decomposed the overall uncertainty to estimate the relative importance of each source of uncertainty. By a multifactorial ANOVA, uncertainty was decomposed into four main factors, namely drought definitions, climate change scenarios, global climate models and global water impact models, and their interactions.</p><p>Our results highlight specific regions where the sign of change disagrees between drought definitions. Importantly, changes in drought frequency in such regions tended to be statistically insignificant with low ensemble member agreement. Drought definition attributed to18% of the main factor uncertainty at the global scale, and the definition was the dominant uncertainty source over 11% of the global land area. The contribution of difference in the drought category showed a higher contribution to overall uncertainty than the difference in scales. The contribution of scenario uncertainty was the least among the main factors in general, though it is a dominant factor in the far-future in a couple of hotspot regions such as the Mediterranean region. Overall, model uncertainties were the primary source of uncertainty, and the definition issue was less important over large areas. However, definition uncertainty was the primal uncertainty source with significant changes in particular regions, such as parts of high-latitude areas in the northern hemisphere. One needs to pay attention to these regions in overviewing future drought change. Nonetheless, what this study quantified is the relative importance of uncertainty stemming from drought definition that should be avoidable or reducible if one treats drought specifically. Our results indicate that we can reduce uncertainty in drought projections to some extent and get a clearer picture by clarifying hydrological processes or sectors of interest.</p>


2021 ◽  
pp. 403-417
Author(s):  
Amit Dubey ◽  
Deepak Swami ◽  
Nitin Joshi

ncrease in the water scarcity and the related rise in demand of water coupled with the threating events of climate change, ultimately witnessed drought in the recent years to occur frequently. Therefore, Drought hydrology is drawing most of the attention. Drought which is a natural hazard can be best characterized by various hydrological and climatological parameters. In order to model drought, researchers have applied various concepts starting from simplistic model to the complex ones. The suitability of different modelling approaches and their negative and positive traits are very essential to comprehend. This paper is an attempt to review various methodologies utilized in modelling of drought such as forecasting of drought, drought modelling based on probability, Global Climate Models (GCM) under climate change scenarios. It is obtained from the present study that the past three decades have witnessed a very significant improvement in the drought modelling studies. For the larger time window of drought forecasting, hybrid models which incorporates large scale climate indices are promisingly suitable. Drought characterization based on copula models for multivariate drought characterization seems to have an edge over the others. At the end some conclusive remarks are made as far as the future drought modelling and research is concerned.


2016 ◽  
Vol 8 (2) ◽  
pp. 30 ◽  
Author(s):  
Micah J. Hewer ◽  
William A. Gough

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.


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