scholarly journals A GCMs-based mathematic model for droughts prediction in the Haihe Basin, China: Multi-GCM Divide-Integration

2016 ◽  
Author(s):  
Dongmei Han ◽  
Denghua Yan ◽  
Xinyi Xu ◽  
Zhongwen Yang ◽  
Yajing Lu
Keyword(s):  
Water Resources ◽  
Spatial Scale ◽  
Climate Models ◽  
Global Climate ◽  
Mathematic Model ◽  
Global Climate Models ◽  
Annual Rainfall ◽  
Severe Drought ◽  
Data Sets ◽  
Integration Model

Abstract. Recently, the skilful prediction of climate change has drawn high attention from the scientific community. Evidence has been reported the skill of prediction is not satisfactory for the magnitude of inter-annual precipitation and extreme precipitation, and at a smaller spatial scale as well. Based on observational data sets and outputs from the Global Climate Models (GCMs), this study aims at achieving a mathematical model, named multi-GCM divide-integration model (MGDI). The MGDI model is developed by hybridizing finer spatial scale and multi-linear regression model (MLRM) on five state-of-art of GCMs to improve the skills of five GCMs, which is applied to the second level of water resources regionalization in China. It is found that the performance after MGDI model correction has been improved significantly over that of individual GCMs. The errors between observation and simulation after correction (1.6 % ~ 4.4%) are within the margin of error (smaller than 5 %) and all of the varying trends in each second level of water resources regionalization were same. Furthermore, this study also used the MGDI model to predict the variation of precipitation and droughts at different spatial scale, including second level of water resources regionalization of China and the whole HHB, for the next 40 years. Predictions indicate the climate will gradually change from drying to wetting over the HHB wherein the trend of annual rainfall is 9.3 mm/10 a. The frequency of drought events will be decreasing as time goes on. The occurrence of mild and severe drought in the Luan River and Jidong Coastal, Tuhai majia River are higher than that in other regions, 9 and 8 respectively. These findings would provide scientific support for current water resources management and future drought-resisting planning of districts in China.

scholarly journals Cambios proyectados de los recursos hídricos bajo escenarios de emisiones RCP4.5 y 8.5 de modelos climáticos globales del CMIP5 en el Altiplano Peruano

2016 ◽  
Vol 18 (2) ◽  
Author(s):  
Efrain Lujano-Laura ◽  
Liz S. Hidalgo-Sanchez ◽  
Bernardino Tapia-Aguilar ◽  
Apolinario Lujano-Laura
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Annual Rainfall ◽  
Palabras Clave ◽  
Australian Community ◽  
Intercomparison Project ◽  
Spatio Temporal

<p>La investigación, se realizó en el ámbito del altiplano Peruano, con el objetivo de evaluar los cambios en la disponibilidad del recurso hídrico bajo escenarios de emisiones de Modelos Climáticos Globales (MCG) del Proyecto de Intercomparación de Modelos Acoplados Fase 5 (CMIP5). La distribución espacio-temporal de la precipitación, se tomó como referencia la climatología 1971 – 2000 y sus proyecciones para el horizonte 2071 – 2100, así mismo para la simulación de caudales se utilizó el modelo hidrológico conceptual de Ingeniería Rural de 2 parámetros, cuyas evaluaciones estadísticas se midieron a través de la eficiencia de Nash y Sutcliffe. El Simulador del Sistema Terrestre y el Clima de la Comunidad Australiana versiones 1.0 y 1.3 (ACCESS1.0 y 1.3) y el Modelo para la Investigación Interdisciplinaria sobre el Clima versión 5 (MIROC5), simularon adecuadamente el ciclo estacional de la precipitación y en base a los resultados, los cambios de precipitaciones para los caminos de concentración representativas (RCP4.5 y 8.5) a finales del siglo XXI, indican un ligero incremento de la precipitación anual en la cuenca Ramis y una disminución para la cuenca Ilave. Es así que las variaciones de las precipitaciones son también reflejadas en los caudales, concluyéndose que las mayores disminuciones del recurso hídrico se darían para la cuenca Ilave, con incrementos ligeros en promedio anual para la cuenca Ramis.</p><p><strong>Palabras clave:</strong> Altiplano Peruano, cambio climático, escenarios climáticos, disponibilidad hídrica.</p><p align="center"><strong>ABSTRACT</strong></p><p>The research was conducted in the area of the Peruvian altiplano with the aim to assess changes in the availability of water resources under emission scenarios Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 5 (CMIP5). The spatio-temporal precipitation distribution was taken as reference climatology 1971 - 2000 and its projections for the horizon 2071 - 2100, also for simulating flows conceptual hydrological model of Rural Engineering 2 parameters are used, whose evaluations statistics were measured through efficiency Nash and Sutcliffe. The Australian Community Climate and Earth System Simulator versions 1.0 and 1.3 (ACCESS1.0 and 1.3) and Model for Interdisciplinary Research on Climate version 5 (MIROC5), adequately simulated the seasonal cycle of precipitation and based results, changes in rainfall for Representative Concentration Pathways (RCP4.5 and 8.5) at the end of the XXI century, indicate a slight increase of annual rainfall of the basin Ramis and a decrease for the Ilave basin. Is thus that variations in rainfall are also reflected in the flows, concluding that the largest decreases of water resources would be given for the Ilave basin, with slight increases in annual average for the basin Ramis.</p><p><strong>Keywords: </strong>Peruvian altiplano,<strong> </strong>climate change, climate scenarios, water availability.</p>

scholarly journals Brief Communication: Drought Likelihood for East Africa

2017 ◽  
Author(s):  
Hui Yang ◽  
Chris Huntingford
Keyword(s):  
East Africa ◽  
Climate Models ◽  
Global Climate ◽  
Extreme Rainfall ◽  
Global Climate Models ◽  
Severe Drought ◽  
East African ◽  
Reanalysis Dataset ◽  
Weather Forecasts ◽  
Medium Range

Abstract. The on-going effects of severe drought in East Africa are causing high levels of malnutrition, hunger, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya need food, water and medical assistance (DEC, 2017). Many factors influence drought stress and ability to respond. However, inevitably it is asked: are elevated atmospheric greenhouse gas (GHG) concentrations altering the likelihood of extreme rainfall deficits? We find small increases in probability of this for East African, based on merging the observation-based reanalysis dataset by the European Centre for Medium-Range Weather Forecasts (ECMWF) (Dee et al., 2011) with Global Climate Models (GCMs) in the CMIP5 database (Taylor et al., 2012).

scholarly journals An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

2013 ◽  
Vol 17 (2) ◽  
pp. 565-578 ◽  
Author(s):  
J. A. Velázquez ◽  
J. Schmid ◽  
S. Ricard ◽  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Hydrological Model ◽  
Global Climate ◽  
Regional Climate ◽  
Structural Complexity ◽  
Global Climate Models ◽  
Hydrological Models ◽  
The Impact

Abstract. Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e., lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by global climate models over a reference (1971–2000) and a future (2041–2070) period. The results show that, for our hydrological model ensemble, the choice of model strongly affects the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model.

scholarly journals Assessment of the Future Impact of Climate Change on the Hydrology of the Mangoky River, Madagascar Using ANN and SWAT

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1239
Author(s):  
Mirindra Finaritra Rabezanahary Tanteliniaina ◽  
Md. Hasibur Rahaman ◽  
Jun Zhai
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Assessment Tool ◽  
Global Climate ◽  
Annual Runoff ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Adaptation To Climate Change ◽  
Artificial Neural Network Ann

The assessment of the impacts of climate change on hydrology is important for better water resources management. However, few studies have been conducted in semi-arid Africa, even less in Madagascar. Here we report, climate-induced future hydrological prediction in Mangoky river, Madagascar using an artificial neural network (ANN) and the soil and water assessment tool (SWAT). The current study downscaled two global climate models on the mid-term, noted the 2040s (2041–2050) and long-term, noted 2090s (2091–2099) under two shared socioeconomic pathways (SSP) scenarios, SSP 3–7.0 and SSP 5–8.5. Statistical indices of both ANN and SWAT showed good performance (R2 > 0.65) of the models. Our results revealed a rise in maximum temperature (4.26–4.69 °C) and minimum temperature (2.74–3.01 °C) in the 2040s and 2090s. Under SSP 3–7.0 and SSP 5–8.5, a decline in the annual precipitation is projected in the 2040s and increased the 2090s. This study found that future precipitation and temperature could significantly decrease annual runoff by 60.59% and 73.77% in the 2040s; and 25.18% and 23.45% in the 2090s under SSP 3–7.0 and SSP 5–8.5, respectively. Our findings could be useful for the adaptation to climate change, managing water resources, and water engineering.

Relative Contribution of Anthropogenic Forcing and Natural Processes to Rainfall Variability over Victoria, Australia

2020 ◽  
Author(s):  
Surendra Rauniyar ◽  
Scott Power
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Models ◽  
Interquartile Range ◽  
Annual Rainfall ◽  
External Forcing ◽  
Cool Season ◽  
Millennium Drought ◽  
Forced Drying

&lt;p&gt;Victoria is the second-most populated and most densely populated state in Australia with a population of over 6.5 million. Over two thirds of the population live in greater Melbourne. It is also a major area for agriculture and tourism and is the second largest economy in Australia, accounting for a quarter of Australia's Gross Domestic Product. Any changes in Victoria's climate has huge impacts in these sectors. Rainfall over Victoria during the cool season (e.g. April to October) has been unusually low since the beginning of the Millennium Drought in 1997 (~12% below the 20&lt;sup&gt;th&lt;/sup&gt; century average). Cool season rainfall contributes two-third to annual rainfall and is very important for many crops and for replenishing reservoirs across the state. Here we examine the extent to which this reduction in cool season rainfall is driven by external forcing, and the prospects for future multi-decadal rainfall, taking both external forcing and internal natural climate variability into account.&lt;/p&gt;&lt;p&gt;We analyse simulations from 40 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) under preindustrial and historical forcing, as well as three scenarios for the 21&lt;sup&gt;st&lt;/sup&gt; century: Representative Concentration Pathway (RCP)2.6, RCP4.5 and RCP8.5, which vary markedly in the amount of greenhouse gas emitted over the coming century. While the 1997-2018 average rainfall for cool season is below the preindustrial average in more than two-thirds of models under the three scenarios, the magnitude of the externally-forced drying is very small (median decline is around -2.5% in all three scenarios with an interquartile range around -5% to +1%). The model ensemble results suggest that external forcing contributed only 20% (interquartile range -41% to 4%) to the drying observed in 1997-2018, relative to 1900-1959. These results suggest that the observed drying was dominated by natural, internal rainfall variability. While the multi-model median is below average from 1997-2018 onwards, the externally-forced drying only becomes clear from 2010-2029, when the proportion of models exhibiting drying increases to over 90% under all three scenarios. This agreement reflects the increase in the magnitude of the externally-forced drying. We estimate that there is a 12% chance that internal rainfall variability will completely offset the externally-forced drying averaged over 2018-2037, regardless of scenario. By the late 21&lt;sup&gt;st&lt;/sup&gt; century the externally forced change under RCP8.5 is so large that drying &amp;#8211; even after taking internally variability into account - appears inevitable.&amp;#160;&lt;/p&gt;&lt;p&gt;Confidence in the modelled projections is lowered because models have difficulty in simulating the magnitude of the observed decline in rainfall. Some of this difficulty appears to arise because most models seem to underestimate multidecadal rainfall variability. Other candidates are: the observed drying may have been primarily due to the occurrence of an extreme, internally-driven event; the models underestimate the magnitude of the externally-forced drying in recent decades; or some combination of the two. If externally-forced drying is underestimated because the response to greenhouse gases is underestimated then the magnitude of projected changes might also be underestimated.&lt;/p&gt;

Evaluating extreme climate indices from CMIP3&5 global climate models and reanalysis data sets: a case study for present climate in the Andes of Ecuador

2017 ◽  
Vol 37 ◽  
pp. 363-379 ◽  
Author(s):  
Lenin Campozano ◽  
Angel Vázquez-Patiño ◽  
Daniel Tenelanda ◽  
Jan Feyen ◽  
Esteban Samaniego ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Climate Indices ◽  
Data Sets ◽  
Present Climate ◽  
Extreme Climate ◽  
The Andes

scholarly journals Increased Drought Risk in South Asia under Warming Climate: Implications of Uncertainty in Potential Evapotranspiration Estimates

2020 ◽  
Vol 21 (12) ◽  
pp. 2979-2996 ◽  
Author(s):  
Saran Aadhar ◽  
Vimal Mishra
Keyword(s):  
Soil Moisture ◽  
South Asia ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Drought Risk ◽  
Severe Drought ◽  
Considerable Uncertainty ◽  
Warming Climate

AbstractObserved and projected changes in potential evapotranspiration (PET) and drought are not well constrained in South Asia. Using five PET estimates [Thornthwaite (PET-TH), Hargreaves–Samani (PET-HS), Penman–Monteith (PET-PM), modified Penman–Monteith (PET-MPM), and energy (PET-EN)] for the observed (1979–2018, from ERA5) and future warming climate, we show that significant warming has occurred in South Asia during 1979–2018. PET changes show considerable uncertainty depending on the method used. For instance, PET-TH has increased significantly while all the other four methods show a decline in PET in the majority of South Asia during the observed period of 1979–2018. The increase in PET-TH is substantially higher than PET-HS, PET-PM, and PET-MPM due to a higher (3–4 times) sensitivity of PET-TH to warming during the observed period. Under the 1.5°, 2.0°, and 2.5°C warming worlds, global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5 GCMs) project increases in PET and drought frequency over the majority of the regions. Drought estimates based on PET-EN and PET-MPM are consistent with soil moisture–based drought estimates and project a substantial increase in the frequency of severe droughts under warming climate in South Asia. In addition, the projected frequency of severe drought based on PET-TH, which is an outlier, is about 5 times higher than PET-EN and PET-MPM. Methods to estimate PET contribute the most in the overall uncertainty of PET and drought projections in South Asia, primarily due to PET-TH. Drought estimates based on PET-TH are not reliable for the observed and projected future climate. Therefore, future drought projections should be either based on PET-EN/PET-MPM or soil moisture.

scholarly journals Historical and Projected Changes to the Stages and Other Characteristics of Severe Canadian Prairie Droughts

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3370
Author(s):  
Barrie Bonsal ◽  
Zhuo Liu ◽  
Elaine Wheaton ◽  
Ronald Stewart
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Severe Drought ◽  
Large Area ◽  
Canadian Prairie ◽  
Canadian Prairies ◽  
Temporal And Spatial Characteristics ◽  
Projected Changes ◽  
Drought Occurrence

Large-area, long-duration droughts are among Canada’s costliest natural disasters. A particularly vulnerable region includes the Canadian Prairies where droughts have, and are projected to continue to have, major impacts. However, individual droughts often differ in their stages such as onset, growth, persistence, retreat, and duration. Using the Standardized Precipitation Evapotranspiration Index, this study assesses historical and projected future changes to the stages and other characteristics of severe drought occurrence across the agricultural region of the Canadian Prairies. Ten severe droughts occurred during the 1900–2014 period with each having unique temporal and spatial characteristics. Projected changes from 29 global climate models (GCMs) with three representative concentration pathways reveal an increase in severe drought occurrence, particularly toward the end of this century with a high emissions scenario. For the most part, the overall duration and intensity of future severe drought conditions is projected to increase mainly due to longer persistence stages, while growth and retreat stages are generally shorter. Considerable variability exists among individual GCM projections, including their ability to simulate observed severe drought characteristics. This study has increased understanding in potential future changes to a little studied aspect of droughts, namely, their stages and associated characteristics. This knowledge can aid in developing future adaptation strategies.

scholarly journals Assessing the Potential Impacts of Climate Changes on Rainfall and Evapotranspiration in the Northwest Region of Bangladesh

Climate ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 94 ◽  
Author(s):  
Fazlul Karim ◽  
Mohammed Mainuddin ◽  
Masud Hasan ◽  
Mac Kirby
Keyword(s):  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Annual Rainfall ◽  
Emission Scenarios ◽  
Rabi Season ◽  
Kharif Season ◽  
Almost All ◽  
Northwest Region

Changes in the natural climate is a major concern for food security across the world, including Bangladesh. This paper presents results from an analysis on quantitative assessment of changes in rainfall and potential evapotranspiration (PET) in the northwest region of Bangladesh, which is a major agricultural hub in the country. The study was conducted using results from 28 global climate models (GCMs), based on IPCC’s 5th assessment report (AR5) for two emission scenarios. Projections were made over the period of 2045 to 2075 for 16 administrative districts in the study area, and the changes were estimated at annual, seasonal and monthly time scale. More projections result in an increase in rainfall than decrease, while almost all projections show an increase in PET. Although annual rainfall is generally projected to increase, some projections show a decrease in some months, especially in December and January. Across the region, the average change projected by the 28 GCMs for the moderate emission was an increase of 235 mm (12.4%) and 44 mm (3.4%) for rainfall and PET, respectively. Increases in rainfall and PET are slightly higher (0.6% and 0.2%, respectively) under high emission scenarios. Increases in both rainfall and PET were projected for two major cropping seasons, Kharif (May-Oct) and Rabi (Nov-Apr). Projections of rainfall show increase in the range of 160 to 250 mm (with an average of 200 mm) during the Kharif season. Although an increase is projected in the Rabi season, the amount is very small (~10mm). It is important to note that rainfall increases mostly in the Kharif season, but PET increases for both Kharif and Rabi seasons. Contrary to rainfall, increase in PET is higher during Rabi season. This information is crucial for better adaptation under increased water demand for agricultural and domestic use.

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