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

Author(s):  
Surendra Rauniyar ◽  
Scott Power

<p>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<sup>th</sup> 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.</p><p>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<sup>st</sup> 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<sup>st</sup> century the externally forced change under RCP8.5 is so large that drying – even after taking internally variability into account - appears inevitable. </p><p>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.</p>

2020 ◽  
Vol 33 (18) ◽  
pp. 8087-8106 ◽  
Author(s):  
Surendra P. Rauniyar ◽  
Scott B. Power

AbstractCool-season (April to October) rainfall dominates the annual average rainfall over Victoria, Australia, and is important for agriculture and replenishing reservoirs. Rainfall during the cool season has been unusually low since the beginning of the Millennium Drought in 1997 (~12% below the twentieth-century average). In this study, 24 CMIP5 climate models are used to estimate 1) the extent to which this drying is driven by external forcing and 2) future rainfall, taking both external forcing and internal natural climate variability into account. All models have preindustrial, historical, and twenty-first-century (RCP2.6, RCP4.5, and RCP8.5) simulations. It is found that rainfall in the past two decades is below the preindustrial average in two-thirds or more of model simulations. However, the magnitude of the multimodel median externally forced drying is equivalent to only 20% of the observed drying (interquartile range of 40% to −4%), suggesting that the drying is dominated by internally generated rainfall variability. Underestimation of internal variability of rainfall by the models, however, increases the uncertainties in these estimates. According to models the anthropogenically forced drying becomes dominant from 2010 to 2029, when drying is evident in over 90% of the model simulations. For the 2018–37 period, it is found that there is only a ~12% chance that internal rainfall variability could completely offset the anthropogenically forced drying. By the late twenty-first century, the anthropogenically forced drying under RCP8.5 is so large that internal variability appears too small to be able to offset it. Confidence in the projections is lowered because models have difficulty in simulating the magnitude of the observed decline in rainfall.


2016 ◽  
Author(s):  
Dongmei Han ◽  
Denghua Yan ◽  
Xinyi Xu ◽  
Zhongwen Yang ◽  
Yajing Lu

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.


Climate ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 94 ◽  
Author(s):  
Fazlul Karim ◽  
Mohammed Mainuddin ◽  
Masud Hasan ◽  
Mac Kirby

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.


Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 897 ◽  
Author(s):  
Duulatov ◽  
Chen ◽  
Amanambu ◽  
Ochege ◽  
Orozbaev ◽  
...  

Climate change-induced precipitation variability is the leading cause of rainfall erosivity that leads to excessive soil losses in most countries of the world. In this paper, four global climate models (GCMs) were used to characterize the spatiotemporal prediction of rainfall erosivity and assess the effect of variations of rainfall erosivity in Central Asia. The GCMs (BCCCSM1-1, IPSLCM5BLR, MIROC5, and MPIESMLR) were statistically downscaled using the delta method under Representative Concentration Pathways (RCPs) 2.6 and 8.5 for two time periods: “Near” and “Far” future (2030s and 2070s). These GCMs data were used to estimate rainfall erosivity and its projected changes over Central Asia. WorldClim data was used as the present baseline precipitation scenario for the study area. The rainfall erosivity (R) factor of the Revised Universal Soil Loss Equation (RUSLE) was used to determine rainfall erosivity. The results show an increase in the future periods of the annual rainfall erosivity compared to the baseline. For all GCMs, with an average change in rainfall erosivity of about 5.6% (424.49 MJ mm ha−1 h−1 year−1) in 2030s and 9.6% (440.57 MJ mm ha−1 h−1 year−1) in 2070s as compared to the baseline of 402 MJ mm ha−1 h−1 year−1. The magnitude of the change varies with the GCMs, with the largest change being 26.6% (508.85 MJ mm ha−1 h−1 year−1), occurring in the MIROC-5 RCP8.5 scenario in the 2070s. Although annual rainfall erosivity shows a steady increase, IPSLCM5ALR (both RCPs and periods) shows a decrease in the average erosivity. Higher rainfall amounts were the prime causes of increasing spatial-temporal rainfall erosivity.


2021 ◽  
Author(s):  
Surendra P Rauniyar ◽  
Scott B Power

Abstract Here we use observations and simulations from 40 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), under preindustrial, historical, and a high emission scenario (RCP8.5) to provide estimates of Victorian cool season (April-October) rainfall for the coming century. This includes a new method which exploits recent research that estimated the relative contribution of external forcing and natural variability to the observed multidecadal decline in cool season rainfall in Victoria from 1997s. The new method is aimed at removing the influence of external forcing on Victoria's cool-season rainfall, effectively rendering a stationary time-series. The resulting historical record is then modified by scaling derived from the mean projected change evident in climate models out to 2100. The results suggest that the median value of the All-Victoria rainfall PDF will decrease monotonically over the remainder of the 21st century under RCP8.5. The likelihood that All-Victoria rainfall in any given year from 2025 onward will be below the observed 5th percentile of the observations (291 mm) increases monotonically, becoming three times larger by the end of the century. The new method is assessed using cross-validation and its ability to hindcast observed multidecadal rainfall change. The latter indicates that CMIP5 models poorly replicate recent interdecadal rainfall change. So, while we have more confidence in the new method because it accounts for the non-stationarity in the observed climate, limitations in the CMIP5 models results in us having low confidence in the reliability of the estimated future rainfall distributions.


Author(s):  
Efrain Lujano-Laura ◽  
Liz S. Hidalgo-Sanchez ◽  
Bernardino Tapia-Aguilar ◽  
Apolinario Lujano-Laura

<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>


2020 ◽  
Vol 21 (11) ◽  
pp. 2607-2621
Author(s):  
Erin Dougherty ◽  
Erin Sherman ◽  
Kristen L. Rasmussen

AbstractCalifornia receives much of its precipitation from cool-season atmospheric rivers, which contribute to water resources and flooding. In winter 2017, a large number of atmospheric rivers caused anomalous winter precipitation, near-saturated soils, and a partial melting of snowpack, which led to excessive runoff that damaged the emergency spillway of the Oroville Dam. Given the positive and negative impacts ARs have in California, it is necessary to understand how they will change in a future climate. While prior studies have examined future changes in the frequency of atmospheric rivers impacting the West Coast of the United States, these studies primarily use coarse global climate models that are unable to resolve the complex terrain of this region. Such a limitation is overcome by using a high-resolution convection-permitting regional climate model, which resolves complex topography and orographic rainfall processes that are the main drivers of heavy precipitation in landfalling atmospheric rivers. This high-resolution model is used to examine changes to precipitation and runoff in California’s cool season from 2002 to 2013, particularly in flood-producing storms associated with atmospheric rivers, in a future, warmer climate using a pseudo–global warming approach. In 45 flood-producing storms, precipitation and runoff increase by 21%–26% and 15%–34%, respectively, while SWE decreases by 32%–90%, with the greatest changes at mid-elevations. These trends are consistent with future precipitation changes during the entire cool season. Results suggest more intense floods and less snowpack available for water resources in the future, which should be carefully considered in California’s future water management plans.


2017 ◽  
Vol 122 (11) ◽  
pp. 5738-5762 ◽  
Author(s):  
Peter A. G. Watson ◽  
Judith Berner ◽  
Susanna Corti ◽  
Paolo Davini ◽  
Jost Hardenberg ◽  
...  

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