scholarly journals ENSO Teleconnection to Eastern African Summer Rainfall in Global Climate Models: Role of the Tropical Easterly Jet

2021 ◽  
Vol 34 (1) ◽  
pp. 293-312
Author(s):  
Amandeep Vashisht ◽  
Benjamin Zaitchik ◽  
Anand Gnanadesikan
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
Summer Rainfall ◽  
Global Climate Models ◽  
Eastern Africa ◽  
Climate Variability And Change ◽  
Tropical Easterly Jet ◽  
Interannual Rainfall Variability

AbstractGlobal climate models (GCMs) are critical tools for understanding and projecting climate variability and change, yet the performance of these models is notoriously weak over much of tropical Africa. To improve this situation, process-based studies of African climate dynamics and their representation in GCMs are required. Here, we focus on summer rainfall of eastern Africa (SREA), which is crucial to the Ethiopian Highlands and feeds the flow of the Blue Nile River. The SREA region is highly vulnerable to droughts, with El Niño–Southern Oscillation (ENSO) being a leading cause of interannual rainfall variability. Adequate understanding and accurate representation of climate features that influence regional variability is an important but often neglected issue when evaluating models. We perform a process-based evaluation of GCMs, focusing on the upper-troposphere tropical easterly jet (TEJ), which has been hypothesized to link ENSO to SREA. We find that most models have an ENSO–TEJ coupling similar to observed, but the models diverge in their representation of TEJ–SREA coupling. Differences in the latter explain the majority (80%) of variability in ENSO teleconnection simulation across the models. This is higher than the variance explained by rainfall coupling with the Somali jet (44%) and African easterly jet (55%). However, our diagnostics of the leading hypothesized mechanism in the models—variability in divergence in the TEJ exit region—are not consistent across models and suggest that a deeper understanding of the mechanisms of TEJ–precipitation coupling should be a priority for studies of climate variability and change in the region.

Drivers of Twenty-First Century U.S. Winter Precipitation Trends in CMIP6 Models: A Storyline-Based Approach

2021 ◽  
pp. 1-48
Author(s):  
Daniel F. Schmidt ◽  
Kevin M. Grise
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
The United States ◽  
Winter Precipitation ◽  
Global Climate Models ◽  
First Century ◽  
Precipitation Trend ◽  
Twenty First Century ◽  
Precipitation Trends

AbstractClimate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each.This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in 21st century U.S. winter precipitation trends across CMIP6 models under the SSP3-7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, the El Niño-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, and the East Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern U.S. result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern U.S. result from a combination of strong global warming and a negative PNA trend.

scholarly journals Assessment of extreme flows and uncertainty under climate change: disentangling the uncertainty contribution of representative concentration pathways, global climate models and internal climate variability

2020 ◽  
Vol 24 (6) ◽  
pp. 3251-3269 ◽  
Author(s):  
Chao Gao ◽  
Martijn J. Booij ◽  
Yue-Ping Xu
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
River Basin ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Internal Climate Variability ◽  
Low Flows ◽  
Uncertainty Sources ◽  
High Flows

Abstract. Projections of streamflow, particularly of extreme flows under climate change, are essential for future water resources management and the development of adaptation strategies to floods and droughts. However, these projections are subject to uncertainties originating from different sources. In this study, we explored the possible changes in future streamflow, particularly for high and low flows, under climate change in the Qu River basin, eastern China. ANOVA (analysis of variance) was employed to quantify the contribution of different uncertainty sources from RCPs (representative concentration pathways), GCMs (global climate models) and internal climate variability, using an ensemble of 4 RCP scenarios, 9 GCMs and 1000 simulated realizations of each model–scenario combination by SDRM-MCREM (a stochastic daily rainfall model coupling a Markov chain model with a rainfall event model). The results show that annual mean flow and high flows are projected to increase and that low flows will probably decrease in 2041–2070 (2050s) and 2071–2100 (2080s) relative to the historical period of 1971–2000, suggesting a higher risk of floods and droughts in the future in the Qu River basin, especially for the late 21st century. Uncertainty in mean flows is mostly attributed to GCM uncertainty. For high flows and low flows, internal climate variability and GCM uncertainty are two major uncertainty sources for the 2050s and 2080s, while for the 2080s, the effect of RCP uncertainty becomes more pronounced, particularly for low flows. The findings in this study can help water managers to become more knowledgeable about and get a better understanding of streamflow projections and support decision making regarding adaptations to a changing climate under uncertainty in the Qu River basin.

scholarly journals Attributing correlation skill of dynamical global precipitation forecasts to statistical ENSO teleconnection using a set theory based approach

2021 ◽  
Author(s):  
Tongtiegang Zhao ◽  
Haoling Chen ◽  
Quanxi Shao
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Models ◽  
Coefficient Of Determination ◽  
Positive Anomaly ◽  
Seasonal Forecasts ◽  
Anomaly Correlation ◽  
Global Precipitation ◽  
Correlation Skill

Abstract. Climate teleconnections are essential for the verification of valuable precipitation forecasts generated by global climate models (GCMs). This paper develops a novel approach to attributing correlation skill of dynamical GCM forecasts to statistical El Niño-Southern Oscillation (ENSO) teleconnection by using the coefficient of determination (R2). Specifically, observed precipitation is respectively regressed against GCM forecasts, Niño3.4 and both of them and then the intersection operation is implemented to quantify the overlapping R2 for GCM forecasts and Niño3.4. The significance of overlapping R2 and the sign of ENSO teleconnection facilitate three cases of attribution, i.e., significantly positive anomaly correlation attributable to positive ENSO teleconnection, attributable to negative ENSO teleconnection and not attributable to ENSO teleconnection. A case study is devised for the Climate Forecast System version 2 (CFSv2) seasonal forecasts of global precipitation. For grid cells around the world, the ratio of significantly positive anomaly correlation attributable to positive (negative) ENSO teleconnection is respectively 10.8 % (11.7 %) in December-January-February (DJF), 7.1 % (7.3 %) in March-April-May (MAM), 6.3 % (7.4 %) in June-July-August (JJA) and 7.0 % (14.3 %) in September-October-November (SON). The results not only confirm the prominent contributions of ENSO teleconnection to GCM forecasts, but also present spatial plots of regions where significantly positive anomaly correlation is subject to positive ENSO teleconnection, negative ENSO teleconnection and teleconnections other than ENSO. Overall, the proposed attribution approach can serve as an effective tool to investigate the source of predictability for GCM seasonal forecasts of global precipitation.

Downscaling Climate Information

2016 ◽  
Author(s):  
Rasmus Benestad
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Local Climate ◽  
Skill Scores ◽  
The Right

What are the local consequences of a global climate change? This question is important for proper handling of risks associated with weather and climate. It also tacitly assumes that there is a systematic link between conditions taking place on a global scale and local effects. It is the utilization of the dependency of local climate on the global picture that is the backbone of downscaling; however, it is perhaps easiest to explain the concept of downscaling in climate research if we start asking why it is necessary. Global climate models are our best tools for computing future temperature, wind, and precipitation (or other climatological variables), but their limitations do not let them calculate local details for these quantities. It is simply not adequate to interpolate from model results. However, the models are able to predict large-scale features, such as circulation patterns, El Niño Southern Oscillation (ENSO), and the global mean temperature. The local temperature and precipitation are nevertheless related to conditions taking place over a larger surrounding region as well as local geographical features (also true, in general, for variables connected to weather/climate). This, of course, also applies to other weather elements. Downscaling makes use of systematic dependencies between local conditions and large-scale ambient phenomena in addition to including information about the effect of the local geography on the local climate. The application of downscaling can involve several different approaches. This article will discuss various downscaling strategies and methods and will elaborate on their rationale, assumptions, strengths, and weaknesses. One important issue is the presence of spontaneous natural year-to-year variations that are not necessarily directly related to the global state, but are internally generated and superimposed on the long-term climate change. These variations typically involve phenomena such as ENSO, the North Atlantic Oscillation (NAO), and the Southeast Asian monsoon, which are nonlinear and non-deterministic. We cannot predict the exact evolution of non-deterministic natural variations beyond a short time horizon. It is possible nevertheless to estimate probabilities for their future state based, for instance, on projections with models run many times with slightly different set-up, and thereby to get some information about the likelihood of future outcomes. When it comes to downscaling and predicting regional and local climate, it is important to use many global climate model predictions. Another important point is to apply proper validation to make sure the models give skillful predictions. For some downscaling approaches such as regional climate models, there usually is a need for bias adjustment due to model imperfections. This means the downscaling doesn’t get the right answer for the right reason. Some of the explanations for the presence of biases in the results may be different parameterization schemes in the driving global and the nested regional models. A final underlying question is: What can we learn from downscaling? The context for the analysis is important, as downscaling is often used to find answers to some (implicit) question and can be a means of extracting most of the relevant information concerning the local climate. It is also important to include discussions about uncertainty, model skill or shortcomings, model validation, and skill scores.

On the relationship between Indian Ocean Dipole, Indian summer monsoon and ENSO

2021 ◽  
Author(s):  
Annalisa Cherchi ◽  
Pascal Terray ◽  
Satyaban Bishoyi Ratna ◽  
Virna Meccia ◽  
Sooraj K.P.
Keyword(s):  
Indian Ocean ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Indian Ocean Dipole ◽  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Models ◽  
The Future ◽  
The Indian Ocean

<p>The Indian Ocean Dipole (IOD) is one of the dominant modes of variability of the tropical Indian Ocean and it has been suggested to have a crucial role in the teleconnection between the Indian summer monsoon and El Nino Southern Oscillation (ENSO). The main ideas at the base of the influence of the IOD on the ENSO-monsoon teleconnection include the possibility that it may strengthen summer rainfall over India, as well as the opposite, and also that it may produce a remote forcing on ENSO itself. The Indian Ocean has been experiencing a warming, larger than any other basins, since the 1950s. During these decades, the summer monsoon rainfall over India decreased and the frequency of Indian Ocean Dipole (IOD) events increased. In the future the IOD is projected to further increase in frequency and amplitude with mean conditions mimicking the characteristics of its positive phase. Still, state of the art global climate models have large biases in representing IOD and monsoon mean state and variability, with potential consequences for properties and related teleconnections projected in the future. This works collects a review study of the influence of the IOD on the ISM and its relationship with ENSO, as well as new results on IOD projections comparing CMIP5 and CMIP6 models.</p>

scholarly journals Possible Increased Frequency of ENSO-Related Dry and Wet Conditions over Some Major Watersheds in a Warming Climate

2020 ◽  
Vol 101 (4) ◽  
pp. E409-E426 ◽  
Author(s):  
Qiaohong Sun ◽  
Chiyuan Miao ◽  
Amir AghaKouchak ◽  
Iman Mallakpour ◽  
Duoying Ji ◽  
...  
Keyword(s):  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
River Basins ◽  
Global Climate Models ◽  
La Niña ◽  
Precipitation Pattern ◽  
La Nina

Abstract Predicting the changes in teleconnection patterns and related hydroclimate extremes can provide vital information necessary to adapt to the effects of the El Niño–Southern Oscillation (ENSO). This study uses the outputs of global climate models to assess the changes in ENSO-related dry/wet patterns and the frequency of severe dry/wet events. The results show anomalous precipitation responding asymmetrically to La Niña and El Niño, indicating the teleconnections may not simply be strengthened. A “dry to drier, wet to wetter” annual anomalous precipitation pattern was projected during La Niña phases in some regions, with drier conditions over southern North America, southern South America, and southern central Asia, and wetter conditions in Southeast Asia and Australia. These results are robust, with agreement from the 26 models and from a subset of 8 models selected for their good performance in capturing observed patterns. However, we did not observe a similar strengthening of anomalous precipitation during future El Niño phases, for which the uncertainties in the projected influences are large. Under the RCP4.5 emissions scenario, 45 river basins under El Niño conditions and 39 river basins under La Niña conditions were predicted to experience an increase in the frequency of severe dry events; similarly, 59 river basins under El Niño conditions and 61 river basins under La Niña conditions were predicted to have an increase in the frequency of severe wet events, suggesting a likely increase in the risk of floods. Our results highlight the implications of changes in ENSO patterns for natural hazards, disaster management, and engineering infrastructure.

scholarly journals Improvement of ENSO Simulation Based on Intermodel Diversity

2015 ◽  
Vol 28 (3) ◽  
pp. 998-1015 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Jong-Seong Kug
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Simulation ◽  
Central Pacific

Abstract In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupled global climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the close connection between the interannual variability and climatological states, the distinctive relation between the intermodel diversity of the interannual variability and that of the basic state is found. Based on this relation, the simulated interannual variabilities can be improved, by correcting their climatological bias. To test this methodology, the dominant intermodel difference in precipitation responses during El Niño–Southern Oscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominant intermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominant intermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatology than the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positive ENSO precipitation anomalies to the east (west). Based on the model’s systematic errors in atmospheric ENSO response and bias, the models with better climatological state tend to simulate more realistic atmospheric ENSO responses. Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. After the statistical correction, simulating quality of the MME ENSO precipitation is distinctively improved. These results provide a possibility that the present methodology can be also applied to improving climate projection and seasonal climate prediction.

scholarly journals Ecological niche modelling predicts significant impacts of future climate change on two endemic rodents in eastern Africa

2021 ◽  
Vol 13 (5) ◽  
pp. 18164-18176
Author(s):  
Aditya Srinivasulu ◽  
Alembrhan Assefa ◽  
Chelmala Srinivasulu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Niche Modelling ◽  
Climatic Scenarios ◽  
Bioclimatic Conditions ◽  
The Impact

The impact of climate change on rodents is well studied, however, many of these studies are restricted to the Americas.  Small- to medium-sized rodents, especially murids, are restricted in their home range and microclimatic niche breadth, and are known to be more sensitive to changes in bioclimatic conditions over time.  We analyzed the effect of future climatic scenarios in the near and distant future, using two global climate models (CanESM5 and MIROC-ES2L) for two shared socio-economic pathways (SSP2-4.5 and SSP5-8.5), on two eastern Africa endemic small-bodied mice: Stenocephalemys albipes and Mastomys awashensis. Our results indicate that while S. albipes showed increases in area of climatic suitability in the future, M. awashensis is predicted to suffer severe decline in the area of its fundamental niche.    

scholarly journals A review of droughts on the African continent: a geospatial and long-term perspective

2014 ◽  
Vol 18 (9) ◽  
pp. 3635-3649 ◽  
Author(s):  
I. Masih ◽  
S. Maskey ◽  
F. E. F. Mussá ◽  
P. Trambauer
Keyword(s):  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Models ◽  
Eastern Africa ◽  
Drought Risk ◽  
African Continent ◽  
Change Models ◽  
Continental Scale ◽  
The Future ◽  
Instrumental Records

Abstract. This paper presents a comprehensive review and analysis of the available literature and information on droughts to build a continental, regional and country level perspective on geospatial and temporal variation of droughts in Africa. The study is based on the review and analysis of droughts occurred during 1900–2013, as well as evidence available from past centuries based on studies on the lake sediment analysis, tree-ring chronologies and written and oral histories and future predictions from the global climate change models. Most of the studies based on instrumental records indicate that droughts have become more frequent, intense and widespread during the last 50 years. The extreme droughts of 1972–1973, 1983–1984 and 1991–1992 were continental in nature and stand unique in the available records. Additionally, many severe and prolonged droughts were recorded in the recent past such as the 1999–2002 drought in northwest Africa, 1970s and 1980s droughts in western Africa (Sahel), 2010–2011 drought in eastern Africa (Horn of Africa) and 2001–2003 drought in southern and southeastern Africa, to name a few. The available (though limited) evidence before the 20th century confirms the occurrence of several extreme and multi-year droughts during each century, with the most prolonged and intense droughts that occurred in Sahel and equatorial eastern Africa. The complex and highly variant nature of many physical mechanisms such as El Niño–Southern Oscillation (ENSO), sea surface temperature (SST) and land–atmosphere feedback adds to the daunting challenge of drought monitoring and forecasting. The future predictions of droughts based on global climate models indicate increased droughts and aridity at the continental scale but large differences exist due to model limitations and complexity of the processes especially for Sahel and northern Africa. However, the available evidence from the past clearly shows that the African continent is likely to face extreme and widespread droughts in future. This evident challenge is likely to aggravate due to slow progress in drought risk management, increased population and demand for water and degradation of land and environment. Thus, there is a clear need for increased and integrated efforts in drought mitigation to reduce the negative impacts of droughts anticipated in the future.

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