scholarly journals Uncertainty of Streamflow Forecasting with the Climate Change Scenario in India

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Ankit Bhatt ◽  
Ajay Pradhan

Streamflow and rainfall estimates have utmost importance to compute detailed water availability and hydrology for many sectors such as agriculture, water management, and food security. There are various models developed over the years for runoff estimation but among them only a few models incorporate climate change factors. Snowmelt and rainfall are the main sources of surface as well as groundwater resource and the main inputs in runoff models for estimation of streamflow. There are numerous factors which leads to climate change which intern affects the distribution on rainfall on spatial and temporal scales and the rate of melting of snows in the Himalayan region. Uncertainties in projected changes in the hydrological systems arise from internal variability in the climatic system, uncertainty about future greenhouse gas and aerosol emissions, the translations of these emissions into climate change by global climate models, and hydrological model uncertainty. Projections become less consistent between models as the spatial scale decreases. The uncertainty of climate model projections for freshwater assessments is often taken into account by using multi-model ensembles. The multi-model ensemble approach is, however, not a guarantee of reducing uncertainty in mathematical models. In recent years the floods have occurred due to high intensity rainfall occurred in a very short time, but in several cases the flooding has also occurred because the rainfall has fallen at times when all the storage systems have not been emptied after the previous rainfall. This is what we call coupled rainfall. There is currently no recommendation for how to take coupled rainfall account when applying the climate change scenario. It is estimated that such changes represent at a large scale, and cannot be applied to shorter temporal and smaller spatial scales. In areas where rainfall and runoff are very low (e.g., desert areas), small changes in runoff can lead to large percentage changes. In some regions, the sign of projected changes in runoff differs from recently observed trends. Moreover, in some areas with projected increases in runoff, different seasonal effects are expected, such as increased wet season runoff and decreased dry season runoff. Studies using results from fewer climate models can be considerably different from the other models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mulalo M. Muluvhahothe ◽  
Grant S. Joseph ◽  
Colleen L. Seymour ◽  
Thinandavha C. Munyai ◽  
Stefan H. Foord

AbstractHigh-altitude-adapted ectotherms can escape competition from dominant species by tolerating low temperatures at cooler elevations, but climate change is eroding such advantages. Studies evaluating broad-scale impacts of global change for high-altitude organisms often overlook the mitigating role of biotic factors. Yet, at fine spatial-scales, vegetation-associated microclimates provide refuges from climatic extremes. Using one of the largest standardised data sets collected to date, we tested how ant species composition and functional diversity (i.e., the range and value of species traits found within assemblages) respond to large-scale abiotic factors (altitude, aspect), and fine-scale factors (vegetation, soil structure) along an elevational gradient in tropical Africa. Altitude emerged as the principal factor explaining species composition. Analysis of nestedness and turnover components of beta diversity indicated that ant assemblages are specific to each elevation, so species are not filtered out but replaced with new species as elevation increases. Similarity of assemblages over time (assessed using beta decay) did not change significantly at low and mid elevations but declined at the highest elevations. Assemblages also differed between northern and southern mountain aspects, although at highest elevations, composition was restricted to a set of species found on both aspects. Functional diversity was not explained by large scale variables like elevation, but by factors associated with elevation that operate at fine scales (i.e., temperature and habitat structure). Our findings highlight the significance of fine-scale variables in predicting organisms’ responses to changing temperature, offering management possibilities that might dilute climate change impacts, and caution when predicting assemblage responses using climate models, alone.


2021 ◽  
Vol 34 (2) ◽  
pp. 509-525
Author(s):  
David P. Rowell ◽  
Rory G. J. Fitzpatrick ◽  
Lawrence S. Jackson ◽  
Grace Redmond

AbstractProjected changes in the intensity of severe rain events over the North African Sahel—falling from large mesoscale convective systems—cannot be directly assessed from global climate models due to their inadequate resolution and parameterization of convection. Instead, the large-scale atmospheric drivers of these storms must be analyzed. Here we study changes in meridional lower-tropospheric temperature gradient across the Sahel (ΔTGrad), which affect storm development via zonal vertical wind shear and Saharan air layer characteristics. Projected changes in ΔTGrad vary substantially among models, adversely affecting planning decisions that need to be resilient to adverse risks, such as increased flooding. This study seeks to understand the causes of these projection uncertainties and finds three key drivers. The first is intermodel variability in remote warming, which has strongest impact on the eastern Sahel, decaying toward the west. Second, and most important, a warming–advection–circulation feedback in a narrow band along the southern Sahara varies in strength between models. Third, variations in southern Saharan evaporative anomalies weakly affect ΔTGrad, although for an outlier model these are sufficiently substantive to reduce warming here to below that of the global mean. Together these uncertain mechanisms lead to uncertain southern Saharan/northern Sahelian warming, causing the bulk of large intermodel variations in ΔTGrad. In the southern Sahel, a local negative feedback limits the contribution to uncertainties in ΔTGrad. This new knowledge of ΔTGrad projection uncertainties provides understanding that can be used, in combination with further research, to constrain projections of severe Sahelian storm activity.


2015 ◽  
Vol 16 (2) ◽  
pp. 762-780 ◽  
Author(s):  
Pablo A. Mendoza ◽  
Martyn P. Clark ◽  
Naoki Mizukami ◽  
Andrew J. Newman ◽  
Michael Barlage ◽  
...  

Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located in the Colorado headwaters region, using four different hydrologic model structures [PRMS, VIC, Noah LSM, and Noah LSM with multiparameterization options (Noah-MP)]. To better understand the role of parameter estimation, model performance and projected hydrologic changes (i.e., changes in the hydrology obtained from hydrologic models due to climate change) are compared before and after calibration with the University of Arizona shuffled complex evolution (SCE-UA) algorithm. Hydrologic changes are examined via a climate change scenario where the Community Climate System Model (CCSM) change signal is used to perturb the boundary conditions of the Weather Research and Forecasting (WRF) Model configured at 4-km resolution. Substantial intermodel differences (i.e., discrepancies between hydrologic models) in the portrayal of climate change impacts on water resources are demonstrated. Specifically, intermodel differences are larger than the mean signal from the CCSM–WRF climate scenario examined, even after the calibration process. Importantly, traditional single-objective calibration techniques aimed to reduce errors in runoff simulations do not necessarily improve intermodel agreement (i.e., same outputs from different hydrologic models) in projected changes of some hydrological processes such as evapotranspiration or snowpack.


Author(s):  
Ifie-emi Francis Oseke ◽  
Geophery Kwame Anornu ◽  
Kwaku Amaning Adjei ◽  
Martin Obada Eduvie

Abstract. The strategies and actions in the management of African River Basins in a warming climate environment have been studied. Using the Gurara Reservoir Catchment in North-West Nigeria as a case study, summations were proposed using hypothetical climate scenarios considering the Global Climate Models prediction and linear trend of the data. Four (4) proposed scenarios of temperature increase (1 % and 2 %) coupled with a decrease in precipitation of (−5 % and −10 %) were combined and applied for the study area. The Water Evaluation and Planning Tool was used to model and evaluates the impact of the earth's rising temperature and declining rainfall on the hydrology and availability of water by investigating its resilience to climate change. Modelling results indicate a reduction in available water within the study area from 4.3 % to 3.5 % compared to the baseline with no climate change scenario, revealing the current water management strategy as not sustainable, uncoordinated, and resulting in overexploitation. The findings could assist in managing future water resources in the catchment by accentuating the need to put in place appropriate adaptation measures to foster resilience to climate change. Practically, it is pertinent to shape more effective policies and regulations within catchments for effective water resources management in reducing water shortage as well as achieving downstream water needs and power benefit in thefuture, while also allowing flexibility in the operation of a reservoir with the ultimate goal of adapting to climate change.


Author(s):  
Rasmus Benestad

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.


2020 ◽  
Vol 33 (2) ◽  
pp. 405-428 ◽  
Author(s):  
Michael A. Alexander ◽  
Sang-ik Shin ◽  
James D. Scott ◽  
Enrique Curchitser ◽  
Charles Stock

AbstractROMS, a high-resolution regional ocean model, was used to study how climate change may affect the northwestern Atlantic Ocean. A control (CTRL) simulation was conducted for the recent past (1976–2005), and simulations with additional forcing at the surface and lateral boundaries, obtained from three different global climate models (GCMs) using the RCP8.5 scenario, were conducted to represent the future (2070–99). The climate change response was obtained from the difference between the CTRL and each of the three future simulations. All three ROMS simulations indicated large increases in sea surface temperatures (SSTs) over most of the domain except off the eastern U.S. seaboard resulting from weakening of the Gulf Stream. There are also substantial intermodel differences in the response, including a southward shift of the Gulf Stream in one simulation and a slight northward shift in the other two, with corresponding changes in eddy activity. The depth of maximum warming varied among the three simulations, resulting in differences in the bottom temperature response in coastal regions, including the Gulf of Maine and the West Florida Shelf. The surface salinity decreased in the northern part of the domain and increased in the south in all three experiments, although the freshening extended much farther south in one ROMS simulation relative to the other two, and also relative to the GCM that provided the large-scale forcing. Thus, while high resolution allows for a better representation of currents and bathymetry, the response to climate change can vary considerably depending on the large-scale forcing.


2019 ◽  
Vol 76 (6) ◽  
pp. 1524-1542
Author(s):  
Melissa A Haltuch ◽  
Z Teresa A’mar ◽  
Nicholas A Bond ◽  
Juan L Valero

Abstract US West Coast sablefish are economically valuable, with landings of 11.8 million pounds valued at over $31 million during 2016, making assessing and understanding the impact of climate change on the California Current (CC) stock a priority for (1) forecasting future stock productivity, and (2) testing the robustness of management strategies to climate impacts. Sablefish recruitment is related to large-scale climate forcing indexed by regionally correlated sea level (SL) and zooplankton communities that pelagic young-of-the-year sablefish feed upon. This study forecasts trends in future sablefish productivity using SL from Global Climate Models (GCMs) and explores the robustness of harvest control rules (HCRs) to climate driven changes in recruitment using management strategy evaluation (MSE). Future sablefish recruitment is likely to be similar to historical recruitment but may be less variable. Most GCMs suggest that decadal SL trends result in recruitments persisting at lower levels through about 2040 followed by higher levels that are more favorable for sablefish recruitment through 2060. Although this MSE suggests that spawning biomass and catches will decline, and then stabilize, into the future under both HCRs, the sablefish stock does not fall below the stock size that leads to fishery closures.


2010 ◽  
Vol 2 (2) ◽  
pp. 148-167 ◽  
Author(s):  
Kirsti Jylhä ◽  
Heikki Tuomenvirta ◽  
Kimmo Ruosteenoja ◽  
Hanna Niemi-Hugaerts ◽  
Krista Keisu ◽  
...  

Abstract A Web site questionnaire survey in Finland suggested that maps illustrating projected shifts of Köppen climatic zones are an effective visualization tool for disseminating climate change information. The climate classification is based on seasonal cycles of monthly-mean temperature and precipitation, and it divides Europe and its adjacent land areas into tundra, boreal, temperate, and dry climate types. Projections of future changes in the climatic zones were composed using multimodel mean projections based on simulations performed with 19 global climate models. The projections imply that, depending on the greenhouse gas scenarios, about half or possibly even two-thirds of the study domain will be affected by shifts toward a warmer or drier climate type during this century. The projected changes within the next few decades are chiefly located near regions where shifts in the borders of the zones have already occurred during the period 1950–2006. The questionnaire survey indicated that the information regarding the shifting climatic zones as disseminated by the maps was generally interpreted correctly, with the average percentage of correct answers being 86%. Additional examples of the use of the climatic zones to communicate climate change information to the public are included.


2011 ◽  
Vol 62 (9) ◽  
pp. 1000 ◽  
Author(s):  
Alistair J. Hobday ◽  
Janice M. Lough

Changes in the physical environment of aquatic systems consistent with climate change have been reported across Australia, with impacts on many marine and freshwater species. The future state of aquatic environments can be estimated by extrapolation of historical trends. However, because the climate is a complex non-linear system, a more process-based approach is probably required, in particular the use of dynamical projections using climate models. Because global climate models operate on spatial scales that typically are too coarse for aquatic biologists, statistical or dynamical downscaling of model output is proposed. Challenges in using climate projections exist; however, projections for some marine and freshwater systems are possible. Higher oceanic temperatures are projected around Australia, particularly for south-eastern Australia. The East Australia Current is projected to transport greater volumes of water southward, whereas the Leeuwin Current on the western coast may weaken. On land, projections suggest that air temperatures will rise and rainfall will decline across much of Australia in coming decades. Together, these changes will result in reduced runoff and hence reduced stream flow and lake storage. Present climate models are particularly limited with regard to coastal and freshwater systems, making the models challenging to use for biological-impact and adaptation studies.


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