scholarly journals Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 268 ◽  
Author(s):  
Ehsan Beigi ◽  
Frank Tsai ◽  
Vijay Singh ◽  
Shih-Chieh Kao

The study investigates the hierarchical uncertainty of multi-ensemble hydroclimate projections for the Southern Hills-Gulf region, USA, considering emission pathways and a global climate model (GCM) as two main sources of uncertainty. Forty projections of downscaled daily air temperature and precipitation from 2010 to 2099 under four emission pathways and ten CMIP5 GCMs are adopted for hydroclimate modeling via the HELP3 hydrologic model. This study focuses on evapotranspiration (ET), surface runoff, and groundwater recharge projections in this century. Climate projection uncertainty is characterized by the hierarchical Bayesian model averaging (HBMA) method, which segregates emission pathway uncertainty and climate model uncertainty. HBMA is able to derive ensemble means and standard deviations, arising from individual uncertainty sources, for ET, runoff, and recharge. The model results show that future recharge in the Southern Hills-Gulf region is more sensitive to different climate projections and exhibits higher variability than ET and runoff. Overall, ET is likely to increase and runoff is likely to decrease in this century given the current emission path scenarios. Runoff are predicted to have an 18% to 20% decrease and ET is predicted to have around a 3% increase throughout the century. Groundwater recharge is likely to increase in this century with a decreasing trend. Recharge would increase about 13% in the early century and will have only a 3% increase in the late century. All hydrological projections have increasing uncertainty towards the end of the century. The HBMA result suggests that the GCM uncertainty dominates the overall hydrological projection uncertainty in the early century and the mid-century. The emission pathway uncertainty becomes important in the late century.

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 493 ◽  
Author(s):  
Leonard Druyan ◽  
Matthew Fulakeza

A prequel study showed that dynamic downscaling using a regional climate model (RCM) over Africa improved the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM: ModelE) simulation of June–September rainfall patterns over Africa. The current study applies bias corrections to the lateral and lower boundary data from the AOGCM driving the RCM, based on the comparison of a 30-year simulation to the actual climate. The analysis examines the horizontal pattern of June–September total accumulated precipitation, the time versus latitude evolution of zonal mean West Africa (WA) precipitation (showing monsoon onset timing), and the latitude versus altitude cross-section of zonal winds over WA (showing the African Easterly Jet and the Tropical Easterly Jet). The study shows that correcting for excessively warm AOGCM Atlantic sea-surface temperatures (SSTs) improves the simulation of key features, whereas applying 30-year mean bias corrections to atmospheric variables driving the RCM at the lateral boundaries does not improve the RCM simulations. We suggest that AOGCM climate projections for Africa should benefit from downscaling by nesting an RCM that has demonstrated skill in simulating African climate, driven with bias-corrected SST.


2019 ◽  
Vol 11 (4) ◽  
pp. 1370-1382 ◽  
Author(s):  
Asma Hanif ◽  
Ashwin Dhanasekar ◽  
Anthony Keene ◽  
Huishu Li ◽  
Kenneth Carlson

Abstract Projected climate change impacts on the hydrological regime and corresponding flood risks were examined for the years 2030 (near-term) and 2050 (long-term), under representative concentration pathways (RCP) 4.5 (moderate) and 8.5 (high) emission scenarios. The United States Army Corps of Engineers' (USACE) Hydrologic Engineering Center's Hydrologic Modeling System was used to simulate the complete hydrologic processes of the various dendritic watershed systems and USACEs' Hydrologic Engineering Center's River Analysis System hydraulic model was used for the two-dimensional unsteady flow flood calculations. Climate projections are based on recent global climate model simulations developed for the International Panel on Climate Change, Coupled Model Inter-comparison Project Phase 5. Hydrographs for frequent (high-recurrence interval) storms were derived from 30-year historical daily precipitation data and decadal projections for both time frames and RCP scenarios. Since the climate projections for each scenario only represented ten years of data, 100-year or 500-year storms cannot be derived. Hence, this novel approach of identifying frequent storms is used as an indicator to compare across the various time frames and climate scenarios. Hydrographs were used to generate inundation maps and results are used to identify vulnerabilities and formulate adaptation strategies to flooding at 43 locations worldwide.


2018 ◽  
Vol 10 (8) ◽  
pp. 2665 ◽  
Author(s):  
Kieu N. Le ◽  
Manoj K. Jha ◽  
Jaehak Jeong ◽  
Philip W. Gassman ◽  
Manuel R. Reyes ◽  
...  

Will soil organic carbon (SOC) and yields increase for conservation management systems in tropical zones in response to the next 100 years? To answer the question, the Environmental Policy Integrated Climate (EPIC) model was used to study the effects of climate change, cropping systems, conservation agriculture (CA) and conservation tillage management practices on SOC and crop productivity in Kampong Cham, Cambodia. The EPIC model was successfully calibrated and validated for crop yields, biomass, SOC and nitrogen based on field data from a five-year field experiment. Historical weather (1994–2013) was used for baseline assessment versus mid-century (2046–2064) and late-century (2081–2100) climate projections generated by the Geophysical Fluids Dynamics Laboratory (GFDL) CM2.1 global climate model. The simulated results showed that upland rice yield would increase the most under the B1 scenario in mid-century for all treatments, followed by soybean and maize. Cassava yield only increased under CA treatment when cultivated as a continuous primary crop. Carbon sequestration was more sensitive to cropping systems and crop rotation than climate change. The results indicated that the rotated CA primary crop (maize) systems should be prioritized for SOC sequestration as well as for increasing crop productivity. In addition, rice systems may increase SOC compared to soybean and cassava.


2009 ◽  
Vol 22 (13) ◽  
pp. 3838-3855 ◽  
Author(s):  
H. G. Hidalgo ◽  
T. Das ◽  
M. D. Dettinger ◽  
D. R. Cayan ◽  
D. W. Pierce ◽  
...  

Abstract This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier “center” timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.


2017 ◽  
Vol 98 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
Nikolina Ban ◽  
Nigel M. Roberts ◽  
Hayley J. Fowler ◽  
Malcolm J. Roberts ◽  
...  

Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.


2015 ◽  
Vol 29 (1) ◽  
pp. 17-35 ◽  
Author(s):  
J. F. Scinocca ◽  
V. V. Kharin ◽  
Y. Jiao ◽  
M. W. Qian ◽  
M. Lazare ◽  
...  

Abstract A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.


2013 ◽  
Vol 52 (12) ◽  
pp. 2699-2714 ◽  
Author(s):  
Peter Hoffmann ◽  
K. Heinke Schlünzen

AbstractA classification of weather patterns (WP) is derived that is tailored to best represent situations relevant for the urban heat island (UHI). Three different types of k-means-based cluster methods are conducted. The explained cluster variance is used as a measure for the quality. Several variables of the 700-hPa fields from the 40-yr ECMWF Re-Analysis (ERA-40) were tested for the classification. The variables as well as the domain for the clustering are chosen in a way to explain the variability of the UHI as best as possible. It turned out that the combination of geopotential height, relative humidity, vorticity, and the 1000–700-hPa thickness is best suited. To determine the optimal cluster number k several statistical measures are applied. Except for autumn (k = 12) an optimal cluster number of k = 7 is found. The WP frequency changes are analyzed using climate projections of two regional climate models (RCM). Both RCMs, the Regional Model (REMO) and Climate Limited-Area Model (CLM), are driven with the A1B simulations from the global climate model ECHAM5. Focusing on the periods 2036–65 and 2071–2100, no change can be found of the frequency for the anticyclonic WP when compared with 1971–2000. Since these WPs are favorable for the development of a strong UHI, the frequency of strong UHI days stays the same for the city of Hamburg,Germany. For other WPs changes can be found for both future periods. At the end of the century, a large increase (17%–40%) in the frequency of the zonal WP and a large decrease (20%–26%) in the southwesterly WP are projected.


2012 ◽  
Vol 26 (21) ◽  
pp. 8269-8288 ◽  
Author(s):  
Alvaro Semedo ◽  
Ralf Weisse ◽  
Arno Behrens ◽  
Andreas Sterl ◽  
Lennart Bengtsson ◽  
...  

Abstract Wind-generated waves at the sea surface are of outstanding importance for both their practical relevance in many aspects, such as coastal erosion, protection, or safety of navigation, and for their scientific relevance in modifying fluxes at the air–sea interface. So far, long-term changes in ocean wave climate have been studied mostly from a regional perspective with global dynamical studies emerging only recently. Here a global wave climate study is presented, in which a global wave model [Wave Ocean Model (WAM)] is driven by atmospheric forcing from a global climate model (ECHAM5) for present-day and potential future climate conditions represented by the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. It is found that changes in mean and extreme wave climate toward the end of the twenty-first century are small to moderate, with the largest signals being a poleward shift in the annual mean and extreme significant wave heights in the midlatitudes of both hemispheres, more pronounced in the Southern Hemisphere and most likely associated with a corresponding shift in midlatitude storm tracks. These changes are broadly consistent with results from the few studies available so far. The projected changes in the mean wave periods, associated with the changes in the wave climate in the middle to high latitudes, are also shown, revealing a moderate increase in the equatorial eastern side of the ocean basins. This study presents a step forward toward a larger ensemble of global wave climate projections required to better assess robustness and uncertainty of potential future wave climate change.


2018 ◽  
Vol 31 (24) ◽  
pp. 10013-10020
Author(s):  
Bernard R. Lipat ◽  
Aiko Voigt ◽  
George Tselioudis ◽  
Lorenzo M. Polvani

Recent analyses of global climate models suggest that uncertainty in the coupling between midlatitude clouds and the atmospheric circulation contributes to uncertainty in climate sensitivity. However, the reasons behind model differences in the cloud–circulation coupling have remained unclear. Here, we use a global climate model in an idealized aquaplanet setup to show that the Southern Hemisphere climatological circulation, which in many models is biased equatorward, contributes to the model differences in the cloud–circulation coupling. For the same poleward shift of the Hadley cell (HC) edge, models with narrower climatological HCs exhibit stronger midlatitude cloud-induced shortwave warming than models with wider climatological HCs. This cloud-induced radiative warming results predominantly from a subsidence warming that decreases cloud fraction and is stronger for narrower HCs because of a larger meridional gradient in the vertical velocity. A comparison of our aquaplanet results with comprehensive climate models suggests that about half of the model uncertainty in the midlatitude cloud–circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the atmosphere, and thus could be removed by improving the climatological circulation in models. This illustrates how understanding of large-scale dynamics can help reduce uncertainty in clouds and their response to climate change.


2016 ◽  
Vol 29 (2) ◽  
pp. 543-560 ◽  
Author(s):  
Ming Zhao ◽  
J.-C. Golaz ◽  
I. M. Held ◽  
V. Ramaswamy ◽  
S.-J. Lin ◽  
...  

Abstract Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the intermodel spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, the authors use a developmental version of the next-generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the model ensemble from phase 5 of CMIP (CMIP5). The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere–land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors’ model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.


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