scholarly journals Grappling with uncertainties in physical climate impact projections of water resources

2020 ◽  
Vol 163 (3) ◽  
pp. 1379-1397 ◽  
Author(s):  
Rutger Dankers ◽  
Zbigniew W. Kundzewicz

AbstractThis paper reviews the sources of uncertainty in physical climate impact assessments. It draws on examples from related fields such as climate modelling and numerical weather prediction in discussing how to interpret the results of multi-model ensembles and the role of model evaluation. Using large-scale, multi-model simulations of hydrological extremes as an example, we demonstrate how large uncertainty at the local scale does not preclude more robust conclusions at the global scale. Finally, some recommendations are made: climate impact studies should be clear about the questions they want to address, transparent about the uncertainties involved, and honest about the assumptions being made.

2017 ◽  
Author(s):  
Christopher J. Merchant ◽  
Frank Paul ◽  
Thomas Popp ◽  
Michael Ablain ◽  
Sophie Bontemps ◽  
...  

Abstract. Climate data records (CDRs) derived from Earth observation (EO) should include rigorous uncertainty information, to support application of the data in policy, climate modelling and numerical weather prediction reanalysis. Uncertainty, error and quality are distinct concepts, and CDR products should follow international norms for presenting quantified uncertainty. Ideally, uncertainty should be quantified per datum in a CDR, and the uncertainty estimates should be able to discriminate more and less certain data with confidence. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence held in the uncertainty estimate provided, or indicators of conditions violating retrieval assumptions). Errors have many sources and some are correlated across a wide range of time and space scales. Error effects that contribute negligibly to the total uncertainty in a single satellite measurement can be the dominant sources of uncertainty in a CDR on large space and long time scales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. Characterisation of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation, where possible. These principles are quite general, but the form of uncertainty information appropriate to different essential climate variables (ECVs) is highly variable, as confirmed by a quick review of the different approaches to uncertainty taken across different ECVs in the European Space Agency’s Climate Change Initiative. User requirements for uncertainty information can conflict with each other, and again a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.


Author(s):  
David A Stainforth ◽  
Thomas E Downing ◽  
Richard Washington ◽  
Ana Lopez ◽  
Mark New

There is a scientific consensus regarding the reality of anthropogenic climate change. This has led to substantial efforts to reduce atmospheric greenhouse gas emissions and thereby mitigate the impacts of climate change on a global scale. Despite these efforts, we are committed to substantial further changes over at least the next few decades. Societies will therefore have to adapt to changes in climate. Both adaptation and mitigation require action on scales ranging from local to global, but adaptation could directly benefit from climate predictions on regional scales while mitigation could be driven solely by awareness of the global problem; regional projections being principally of motivational value. We discuss how recent developments of large ensembles of climate model simulations can be interpreted to provide information on these scales and to inform societal decisions. Adaptation is most relevant as an influence on decisions which exist irrespective of climate change, but which have consequences on decadal time-scales. Even in such situations, climate change is often only a minor influence; perhaps helping to restrict the choice of ‘no regrets’ strategies. Nevertheless, if climate models are to provide inputs to societal decisions, it is important to interpret them appropriately. We take climate ensembles exploring model uncertainty as potentially providing a lower bound on the maximum range of uncertainty and thus a non-discountable climate change envelope. An analysis pathway is presented, describing how this information may provide an input to decisions, sometimes via a number of other analysis procedures and thus a cascade of uncertainty. An initial screening is seen as a valuable component of this process, potentially avoiding unnecessary effort while guiding decision makers through issues of confidence and robustness in climate modelling information. Our focus is the usage of decadal to centennial time-scale climate change simulations as inputs to decision making, but we acknowledge that robust adaptation to the variability of present day climate encourages the development of less vulnerable systems as well as building critical experience in how to respond to climatic uncertainty.


2021 ◽  
Author(s):  
Christian M. Grams

<p>Weather regimes are quasi-stationary, persistent, and recurrent states of the large-scale extratropical circulation. In the Atlantic-European region these explain most of the atmospheric variability on sub-seasonal time scales. However, current numerical weather prediction (NWP) systems struggle in correctly predicting weather regime life cycles. Latent heat release in ascending air streams injects air into the upper troposphere, which might ultimately result in blocking. Such diabatic outflow is often linked to warm conveyor belt (WCB) activity and has been shown to be involved in upscale error growth up to the regime scale. This study systematically investigates the role of diabatic outflow in the life cycle of Atlantic-European weather regimes.</p><p>An extended definition of 7 year-round Atlantic-European weather regimes from 37 years of ERA-Interim reanalysis is used. This is based on an EOF analysis and k-means clustering of normalized low-pass-filtered 500hPa geopotential height anomalies. Furthermore an objective regime life cycle is derived. The role of cloud-diabatic processes in European weather regimes is assessed based on time lag analysis of WCB activity at specific life cycle stages.</p><p>Results indicate that the period prior to regime onset is characterized by important changes in location and frequency of WCB occurrence. Most importantly, prior to the onset of regimes characterized by blocking, WCB activity increases significantly upstream of the incipient blocking even before blocking is detectable and persists over the blocked region later. This suggests that diabatic WCB outflow helps to establish and maintain blocked regimes. Thus it is important to correctly represent cloud-diabatic processes in NWP models across multiple scales in order to predict the large-scale circulation accurately. Ongoing work now systematically investigates the representation of WCB activity in current NWP systems and how this relates to the forecast skill for weather regimes.</p>


2012 ◽  
Vol 8 (4) ◽  
pp. 616-619 ◽  
Author(s):  
E. Gómez-Díaz ◽  
J. A. Morris-Pocock ◽  
J. González-Solís ◽  
K. D. McCoy

Parasites represent ideal models for unravelling biogeographic patterns and mechanisms of diversification on islands. Both host-mediated dispersal and within-island adaptation can shape parasite island assemblages. In this study, we examined patterns of genetic diversity and structure of Ornithodoros seabird ticks within the Cape Verde Archipelago in relation to their global phylogeography. Contrary to expectations, ticks from multiple, geographically distant clades mixed within the archipelago. Trans-oceanic colonization via host movements probably explains high local tick diversity, contrasting with previous research that suggests little large-scale dispersal in these birds. Although host specificity was not obvious at a global scale, host-associated genetic structure was found within Cape Verde colonies, indicating that post-colonization adaptation to specific hosts probably occurs. These results highlight the role of host metapopulation dynamics in the evolutionary ecology and epidemiology of avian parasites and pathogens.


2017 ◽  
Vol 9 (2) ◽  
pp. 511-527 ◽  
Author(s):  
Christopher J. Merchant ◽  
Frank Paul ◽  
Thomas Popp ◽  
Michael Ablain ◽  
Sophie Bontemps ◽  
...  

Abstract. The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation when possible. These principles are quite general, but the approach to providing uncertainty information appropriate to different ECVs is varied, as confirmed by a brief review across different ECVs in the CCI. User requirements for uncertainty information can conflict with each other, and a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight concrete recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.


2020 ◽  
Vol 6 (37) ◽  
pp. eabb6704
Author(s):  
Tianchen He ◽  
Jacopo Dal Corso ◽  
Robert J. Newton ◽  
Paul B. Wignall ◽  
Benjamin J. W. Mills ◽  
...  

The role of ocean anoxia as a cause of the end-Triassic marine mass extinction is widely debated. Here, we present carbonate-associated sulfate δ34S data from sections spanning the Late Triassic–Early Jurassic transition, which document synchronous large positive excursions on a global scale occurring in ~50 thousand years. Biogeochemical modeling demonstrates that this S isotope perturbation is best explained by a fivefold increase in global pyrite burial, consistent with large-scale development of marine anoxia on the Panthalassa margin and northwest European shelf. This pyrite burial event coincides with the loss of Triassic taxa seen in the studied sections. Modeling results also indicate that the pre-event ocean sulfate concentration was low (<1 millimolar), a common feature of many Phanerozoic deoxygenation events. We propose that sulfate scarcity preconditions oceans for the development of anoxia during rapid warming events by increasing the benthic methane flux and the resulting bottom-water oxygen demand.


2019 ◽  
Author(s):  
Zak Kipling ◽  
Laurent Labbouz ◽  
Philip Stier

Abstract. The interactions between aerosols and convective clouds represent some of the greatest uncertainties in the climate impact of aerosols in the atmosphere. A wide variety of mechanisms have been proposed by which aerosols may invigorate, suppress, or change the properties of individual convective clouds, some of which can be reproduced in high-resolution limited-area models. However, there may also be mesoscale, regional or global adjustments which modulate or dampen such impacts which cannot be captured in the limited domain of such models. The Convective Cloud Field Model (CCFM) provides a mechanism to explicitly simulate a population of convective clouds within each grid column at resolutions used for global climate modelling, so that a representation of the microphysical aerosol response within each parameterised cloud type is possible. Using CCFM within the global aerosol–climate model ECHAM–HAM, we demonstrate how the parameterised cloud field responds to the present-day anthropogenic aerosol perturbation in different regions. In particular, we show that in regions with strongly-forced deep convection and/or significant aerosol effects via large-scale processes, the changes in the convective cloud field due to microphysical effects is rather small; however in a more weakly-forced regime such as the Caribbean, where large-scale aerosol effects are small, a signature of convective invigoration does become apparent.


2014 ◽  
Vol 15 (1) ◽  
pp. 474-488 ◽  
Author(s):  
Naoki Mizukami ◽  
Martyn P. Clark ◽  
Andrew G. Slater ◽  
Levi D. Brekke ◽  
Marketa M. Elsner ◽  
...  

Abstract Process-based hydrologic models require extensive meteorological forcing data, including data on precipitation, temperature, shortwave and longwave radiation, humidity, surface pressure, and wind speed. Observations of precipitation and temperature are more common than other variables; consequently, radiation, humidity, pressure, and wind speed often must be either estimated using empirical relationships with precipitation and temperature or obtained from numerical weather prediction models. This study examines two climate forcing datasets using different methods to estimate radiative energy fluxes and humidity and investigates the effects of the choice of forcing data on hydrologic simulations over the mountainous upper Colorado River basin (293 472 km2). Comparisons of model simulations forced by two climate datasets illustrate that the methods used to estimate shortwave radiation impact hydrologic states and fluxes, particularly at high elevation (e.g., ~20% difference in runoff above 3000-m elevation), substantially altering the timing of snowmelt and runoff (~20 days difference) and the partitioning of precipitation between evapotranspiration and runoff. The different forcing datasets also exhibit differences in hydrologic sensitivity to interannual temperature at high elevation. The results suggest that the choice of forcing dataset is an important consideration when conducting climate impact assessments and the subsequent applications of these assessments for water resources planning and management.


2020 ◽  
Vol 20 (7) ◽  
pp. 4445-4460
Author(s):  
Zak Kipling ◽  
Laurent Labbouz ◽  
Philip Stier

Abstract. The interactions between aerosols and convective clouds represent some of the greatest uncertainties in the climate impact of aerosols in the atmosphere. A wide variety of mechanisms have been proposed by which aerosols may invigorate, suppress or change the properties of individual convective clouds, some of which can be reproduced in high-resolution limited-area models. However, there may also be mesoscale, regional or global adjustments which modulate or dampen such impacts which cannot be captured in the limited domain of such models. The Convective Cloud Field Model (CCFM) provides a mechanism to simulate a population of convective clouds, complete with microphysics and interactions between clouds, within each grid column at resolutions used for global climate modelling, so that a representation of the microphysical aerosol response within each parameterised cloud type is possible. Using CCFM within the global aerosol–climate model ECHAM–HAM, we demonstrate how the parameterised cloud field responds to the present-day anthropogenic aerosol perturbation in different regions. In particular, we show that in regions with strongly forced deep convection and/or significant aerosol effects via large-scale processes, the changes in the convective cloud field due to microphysical effects are rather small; however in a more weakly forced regime such as the Caribbean, where large-scale aerosol effects are small, a signature of convective invigoration does become apparent.


2018 ◽  
Vol 15 ◽  
pp. 117-126 ◽  
Author(s):  
Stephen Blenkinsop ◽  
Hayley J. Fowler ◽  
Renaud Barbero ◽  
Steven C. Chan ◽  
Selma B. Guerreiro ◽  
...  

Abstract. Historical in situ sub-daily rainfall observations are essential for the understanding of short-duration rainfall extremes but records are typically not readily accessible and data are often subject to errors and inhomogeneities. Furthermore, these events are poorly quantified in projections of future climate change making adaptation to the risk of flash flooding problematic. Consequently, knowledge of the processes contributing to intense, short-duration rainfall is less complete compared with those on daily timescales. The INTENSE project is addressing this global challenge by undertaking a data collection initiative that is coupled with advances in high-resolution climate modelling to better understand key processes and likely future change. The project has so far acquired data from over 23 000 rain gauges for its global sub-daily rainfall dataset (GSDR) and has provided evidence of an intensification of hourly extremes over the US. Studies of these observations, combined with model simulations, will continue to advance our understanding of the role of local-scale thermodynamics and large-scale atmospheric circulation in the generation of these events and how these might change in the future.


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