scholarly journals An introduction to stable water isotopes in climate models: benefits of forward proxy modelling for paleoclimatology

2010 ◽  
Vol 6 (1) ◽  
pp. 115-129 ◽  
Author(s):  
C. Sturm ◽  
Q. Zhang ◽  
D. Noone

Abstract. Stable water isotopes have been measured in a wide range of climate archives, with the purpose of reconstructing regional climate variations. Yet the common assumption that the isotopic signal is a direct indicator of temperature proves to be misleading under certain circumstances, since its relationship with temperature also depends on e.g. atmospheric circulation and precipitation seasonality. Here we introduce the principles, benefits and caveats of using climate models with embedded water isotopes as a support for the interpretation of isotopic climate archives. A short overview of the limitations of empirical calibrations of isotopic proxy records is presented. In some cases, the underlying hypotheses are not fulfilled and the calibration contradicts the physical interpretation of isotopic fractionation. The simulation of climate and its associated isotopic signal, despite difficulties related to downscaling and intrinsic atmospheric variability, can provide a "transfer function" between the isotopic signal and the considered climate variable. The relationship between modelled temperature and isotopic signal is analysed under present-day, pre-industrial and mid-Holocene conditions. The linear regression relationship is statistically more significant for precipitation-weighted annual temperature than mean annual temperature, yet the regression slope varies greatly between the time-slice experiments. Temperature reconstructions that do not account for the slope variations will in this case underestimate the low-frequency variability and overestimate high-frequency variability from the isotopic proxy record. The spatial variability of the simulated δ18O-temperature slope further indicates that the isotopic signal is primarily controlled by synoptic atmospheric circulation rather than local temperature.

2009 ◽  
Vol 5 (3) ◽  
pp. 1697-1729 ◽  
Author(s):  
C. Sturm ◽  
Q. Zhang ◽  
D. Noone

Abstract. Stable water isotopes have been measured in a wide range of climate archives, with the purpose of reconstructing regional climate variations. Yet the common assumption that the isotopic signal is a direct indicator of temperature proves to be misleading under certain circumstances, since its relationship with temperature also depends on e.g. atmospheric circulation and precipitation seasonality. The present article introduces the principles, benefits and caveats of using climate models with embedded water isotopes as a support for the interpretation of isotopic climate archives. A short overview of the limitations of empirical calibrations of isotopic proxy records is presented, with emphasis on the physical processes that infirm its underlying hypotheses. The simulation of climate and its associated isotopic signal, despite difficulties related to downscaling and intrinsic atmospheric variability, can provide a "transfer function" between the isotopic signal and the considered climate variable. The multi-proxy data can then be combined with model output to produce a physically consistent climate reconstruction and its confidence interval. A sensitivity study with the isotope-enabled global circulation model CAM3iso under idealised present-day, pre-industrial and mid-Holocene is presented to illustrate the impact of a changing climate on the isotope-temperature relationship.


2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.


2019 ◽  
Vol 5 (4) ◽  
pp. 372-389 ◽  
Author(s):  
Robert C. J. Wills ◽  
Rachel H. White ◽  
Xavier J. Levine

Abstract Purpose of Review Stationary waves are planetary-scale longitudinal variations in the time-averaged atmospheric circulation. Here, we consider the projected response of Northern Hemisphere stationary waves to climate change in winter and summer. We discuss how the response varies across different metrics, identify robust responses, and review proposed mechanisms. Recent Findings Climate models project shifts in the prevailing wind patterns, with corresponding impacts on regional precipitation, temperature, and extreme events. Recent work has improved our understanding of the links between stationary waves and regional climate and identified robust stationary wave responses to climate change, which include an increased zonal lengthscale in winter, a poleward shift of the wintertime circulation over the Pacific, a weakening of monsoonal circulations, and an overall weakening of stationary wave circulations, particularly their divergent component and quasi-stationary disturbances. Summary Numerous factors influence Northern Hemisphere stationary waves, and mechanistic theories exist for only a few aspects of the stationary wave response to climate change. Idealized studies have proven useful for understanding the climate responses of particular atmospheric circulation features and should be a continued focus of future research.


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 56 (70) ◽  
pp. 175-183 ◽  
Author(s):  
Andrew Zammit-Mangion ◽  
Jonathan L. Bamber ◽  
Nana W. Schoen ◽  
Jonathan C. Rougier

AbstractCombinations of various numerical models and datasets with diverse observation characteristics have been used to assess the mass evolution of ice sheets. As a consequence, a wide range of estimates have been produced using markedly different methodologies, data, approximation methods and model assumptions. Current attempts to reconcile these estimates using simple combination methods are unsatisfactory, as common sources of errors across different methodologies may not be accurately quantified (e.g. systematic biases in models). Here we provide a general approach which deals with this issue by considering all data sources simultaneously, and, crucially, by reducing the dependence on numerical models. The methodology is based on exploiting the different space–time characteristics of the relevant ice-sheet processes, and using statistical smoothing methods to establish the causes of the observed change. In omitting direct dependence on numerical models, the methodology provides a novel means for assessing glacio-isostatic adjustment and climate models alike, using remote-sensing datasets. This is particularly advantageous in Antarctica, where in situ measurements are difficult to obtain. We illustrate the methodology by using it to infer Antarctica’s mass trend from 2003 to 2009 and produce surface mass-balance anomaly estimates to validate the RACMO2.1 regional climate model.


2017 ◽  
Vol 30 (22) ◽  
pp. 9097-9118 ◽  
Author(s):  
Paulo Ceppi ◽  
Theodore G. Shepherd

The projected response of the atmospheric circulation to the radiative changes induced by CO2 forcing and climate feedbacks is currently uncertain. In this modeling study, the impact of CO2-induced climate feedbacks on changes in jet latitude and speed is assessed by imposing surface albedo, cloud, and water vapor feedbacks as if they were forcings in two climate models, CAM4 and ECHAM6. The jet response to radiative feedbacks can be broadly interpreted through changes in midlatitude baroclinicity. Clouds enhance baroclinicity, favoring a strengthened, poleward-shifted jet; this is mitigated by surface albedo changes, which have the opposite effect on baroclinicity and the jet, while water vapor has opposing effects on upper- and lower-level baroclinicity with little net impact on the jet. Large differences between the CAM4 and ECHAM6 responses illustrate how model uncertainty in radiative feedbacks causes a large spread in the baroclinicity response to CO2 forcing. Across the CMIP5 models, differences in shortwave feedbacks by clouds and albedo are a dominant contribution to this spread. Forcing CAM4 with shortwave cloud and albedo feedbacks from a representative set of CMIP5 models yields a wide range of jet responses that strongly correlate with the meridional gradient of the anomalous shortwave heating and the associated baroclinicity response. Differences in shortwave feedbacks statistically explain about 50% of the intermodel spread in CMIP5 jet shifts for the set of models used, demonstrating the importance of constraining radiative feedbacks for accurate projections of circulation changes.


2016 ◽  
Vol 29 (19) ◽  
pp. 6923-6935 ◽  
Author(s):  
Michael A. Rawlins ◽  
Raymond S. Bradley ◽  
Henry F. Diaz ◽  
John S. Kimball ◽  
David A. Robinson

Abstract This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada.


2016 ◽  
Vol 29 (7) ◽  
pp. 2621-2633 ◽  
Author(s):  
Mingkai Jiang ◽  
Benjamin S. Felzer ◽  
Dork Sahagian

Abstract The proper understanding of precipitation variability, seasonality, and predictability are important for effective environmental management. Precipitation and its associated extremes vary in magnitude and duration both spatially and temporally, making it one of the most challenging climate parameters to predict on the basis of global and regional climate models. Using information theory, an improved understanding of precipitation predictability in the conterminous United States over the period of 1949–2010 is sought based on a gridded monthly precipitation dataset. Predictability is defined as the recurrent likelihood of patterns described by the metrics of magnitude variability and seasonality. It is shown that monthly mean precipitation and duration-based dry and wet extremes are generally highly variable in the east compared to those in the west, while the reversed spatial pattern is observed for intensity-based wetness indices except along the Pacific Northwest coast. It is thus inferred that, over much of the U.S. landscape, variations of monthly mean precipitation are driven by the variations in precipitation occurrences rather than the intensity of infrequent heavy rainfall. It is further demonstrated that precipitation seasonality for means and extremes is homogeneously invariant within the United States, with the exceptions of the West Coast, Florida, and parts of the Midwest, where stronger seasonality is identified. A proportionally higher role of variability in regulating precipitation predictability is demonstrated. Seasonality surpasses variability only in parts of the West Coast. The quantified patterns of predictability for precipitation means and extremes have direct applications to those phenomena influenced by climate periodicity, such as biodiversity and ecosystem management.


Sign in / Sign up

Export Citation Format

Share Document