Variability of surface climate in simulations of past and future (original) (raw)
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2020
Climate-model-based paleoclimatic time-series data are being used increasingly in ecological and evolutionary models to improve our understanding of the biogeographical processes that drive patterns of biodiversity across time. When models calibrated in past are driven by simulations of future climate change, the subsequent results can strengthen decisions regarding the future state of biodiversity. This, however, requires harmonised simulations of past and future temperature and precipitation changes. Here we provide harmonised, continuous global coverages of trend, variability, and signal-to-noise ratio for air temperature and precipitation from the Last Glacial Maximum to the end of the 21st Century. Thresholds of natural variability in trends in annual, area-weighted regional- and global-mean temperature enable users to identify and subset the dataset to periods in Earth’s history when climatic conditions were extremely unstable. By providing access to continuous simulated estim...
Geophysical Research Letters, 2013
1] Precipitation extremes are expected to increase in a warming climate; thus, it is essential to characterize their potential future changes. Here we evaluate eight highresolution global climate model simulations in the twentieth century and provide new evidence on projected global precipitation extremes for the 21st century. A significant intensification of daily extremes for all seasons is projected for the middle and high latitudes of both hemispheres at the end of the present century. For the subtropics and tropics, the lack of reliable and consistent estimations found for both the historical and future simulations might be connected with model deficiencies in the representation of organized convective systems. Low intermodel variability and good agreement with high-resolution regional observations are found for the twentieth century winter over the Northern Hemisphere middle and high latitudes. Citation: Toreti, A.,
2021
Millennial-scale East Asian monsoon variability is closely associated with natural hazards through long-term variability in flood and drought cycles. Therefore, exploring what drives the millennial-scale variability is of significant importance for future prediction of extreme climates. Here we present a new East Asian summer monsoon (EASM) rainfall reconstruction from the northwest Chinese Loess Plateau (CLP) spanning the past 650 kyr. The magnitude of millennial-scale variability (MMV) in EASM rainfall is linked to ice volume and greenhouse gas (GHG) at the 100 kyr eccentricity band and to GHG and summer insolation at the precession band. At the glacial-interglacial timescale, gradual changes in CO 2 during intermediate glaciations lead to increased variability in North Atlantic stratification and Atlantic meridional overturning circulation, propagating abrupt climate changes into East Asia via the westerlies. Within the 100 kyr cycle, precession variability further enhances the response, showing that stronger insolation and increased atmospheric GHG cause increases in the MMV of EASM rainfall. These findings indicate increased extreme precipitation events under future warming scenarios, consistent with model results.
Climate and carbon-cycle variability over the last millennium
2010
A long-standing task in climate research has been to distinguish between anthropogenic climate change and natural climate variability. A prerequisite for fulfilling this task is the understanding of the relative roles of external drivers and internal variability of climate and the carbon cycle. Here, we present the first ensemble simulations over 5 the last 1200 years with a comprehensive Earth system model including a fully interactive carbon cycle. Applying up-to-date reconstructions of external forcing including the recent low-amplitude estimates of solar variations, the ensemble simulations reproduce temperature evolutions consistent with the range of reconstructions. The 20th-century warming trend stands out against all pre-industrial trends within the ensemble. Volcanic 10 eruptions are necessary to explain variations in pre-industrial climate such as the Little Ice Age; yet only the strongest, repeated eruptions lead to cooling trends that stand out against the internal variability across all ensemble members. The simulated atmospheric CO 2 concentrations exhibit a stable carbon cycle over the pre-industrial era with multi-centennial variations somewhat smaller than in the observational records. Early 15 land-cover changes have modulated atmospheric CO 2 concentrations only slightly. We provide a model-based quantification of the sensitivity (termed γ) of the global carbon cycle to temperature for a variety of climate and forcing conditions. The magnitude of γ agrees with a recent statistical assessment based on reconstruction data. We diagnose a distinct dependence of γ on the forcing strength and time-scales involved, thus 20 providing an explanation for the systematic difference in the observational estimates for different segments of the last millennium.
Assessment of inter-model variability and biases of the global water cycle in CMIP3 climate models
2011
Global water cycle assessment in CMIP3 climate models 2 ABSTRACT 9 Observed changes such as increasing global temperatures and the intensification of the global water cycle in the 10 20 th century are also robust results of coupled general circulation models (CGCMs). In spite of this success 11 model-to-model variability and biases that are small in first order climate responses however, have implications 12 for climate predictability especially when multi-model means are used. We show that most climate simulations 13 of 20 th and 21 st century A2 scenario performed with CMIP3 (Coupled Model Intercomparison Project Phase 3) 14 models have deficiencies in simulating the global atmospheric moisture balance. Large biases of only a few 15 models (some biases reach the simulated global precipitation changes in the 20 th and 21 st century) affect the 16 multi-model mean global moisture budget and an imbalanced flux of -0.14 Sv exists whereas the multi-model 17 median imbalance is only -0.02 Sv. For most models, the detected imbalances furthermore change over time. As 18 a consequence, in 13 of the 18 CMIP3 models examined, global annual mean precipitation exceeds global 19 evaporation, indicating that there should be a "leaking" (decrease) of moisture from the atmosphere whereas for 20 the remaining 5 models a "flooding" is implied. Nonetheless, in all models, the actual atmospheric moisture 21 content and its variability correctly increases during the course of the 20 th and 21 st centuries. These 22 discrepancies therefore imply an unphysical and hence "ghost" sink / source of atmospheric moisture in the 23 models whose atmospheres flood / leak. The source / sink of moisture can also be regarded as atmospheric latent 24 heating / cooling and hence as positive / negative perturbations of the atmospheric energy budget or non-25 radiative forcings in the range of -1 to +6 W/m 2 (median is +0.1 W/m 2 ). The inter-model variability of the global 26 atmospheric moisture transport from oceans to land areas, which impacts the terrestrial water cycle, is also quite 27 high and ranges from 0.26 to 1.78 Sv. In the 21 st century this transport to land increases by about 5% per century 28 with a model-to-model range from 1 to 13% per century. We suggest that this variability is partially due to the 29 different implementations of aerosol forcings in the models. The pole wards shifts of dry zones in climate 30 simulations of the 21 st century are also assessed in this study. It is shown that the multi-model means of the two 31 subsets of models with negative and positive imbalances in the atmospheric moisture budget produce spatial 32 shifts in the dry zone positions similar in size of the spatial shifts expected from 21 st century global warming 33 simulations. Thus, in this example of the dry zone extension, spatial multi-model means also depend on the 34 selection of models which should be considered with caution in future analysis. 2010). The atmospheric moisture content is by far the smallest storage term in the global water cycle. Although 63 small variations in atmospheric moisture content can play key roles in the energy balance of the planet. Latent 64 heating redistributes energy in the vertical column and cloud formation affects the emission of infrared and 65 reflection of solar radiation while water vapor absorbs near-infrared and infrared radiation (e.g., Hansen et al. 66 1997, and Previdi and Liepert 2011). The atmospheric moisture transport from oceans to land constitutes the 67 moisture input to the continental freshwater cycle. Hence the atmospheric, "oceans to land" moisture transport 68 needs to be accurately predicted for reliable climate impact assessments. Another example of the importance of 69 the atmospheric moisture balance is that the spatial distribution of the net amount of the fluxes of precipitation 70 and evaporation identify the boundaries of the dry zones on Earth. These processes are investigated in this study.
Quaternary Science Reviews, 2005
Ten simulations are performed with a three-dimensional climate model over the last millennium driven by the main natural and anthropogenic forcing. The results are compared to available reconstructions in order to evaluate the relative contribution of internal and forced variability during this period. At hemispheric and nearly hemispheric scale, the impact of the forcing is clear in all the simulations and knowing the forced response provides already a large amount of information about the behaviour of the climate system. Besides, at regional and local scales, the forcing has only a weak contribution in the simulated variability compared to internal variability. This result could be used to refine our conception of "Medieval Warm Period" and "Little Ice Age" (MWP and LIA). They were global phenomena, since the temperature averaged over the Northern Hemisphere was generally higher (lower) during those periods because of a stronger (weaker) external forcing at that time. Nevertheless, at local-scale, the sign of the internal temperature variations determines to what extent the forced response will be actually visible or even masked by internal noise. Because of this role of internal variability, synchronous peak temperatures during the MWP or LIA between different locations are unlikely.
Global trends in extreme precipitation: climate models versus observations
Precipitation events are expected to become substantially more intense under global warming, but few global comparisons of observations and climate model simulations are available to constrain predictions of future changes in precipitation extremes. We present a systematic global-scale comparison of changes in historical annualmaximum daily precipitation between station observations (compiled in HadEX2) and the suite of global climate models contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We use both parametric and non-parametric methods to quantify the strength of trends in extreme precipitation in observations and models, taking care to sample them spatially and temporally in comparable ways. We find that both observations and models show generally increasing trends in extreme precipitation since 1901, with the largest changes in the deep tropics. Annual-maximum daily precipitation (Rx1day) has increased faster in the observations than in most of the CMIP5 models. On a global scale, the observational annual-maximum daily precipitation has increased by an average of 5.73 mm over the last 110 years, or 8.5 % in relative terms. This corresponds to an increase of 10 % K −1 in global warming since 1901, which is larger than the average of climate models, with 8.3 % K −1 . The average rate of increase in extreme precipitation per K of warming in both models and observations is higher than the rate of increase in atmospheric water vapor content per K of warming expected from the Clausius-Clapeyron equation. We expect our findings to help inform assessments of precipitationrelated hazards such as flooding, droughts and storms.
Climate Dynamics, 2006
We present and describe in detail the advantages and limitations of a technique that combines in an optimal way model results and proxy-data time series in order to obtain states of the climate system consistent with model physics, reconstruction of past radiative forcing and proxy records. To achieve this goal, we select among an ensemble of simulations covering the last millennium performed with a low-resolution 3-D climate model the ones that minimise a cost function. This cost function measures the misfit between model results and proxy records. In the framework of the tests performed here, an ensemble of 30 to 40 simulations appears sufficient to reach reasonable correlations between model results and reconstructions, in configurations for which a small amount of data is available as well as in data-rich areas. Preliminary applications of the technique show that it can be used to provide reconstructions of past large-scale temperature changes, complementary to the ones obtained by statistical methods. Furthermore, as model results include a representation of atmospheric and oceanic circulations, it can be used to provide insights into some amplification mechanisms responsible for past temperature changes. On the other hand, if the number of proxy records is too low, it could not be used to provide reconstructions of past changes at a regional scale.
Climate model benchmarking with glacial and mid-Holocene climates
Climate Dynamics, 2013
Past climates provide a test of models' ability to predict climate change. We present a comprehensive evaluation of state-of-the-art models against Last Glacial Maximum and mid-Holocene climates, using reconstructions of land and ocean climates and simulations from the Palaeoclimate Modelling and Coupled Modelling Intercomparison Projects. Newer models do not perform better than earlier versions despite higher resolution and complexity. Differences in climate sensitivity only weakly account for differences in model performance. In the glacial, models consistently underestimate land cooling (especially in winter) and overestimate ocean surface cooling (especially in the tropics). In the mid-Holocene, models generally underestimate the precipitation increase in the northern monsoon regions, and overestimate summer warming in central Eurasia. Models generally capture large-scale gradients of climate change but have more limited ability to reproduce spatial patterns. Despite these common biases, some models perform better than others.