scholarly journals A pseudoproxy assessment of why climate field reconstruction methods perform the way they do in time and space

2021 ◽  
Vol 17 (6) ◽  
pp. 2583-2605
Author(s):  
Sooin Yun ◽  
Jason E. Smerdon ◽  
Bo Li ◽  
Xianyang Zhang
Keyword(s):  
Temperature Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Ice Cores ◽  
Empirical Orthogonal Functions ◽  
Spatial Covariance ◽  
Statistical Measures ◽  
Reconstruction Methods ◽  
Assessment Metrics

Abstract. Spatiotemporal paleoclimate reconstructions that seek to estimate climate conditions over the last several millennia are derived from multiple climate proxy records (e.g., tree rings, ice cores, corals, and cave formations) that are heterogeneously distributed across land and marine environments. Assessing the skill of the methods used for these reconstructions is critical as a means of understanding the spatiotemporal uncertainties in the derived reconstruction products. Traditional statistical measures of skill have been applied in past applications, but they often lack formal null hypotheses that incorporate the spatiotemporal characteristics of the fields and allow for formal significance testing. More recent attempts have developed assessment metrics to evaluate the difference of the characteristics between two spatiotemporal fields. We apply these assessment metrics to results from synthetic reconstruction experiments based on multiple climate model simulations to assess the skill of four reconstruction methods. We further interpret the comparisons using analysis of empirical orthogonal functions (EOFs) that represent the noise-filtered climate field. We demonstrate that the underlying features of a targeted temperature field that can affect the performance of CFRs include the following: (i) the characteristics of the eigenvalue spectrum, namely the amount of variance captured in the leading EOFs; (ii) the temporal stability of the leading EOFs; (iii) the representation of the climate over the sampling network with respect to the global climate; and (iv) the strength of spatial covariance, i.e., the dominance of teleconnections, in the targeted temperature field. The features of climate models and reconstruction methods identified in this paper demonstrate more detailed assessments of reconstruction methods and point to important areas of testing and improving real-world reconstruction methods.

scholarly journals A pseudoproxy assessment of why climate field reconstruction methods perform the way they do in time and space

2021 ◽  
Author(s):  
Sooin Yun ◽  
Jason E. Smerdon ◽  
Bo Li ◽  
Xianyang Zhang
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Ice Cores ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Climate Conditions ◽  
Statistical Measures ◽  
Reconstruction Methods ◽  
Assessment Metrics ◽  
The Difference

Abstract. Spatiotemporal paleoclimate reconstructions that seek to estimate climate conditions over the last several millennia are derived from multiple climate proxy records (e.g. tree rings, ice cores, corals, and cave formations) that are heterogeneously distributed across land and marine environments. Assessing the skill of the methods used for these reconstructions is critical as a means of understanding the spatiotemporal uncertainties in the derived reconstruction products. Traditional statistical measures of skill have been applied in past applications, but they often lack formal null hypotheses that incorporate the spatiotemporal characteristics of the fields and allow for formal significance testing. More recent attempts have developed assessment metrics to evaluate the difference of the characteristics between two spatiotemporal fields. We apply these assessment metrics herein to results from synthetic reconstruction experiments based on multiple climate model simulations to assess the skill of four reconstruction methods. We further interpret the comparisons using analysis of Empirical Orthogonal Functions that represent the noise-filtered climate field. The features of climate models and reconstruction methods identified in this paper demonstrate more detailed assessments of reconstruction methods and point to important areas of testing and improving real-world reconstruction methods.

Reconstructing the distribution of surface mass balance over East Antarctica (DML) from 1850 to present day

2020 ◽  
Author(s):  
Nicolas Ghilain ◽  
Stéphane Vannitsem ◽  
Quentin Dalaiden ◽  
Hugues Goosse
Keyword(s):  
Spatial Distribution ◽  
Mass Balance ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Ice Cores ◽  
Global Climate Models ◽  
East Antarctica ◽  
Surface Mass Balance ◽  
Surface Mass

<p>Over recent decades, the Antarctic Ice Sheet has witnessed large spatial variations at its surface through the surface mass balance (SMB). Since the complex Antarctic topography, working at high resolution is crucial to represent accurately the dynamics of SMB. While ice cores provide a mean to infer the SMB over centuries, the view is very spatially constrained. Global Climate models estimate the spatial distribution of SMB over centuries, but with a too coarse resolution with regards to the large variations due to local orographic effects. We have therefore explored a methodology to statistically downscale the SMB components from the climate model historical simulations (1850-present day). An analogue method is set up over a period of 30 years with the ERA-Interim reanalysis (1979-2010 AD) and associated with SMB components from the Regional Atmospheric Climate Model (RACMO) at 5 km spatial resolution over Dronning Maud in East Antarctica. The same method is then applied to the period from 1850 to present days using an ensemble of 10 simulations from the CESM2 model. This method enables to derive a spatial distribution of SMB. In addition, the changes in precipitation delivery mechanisms can be unveiled.</p>

scholarly journals The influence of non-stationary ENSO teleconnections on reconstructions of paleoclimate using a pseudoproxy framework

2015 ◽  
Vol 11 (4) ◽  
pp. 3853-3895 ◽  
Author(s):  
R. Batehup ◽  
S. McGregor ◽  
A. J. E. Gallant
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Proxy Records ◽  
Enso Teleconnections ◽  
Reconstruction Methods ◽  
Paleoclimate Records ◽  
Proxy Reconstructions

Abstract. Reconstructions of the El Niño-Southern Oscillation (ENSO) ideally require high-quality, annually-resolved and long-running paleoclimate proxy records in the eastern tropical Pacific Ocean, located in ENSO's centre-of-action. However, to date, the paleoclimate records that have been extracted in the region are short or temporally and spatially sporadic, limiting the information that can be provided by these reconstructions. Consequently, most ENSO reconstructions exploit the downstream influences of ENSO on remote locations, known as teleconnections, where longer records from paleoclimate proxies exist. However, using teleconnections to reconstruct ENSO relies on the assumption that the relationship between ENSO and the remote location is stationary in time. Increasing evidence from observations and climate models suggests that some teleconnections are, in fact, non-stationary, potentially threatening the validity of those paleoclimate reconstructions that exploit teleconnections. This study examines the implications of non-stationary teleconnections on modern multi-proxy reconstructions of ENSO. The sensitivity of the reconstructions to non-stationary teleconnections were tested using a suite of idealized pseudoproxy experiments that employed output from a fully coupled global climate model. Reconstructions of the variance in the Niño 3.4 index, representing ENSO variability, were generated using four different methods to which surface temperature data from the GFDL CM2.1 was applied as a pseudoproxy. As well as sensitivity of the reconstruction to the method, the experiments tested the sensitivity of the reconstruction to the number of non-stationary pseudoproxies and the location of these proxies. ENSO reconstructions in the pseudoproxy experiments were not sensitive to non-stationary teleconnections when global, uniformly-spaced networks of a minimum of approximately 20 proxies were employed. Neglecting proxies from ENSO's center-of-action still produced skillful reconstructions, but the chance of generating a skillful reconstruction decreased. Reconstruction methods that utilized raw time series were the most sensitive to non-stationary teleconnections, while calculating the running variance of pseudoproxies first, appeared to improve the robustness of the resulting reconstructions. The results suggest that caution should be taken when developing reconstructions using proxies from a single teleconnected region, or those that use less than 20 source proxies.

scholarly journals The influence of non-stationary teleconnections on palaeoclimate reconstructions of ENSO variance using a pseudoproxy framework

2015 ◽  
Vol 11 (12) ◽  
pp. 1733-1749 ◽  
Author(s):  
R. Batehup ◽  
S. McGregor ◽  
A. J. E. Gallant
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Proxy Records ◽  
Reconstruction Methods ◽  
Proxy Reconstructions ◽  
The Relationship ◽  
Fully Coupled

Abstract. Reconstructions of the El Niño–Southern Oscillation (ENSO) ideally require high-quality, annually resolved and long-running palaeoclimate proxy records in the eastern tropical Pacific Ocean, located in ENSO's centre of action. However, to date, the palaeoclimate records that have been extracted in the region are short or temporally and spatially sporadic, limiting the information that can be provided by these reconstructions. Consequently, most ENSO reconstructions exploit the downstream influences of ENSO on remote locations, known as teleconnections, where longer records from palaeoclimate proxies exist. However, using teleconnections to reconstruct ENSO relies on the assumption that the relationship between ENSO and the remote location is stationary in time. Increasing evidence from observations and climate models suggests that some teleconnections are, in fact, non-stationary, potentially threatening the validity of those palaeoclimate reconstructions that exploit teleconnections. This study examines the implications of non-stationary teleconnections on modern multi-proxy reconstructions of ENSO variance. The sensitivity of the reconstructions to non-stationary teleconnections were tested using a suite of idealised pseudoproxy experiments that employed output from a fully coupled global climate model. Reconstructions of the variance in the Niño 3.4 index representing ENSO variability were generated using four different methods. Surface temperature data from the GFDL CM2.1 were used as pseudoproxies for these reconstruction methods. As well as sensitivity of the reconstruction to the method, the experiments tested the sensitivity of the reconstruction to the number of non-stationary pseudoproxies and the location of these proxies. We find that non-stationarities can act to degrade the skill of ENSO variance reconstructions. However, when global, randomly spaced networks (assuming a minimum of approximately 20 proxies) were employed, the resulting pseudoproxy ENSO reconstructions were not sensitive to non-stationary teleconnections. Neglecting proxies from ENSO's centre of action still produced skilful reconstructions, but with a lower likelihood. Different reconstruction methods exhibited varying sensitivities to non-stationary pseudoproxies, which affected the robustness of the resulting reconstructions. The results suggest that caution should be taken when developing reconstructions using proxies from a single teleconnected region, or those that use less than 20 source proxies.

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

2021 ◽  
pp. 1-69
Author(s):  
Zane Martin ◽  
Clara Orbe ◽  
Shuguang Wang ◽  
Adam Sobel
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Quasi Biennial Oscillation ◽  
Meridional Winds ◽  
Goddard Institute ◽  
Minimal Bias

AbstractObservational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

scholarly journals A prognostic pollen emissions model for climate models (PECM1.0)

2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner
Keyword(s):  
United States ◽  
Land Cover ◽  
Climate Models ◽  
Climate Model ◽  
Vegetation Type ◽  
Global Climate ◽  
The United States ◽  
Global Climate Models ◽  
Pollen Counts ◽  
Surface Pollen

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

Impact of heterogeneous chemistry on the distribution of Glyoxal and Methylglyoxal in the troposphere

2021 ◽  
Author(s):  
Ramiro Checa-Garcia ◽  
Didier Didier Hauglustaine ◽  
Yves Balkanski ◽  
Paola Formenti
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Experimental Simulation ◽  
Heterogeneous Chemistry ◽  
Closed Set ◽  
Sensitivity Studies ◽  
The Tropics

<p>Glyoxal (GL) and methylglyoxal (MGL) are the smallest di-carbonyls present in the atmosphere. They hydrate easily, a process that is followed by an oligomerisation. As a consequence, it is considered that they participate actively in the formation of secondary organic aerosols (SOA) and therefore, they are being introduced in the current climate models with interactive chemistry to assess their importance on atmospheric chemistry. In our study we present the introduction of glyoxal in the INCA global model. A new closed set of gas-phase  reactions is analysed first with a box model. Then the simulated global distribution of glyoxal by the global climate model is compared with satellite observations. We show that the oxidation of volatile organic compounds and acetylene, together with the photolysis of more complex di-carbonyls allows us to reproduce well glyoxal seasonal cycle in the tropics but it requires an additional sink in several northern hemispheric regions. Additional sensitivity studies are being conducted by introducing  GL and MGL interactions with dust and SOA according to new uptake  coefficients obtained by dedicated experiments in the CESAM instrument (Chamber of Experimental Simulation of Atmospheric Multiphases). The effects of these heterogeneous chemistry processes will be quantified in the light of the new chamber measurements  and also evaluated in terms of optical properties of aged dust aerosol  and the changes in direct radiative effects  of the involved aerosol species.</p>

How detailed do cloud microphysics need to be in climate models?

2021 ◽  
Author(s):  
Ulrike Proske ◽  
Sylvaine Ferrachat ◽  
David Neubauer ◽  
Ulrike Lohmann
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Computing Time ◽  
Cloud Microphysics ◽  
Model Response ◽  
Microphysical Processes ◽  
Improved Accuracy

<p>Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedláček, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.</p><p>This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time.<br>The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.</p><p> </p><p><br>Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). “Climate Models Are Uncertain, but We Can Do Something About It”. In: Eos 99. doi: 10.1029/2018EO093757</p><p>Knutti, Reto and Jan Sedláček (Apr. 2013). “Robustness and Uncertainties in the New CMIP5 Climate Model Projections”. In: Nature Climate Change 3.4, pp. 369–373. doi: 10.1038/nclimate1716</p>

scholarly journals Back to the Future: Using Long-Term Observational and Paleo-Proxy Reconstructions to Improve Model Projections of Antarctic Climate

Geosciences ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 255 ◽  
Author(s):  
Thomas J. Bracegirdle ◽  
Florence Colleoni ◽  
Nerilie J. Abram ◽  
Nancy A. N. Bertler ◽  
Daniel A. Dixon ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Ice Core ◽  
Global Climate Models ◽  
Climate Projections ◽  
Past Performance ◽  
Wide Range ◽  
Proxy Reconstructions

Quantitative estimates of future Antarctic climate change are derived from numerical global climate models. Evaluation of the reliability of climate model projections involves many lines of evidence on past performance combined with knowledge of the processes that need to be represented. Routine model evaluation is mainly based on the modern observational period, which started with the establishment of a network of Antarctic weather stations in 1957/58. This period is too short to evaluate many fundamental aspects of the Antarctic and Southern Ocean climate system, such as decadal-to-century time-scale climate variability and trends. To help address this gap, we present a new evaluation of potential ways in which long-term observational and paleo-proxy reconstructions may be used, with a particular focus on improving projections. A wide range of data sources and time periods is included, ranging from ship observations of the early 20th century to ice core records spanning hundreds to hundreds of thousands of years to sediment records dating back 34 million years. We conclude that paleo-proxy records and long-term observational datasets are an underused resource in terms of strategies for improving Antarctic climate projections for the 21st century and beyond. We identify priorities and suggest next steps to addressing this.

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