A new method for studying the extratropical response to tropical precipitation anomalies and its role in improving projections of Northern Hemisphere climate variability

2020 ◽  
Author(s):  
Natasha Senior ◽  
Manoj Joshi ◽  
Adrian Matthews ◽  
Pranab Deb
Keyword(s):  
Climate Variability ◽  
Northern Hemisphere ◽  
Geopotential Height ◽  
Climate Models ◽  
Linear Response Theory ◽  
Teleconnection Pattern ◽  
Cmip5 Models ◽  
Boreal Winter ◽  
Response Functions ◽  
Tropical Precipitation

<p>Intensification of extreme precipitation and weather events are some of the projections under a 2°C average global temperature increase scenario. Rossby wave trains may be triggered by anomalous tropical precipitation through the interaction of the associated upper level divergent wind and the vorticity gradients of the subtropical jet streams. In this way, anomalous tropical precipitation can influence weather patterns in the Northern Hemisphere. Owing to the quasi-linearity of this teleconnection pattern, it may be studied statistically as a series of signal-response functions. Here the anomalous precipitation events are treated as input forcings and the resulting geopotential height anomalies are the output signals. Through calculating the response functions we are able to realistically capture the 250 hPa geopotential height response to a step-like change in precipitation over the Maritime Continent or the eastern Indian Ocean during the boreal winter. When examining these responses using the same forcing for a selection of CMIP5 models, we find that there is a large inter-model spread, owing to differences in the model basic state. Since these teleconnection patterns are not faithfully represented in climate models, this can obscure our ability to develop realistic projections of atmospheric circulation and extreme weather. We discuss the potential of the linear response theory method to provide improved projections for Northern Hemisphere climate variability.</p>

Projections of future atmospheric circulation changes using the extratropical linear step response to tropical precipitation

2021 ◽  
Author(s):  
Natasha Senior ◽  
Adrian Matthews ◽  
Manoj Joshi
Keyword(s):  
Atmospheric Circulation ◽  
Linear Response ◽  
Hydrological Cycle ◽  
Linear Response Theory ◽  
Teleconnection Pattern ◽  
Step Response ◽  
Cmip5 Models ◽  
Boreal Winter ◽  
Response Theory ◽  
Circulation Changes

<p>The global hydrological cycle is expected to intensify under a warming climate. Since extratropical Rossby wave trains are triggered by tropical convection, this will impact the atmospheric circulation in the extratropics. Owing to the approximate linearity of the teleconnection pattern, we can use a method based in linear response theory to quantify this extratropical response using a step response function. We have examined the step response functions for a selection of CMIP5 pre-industrial control runs and reanalysis data,  in particular studying the response during the boreal winter. We found there to a large intermodel spread in the response pattern owing to differences in representations of the model basic state. In the current work, we use a 'perfect model' approach to conduct a systematic study of the performance of the linear response method in projecting future winter-time northern hemisphere circulation changes using the present day (1986-2005) model basic states, comparing these to those projected by CMIP5 models under a 3 degree rise in mean global temperature anomaly above pre-industrial. We demonstrate how, given a projected precipitation change pattern, the linear response theory method can compete with the models in providing faithful projections for the extratropical circulation changes.</p>

scholarly journals Cross-Seasonal Relationship between the Boreal Autumn SAM and Winter Precipitation in the Northern Hemisphere in CMIP5

2016 ◽  
Vol 29 (18) ◽  
pp. 6617-6636 ◽  
Author(s):  
Ting Liu ◽  
Jianping Li ◽  
Juan Feng ◽  
Xiaofan Wang ◽  
Yang Li
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Decisive Role ◽  
Winter Precipitation ◽  
Systematic Evaluation ◽  
Cmip5 Models ◽  
Type I ◽  
Sst Variability ◽  
Ocean Atmosphere ◽  
The Cross

Abstract Recent work suggests that the boreal autumn Southern Hemisphere annular mode (SAM) favors a tripole pattern of winter precipitation anomalies in the Northern Hemisphere. This study focuses on the abilities of climate models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to reproduce the physical processes involved in this observed cross-seasonal connection. A systematic evaluation suggested that 16 out of 25 models were essentially capable of reproducing this cross-seasonal connection. Two categories of models were selected to explore the underlying reasons for these successful simulations. Models that successfully simulated the cross-seasonal relationship were placed in the type-I category, and these performed well in reproducing the related physical mechanism, known as the “coupled ocean–atmosphere bridge,” in terms of the SST variability associated with the SAM and response of the meridional circulation to these SST anomalies. In contrast, the type-II category of models showed poor performance in representing the related processes and associated feedbacks, and the model biases compromised the performance of the simulated cross-seasonal relationship. These results demonstrate that the capability of the CMIP5 models to reproduce SST variability associated with the boreal autumn SAM and related coupled ocean–atmosphere bridge process plays a decisive role in the successful simulation of the cross-seasonal relationship.

The Double-ITCZ Bias in CMIP6 Models

2020 ◽  
Author(s):  
Baijun Tian
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Tropical Precipitation ◽  
Double Itcz ◽  
Intercomparison Project ◽  
Fully Coupled

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>

Evaluation of snow albedo feedback simulated by CMIP6 coupled climate models

2020 ◽  
Author(s):  
jiangling hu ◽  
duoying ji
Keyword(s):  
Climate Change ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Climate Models ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Simulation Research ◽  
Albedo Feedback ◽  
Snow Albedo ◽  
Autumn And Winter

<p>As the land surface warms, a subsequent reduction in snow and ice cover reveals a less reflective surface that absorbs more solar radiation, which further enhances the initial warming. This positive feedback climate mechanism is the snow albedo feedback (SAF), which will exacerbate climate warming and is the second largest contributor to Arctic amplification. Snow albedo feedback will increase the sensitivity of climate change in the northern hemisphere, which affects the accuracy of climate models in simulation research of climate change, and further affects the credibility of future climate prediction results.</p><p>Using the latest generation of climate models from CMIP6 (Coupled Model Intercomparison Project Version 6), we analyze seasonal cycle snow albedo feedback in Northern Hemisphere extratropics. We find that the strongest SAF strength is in spring (mean: -1.34 %K<sup>-1</sup>), second strongest is autumn (mean: -1.01 %K<sup>-1</sup>), the weakest is in summer (mean: -0.18 %K<sup>-1</sup>). Except summer, the SAF strength is approximately 0.15% K<sup>-1</sup> larger than CMIP5 models in the other three seasons. The spread of spring SAF strength (range: -1.09 to -1.37% K<sup>-1</sup>) is larger than CMIP5 models. Oppositely, the spread of summer SAF strength (range: 0.20 to -0.56% K<sup>-1</sup>) is smaller than CMIP5 models. When compared with CMIP5 models, the spread of autumn and winter SAF strength have not changed much.</p>

scholarly journals The Predictors and Forecast Skill of Northern Hemisphere Teleconnection Patterns for Lead Times of 3–4 Weeks

2017 ◽  
Vol 145 (7) ◽  
pp. 2855-2877 ◽  
Author(s):  
Jiaxin Black ◽  
Nathaniel C. Johnson ◽  
Stephen Baxter ◽  
Steven B. Feldstein ◽  
Daniel S. Harnos ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Geopotential Height ◽  
Longwave Radiation ◽  
Teleconnection Pattern ◽  
Forecast Skill ◽  
Lead Times ◽  
Least Squares Regression ◽  
Atmospheric Flow ◽  
Teleconnection Patterns ◽  
The Pacific

The Pacific–North American pattern (PNA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are three dominant teleconnection patterns known to strongly affect December–February surface weather in the Northern Hemisphere. A partial least squares regression (PLSR) method is adopted in this study to generate wintertime two-week statistical forecasts of these three teleconnection pattern indices for lead times of up to five weeks over the 1980–2013 period. The PLSR approach generates forecasts for the teleconnection pattern indices by maximizing the variance explained by predictor indices determined as linear combinations of predictor fields, which include gridded outgoing longwave radiation (OLR), 300-hPa geopotential height (Z300), and 50-hPa geopotential height (Z50). Overall, the PLSR models yield statistically significant skill at all lead times up to five weeks. In particular, cross-validated correlations between the combined weeks 3–4 PLSR forecasts and verification for the PNA, NAO, and AO indices are 0.34, 0.28, and 0.41, respectively. The PLSR approach also allows the authors to isolate a small number of predictor patterns that help shed light on the sources of prediction skill for each teleconnection pattern. As expected, the results reveal the importance of tropical convection (OLR) for forecast skill in weeks 3–4, but the initial atmospheric flow (Z300) accounts for a substantial fraction of the skill as well. Overall, the results of this study provide promise for improving subseasonal-to-seasonal (S2S) forecasts and the physical understanding of predictability on these time scales.

scholarly journals High-Resolution Global Climate Simulations with the ECMWF Model in Project Athena: Experimental Design, Model Climate, and Seasonal Forecast Skill

2012 ◽  
Vol 25 (9) ◽  
pp. 3155-3172 ◽  
Author(s):  
T. Jung ◽  
M. J. Miller ◽  
T. N. Palmer ◽  
P. Towers ◽  
N. Wedi ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Seasonal Forecast ◽  
Horizontal Resolution ◽  
Forecast Skill ◽  
Boreal Winter ◽  
Project Athena ◽  
The Tropics ◽  
Ecmwf Model

The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena—an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models. In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden–Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena.

scholarly journals 21st century changes in snow water equivalent over Northern Hemisphere landmasses due to increasing temperature, projected with the CMIP5 models

2015 ◽  
Vol 9 (2) ◽  
pp. 2135-2166 ◽  
Author(s):  
H. X. Shi ◽  
C. H. Wang
Keyword(s):  
Northern Hemisphere ◽  
21St Century ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
The Tibetan Plateau ◽  
High Latitudes ◽  
Snow Water ◽  
Increasing Temperature

Abstract. Changes in snow water equivalent (SWE) over Northern Hemisphere (NH) landmasses are investigated for the early (2016–2035), middle (2046–2065) and late (2080–2099) 21st century using twenty global climate models, which are from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The results show that, relative to the 1986–2005 mean, the multi-model ensemble projects a significant decrease in SWE for most regions, particularly over the Tibetan Plateau and western North America, but an increase in eastern Siberia. Seasonal SWE projections show an overall decreasing trend, with the greatest reduction in spring, which is linked to the stronger inverse partial correlation between the SWE and increasing temperature. Moreover, zonal mean annual SWE exhibits significant reductions in three Representative Concentration Pathways (RCP), a stronger linear relationship between SWE and temperature at mid–high latitudes suggests the reduction in SWE there is related to rising temperature. However, the rate of reduction in SWE declines gradually during the 21st century, indicating that the temperature may reach a threshold value that decreases the rate of SWE reduction. A large reduction in zonal maximum SWE (ZMSWE) between 30° and 40° N is evident in all 21st century for the three RCPs, while RCP8.5 alone indicates a further reduction at high latitudes in the late period of the century. This pattern implies that ZMSWE is affected not only by a terrain factor but also by the increasing temperature. In summary, our results show both a decreasing trend in SWE in the 21st century and a decline in the rate of SWE reduction over the 21st century despite rising temperatures.

scholarly journals Multi-annual modes in the 20th century temperature variability in reanalyses and CMIP5 models

2016 ◽  
Vol 9 (11) ◽  
pp. 4097-4109
Author(s):  
Heikki Järvinen ◽  
Teija Seitola ◽  
Johan Silén ◽  
Jouni Räisänen
Keyword(s):  
Climate Variability ◽  
20Th Century ◽  
Climate Models ◽  
Spectral Power ◽  
Singular Spectrum Analysis ◽  
Reanalysis Data ◽  
Cmip5 Models ◽  
Data Sets ◽  
Near Surface ◽  
Annual Variability

Abstract. A performance expectation is that Earth system models simulate well the climate mean state and the climate variability. To test this expectation, we decompose two 20th century reanalysis data sets and 12 CMIP5 model simulations for the years 1901–2005 of the monthly mean near-surface air temperature using randomised multi-channel singular spectrum analysis (RMSSA). Due to the relatively short time span, we concentrate on the representation of multi-annual variability which the RMSSA method effectively captures as separate and mutually orthogonal spatio-temporal components. This decomposition is a unique way to separate statistically significant quasi-periodic oscillations from one another in high-dimensional data sets.The main results are as follows. First, the total spectra for the two reanalysis data sets are remarkably similar in all timescales, except that the spectral power in ERA-20C is systematically slightly higher than in 20CR. Apart from the slow components related to multi-decadal periodicities, ENSO oscillations with approximately 3.5- and 5-year periods are the most prominent forms of variability in both reanalyses. In 20CR, these are relatively slightly more pronounced than in ERA-20C. Since about the 1970s, the amplitudes of the 3.5- and 5-year oscillations have increased, presumably due to some combination of forced climate change, intrinsic low-frequency climate variability, or change in global observing network. Second, none of the 12 coupled climate models closely reproduce all aspects of the reanalysis spectra, although some models represent many aspects well. For instance, the GFDL-ESM2M model has two nicely separated ENSO periods although they are relatively too prominent as compared with the reanalyses. There is an extensive Supplement and YouTube videos to illustrate the multi-annual variability of the data sets.

scholarly journals Dynamics and Predictability of Hemispheric-Scale Multidecadal Climate Variability in an Observationally Constrained Mechanistic Model

2020 ◽  
Vol 33 (11) ◽  
pp. 4599-4620 ◽  
Author(s):  
Sergey Kravtsov
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Mechanistic Model ◽  
Covariance Structure ◽  
Deep Ocean ◽  
Ocean Dynamics ◽  
Cmip5 Models ◽  
Model Parameters ◽  
Atmospheric Noise ◽  
Multidecadal Climate Variability

AbstractThis paper addresses the dynamics of internal hemispheric-scale multidecadal climate variability by postulating an energy-balance (EBM) model comprising two deep-ocean oscillators in the Atlantic and Pacific basins, coupled through their surface mixed layers via atmospheric teleconnections. This system is linear and driven by the atmospheric noise. Two sets of the EBM model parameters are developed by fitting the EBM-based mixed-layer temperature covariance structure to best mimic basin-average North Atlantic/Pacific sea surface temperature (SST) covariability in either observations or control simulations of comprehensive climate models within the CMIP5 project. The differences between the dynamics underlying the observed and CMIP5-simulated multidecadal climate variability and predictability are encapsulated in the algebraic structure of the two EBM model versions so obtained: EBMCMIP5 and EBMOBS. The multidecadal variability in EBMCMIP5 is overall weaker and amounts to a smaller fraction of the total SST variability than in EBMOBS, pointing to a lower potential decadal predictability of virtual CMIP5 climates relative to that of the actual climate. The EBMCMIP5 decadal hemispheric teleconnections (and, by inference, those in CMIP5 models) are largely controlled by the variability of the Pacific, in which the ocean, due to its large thermal and dynamical memory, acts as a passive integrator of atmospheric noise. By contrast, EBMOBS features a stronger two-way coupling between the Atlantic and Pacific multidecadal oscillators, thereby suggesting the existence of a hemispheric-scale and, perhaps, global multidecadal mode associated with internal ocean dynamics. The inferred differences between the observed and CMIP5 simulated climate variability stem from a stronger communication between the deep ocean and surface processes implicit in the observational data.

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