scholarly journals MJO Teleconnections over the PNA Region in Climate Models. Part I: Performance- and Process-Based Skill Metrics

2020 ◽  
Vol 33 (3) ◽  
pp. 1051-1067 ◽  
Author(s):  
Jiabao Wang ◽  
Hyemi Kim ◽  
Daehyun Kim ◽  
Stephanie A. Henderson ◽  
Cristiana Stan ◽  
...  
Keyword(s):  
Model Comparison ◽  
Climate Models ◽  
Global Climate ◽  
Objective Evaluation ◽  
Global Climate Models ◽  
Height Anomaly ◽  
Boreal Winter ◽  
Central Pacific ◽  
Wave Source ◽  
Teleconnection Patterns

AbstractWe propose a set of MJO teleconnection diagnostics that enables an objective evaluation of model simulations, a fair model-to-model comparison, and a consistent tracking of model improvement. Various skill metrics are derived from teleconnection diagnostics including five performance-based metrics that characterize the pattern, amplitude, east–west position, persistence, and consistency of MJO teleconnections and additional two process-oriented metrics that are designed to characterize the location and intensity of the anomalous Rossby wave source (RWS). The proposed teleconnection skill metrics are used to compare the characteristics of boreal winter MJO teleconnections (500-hPa geopotential height anomaly) over the Pacific–North America (PNA) region in 29 global climate models (GCMs). The results show that current GCMs generally produce MJO teleconnections that are stronger, more persistent, and extend too far to the east when compared to those observed in reanalysis. In general, models simulate more realistic teleconnection patterns when the MJO is in phases 2–3 or phases 7–8, which are characterized by a dipole convection pattern over the Indian Ocean and western to central Pacific. The higher model skill for phases 2, 7, and 8 may be due to these phases producing more consistent teleconnection patterns between individual MJO events than other phases, although the consistency is lower in most models than observed. Models that simulate realistic RWS patterns better reproduce MJO teleconnection patterns.

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.

One stomatal model to rule them all? Evaluating competing hypotheses to regulate the exchange of carbon and water against experimental data

2020 ◽  
Author(s):  
Manon Sabot ◽  
Martin De Kauwe ◽  
Belinda Medlyn ◽  
Andy Pitman
Keyword(s):  
Stomatal Conductance ◽  
Land Surface ◽  
Model Comparison ◽  
Climate Models ◽  
Global Climate ◽  
Model Performance ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Model Complexity ◽  
Coupled Climate Models

<p>Nearly 2/3 of the annual global evapotranspiration (ET) over land arises from the vegetation. Yet, coupled-climate models only attribute between 22% – 58% of the annual terrestrial ET to plants. In coupled-climate models, the exchange of carbon and water between the terrestrial biosphere and the atmosphere is simulated by land-surface models (LSMs). Within those LSMs, stomatal conductance (g<sub>s</sub>) models allow plants to regulate their transpiration and carbon uptake, but most are empirically linked to climate, soil moisture availabilty, and CO<sub>2</sub>. Therefore, how and which g<sub>s</sub> schemes are implemented within LSMs is a key source of model uncertainty. This uncertainty has led to considerable investment in theory development in the recent years; multiple alternative hypotheses of optimal leaf-level regulation of gas exchange have been proposed as solutions to reduce existing model biases. However, a systematic inter-model evaluation is lacking (i.e. inter-model comparison within a single framework is needed to understand how different mechanistic assumptions across these new g<sub>s</sub> models affect plant behaviour). Here, we asked how, and under what conditions, nine novel optimal g<sub>s</sub> models differ from one another. The models were trained to match under average conditions before being subjected to: (i) a dry-down, (ii) high vapour pressure deficit, and (iii) elevated CO<sub>2</sub>. These experiments allowed us to identify the models’ specific responses and sensitivities. To further assess whether the models’ responses were realistic, we tested them against photosynthetic and hydraulic field data measured along mesic-xeric gradients in Europe and Australia. Finally, we evaluated model performance versus model complexity and the amount of information taken in by each model, which enables us to make recommendations regarding the use of stomatal conductance schemes in global climate models.</p>

scholarly journals MJO Teleconnections over the PNA Region in Climate Models. Part II: Impacts of the MJO and Basic State

2020 ◽  
Vol 33 (12) ◽  
pp. 5081-5101
Author(s):  
Jiabao Wang ◽  
Hyemi Kim ◽  
Daehyun Kim ◽  
Stephanie A. Henderson ◽  
Cristiana Stan ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Westerly Jet ◽  
The Pacific ◽  
Southward Shift ◽  
Baroclinic Model ◽  
Strong Amplitude ◽  
The Mean

AbstractIn an assessment of 29 global climate models (GCMs), Part I of this study identified biases in boreal winter MJO teleconnections in anomalous 500-hPa geopotential height over the Pacific–North America (PNA) region that are common to many models: an eastward shift, a longer persistence, and a larger amplitude. In Part II, we explore the relationships of the teleconnection metrics developed in Part I with several existing and newly developed MJO and basic state (the mean subtropical westerly jet) metrics. The MJO and basic state diagnostics indicate that the MJO is generally weaker and less coherent and propagates faster in models compared to observations. The mean subtropical jet also exhibits notable biases such as too strong amplitude, excessive eastward extension, or southward shift. The following relationships are found to be robust among the models: 1) models with a faster MJO propagation tend to produce weaker teleconnections; 2) models with a less coherent eastward MJO propagation tend to simulate more persistent MJO teleconnections; 3) models with a stronger westerly jet produce stronger and eastward shifted MJO teleconnections; 4) models with an eastward extended jet produce an eastward shift in MJO teleconnections; and 5) models with a southward shifted jet produce stronger MJO teleconnections. The results are supported by linear baroclinic model experiments. Our results suggest that the larger amplitude and eastward shift biases in GCM MJO teleconnections can be attributed to the biases in the westerly jet, and that the longer persistence bias is likely due to the lack of coherent eastward MJO propagation.

Climate engineering to mitigate the projected 21st-century terrestrial drying of the Americas: a direct comparison of carbon capture and sulfur injection

2021 ◽  
Author(s):  
Yangyang Xu ◽  
Lei Lin ◽  
Simone Tilmes ◽  
Katherine Dagon ◽  
Lili Xia ◽  
...  
Keyword(s):  
Global Warming ◽  
South America ◽  
21St Century ◽  
Carbon Capture ◽  
Model Comparison ◽  
Climate Models ◽  
Global Climate ◽  
Low Cost ◽  
Amazon Region ◽  
Global Climate Models

<p>To mitigate the projected global warming in the 21st century, it is well-recognized that society needs to cut CO2 emissions and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the “well below 2 ◦C” aspiration in the Paris Agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to decarbonization, to reach negative net emissions at the mid-century mark. Another ambitious proposal is solar-radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in public debate for years, these two leading geoengineering schemes have not been directly compared under a consistent analytical framework using global climate models.</p><p>Here we present the first explicit analysis of the hydroclimate impacts of these two geoengineering approaches using two recently available large-ensemble model experiments conducted by a family of state-of-the-art Earth system models. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century in detailed terms of the potential mitigation benefits, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming in these simulations, sulfur injection is less effective in curbing the worsening trend of regional land aridity in the Americas under RCP8.5 when compared with carbon capture. Temporally, the climate benefit of sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the sulfur injection scheme is particularly more effective for the sub-Amazon region (southern Brazil), while the carbon capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as an inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of sulfur injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emission cuts and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessments in other parts of the world.</p>

scholarly journals Improvement of ENSO Simulation Based on Intermodel Diversity

2015 ◽  
Vol 28 (3) ◽  
pp. 998-1015 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Jong-Seong Kug
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Simulation ◽  
Central Pacific

Abstract In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupled global climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the close connection between the interannual variability and climatological states, the distinctive relation between the intermodel diversity of the interannual variability and that of the basic state is found. Based on this relation, the simulated interannual variabilities can be improved, by correcting their climatological bias. To test this methodology, the dominant intermodel difference in precipitation responses during El Niño–Southern Oscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominant intermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominant intermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatology than the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positive ENSO precipitation anomalies to the east (west). Based on the model’s systematic errors in atmospheric ENSO response and bias, the models with better climatological state tend to simulate more realistic atmospheric ENSO responses. Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. After the statistical correction, simulating quality of the MME ENSO precipitation is distinctively improved. These results provide a possibility that the present methodology can be also applied to improving climate projection and seasonal climate prediction.

scholarly journals Short Warm-Side Temperature Distribution Tails Drive Hot Spots of Warm Temperature Extreme Increases under Near-Future Warming

2018 ◽  
Vol 31 (23) ◽  
pp. 9469-9487 ◽  
Author(s):  
Paul C. Loikith ◽  
J. David Neelin ◽  
Joyce Meyerson ◽  
Jacob S. Hunter
Keyword(s):  
Hot Spots ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Global Evaluation ◽  
Underlying Distribution ◽  
Future Warming

Regions of shorter-than-Gaussian warm-side temperature anomaly distribution tails are shown to occur in spatially coherent patterns in global reanalysis. Under such conditions, future warming may be manifested in more complex ways than if the underlying distribution were close to Gaussian. For example, under a uniform warm shift, the simplest prototype for future warming, a location with a short tail would experience a greater increase in extreme warm exceedances relative to a fixed threshold compared to if the distribution were Gaussian. The associated societal and environmental impacts make realistic representation of these short tails an important target for climate models. Global evaluation of the ability for a suite of global climate models (GCMs) contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests that most models approximately capture the principal observed coherent regions of short tails. This suggests the underlying dynamics and physics occur on scales resolved by the models, and helps build confidence in model simulations of extremes. Furthermore, most GCMs show more rapid future increases in exceedances of the historical 95th percentile in regions exhibiting short tails in the historical climate. These regions, where the ratio of exceedances projected by the GCM compared to that expected from a Gaussian sometimes exceeds 1.5, are termed hot spots. Prominent hot spots include western North America, Central America, a broad swath of northwestern Eurasia, and the Indochina Peninsula during boreal winter. During boreal summer, central and western Australia, parts of southern Africa, and portions of central South America are major hot spots.

Distinct Patterns of Cloud Changes Associated with Decadal Variability and Their Contribution to Observed Cloud Cover Trends

2019 ◽  
Vol 32 (21) ◽  
pp. 7281-7301
Author(s):  
Yong-Jhih Chen ◽  
Yen-Ting Hwang ◽  
Mark D. Zelinka ◽  
Chen Zhou
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Climate Models ◽  
Decadal Variability ◽  
Global Climate ◽  
Global Climate Models ◽  
Central Pacific ◽  
The Pacific ◽  
Low Cloud ◽  
Low Cloud Cover

Abstract With the goal of understanding the relative roles of anthropogenic and natural factors in driving observed cloud trends, this study investigates cloud changes associated with decadal variability including the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO). In the preindustrial simulations of CMIP5 global climate models (GCMs), the spatial patterns and the vertical structures of the PDO-related cloud cover changes in the Pacific are consistent among models. Meanwhile, the models show consistent AMO impacts on high cloud cover in the tropical Atlantic, subtropical eastern Pacific, and equatorial central Pacific, and on low cloud cover in the North Atlantic and subtropical northeast Pacific. The cloud cover changes associated with the PDO and the AMO can be understood via the relationships between large-scale meteorological parameters and clouds on interannual time scales. When compared to the satellite records during the period of 1983–2009, the patterns of total and low cloud cover trends associated with decadal variability are significantly correlated with patterns of cloud cover trends in ISCCP observations. On the other hand, the pattern of the estimated greenhouse gas (GHG)-forced trends of total cloud cover differs from that related to decadal variability, and may explain the positive trends in the subtropical southeast Pacific, negative trends in the midlatitudes, and positive trends poleward of 50°N/S. In most models, the magnitude of the estimated decadal variability contribution to the observed cloud cover trends is larger than that contributed by GHG, suggesting the observed cloud cover trends are more closely related to decadal variability than to GHG-induced warming.

Intraseasonal Vertical Cloud Regimes Based on CloudSat Observations over the Tropics

2020 ◽  
Vol 12 (14) ◽  
pp. 2273 ◽  
Author(s):  
Meng-Pai Hung ◽  
Wei-Ting Chen ◽  
Chien-Ming Wu ◽  
Peng-Jen Chen ◽  
Pei-Ning Feng
Keyword(s):  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Empirical Orthogonal Functions ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Orthogonal Functions ◽  
Temporal Variance ◽  
Cloud Regimes

This study identifies the evolution of tropical vertical cloud regimes (CRs) and their associated heating structures on the intraseasonal time scales. Using the cloud classification retrievals of CloudSat during boreal winter between 2006 and 2017, the CR index is defined as the leading pair of the combined multivariate empirical orthogonal functions of the daily mean frequency of deep, high, and low clouds over the tropical Indian Ocean, Maritime Continents, and the Western Pacific. The principal components of the CR index exhibit robust temporal variance in the 30 to 80 day intraseasonal band. Based on the propagation stages of the CRs, the coherent vertical structures of cloud composition and large-scale moisture and vertical motion exhibit a westward-tilted structure. The associated Q1-QR diabatic heating and cloud radiative forcing are consistent with the key characteristics of the Madden Julian Oscillation (MJO) documented in the previous studies. Lastly, an MJO case study showcases that the presented approach characteristically captures the propagation of moisture, cloud vertical structure, and precipitation activity across spatial and temporal scales. The current results suggest that the CR index can potentially serve as an evaluation metric to cloud-associated processes in the simulated tropical intraseasonal variability in global climate models.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models
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