Bias nonstationarity of global climate model outputs: The role of internal climate variability and climate model sensitivity

2018 ◽  
Vol 39 (4) ◽  
pp. 2278-2294 ◽  
Author(s):  
Yu Hui ◽  
Jie Chen ◽  
Chong‐Yu Xu ◽  
Lihua Xiong ◽  
Hua Chen
Keyword(s):  
Climate Variability ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Sensitivity ◽  
Internal Climate Variability

scholarly journals The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

2018 ◽  
Vol 18 (11) ◽  
pp. 2991-3006 ◽  
Author(s):  
Matthew D. K. Priestley ◽  
Helen F. Dacre ◽  
Len C. Shaffrey ◽  
Kevin I. Hodges ◽  
Joaquim G. Pinto
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geographic Region ◽  
Near Surface ◽  
Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

scholarly journals Role of Maritime Continent Land Convection on the Mean State and MJO Propagation

2020 ◽  
Vol 33 (5) ◽  
pp. 1659-1675 ◽  
Author(s):  
Min-Seop Ahn ◽  
Daehyun Kim ◽  
Yoo-Geun Ham ◽  
Sungsu Park
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Critical Role ◽  
Moisture Gradient ◽  
Moisture Distribution ◽  
Boreal Winter ◽  
Maritime Continent ◽  
The Mean

AbstractThe Maritime Continent (MC) region is known as a “barrier” in the life cycle of the Madden–Julian oscillation (MJO). During boreal winter, the MJO detours the equatorial MC land region southward and propagates through the oceanic region. Also, about half of the MJO events that initiate over the Indian Ocean cease around the MC. The mechanism through which the MC affects MJO propagation, however, has remained unanswered. The current study investigates the MJO–MC interaction with a particular focus on the role of MC land convection. Using a global climate model that simulates both mean climate and MJO realistically, we performed two sensitivity experiments in which updraft plume radius is set to its maximum and minimum value only in the MC land grid points, making convective top deeper and shallower, respectively. Our results show that MC land convection plays a key role in shaping the 3D climatological moisture distribution around the MC through its local and nonlocal effects. Shallower and weaker MC land convection results in a steepening of the vertical and meridional mean moisture gradient over the MC region. The opposite is the case when MC land convection becomes deeper and stronger. The MJO’s eastward propagation is enhanced (suppressed) with the steeper (lower) mean moisture gradient. The moist static energy (MSE) budget of the MJO reveals the vertical and meridional advection of the mean MSE by MJO wind anomalies as the key processes that are responsible for the changes in MJO propagation characteristics. Our results pinpoint the critical role of the background moisture gradient on MJO propagation.

Quantification of terrestrial regional climate variability from a large database of pollen-based reconstructions and implications for future projections

2020 ◽  
Author(s):  
Raphael Hébert ◽  
Ulrike herzschuh ◽  
Thomas Laepple
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Irregular Sampling ◽  
Large Database ◽  
Spatial Correlation Structure ◽  
Pollen Records

<p>Multidecadal to millenial timescale climate variability has been investigated over the ocean</p><p>using extensive proxy data and it was found to yield coherent interproxy estimates of global and regional sea-surface temperature (SST) climate variability (Laepple and Huybers, 2014). Global Climate Model (GCM) simulations on the other hand, were found to exhibit an increasingly large deficit of regional SST climate variability for increasingly longer timescales.</p><p>Further investigation is needed to better quantify terrestrial climate variability for long</p><p>timescales and validate climate models.</p><p>Vegetation related proxies such as tree rings and pollen records are the most widespread</p><p>types of archives available to investigate terrestrial climate variability. Tree ring records are</p><p>particularly useful for short time scales estimates due to their annual resolution, while pollen-based reconstructions are necessary to cover the longer timescales. In the present work, we use a large database of 1873 pollen records covering the northern hemisphere in order to quantify Holocene vegetation and climate variability for the first time at centennial to multi-millenial timescales.</p><p>To ensure the robustness of our results, we are particularly interested in the spatio-temporal representativity of the archived signal in pollen records after taking into account the effective spatial scale, the intermittent and irregular sampling, the age-uncertainty and the sediment mixing effect. A careful treatment of the proxy formation allows us to investigate the spatial correlation structure of the pollen-based climate reconstructions as a function of timescales. The pollen data results are then contrasted with the analysis replicated using transient Holocene simulations produced with state-of-the-art climate models as well as stochastic climate model simulations.Our results indicate a substantial gap in terrestrial climate variability between the climate model simulations and the pollen reconstructions at centennial to multi-millenial timescales, mirroring the variability gap found in the marine domain. Finally, we investigate how future climate model projections with greater internal variability would be affected, and how this increases the uncertainty of regional land temperature projections.</p>

scholarly journals Risk assessment of a water supply system under climate variability: a stochastic approach

2011 ◽  
Vol 38 (3) ◽  
pp. 252-262 ◽  
Author(s):  
Beatrice B. Yung ◽  
Bryan A. Tolson ◽  
Donald H. Burn
Keyword(s):  
Climate Variability ◽  
Population Growth ◽  
Water Supply ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Demand Management ◽  
Stochastic Approach ◽  
Supply System ◽  
Water Supply System

A model is developed to assess risk to a municipal water supply system under the influence of population growth and climate variability. To incorporate the uncertainty in water use, a model that combines time series Monte Carlo simulations and a deterministic artificial neural network (ANN) is developed to simulate the daily water demand under climate variation. The model is first applied to assess how climate change alters the risk of a current water supply system and is then used to estimate the effects of demand management programs and system expansion. The model quantifies water supply system risk in terms of reliability, resiliency, and vulnerability (RRV). The model evaluates 11 scenarios defined by combining various population growth forecasts, demand management programs, system expansions, and global climate model (GCM) scenarios. The simulation results suggest that a rise in temperature and a change in precipitation magnitude will negatively impact the performance of the case study system.

The Sensitivity of the Tropical-Mean Radiation Budget

2005 ◽  
Vol 18 (16) ◽  
pp. 3189-3203 ◽  
Author(s):  
Amy C. Clement ◽  
Brian Soden
Keyword(s):  
Climate Model ◽  
Decadal Variability ◽  
Global Climate ◽  
Global Climate Model ◽  
Hadley Circulation ◽  
Radiation Budget ◽  
Convective Precipitation ◽  
Model Sensitivity ◽  
Precipitation Efficiency ◽  
Sensitivity Experiments

Abstract A key disagreement exists between global climate model (GCM) simulations and satellite observations of the decadal variability in the tropical-mean radiation budget. Measurements from the Earth Radiation Budget Experiment (ERBE) over the period 1984–2001 indicate a trend of increasing longwave emission and decreasing shortwave reflection that no GCM can currently reproduce. Motivated by these results, a series of model sensitivity experiments is performed to investigate hypotheses that have been advanced to explain this discrepancy. Specifically, the extent to which a strengthening of the Hadley circulation or a change in convective precipitation efficiency can alter the tropical-mean radiation budget is assessed. Results from both model sensitivity experiments and an empirical analysis of ERBE observations suggest that the tropical-mean radiation budget is remarkably insensitive to changes in the tropical circulation. The empirical estimate suggests that it would require at least a doubling in strength of the Hadley circulation in order to generate the observed decadal radiative flux changes. In contrast, rather small changes in a model’s convective precipitation efficiency can generate changes comparable to those observed, provided that the precipitation efficiency lies near the upper end of its possible range. If, however, the precipitation efficiency of tropical convective systems is more moderate, the model experiments suggest that the climate would be rather insensitive to changes in its value. Further observations are necessary to constrain the potential effects of microphysics on the top-of-atmosphere radiation budget.

scholarly journals Climate Variability in Monsoon and Arid Regions Attributable to Dynamic Vegetation in a Global Climate Model

2018 ◽  
Vol 96 (4) ◽  
pp. 391-403
Author(s):  
Hongli WANG ◽  
Linjing QIU ◽  
Xiaoning XIE ◽  
Zhiyuan WANG ◽  
Xiaodong LIU
Keyword(s):  
Climate Variability ◽  
Arid Regions ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model

scholarly journals On the role of sea-ice transport in modifying arctic responses to global climate change

1997 ◽  
Vol 25 ◽  
pp. 102-106 ◽  
Author(s):  
James Maslanik ◽  
Jeremy Dunn
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
The Arctic ◽  
Climate Change Responses ◽  
Ice Conditions ◽  
Arctic Ice ◽  
Ice Pack

The role of dynamics in modifying the response of the Arctic ice pack to inter-annually varying forcings and to climate perturbations is investigated using simulations from a two-dimensional ice model and a global climate model (GCM). Inter-annual variability in ice-covered area for 1985-93 is dominated by ice transport, and different transport regimes affect substantially the response of the ice pack to climate perturbations. The thermodynamic-only simulations are more sensitive to initial ice conditions, and respond less than the dynamk-thermodynamic model to small perturbations, but with a greater response to larger perturbations. Comparisons of GCM simulations that use different ice treatments highlights the importance of considering the distribution of ice thickness and extent in assessing climate-change responses.

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