scholarly journals Tropical Pacific Climate and Its Response to Global Warming in the Kiel Climate Model

2009 ◽  
Vol 22 (1) ◽  
pp. 71-92 ◽  
Author(s):  
W. Park ◽  
N. Keenlyside ◽  
M. Latif ◽  
A. Ströh ◽  
R. Redler ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Co2 Concentration ◽  
Tropical Pacific ◽  
Equatorial Pacific ◽  
Cold Bias ◽  
The Tropical Pacific

Abstract A new, non-flux-corrected, global climate model is introduced, the Kiel Climate Model (KCM), which will be used to study internal climate variability from interannual to millennial time scales and climate predictability of the first and second kind. The version described here is a coarse-resolution version that will be employed in extended-range integrations of several millennia. KCM’s performance in the tropical Pacific with respect to mean state, annual cycle, and El Niño–Southern Oscillation (ENSO) is described. Additionally, the tropical Pacific response to global warming is studied. Overall, climate drift in a multicentury control integration is small. However, KCM exhibits an equatorial cold bias at the surface of the order 1°C, while strong warm biases of several degrees are simulated in the eastern tropical Pacific on both sides off the equator, with maxima near the coasts. The annual and semiannual cycles are realistically simulated in the eastern and western equatorial Pacific, respectively. ENSO performance compares favorably to observations with respect to both amplitude and period. An ensemble of eight greenhouse warming simulations was performed, in which the CO2 concentration was increased by 1% yr−1 until doubling was reached, and stabilized thereafter. Warming of equatorial Pacific sea surface temperature (SST) is, to first order, zonally symmetric and leads to a sharpening of the thermocline. ENSO variability increases because of global warming: during the 30-yr period after CO2 doubling, the ensemble mean standard deviation of Niño-3 SST anomalies is increased by 26% relative to the control, and power in the ENSO band is almost doubled. The increased variability is due to both a strengthened (22%) thermocline feedback and an enhanced (52%) atmospheric sensitivity to SST; both are associated with changes in the basic state. Although variability increases in the mean, there is a large spread among ensemble members and hence a finite probability that in the “model world” no change in ENSO would be observed.

scholarly journals Black Carbon Increases Frequency of Extreme ENSO Events

2019 ◽  
Vol 32 (23) ◽  
pp. 8323-8333 ◽  
Author(s):  
Sijia Lou ◽  
Yang Yang ◽  
Hailong Wang ◽  
Jian Lu ◽  
Steven J. Smith ◽  
...  
Keyword(s):  
Black Carbon ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Co2 Concentration ◽  
Enso Events ◽  
Aerosol Forcing ◽  
Earth’S Climate

ABSTRACT El Niño–Southern Oscillation (ENSO) is the leading mode of Earth’s climate variability at interannual time scales with profound ecological and societal impacts, and it is projected to intensify in many climate models as the climate warms under the forcing of increasing CO2 concentration. Since the preindustrial era, black carbon (BC) emissions have substantially increased in the Northern Hemisphere. But how BC aerosol forcing may influence the occurrence of the extreme ENSO events has rarely been investigated. In this study, using simulations of a global climate model, we show that increases in BC emissions from both the midlatitudes and Arctic weaken latitudinal temperature gradients and northward heat transport, decrease tropical energy divergence, and increase sea surface temperature over the tropical oceans, with a surprising consequential increase in the frequency of extreme ENSO events. A corollary of this study is that reducing BC emissions might serve to mitigate the possible increasing frequency of extreme ENSO events under greenhouse warming, if the modeling result can be translated into the climate in reality.

scholarly journals Global warming precipitation accumulation increases above the current-climate cutoff scale

2017 ◽  
Vol 114 (6) ◽  
pp. 1258-1263 ◽  
Author(s):  
J. David Neelin ◽  
Sandeep Sahany ◽  
Samuel N. Stechmann ◽  
Diana N. Bernstein
Keyword(s):  
Global Warming ◽  
Probability Density ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Storm Event ◽  
Current Climate ◽  
Order Of Magnitude ◽  
Climate Model Simulations ◽  
Precipitation Loss

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

scholarly journals Lengthening of summer season over the Northern Hemisphere under 1.5°C and 2.0°C global warming

2021 ◽  
Author(s):  
Bo-Joung Park ◽  
Seung-Ki Min ◽  
Evan Weller
Keyword(s):  
Global Warming ◽  
East Asia ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Late Summer ◽  
Industrial Condition ◽  
Summer Season ◽  
Hot Days

Abstract Summer season has lengthened substantially across Northern Hemisphere (NH) land over the past decades, which has been attributed to anthropogenic greenhouse gas increases. This study examines additional future changes in summer season onset and withdrawal under 1.5℃ and 2.0℃ global warming conditions using multiple atmospheric global climate model (AGCM) large-ensemble simulations from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. Five AGCMs provide more than 100 runs of 10-year length for three experiments: All-Hist (current decade: 2006-2015), Plus15, and Plus20 (1.5℃ and 2.0℃ above pre-industrial condition, respectively). Results show that with 1.5℃ and 2.0℃ warmer conditions summer season will become longer by a few days to weeks over entire NH lands, with slightly larger contributions by delay in withdrawal due to stronger warming in late summer. Stronger changes are observed more in middle latitudes than high latitudes and largest expansion (up to three weeks) is found over East Asia and the Mediterranean. Associated changes in summer-like day frequency is further analyzed focusing on the extended summer edges. The hot days occur more frequently in lower latitudes including East Asia, USA and Mediterranean, in accord with largest summer season lengthening. Further, difference between Plus15 and Plus20 indicates that summer season lengthening and associated increases in hot days can be reduced significantly if warming is limited to 1.5℃. Overall, similar results are obtained from CMIP5 coupled GCM simulations (based on RCP8.5 scenario experiments), suggesting a weak influence of air-sea coupling on summer season timing changes.

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.

Large internal variability dominates over global warming signal in observed lower stratospheric QBO amplitude

2021 ◽  
pp. 1-43
Author(s):  
Aaron Match ◽  
Stephan Fueglistaler
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Internal Variability ◽  
Dynamical Process ◽  
Quasi Biennial Oscillation ◽  
Amplitude Profile ◽  
Biennial Oscillation ◽  
Middle Stratosphere

AbstractGlobal warming projections of dynamics are less robust than projections of thermodynamics. However, robust aspects of the thermodynamics can be used to constrain some dynamical aspects. This paper argues that tropospheric expansion under global warming (a thermodynamical process) explains changes in the amplitude of the Quasi-Biennial Oscillation (QBO) in the lower and middle stratosphere (a dynamical process). A theoretical scaling for tropospheric expansion of approximately 6 hPa K−1 is derived, which agrees well with global climate model (GCM) experiments. Using this theoretical scaling, the response of QBO amplitude to global warming is predicted by shifting the climatological QBO amplitude profile upwards by 6 hPa per Kelvin of global warming. In global warming simulations, QBO amplitude in the lower- to mid-stratosphere shifts upwards as predicted by tropospheric expansion. Applied to observations, the tropospheric expansion framework suggests a historical weakening of QBO amplitude at 70 hPa of 3% decade−1 from 1953-2020. This expected weakening trend is half of the 6% decade−1 from 1953-2012 detected and attributed to global warming in a recent study. The previously reported trend was reinforced by record low QBO amplitudes during the mid-2000s, from which the QBO has since recovered. Given the modest weakening expected on physical grounds, past decadal modulations of QBO amplitude are reinterpreted as a hitherto unrecognized source of internal variability. This large internal variability dominates over the global warming signal, such that despite 65 years of observations, there is not yet a statistically significant weakening trend.

scholarly journals Seasonal Drought in the Greater Horn of Africa and Its Recent Increase during the March–May Long Rains

2014 ◽  
Vol 27 (21) ◽  
pp. 7953-7975 ◽  
Author(s):  
Bradfield Lyon
Keyword(s):  
Atmospheric Circulation ◽  
Climate Model ◽  
Southern Oscillation ◽  
Meteorological Drought ◽  
Tropical Pacific ◽  
Horn Of Africa ◽  
New Findings ◽  
Climate Model Simulations ◽  
Greater Horn Of Africa ◽  
The Tropical Pacific

Abstract This paper provides a review of atmospheric circulation and sea surface temperature (SST) conditions that are associated with meteorological drought on the seasonal time scale in the Greater Horn of Africa (the region 10°S–15°N, 30°–52°E). New findings regarding a post-1998 increase in drought frequency during the March–May (MAM) “long rains” are also reported. The period 1950–2010 is emphasized, although rainfall and SST data from 1901–2010 are used to place the recent long rains decline in a multidecadal context. For the latter case, climate model simulations and isolated basin SST experiments are also utilized. Climatologically, rainfall exhibits a unimodal June–August (JJA) maximum in west-central Ethiopia with a generally bimodal [MAM and October–December (OND) maxima] distribution in locations to the south and east. Emphasis will be on these three seasons. SST anomalies in the tropical Pacific and Indian Oceans show the strongest association with drought during OND in locations having a bimodal annual cycle, with weaker associations during MAM. The influence of the El Niño–Southern Oscillation (ENSO) phenomenon critically depends on its ability to affect SSTs outside the Pacific. Salient features of the anomalous atmospheric circulation during drought events in different locations and seasons are discussed. The post-1998 decline in the long rains is found to be driven strongly (although not necessarily exclusively) by natural multidecadal variability in the tropical Pacific rather than anthropogenic climate change. This conclusion is supported by observational analyses and climate model experiments, which are presented.

Distributions of Tropical Precipitation Cluster Power and Their Changes under Global Warming. Part I: Observational Baseline and Comparison to a High-Resolution Atmospheric Model

2017 ◽  
Vol 30 (20) ◽  
pp. 8033-8044 ◽  
Author(s):  
Kevin M. Quinn ◽  
J. David Neelin
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Rain Rate ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Aggregate Size ◽  
Atmospheric Model ◽  
Rain Rates ◽  
High Cluster

Abstract The total amount of precipitation integrated across a precipitation feature (contiguous precipitating grid cells exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance, expressed as the rate of water mass lost or latent heat released (i.e., the power of the disturbance). The probability distribution of cluster power is examined over the tropics using Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite-retrieved rain rates and global climate model output. Observed distributions are scale-free from the smallest clusters up to a cutoff scale at high cluster power, after which the probability drops rapidly. After establishing an observational baseline, precipitation from the High Resolution Atmospheric Model (HiRAM) at two horizontal grid spacings (roughly 0.5° and 0.25°) is compared. When low rain rates are excluded by choosing a minimum rain-rate threshold in defining clusters, the model accurately reproduces observed cluster power statistics at both resolutions. Middle and end-of-century cluster power distributions are investigated in HiRAM in simulations with prescribed sea surface temperatures and greenhouse gas concentrations from a “business as usual” global warming scenario. The probability of high cluster power events increases strongly by end of century, exceeding a factor of 10 for the highest power events for which statistics can be computed. Clausius–Clapeyron scaling accounts for only a fraction of the increased probability of high cluster power events.

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.

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