scholarly journals Oceanic forcing of the global warming slowdown in multi‐model simulations

2020 ◽  
Vol 40 (14) ◽  
pp. 5829-5842 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Tore Furevik ◽  
Yongqi Gao ◽  
Huijun Wang ◽  
...  
Keyword(s):  
Global Warming ◽  
Model Simulations ◽  
Oceanic Forcing

Elevation-Dependent Climate Change in the European Alps

2020 ◽  
Author(s):  
Michael Kuhn ◽  
Marc Olefs
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Global Warming ◽  
Atmospheric Pressure ◽  
Atmospheric Aerosol ◽  
European Alps ◽  
Model Simulations ◽  
Vapor Cloud ◽  
Pressure Water ◽  
Time Changes

Elevation-dependent climate change has been observed in the European Alps in the context of global warming and as a consequence of Alpine orography. It is most obvious in elevation-dependent warming, conveniently defined as the linear regression of the time series of temperatures against elevation, and it reaches values of several tenths of a degree per 1,000 m elevation per decade. Observed changes in temperature have forced changes in atmospheric pressure, water vapor, cloud condensation, fluxes of infrared and solar radiation, snow cover, and evaporation, which have affected the Alpine surface energy and water balance in different ways at different elevations. At the same time, changes in atmospheric aerosol optical depth, in atmospheric circulation, and in the frequency of weather types have contributed to the observed elevation-dependent climate change in the European Alps. To a large extent, these observations have been reproduced by model simulations.

scholarly journals Reconciling Theories for Human and Natural Attribution of Recent East Africa Drying

2017 ◽  
Vol 30 (6) ◽  
pp. 1939-1957 ◽  
Author(s):  
Andrew Hoell ◽  
Martin Hoerling ◽  
Jon Eischeid ◽  
Xiao-Wei Quan ◽  
Brant Liebmann
Keyword(s):  
Global Warming ◽  
East Africa ◽  
Decadal Variability ◽  
Coupled Model ◽  
Western Pacific ◽  
East African ◽  
Coupled Models ◽  
Central Pacific ◽  
Model Simulations ◽  
African Rainfall

Abstract Two theories for observed East Africa drying trends during March–May 1979–2013 are reconciled. Both hypothesize that variations in tropical sea surface temperatures (SSTs) caused East Africa drying. The first invokes a mainly human cause resulting from sensitivity to secular warming of Indo–western Pacific SSTs. The second invokes a mainly natural cause resulting from sensitivity to a strong articulation of ENSO-like Pacific decadal variability involving warming of the western Pacific and cooling of the central Pacific. Historical atmospheric model simulations indicate that observed SST variations contributed significantly to the East Africa drying trend during March–May 1979–2013. By contrast, historical coupled model simulations suggest that external radiative forcing alone, including the ocean’s response to that forcing, did not contribute significantly to East Africa drying. Recognizing that the observed SST variations involved a commingling of natural and anthropogenic effects, this study diagnosed how East African rainfall sensitivity was conditionally dependent on the interplay of those factors. East African rainfall trends in historical coupled models were intercompared between two composites of ENSO-like decadal variability, one operating in the early twentieth century before appreciable global warming and the other in the early twenty-first century of strong global warming. The authors find the coaction of global warming with ENSO-like decadal variability can significantly enhance 35-yr East Africa drying trends relative to when the natural mode of ocean variability acts alone. A human-induced change via its interplay with an extreme articulation of natural variability may thus have been key to Africa drying; however, these results are speculative owing to differences among two independent suites of coupled model ensembles.

scholarly journals Weather extremes over Europe under 1.5 and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2021 ◽  
Vol 12 (2) ◽  
pp. 457-468
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Climate Indices ◽  
Weather Extremes ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel dataset of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. This is a unique and physically consistent dataset, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100×10-year simulations and 25×10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. To demonstrate how adaptation-relevant information can be derived from the HAPPI dataset, changes in four climate indices for periods with 1.5 and 2.0 ∘C global warming are quantified. These indices include number of days per year with daily mean near-surface apparent temperature of >28 ∘C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-year return period (RI50yr); and the annual consecutive dry days (CDDs). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature-related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 ∘C.

scholarly journals Global warming changes tropical cyclone translation speed

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Munehiko Yamaguchi ◽  
Johnny C. L. Chan ◽  
Il-Ju Moon ◽  
Kohei Yoshida ◽  
Ryo Mizuta
Keyword(s):  
Global Warming ◽  
Relative Frequency ◽  
Heavy Rain ◽  
Translation Speed ◽  
Model Simulations ◽  
Slow Moving ◽  
Rain Rates ◽  
Historical Model ◽  
Global Mean ◽  
Expected Increase

AbstractSlow-moving tropical cyclones (TCs) can cause heavy rain because of their duration of influence. Combined with expected increase in rain rates associated with TCs in a warmer climate, there is growing interest in TC translation speed in the past and future. Here we present that a slowdown trend of the translation speed is not simulated for the period 1951–2011 based on historical model simulations. We also find that the annual-mean translation speed could increase under global warming. Although previous studies show large uncertainties in the future projections of TC characteristics, our model simulations show that the average TC translation speed at higher latitudes becomes smaller in a warmer climate, but the relative frequency of TCs at higher latitudes increases. Since the translation speed is much larger in the extratropics, the increase in the relative frequency of TCs at higher latitudes compensates the reduction of the translation speed there, leading to a global mean increase in TC translation speed.

Changes of cooling near mesopause under global warming from observations and model simulations

2017 ◽  
Vol 53 (4) ◽  
pp. 383-391 ◽  
Author(s):  
I. I. Mokhov ◽  
A. I. Semenov ◽  
E. M. Volodin ◽  
M. A. Dembitskaya
Keyword(s):  
Global Warming ◽  
Model Simulations

scholarly journals Projected Changes in Snow Water Equivalent over the Tibetan Plateau under Global Warming of 1.5° and 2°C

2020 ◽  
Vol 33 (12) ◽  
pp. 5141-5154
Author(s):  
Qinglong You ◽  
Fangying Wu ◽  
Hongguo Wang ◽  
Zhihong Jiang ◽  
Nick Pepin ◽  
...  
Keyword(s):  
Global Warming ◽  
Tibetan Plateau ◽  
Snow Water Equivalent ◽  
Coupled Model ◽  
The Tibetan Plateau ◽  
Model Simulations ◽  
The Future ◽  
Snow Water ◽  
Positive Correlations ◽  
Projected Changes

AbstractSnow water equivalent (SWE) is a critical parameter for characterizing snowpack, which has a direct influence on the hydrological cycle, especially over high terrain. In this study, SWE from 18 coupled model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is validated against the Canadian Sea Ice and Snow Evolution Network (CanSISE) SWE. The model simulations under RCP8.5 and RCP4.5 are employed to investigate projected changes in spring/winter SWE over the Tibetan Plateau (TP) under global warming of 1.5° and 2°C. Most CMIP5 models overestimate the CanSISE SWE. A decrease in mean spring/winter SWE for both RCPs over most regions of the TP is predicted in the future, with most significant reductions over the western TP, consistent with pronounced warming in that region. This is supported by strong positive correlations between SWE and mean temperature in the future in both seasons. Compared with the preindustrial period, spring/winter SWE over the TP under global warming of 1.5° and 2°C will reduce significantly, at faster rates than over China as a whole and the Northern Hemisphere. SWE changes over the TP do not show a simple elevation dependency under global warming of 1.5° and 2°C, with maximum changes in the elevation band of 4000–4500 m. Moreover, there are also strong positive correlations between projected SWE and historical mean SWE, indicating that the initial conditions of SWE are an important parameter of future SWE under specific global warming scenarios.

scholarly journals Diagnosing ENSO and Global Warming Tropical Precipitation Shifts Using Surface Relative Humidity and Temperature

2018 ◽  
Vol 31 (4) ◽  
pp. 1413-1433 ◽  
Author(s):  
Alexander Todd ◽  
Matthew Collins ◽  
F. Hugo Lambert ◽  
Robin Chadwick
Keyword(s):  
Global Warming ◽  
Relative Humidity ◽  
Climate Model ◽  
Southern Oscillation ◽  
Precipitation Change ◽  
Method Performance ◽  
Model Simulations ◽  
Tropical Precipitation ◽  
Climate Model Simulations ◽  
Precipitation Changes

Large uncertainty remains in future projections of tropical precipitation change under global warming. A simplified method for diagnosing tropical precipitation change is tested here on present-day El Niño–Southern Oscillation (ENSO) precipitation shifts. This method, based on the weak temperature gradient approximation, assumes precipitation is associated with local surface relative humidity (RH) and surface air temperature (SAT), relative to the tropical mean. Observed and simulated changes in RH and SAT are subsequently used to diagnose changes in precipitation. Present-day ENSO precipitation shifts are successfully diagnosed using observations (correlation r = 0.69) and an ensemble of atmosphere-only (0.51 ≤ r ≤ 0.8) and coupled (0.5 ≤ r ≤ 0.87) climate model simulations. RH ( r = 0.56) is much more influential than SAT ( r = 0.27) in determining ENSO precipitation shifts for observations and climate model simulations over both land and ocean. Using intermodel differences, a significant relationship is demonstrated between method performance over ocean for present-day ENSO and projected global warming ( r = 0.68). As a caveat, the authors note that mechanisms leading to ENSO-related precipitation changes are not a direct analog for global warming–related precipitation changes. The diagnosis method presented here demonstrates plausible mechanisms that relate changes in precipitation, RH, and SAT under different climate perturbations. Therefore, uncertainty in future tropical precipitation changes may be linked with uncertainty in future RH and SAT changes.

scholarly journals Global Warming and Western North Pacific Typhoon Activity from an Observational Perspective

2004 ◽  
Vol 17 (23) ◽  
pp. 4590-4602 ◽  
Author(s):  
Johnny C. L. Chan ◽  
Kin Sik Liu
Keyword(s):  
Global Warming ◽  
El Niño ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Climate Model ◽  
El Nino ◽  
Interannual Variations ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract Based on results from climate model simulations, many researchers have suggested that because of global warming, the sea surface temperature (SST) will likely increase, which will then lead to an increase in the intensity of tropical cyclones (TCs). This paper reports results of a study of the relationship between SST and observed typhoon activity (which is used as a proxy for the intensity of TCs averaged over a season) over the western North Pacific (WNP) for the past 40 yr. The average typhoon activity over a season is found to have no significant relationship with SST in the WNP but increases when the SST over the equatorial eastern Pacific Ocean is above normal. The mean annual typhoon activity is generally higher (lower) during an El Niño (La Niña) year. Such interannual variations of typhoon activity appear to be largely constrained by the large-scale atmospheric factors that are closely related to the El Niño–Southern Oscillation (ENSO) phenomenon. These large-scale dynamic and thermodynamic factors include low-level relative vorticity, vertical wind shear, and moist static energy. Such results are shown to be physically consistent with one another and with those from previous studies on the interannual variations of TC activity. The results emphasize the danger of drawing conclusions about future TC intensity based on current climate model simulations that are not designed to make such predictions.

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