Water cycle changes over the Mediterranean: a comparison study of a super-high-resolution global model with CMIP3

Author(s):  
Fengjun Jin ◽  
Akio Kitoh ◽  
Pinhas Alpert

Water cycle components over the Mediterranean for both a current run (1979–2007) and a future run (2075–2099) are studied with the Japan Meteorological Agency’s 20 km grid global climate model. Results are compared with another study using the Coupled Model Intercomparison Project Phase 3 ensemble model (hereafter, the Mariotti model). Our results are surprisingly close to Mariotti’s. The projected mean annual change rates of precipitation ( P ) between the future and the current run for sea and land are −11 per cent and −10 per cent, respectively, which are not as high as Mariotti’s. Projected changes for evaporation ( E ) are +9.3 per cent and −3.6 per cent, compared with +7.2 per cent and −8.1 per cent in Mariotti’s study, respectively. However, no significant difference in the change in P – E over the sea body was found between these two studies. The increased E over the eastern Mediterranean was found to be higher than that in the western Mediterranean, but the P decrease was lower. The net moisture budget, P – E , shows that the eastern Mediterranean will become even drier than the western Mediterranean. The river model suggests decreasing water inflow to the Mediterranean of approximately 36 per cent (excluding the Nile).

2015 ◽  
Vol 47 (5-6) ◽  
pp. 1913-1924 ◽  
Author(s):  
M. Tous ◽  
G. Zappa ◽  
R. Romero ◽  
L. Shaffrey ◽  
P. L. Vidale

2014 ◽  
Vol 7 (6) ◽  
pp. 8975-9015
Author(s):  
E. M. Knudsen ◽  
J. E. Walsh

Abstract. Metrics of storm activity in Northern Hemisphere high- and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA-Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December), the period when the ongoing and projected Arctic sea ice retreat is greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1-M, although the tracks are somewhat better resolved in the higher-resolution ERA-Interim and CCSM4. The tracks are projected to shift polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high-latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high-latitudes, especially the Baffin Bay/Davis Strait region. Autumn precipitation is projected to increase significantly across the entire high-latitudes. Together with the projected increases in storm intensity and sea level and the loss of sea ice, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century.


2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.


2015 ◽  
Vol 143 (2) ◽  
pp. 524-535 ◽  
Author(s):  
Baoqiang Xiang ◽  
Shian-Jiann Lin ◽  
Ming Zhao ◽  
Shaoqing Zhang ◽  
Gabriel Vecchi ◽  
...  

Abstract While tropical cyclone (TC) prediction, in particular TC genesis, remains very challenging, accurate prediction of TCs is critical for timely preparedness and mitigation. Using a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the authors studied the predictability of two destructive landfall TCs: Hurricane Sandy in 2012 and Super Typhoon Haiyan in 2013. Results demonstrate that the geneses of these two TCs are highly predictable with the maximum prediction lead time reaching 11 days. The “beyond weather time scale” predictability of tropical cyclogenesis is primarily attributed to the model’s skillful prediction of the intraseasonal Madden–Julian oscillation (MJO) and the westward propagation of easterly waves. Meanwhile, the landfall location and time can be predicted one week ahead for Sandy’s U.S landfall, and two weeks ahead for Haiyan’s landing in the Philippines. The success in predicting Sandy and Haiyan, together with low false alarms, indicates the potential of using the GFDL coupled model for extended-range predictions of TCs.


2015 ◽  
Vol 28 (17) ◽  
pp. 6938-6959 ◽  
Author(s):  
Alex J. Cannon ◽  
Stephen R. Sobie ◽  
Trevor Q. Murdock

Abstract Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models. Although they are effective at removing historical biases relative to observations, it has been found that quantile mapping can artificially corrupt future model-projected trends. Previous studies on the modification of precipitation trends by quantile mapping have focused on mean quantities, with less attention paid to extremes. This article investigates the extent to which quantile mapping algorithms modify global climate model (GCM) trends in mean precipitation and precipitation extremes indices. First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly preserves relative changes in precipitation quantiles is presented. QDM is compared on synthetic data with detrended quantile mapping (DQM), which is designed to preserve trends in the mean, and with standard quantile mapping (QM). Next, methods are applied to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation projections over Canada. Performance is assessed based on precipitation extremes indices and results from a generalized extreme value analysis applied to annual precipitation maxima. QM can inflate the magnitude of relative trends in precipitation extremes with respect to the raw GCM, often substantially, as compared to DQM and especially QDM. The degree of corruption in the GCM trends by QM is particularly large for changes in long period return values. By the 2080s, relative changes in excess of +500% with respect to historical conditions are noted at some locations for 20-yr return values, with maximum changes by DQM and QDM nearing +240% and +140%, respectively, whereas raw GCM changes are never projected to exceed +120%.


2016 ◽  
Vol 9 (7) ◽  
pp. 2335-2355 ◽  
Author(s):  
Erlend M. Knudsen ◽  
John E. Walsh

Abstract. Metrics of storm activity in Northern Hemisphere high and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA-Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December) – the period when the ongoing and projected Arctic sea ice retreat is the greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1-M, although the tracks are somewhat better resolved in the higher-resolution ERA-Interim and CCSM4. The tracks show indications of shifting polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high latitudes, especially the Baffin Bay/Davis Strait region in September. Autumn precipitation is projected to increase significantly across the entire high latitudes. Together with the projected loss of sea ice and increases in storm intensity and sea level, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century.


2021 ◽  
Author(s):  
Francisco González-Galindo ◽  
Jean-Yves Chaufray ◽  
Franck Lefèvre ◽  
Franck Montmessin ◽  
Margaux Vals ◽  
...  

<p>The thermal escape of hydrogen from Mars is recognized as one of the major drivers of the long-term climatic evolution of the planet. Recent works have shown that, contrary to what was previously believed, water is not trapped in the lower atmosphere of Mars. Instead, it can be transported to the middle/upper atmosphere, producing layers of supersaturated water (Fedorova et al., 2018, 2021). Upper atmospheric water can then be converted to hydrogen by photolysis or chemical reactions with ions, boosting the rate of hydrogen escape (Chaffin et al., 2017; Stone et al., 2020). Strong seasonal variations in the escape rate, and significant increases of both the water abundance in the mesosphere and the hydrogen escape rate during dust storms, evidence the strong coupling between the hydrogen escape and the water cycle (Chaffin et al., 2014; Fedorova et al., 2018, 2020). A global model able to simulate all the processes related to water, from the ice sublimation to the transport to the upper atmosphere and its atmospheric escape, is needed in order to help interpreting the observations. This model can also be used to explore also the water cycle and hydrogen escape on past Mars conditions characterized by different orbital parameters, allowing for a better estimation of the accumulated escape rate.</p> <p>Previous simulations with the LMD-Mars Global Climate Model (LMD-MGCM), and their comparison with observational results by SPICAM/Mars Express showed that the simulated escape rate was underestimated, in particular during the second half of the Martian year (Chaufray et al., 2021). However, those simulations did not take into account the microphysical processes producing water supersaturation, and thus underestimated the role of water transport in the escape rate. In addition, the model did not include the photochemistry of water-derived ions, which can play an important role in converting water into hydrogen (Stone et al., 2020).</p> <p>New simulations with an improved version of the LMD-MGCM have been produced that overcome those previous limitations. The water cloud microphysics has now been fully considered in the simulations, using the model by Navarro et al. (2014). The photochemical model has been updated to include water-derived ions (H2O+, H3O+, OH+). Also, the deuterium fractionation model has been improved (Rossi et al., 2021), and deuterated species have been included in the photochemical model. While this last modification is not expected to modify the hydrogen escape rate, the inclusion of deuterated species can provide important diagnostics on the hydrogen escape and its accumulation over Mars history.</p> <p>In this presentation we will show the results of the improved version of the LMD-MGCM, comparing with available observations. The focus will be on the predicted hydrogen escape rate, and how it is affected by the inclusion of different physical processes. We find that including the possibility of water supersaturation increases the Hydrogen escape rate in more than one order of magnitude at most seasons, taking the simulated rate to better agreement with SPICAM observations during the second half of the year. This confirms previous observational results indicating the importance of water supersaturation (Fedorova et al. 2020). We also find that the inclusion of water-derived ions in the photochemistry also increases the escape rate, in particular during the first part of the year. We will also compare the predicted water abundance in the mesosphere with Mars Express and ExoMars TGO observations, and the abundances of water-derived ions with NGIMS/MAVEN measurements.</p> <p>References:</p> <p>Chaffin, M. et al., Unexpected variability of Martian hydrogen escape, Geophysical Research Letters, Volume 41, pp. 314-320 (2014)</p> <p>Chaffin, M. et al., Elevated atmospheric escape of atomic hydrogen from Mars induced by high-altitude water, Nature Geoscience, 10, pp. 174-178 (2017)</p> <p>Fedorova, A. et al., Water vapor in the middle atmosphere of Mars during the 2007 global dust storm, Icarus, 300, pp. 440-457 (2018)</p> <p>Fedorova, A. et al., Stormy water on Mars: The distribution and saturation of atmospheric water during the dusty season, Science, 367, pp. 297-300 (2020)</p> <p>Fedorova, A. et al., Multi-Annual Monitoring of the Water Vapor Vertical Distribution on Mars by SPICAM on Mars Express, Journal of Geophysical Research: Planets, 126, e06616 (2021)</p> <p>Navarro, T. et al., Global climate modeling of the Martian water cycle with improved microphysics and radiatively active water ice clouds, Journal of Geophysical Research: Planets, 119, pp. 1479-1495 (2014)</p> <p>Rossi, L. et al., The Effect of the Martian 2018 Global Dust Storm on HDO as Predicted by a Mars Global Climate Model, Geophysical Research Letters, 48, e90962 (2021)</p> <p>Stone, S. et al., Hydrogen escape from Mars is driven by seasonal and dust storm transport of water,Science, 370, pp. 824-831 (2020)</p>


2015 ◽  
Vol 8 (12) ◽  
pp. 10539-10583 ◽  
Author(s):  
V. Eyring ◽  
S. Bony ◽  
G. A. Meehl ◽  
C. Senior ◽  
B. Stevens ◽  
...  

Abstract. By coordinating the design and distribution of global climate model simulations of the past, current and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima experiments) and the CMIP Historical Simulation (1850–near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP, (2) common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble, and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given climate variability, predictability and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.


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