scholarly journals Feedback of mesoscale ocean currents on atmospheric winds in high-resolution coupled models and implications for the forcing of ocean-only models

2017 ◽  
Author(s):  
Rafael Abel ◽  
Claus W. Böning ◽  
Richard J. Greatbatch ◽  
Helene T. Hewitt ◽  
Malcolm J. Roberts
Keyword(s):  
Climate Model ◽  
Global Climate Model ◽  
Surface Wind ◽  
Ocean Currents ◽  
Global Ocean ◽  
Ocean Current ◽  
Western Boundary ◽  
Coupling Coefficients ◽  
Coupled Models ◽  
Near Surface

Abstract. The repercussions of surface ocean currents for the near-surface wind and the air-sea momentum flux are investigated in two versions of a global climate model with eddying ocean. The focus is on the effect of mesoscale ocean current features at scales of less than 150 km, by considering high-pass filtered, monthly-mean model output fields. We find a clear signature of a mesoscale oceanic imprint in the wind fields over the energetic areas of the oceans, particularly along the extensions of the western boundary currents and the Antarctic Circumpolar Current. These areas are characterized by a positive correlation between mesoscale perturbations in the curl of the surface currents and the wind curl. The coupling coefficients are spatially non-uniform and show a pronounced seasonal cycle. The positive feedback of mesoscale current features on the near-surface wind acts in opposition to their damping effect on the wind stress. A tentative incorporation of this feedback in the surface stress formulation of an eddy-permitting global ocean-only model leads to a gain in the kinetic energy of up to 10 %, suggesting a fundamental shortcoming of present ocean model configurations.

scholarly journals Downscaling the climate change for oceans around Australia

2012 ◽  
Vol 5 (1) ◽  
pp. 425-458 ◽  
Author(s):  
M. A. Chamberlain ◽  
C. Sun ◽  
R. J. Matear ◽  
M. Feng ◽  
S. J. Phipps
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Ocean Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
Coupled Models

Abstract. At present, global climate models used to project changes in climate do not resolve mesoscale ocean features such as boundary currents and eddies. These missing features may be important to realistically project the marine impacts of climate change. Here we present a framework for dynamically downscaling coarse climate change projections utilising a global ocean model that resolves these features in the Australian region. The downscaling model used here is ocean-only. The ocean feedback on the air-sea fluxes is explored by restoring to surface temperature and salinity, as well as a calculated feedback to wind stress. These feedback approximations do not replace the need for fully coupled models, but they allow us to assess the sensitivity of the ocean in downscaled climate change simulations. Significant differences are found in sea surface temperature, salinity, stratification and transport between the downscaled projections and those of the climate model. While the magnitude of the climate change differences may vary with the feedback parameterisation used, the patterns of the climate change differences are consistent and develop rapidly indicating they are mostly independent of feedback that ocean differences may have on the air-sea fluxes. Until such a time when it is feasible to regularly run a global climate model with eddy resolution, our framework for ocean climate change downscaling provides an attractive way to explore how climate change may affect the mesoscale ocean environment.

scholarly journals A bias-corrected CMIP5 dataset for Africa using the CDF-t method – a contribution to agricultural impact studies

2018 ◽  
Vol 9 (1) ◽  
pp. 313-338 ◽  
Author(s):  
Adjoua Moise Famien ◽  
Serge Janicot ◽  
Abe Delfin Ochou ◽  
Mathieu Vrac ◽  
Dimitri Defrance ◽  
...  
Keyword(s):  
West Africa ◽  
Air Temperature ◽  
Climate Model ◽  
Global Climate Model ◽  
Cumulative Distribution ◽  
Shortwave Radiation ◽  
Climate Change Scenarios ◽  
Reference Dataset ◽  
Near Surface ◽  
The Impact

Abstract. The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950–2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

scholarly journals Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
East China ◽  
Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

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 Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 831-852 ◽  
Author(s):  
Maria Belmonte Rivas ◽  
Ad Stoffelen
Keyword(s):  
Large Scale ◽  
Surface Wind ◽  
Atmospheric Stability ◽  
Ocean Current ◽  
Western Boundary ◽  
Boundary Current ◽  
Wind Stress Curl ◽  
Meridional Winds ◽  
Mesoscale Convective ◽  
Transient Wind

Abstract. This paper analyzes the differences between ERA-Interim and ERA5 surface winds fields relative to Advanced Scatterometer (ASCAT) ocean vector wind observations, after adjustment for the effects of atmospheric stability and density, using stress-equivalent winds (U10S) and air–sea relative motion using ocean current velocities. In terms of instantaneous root mean square (rms) wind speed agreement, ERA5 winds show a 20 % improvement relative to ERA-Interim and a performance similar to that of currently operational ECMWF forecasts. ERA5 also performs better than ERA-Interim in terms of mean and transient wind errors, wind divergence and wind stress curl biases. Yet, both ERA products show systematic errors in the partition of the wind kinetic energy into zonal and meridional, mean and transient components. ERA winds are characterized by excessive mean zonal winds (westerlies) with too-weak mean poleward flows in the midlatitudes and too-weak mean meridional winds (trades) in the tropics. ERA stress curl is too cyclonic in midlatitudes and high latitudes, with implications for Ekman upwelling estimates, and lacks detail in the representation of sea surface temperature (SST) gradient effects (along the equatorial cold tongues and Western Boundary Current (WBC) jets) and mesoscale convective airflows (along the Intertropical Convergence Zone and the warm flanks for the WBC jets). It is conjectured that large-scale mean wind biases in ERA are related to their lack of high-frequency (transient wind) variability, which should be promoting residual meridional circulations in the Ferrel and Hadley cells.

scholarly journals ENSO Predictability of a Fully Coupled GCM Model Using Singular Vector Analysis

2006 ◽  
Vol 19 (14) ◽  
pp. 3361-3377 ◽  
Author(s):  
Youmin Tang ◽  
Richard Kleeman ◽  
Sonya Miller
Keyword(s):  
Singular Vector ◽  
Climate Model ◽  
Global Climate Model ◽  
Heat Content ◽  
Enso Cycle ◽  
Coupled Models ◽  
Error Norm ◽  
Singular Vectors ◽  
Enso Predictability ◽  
Fully Coupled

Abstract Using a recently developed method of computing climatically relevant singular vectors (SVs), the error growth properties of ENSO in a fully coupled global climate model are investigated. In particular, the authors examine in detail how singular vectors are influenced by the phase of ENSO cycle—the physical variable under consideration as well as the error norm deployed. Previous work using SVs for studying ENSO predictability has been limited to intermediate or hybrid coupled models. The results show that the singular vectors share many of the properties already seen in simpler models. Thus, for example, the singular vector spectrum is dominated by one fastest growing member, regardless of the phase of ENSO cycle and the variable of perturbation or the error norm; in addition the growth rates of the singular vectors are very sensitive to the phase of the ENSO cycle, the variable of perturbation, and the error norm. This particular CGCM also displays some differences from simpler models; thus subsurface temperature optimal patterns are strongly sensitive to the phase of ENSO cycle, and at times an east–west dipole in the eastern tropical Pacific basin is seen. This optimal pattern also appears for SST when the error norm is defined using Niño-4. Simpler models consistently display a single-sign equatorial signature in the subsurface corresponding perhaps to the Wyrtki buildup of heat content before a warm event. Some deficiencies in the CGCM and their possible influences on SV growth are also discussed.

Relating Satellite-Observed Cloud Properties from MODIS to Meteorological Conditions for Marine Boundary Layer Clouds

2010 ◽  
Vol 23 (6) ◽  
pp. 1374-1391 ◽  
Author(s):  
Guang J. Zhang ◽  
Andrew M. Vogelmann ◽  
Michael P. Jensen ◽  
William D. Collins ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
Meteorological Parameters ◽  
Marine Boundary Layer ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Liquid Water Path ◽  
Near Surface ◽  
Cloud Properties ◽  
Lower Tropospheric Stability

Abstract This study examines 6 yr of cloud properties observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra satellite in five prominent marine boundary layer (MBL) cloud regions (California, Peru, Canary, Angola, and Australia) and investigates their relationships with near-surface meteorological parameters obtained from NCEP reanalyses. About 62 000 independent scenes are used to examine the instantaneous relationships between cloud properties and meteorological parameters that may be used for global climate model (GCM) diagnostics and parameterization. Cloud liquid water path (LWP) generally increases with lower-tropospheric stability (LTS) and lifting condensation level (LCL), whereas cloud drizzle frequency is favored by weak LTS and negligible cold air advection. Cloud fraction (CF) depends strongly on variations in LTS, and to a lesser extent on surface air temperature advection and LCL, although the relationships vary from region to region. The authors propose capturing the effects of these three parameters on CF via their linear combination in terms of a single parameter, the effective lower-tropospheric stability (eLTS). Results indicate that eLTS offers a marked improvement over LTS alone in explaining the median CF variations within the different study regions. A parameterization of CF in terms of eLTS is provided, which produces results that are improved over those of Klein and Hartmann’s LTS-only parameterization. However, the new parameterization may not predict the observed variability correctly, and the authors propose a method that might address this shortcoming via a statistical approach.

scholarly journals Mean Dynamic Topography of the Ocean Derived from Satellite and Drifting Buoy Data Using Three Different Techniques*

2009 ◽  
Vol 26 (9) ◽  
pp. 1910-1919 ◽  
Author(s):  
Nikolai Maximenko ◽  
Peter Niiler ◽  
Luca Centurioni ◽  
Marie-Helene Rio ◽  
Oleg Melnichenko ◽  
...  
Keyword(s):  
Ocean Surface ◽  
Horizontal Resolution ◽  
Global Ocean ◽  
Momentum Balance ◽  
Small Scale ◽  
Western Boundary ◽  
Dynamic Topography ◽  
Geoid Model ◽  
Near Surface ◽  
Mean Dynamic Topography

Abstract Presented here are three mean dynamic topography maps derived with different methodologies. The first method combines sea level observed by the high-accuracy satellite radar altimetry with the geoid model of the Gravity Recovery and Climate Experiment (GRACE), which has recently measured the earth’s gravity with unprecedented spatial resolution and accuracy. The second one synthesizes near-surface velocities from a network of ocean drifters, hydrographic profiles, and ocean winds sorted according to the horizontal scales. In the third method, these global datasets are used in the context of the ocean surface momentum balance. The second and third methods are used to improve accuracy of the dynamic topography on fine space scales poorly resolved in the first method. When they are used to compute a multiyear time-mean global ocean surface circulation on a 0.5° horizontal resolution, both contain very similar, new small-scale midocean current patterns. In particular, extensions of western boundary currents appear narrow and strong despite temporal variability and exhibit persistent meanders and multiple branching. Also, the locations of the velocity concentrations in the Antarctic Circumpolar Current become well defined. Ageostrophic velocities reveal convergent zones in each subtropical basin. These maps present a new context in which to view the continued ocean monitoring with in situ instruments and satellites.

scholarly journals Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations

2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
System Model ◽  
Low Resolution ◽  
Coupled Models ◽  
Climate System Model ◽  
Model Version ◽  
Coupled Global Climate Model

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.

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