scholarly journals Variance of the Equatorial Atmospheric Circulations in the Reanalysis

2021 ◽  
Vol 9 (12) ◽  
pp. 1386
Author(s):  
Emmanuel OlaOluwa Eresanya ◽  
Yuping Guan

The structure of the equatorial atmospheric circulation, as defined by the zonal mass streamfunction (ZMS), computed using the new fifth-generation ECMWF reanalysis for the global climate and weather (ERA-5) and the National Centers for Environmental Prediction NCEP–US Department of Energy reanalysis (NCEP-2) reanalysis products, is investigated and compared with Coupled Model Intercomparison Project Phase 6 (CMIP 6) ensemble mean. The equatorial atmospheric circulations majorly involve three components: the Indian Ocean cell (IOC), the Pacific Walker cell (POC) and the Atlantic Ocean cell (AOC). The IOC, POC and AOC average monthly or seasonal cycle peaks around March, June and February, respectively. ERA-5 has a higher IOC intensity from February to August, whereas NCEP-2 has a greater IOC intensity from September to December; NCEP-2 indicates greater POC intensity from January to May, whereas ERA-5 shows higher POC intensity from June to October. For the AOC, ERA-5 specifies greater intensity from March to August and NCEP-2 has a higher intensity from September to December. The equatorial atmospheric circulations cells vary in the reanalysis products, the IOC is weak and wider (weaker and smaller) in the ERA-5 (NCEP-2), the POC is more robust and wider (feebler and teensier) in NCEP-2 (ERA-5) and the AOC is weaker and wider (stronger and smaller) in ERA-5 (NCEP-2). ERA-5 revealed a farther westward POC and AOC compared to NCEP-2. In the CMIP 6 model ensemble mean (MME), the equatorial atmospheric circulations mean state indicated generally weaker cells, with the IOC smaller and the POC greater swinging eastward and westward, respectively, while the AOC is more westward. These changes in equatorial circulation correspond to changes in dynamically related heating in the tropics.

2012 ◽  
Vol 25 (15) ◽  
pp. 5416-5431 ◽  
Author(s):  
Masahiro Watanabe ◽  
Hideo Shiogama ◽  
Tokuta Yokohata ◽  
Youichi Kamae ◽  
Masakazu Yoshimori ◽  
...  

Abstract This study proposes a systematic approach to investigate cloud-radiative feedbacks to climate change induced by an increase of CO2 concentrations in global climate models (GCMs). Based on two versions of the Model for Interdisciplinary Research on Climate (MIROC), which have opposite signs for cloud–shortwave feedback (ΔSWcld) and hence different equilibrium climate sensitivities (ECSs), hybrid models are constructed by replacing one or more parameterization schemes for cumulus convection, cloud, and turbulence between them. An ensemble of climate change simulations using a suite of eight models, called a multiphysics ensemble (MPE), is generated. The MPE provides a range of ECS as wide as the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble and reveals a different magnitude and sign of ΔSWcld over the tropics, which is crucial for determining ECS. It is found that no single process controls ΔSWcld, but that the coupling of two processes does. Namely, changing the cloud and turbulence schemes greatly alters the mean and the response of low clouds, whereas replacing the convection and cloud schemes affects low and middle clouds over the convective region. For each of the circulation regimes, ΔSWcld and cloud changes in the MPE have a nonlinear, but systematic, relationship with the mean cloud amount, which can be constrained from satellite estimates. The analysis suggests a positive feedback over the subsidence regime and a near-neutral or weak negative ΔSWcld over the convective regime in these model configurations, which, however, may not be carried into other models.


2010 ◽  
Vol 138 (12) ◽  
pp. 4542-4560 ◽  
Author(s):  
John E. Janowiak ◽  
Peter Bauer ◽  
Wanqiu Wang ◽  
Phillip A. Arkin ◽  
Jon Gottschalck

Abstract In this paper, the results of an examination of precipitation forecasts for 1–30-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) during November 2007–February 2008 are presented. The performance of the model precipitation forecasts are examined in global and regional contexts, and results of a case study of precipitation variations that are associated with a moderate to strong Madden–Julian oscillation (MJO) event are presented. The precipitation forecasts from the ECMWF and NCEP operational prediction models have nearly identical temporal correlation with observed precipitation at forecast leads from 2 to 9 days over the Northern Hemisphere during the cool season, despite the higher resolution of the ECMWF operational model, while the ECMWF operational model forecasts are slightly better in the tropics and the Southern Hemisphere during the warm season. The ECMWF Re-Analysis Interim (ERA-Interim) precipitation forecasts perform only slightly worse than the NCEP operational model, while NCEP’s Climate Forecast System low-resolution coupled model forecasts perform the worst among the four models. In terms of bias, the ECMWF operational model performs the best among the four model forecasts that were examined, particularly with respect to the ITCZ regions in both the Atlantic and Pacific. Local temporal correlations that were computed on daily precipitation totals for day-2 forecasts against observations indicate that the operational models at ECMWF and NCEP perform the best during the 4-month study period, and that all of the models have low to insignificant correlations over land and over much of the tropics. They perform the best in subtropical and extratropical oceanic regions. Also presented are results that show that striking improvements have been made over the past two decades in the ability of the models to represent precipitation variations that are associated with MJO. The model precipitation forecasts exhibit the ability to characterize the evolution of precipitation variations during a moderate–strong period of MJO conditions for forecast leads as long as 10 days.


2016 ◽  
Author(s):  
Stephen M. Griffies ◽  
Gokhan Danabasoglu ◽  
Paul J. Durack ◽  
Alistair J. Adcroft ◽  
V. Balaji ◽  
...  

Abstract. The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses these aims in two complementary manners: (A) by providing an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing, (B) by providing a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) offering details for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows that of the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II have become the standard method to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP (Scenario MIP), as well as the ocean-sea ice OMIP simulations. The bulk of this paper offers scientific rationale for saving these diagnostics.


2005 ◽  
Vol 22 (9) ◽  
pp. 1353-1372 ◽  
Author(s):  
Sarah T. Gille

Abstract Four years of ocean vector wind data are used to evaluate statistics of wind stress over the ocean. Raw swath wind stresses derived from the Quick Scatterometer (QuikSCAT) are compared with five different global gridded wind products, including products based on scatterometer observations, meteorological analysis winds from the European Centre for Medium-Range Weather Forecasts, and reanalysis winds from the National Centers for Environmental Prediction. Buoy winds from a limited number of sites in the Pacific Ocean are also considered. Probability density functions (PDFs) computed for latitudinal bands show that mean wind stresses for the six global products are largely in agreement, while variances differ substantially, by a factor of 2 or more, with swath wind stresses indicating highest variances for meridional winds and for zonal winds outside the Tropics. Higher moments of the PDFs also differ. Kurtoses are large for all wind products, implying that PDFs are not Gaussian. None of the available gridded products fully captures the range of extreme wind events seen in the raw swath data. Frequency spectra for the five gridded products agree with frequency spectra from swath data at low frequencies, but spectral slopes differ at higher frequencies, particularly for frequencies greater than 100 cycles per year (cpy), which are poorly resolved by a single scatterometer. In the frequency range between 10 and 90 cpy that is resolved by the scatterometer, spectra derived from swath data are flatter than spectra from gridded products and are judged to be flatter than ω−2/3 at all latitudes.


2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.


2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Suchada Kamworapan ◽  
Chinnawat Surussavadee

This study evaluates the performances of all forty different global climate models (GCMs) that participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for simulating climatological temperature and precipitation for Southeast Asia. Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. The results show that the performances of different GCMs vary greatly. CNRM-CM5-2 performs best among the 40 GCMs, where its total error is 3.25 times less than that of GCM performing worst. The performance of CNRM-CM5-2 is compared with those of the ensemble average of all 40 GCMs (40-GCM-Ensemble) and the ensemble average of the 6 best GCMs (6-GCM-Ensemble) for four categories, i.e., temperature only, precipitation only, land only, and sea only. While 40-GCM-Ensemble performs best for temperature, 6-GCM-Ensemble performs best for precipitation. 6-GCM-Ensemble performs best for temperature and precipitation simulations over sea, whereas CNRM-CM5-2 performs best over land. Overall results show that 6-GCM-Ensemble performs best and is followed by CNRM-CM5-2 and 40-GCM-Ensemble, respectively. The total errors of 6-GCM-Ensemble, CNRM-CM5-2, and 40-GCM-Ensemble are 11.84, 13.69, and 14.09, respectively. 6-GCM-Ensemble and CNRM-CM5-2 agree well with observations and can provide useful climate simulations for Southeast Asia. This suggests the use of 6-GCM-Ensemble and CNRM-CM5-2 for climate studies and projections for Southeast Asia.


2013 ◽  
Vol 6 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
J. Xu ◽  
L. Zhao ◽  

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (radiosonde, reanalysis, CMIP3 and CMIP5), although similarities can be observed. Compared to the CMIP3 model simulations, the simulations in some of the CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.


2020 ◽  
Author(s):  
Baijun Tian

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>


2014 ◽  
Vol 32 (7) ◽  
pp. 793-807 ◽  
Author(s):  
M. Calisto ◽  
D. Folini ◽  
M. Wild ◽  
L. Bengtsson

Abstract. In this paper, radiative fluxes for 10 years from 11 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and from CERES satellite observations have been analyzed and compared. Under present-day conditions, the majority of the investigated CMIP5 models show a tendency towards a too-negative global mean net cloud radiative forcing (NetCRF) as compared to CERES. A separate inspection of the long-wave and shortwave contribution (LWCRF and SWCRF) as well as cloud cover points to different shortcomings in different models. Models with a similar NetCRF still differ in their SWCRF and LWCRF and/or cloud cover. Zonal means mostly show excessive SWCRF (too much cooling) in the tropics between 20° S and 20° N and in the midlatitudes between 40 to 60° S. Most of the models show a too-small/too-weak LWCRF (too little warming) in the subtropics (20 to 40° S and N). Difference maps between CERES and the models identify the tropical Pacific Ocean as an area of major discrepancies in both SWCRF and LWCRF. The summer hemisphere is found to pose a bigger challenge for the SWCRF than the winter hemisphere. The results suggest error compensation to occur between LWCRF and SWCRF, but also when taking zonal and/or annual means. Uncertainties in the cloud radiative forcing are thus still present in current models used in CMIP5.


2022 ◽  
Author(s):  
Mohammad Naser Sediqi ◽  
Vempi Satriya Adi Hendrawan ◽  
Daisuke Komori

Abstract The global climate models (GCMs) of Coupled Model Intercomparison Project phase 6 (CMIP6) were used spatiotemporal projections of precipitation and temperature over Afghanistan for three shared socioeconomic pathways (SSP1-2.6, 2-4.5 and 5-8.5) and two future time horizons, early (2020-2059) and late (2060-2099). The Compromise Programming (CP) approach was employed to order the GCMs based on their skill to replicate precipitation and temperature climatology for the reference period (1975-2014). Three models, namely ACCESS-CM2, MPI-ESM1-2-LR, and FIO-ESM-2-0, showed the highest skill in simulating all three variables, and therefore, were chosen for the future projections. The ensemble mean of the GCMs showed an increase in maximum temperature by 1.5-2.5oC, 2.7-4.3 oC, and 4.5-5.3 oC and minimum temperature by 1.3-1.8 oC, 2.2-3.5 oC, and 4.6-5.2 oC for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively in the later period. Meanwhile, the changes in precipitation in the range of -15-18%, -36-47% and -40-68% for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The temperature and precipitation were projected to increase in the highlands and decrease over the deserts, indicating dry regions would be drier and wet regions wetter.


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