scholarly journals The Impact of Air–Sea Interactions on the Predictability of the Tropical Intraseasonal Oscillation

2008 ◽  
Vol 21 (22) ◽  
pp. 5870-5886 ◽  
Author(s):  
Kathy Pegion ◽  
Ben P. Kirtman
Keyword(s):  
Zonal Wind ◽  
Climate Model ◽  
Intraseasonal Oscillation ◽  
Coupled Model ◽  
Longwave Radiation ◽  
Boreal Winter ◽  
Potential Predictability ◽  
Key Factor ◽  
The Impact ◽  
Tropical Intraseasonal Oscillation

Abstract This study investigates whether air–sea interactions contribute to differences in the predictability of the boreal winter tropical intraseasonal oscillation (TISO) using the NCEP operational climate model. A series of coupled and uncoupled, “perfect” model predictability experiments are performed for 10 strong model intraseasonal events. The uncoupled experiments are forced by prescribed SST containing different types of variability. These experiments are specifically designed to be directly comparable to actual forecasts. Predictability estimates are calculated using three metrics, including one that does not require the use of time filtering. The estimates are compared between these experiments to determine the impact of coupled air–sea interactions on the predictability of the tropical intraseasonal oscillation and the sensitivity of the potential predictability estimates to the different SST forcings. Results from all three metrics are surprisingly similar. They indicate that predictability estimates are longest for precipitation and outgoing longwave radiation (OLR) when the ensemble mean from the coupled model is used. Most importantly, the experiments that contain intraseasonally varying SST consistently predict the control events better than those that do not for precipitation, OLR, 200-hPa zonal wind, and 850-hPa zonal wind after the first 10 days. The uncoupled model is able to predict the TISO with similar skill to that of the coupled model, provided that an SST forecast that includes these intraseasonal variations is used to force the model. This indicates that the intraseasonally varying SSTs are a key factor for increased predictability and presumably better prediction of the TISO.

scholarly journals QBO Influence on MJO Amplitude over the Maritime Continent: Physical Mechanisms and Seasonality

2019 ◽  
Vol 147 (1) ◽  
pp. 389-406 ◽  
Author(s):  
Casey R. Densmore ◽  
Elizabeth R. Sanabia ◽  
Bradford S. Barrett
Keyword(s):  
Zonal Wind ◽  
Function Analysis ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Dominant Mode ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Maritime Continent ◽  
Quasi Biennial Oscillation ◽  
Convective Envelope

AbstractThe quasi-biennial oscillation (QBO) is stratified by stratospheric zonal wind direction and height into four phase pairs [easterly midstratospheric winds (QBOEM), easterly lower-stratospheric winds, westerly midstratospheric winds (QBOWM), and westerly lower-stratospheric winds] using an empirical orthogonal function analysis of daily stratospheric (100–10 hPa) zonal wind data during 1980–2017. Madden–Julian oscillation (MJO) events in which the MJO convective envelope moved eastward across the Maritime Continent (MC) during 1980–2017 are identified using the Real-time Multivariate MJO (RMM) index and the outgoing longwave radiation (OLR) MJO index (OMI). Comparison of RMM amplitudes by the QBO phase pair over the MC (RMM phases 4 and 5) reveals that boreal winter MJO events have the strongest amplitudes during QBOEM and the weakest amplitudes during QBOWM, which is consistent with QBO-driven differences in upper-tropospheric lower-stratospheric (UTLS) static stability. Additionally, boreal winter RMM events over the MC strengthen during QBOEM and weaken during QBOWM. In the OMI, those amplitude changes generally shift eastward to the eastern MC and western Pacific Ocean, which may result from differences in RMM and OMI index methodologies. During boreal summer, as the northeastward-propagating boreal summer intraseasonal oscillation (BSISO) becomes the dominant mode of intraseasonal variability, these relationships are reversed. Zonal differences in UTLS stability anomalies are consistent with amplitude changes of eastward-propagating MJO events across the MC during boreal winter, and meridional stability differences are consistent with amplitude changes of northeastward-propagating BSISO events during boreal summer. Results remain consistent when stratifying by neutral ENSO phase.

scholarly journals Estimate of the Predictability of Boreal Summer and Winter Intraseasonal Oscillations from Observations

2011 ◽  
Vol 139 (8) ◽  
pp. 2421-2438 ◽  
Author(s):  
Ruiqiang Ding ◽  
Jianping Li ◽  
Kyong-Hwan Seo
Keyword(s):  
Spatial Distribution ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Potential Predictability ◽  
The North ◽  
Intraseasonal Oscillations ◽  
The North Pacific

AbstractTropical intraseasonal variability (TISV) shows two dominant modes: the boreal winter Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). The two modes differ in intensity, frequency, and movement, thereby presumably indicating different predictabilities. This paper investigates differences in the predictability limits of the BSISO and the boreal winter MJO based on observational data. The results show that the potential predictability limit of the BSISO obtained from bandpass-filtered (30–80 days) outgoing longwave radiation (OLR), 850-hPa winds, and 200-hPa velocity potential is close to 5 weeks, comparable to that of the boreal winter MJO. Despite the similarity between the potential predictability limits of the BSISO and MJO, the spatial distribution of the potential predictability limit of the TISV during summer is very different from that during winter. During summer, the limit is relatively low over regions where the TISV is most active, whereas it is relatively high over the North Pacific, North Atlantic, southern Africa, and South America. The spatial distribution of the limit during winter is approximately the opposite of that during summer. For strong phases of ISO convection, the initial error of the BSISO shows a more rapid growth than that of the MJO. The error growth is rapid when the BSISO and MJO enter the decaying phase (when ISO signals are weak), whereas it is slow when convection anomalies of the BSISO and MJO are located in upstream regions (when ISO signals are strong).

Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

2013 ◽  
Vol 26 (1) ◽  
pp. 231-245 ◽  
Author(s):  
Michael Winton ◽  
Alistair Adcroft ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
Larry W. Horowitz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
Historical Simulation ◽  
Model Version ◽  
Salinity Response ◽  
The Impact

Abstract The influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities is examined by comparing three GFDL climate models used for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The base model ESM2M is closely related to GFDL’s CMIP3 climate model version 2.1 (CM2.1), and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. The authors compare the impact of this “ocean swap” with an “atmosphere swap” that produces the GFDL Climate Model version 3 (CM3) by replacing the AM2 atmospheric component with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multidecadal response time scale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high-latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early twentieth century and an associated cooling, which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

scholarly journals Randomly correcting model errors in the ARPEGE-Climate v6.1 component of CNRM-CM: applications for seasonal forecasts

2016 ◽  
Vol 9 (6) ◽  
pp. 2055-2076 ◽  
Author(s):  
Lauriane Batté ◽  
Michel Déqué
Keyword(s):  
Stochastic Dynamics ◽  
Stochastic Perturbation ◽  
Coupled Model ◽  
Seasonal Forecasting ◽  
Stochastic Methods ◽  
Boreal Winter ◽  
Model Errors ◽  
Seasonal Forecasts ◽  
Error Statistics ◽  
The Impact

Abstract. Stochastic methods are increasingly used in global coupled model climate forecasting systems to account for model uncertainties. In this paper, we describe in more detail the stochastic dynamics technique introduced by Batté and Déqué (2012) in the ARPEGE-Climate atmospheric model. We present new results with an updated version of CNRM-CM using ARPEGE-Climate v6.1, and show that the technique can be used both as a means of analyzing model error statistics and accounting for model inadequacies in a seasonal forecasting framework.The perturbations are designed as corrections of model drift errors estimated from a preliminary weakly nudged re-forecast run over an extended reference period of 34 boreal winter seasons. A detailed statistical analysis of these corrections is provided, and shows that they are mainly made of intra-month variance, thereby justifying their use as in-run perturbations of the model in seasonal forecasts. However, the interannual and systematic error correction terms cannot be neglected. Time correlation of the errors is limited, but some consistency is found between the errors of up to 3 consecutive days.These findings encourage us to test several settings of the random draws of perturbations in seasonal forecast mode. Perturbations are drawn randomly but consistently for all three prognostic variables perturbed. We explore the impact of using monthly mean perturbations throughout a given forecast month in a first ensemble re-forecast (SMM, for stochastic monthly means), and test the use of 5-day sequences of perturbations in a second ensemble re-forecast (S5D, for stochastic 5-day sequences). Both experiments are compared in the light of a REF reference ensemble with initial perturbations only. Results in terms of forecast quality are contrasted depending on the region and variable of interest, but very few areas exhibit a clear degradation of forecasting skill with the introduction of stochastic dynamics. We highlight some positive impacts of the method, mainly on Northern Hemisphere extra-tropics. The 500 hPa geopotential height bias is reduced, and improvements project onto the representation of North Atlantic weather regimes. A modest impact on ensemble spread is found over most regions, which suggests that this method could be complemented by other stochastic perturbation techniques in seasonal forecasting mode.

scholarly journals A Precipitation-Based Index for Tropical Intraseasonal Oscillations

2020 ◽  
Vol 33 (3) ◽  
pp. 805-823 ◽  
Author(s):  
Shuguang Wang
Keyword(s):  
Real Time ◽  
Decadal Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Eof Analysis ◽  
Intraseasonal Oscillations ◽  
Precipitation Anomalies ◽  
Tropical Intraseasonal Oscillations

AbstractCharacteristic patterns of precipitation-associated tropical intraseasonal oscillations, including the Madden–Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO), are identified using local empirical orthogonal function (EOF) analysis of the Tropical Rainfall Measuring Mission (TRMM) precipitation data as a function of the day of the year. The explained variances of the EOF analysis show two peaks across the year: one in the middle of the boreal winter corresponding to the MJO and the other in the middle of summer corresponding to the BSISO. Comparing the fractional variance indicates that the BSISO is more coherent than the MJO during the TRMM period. Similar EOF analyses with the outgoing longwave radiation (OLR) confirm this result and indicate that the BSISO is less coherent before the TRMM era (1979–98). In contrast, the MJO exhibits much less decadal variability. A precipitation-based index for tropical intraseasonal oscillation (PII) is derived by projecting bandpass-filtered precipitation anomalies to the two leading EOFs as a function of day of the year. A real-time version that approximates the PII is further developed using precipitation anomalies without any bandpass filtering. It is further shown that this real-time PII index may be used to diagnose precipitation in the subseasonal forecasts.

scholarly journals The Effect of a Well-Resolved Stratosphere on Surface Climate: Differences between CMIP5 Simulations with High and Low Top Versions of the Met Office Climate Model

2012 ◽  
Vol 25 (20) ◽  
pp. 7083-7099 ◽  
Author(s):  
S. C. Hardiman ◽  
N. Butchart ◽  
T. J. Hinton ◽  
S. M. Osprey ◽  
L. J. Gray
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Circulation Model ◽  
Climate Simulation ◽  
Reanalysis Dataset ◽  
Quasi Biennial Oscillation ◽  
Surface Climate ◽  
The Impact

Abstract The importance of using a general circulation model that includes a well-resolved stratosphere for climate simulations, and particularly the influence this has on surface climate, is investigated. High top model simulations are run with the Met Office Unified Model for the Coupled Model Intercomparison Project Phase 5 (CMIP5). These simulations are compared to equivalent simulations run using a low top model differing only in vertical extent and vertical resolution above 15 km. The period 1960–2002 is analyzed and compared to observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset. Long-term climatology, variability, and trends in surface temperature and sea ice, along with the variability of the annular mode index, are found to be insensitive to the addition of a well-resolved stratosphere. The inclusion of a well-resolved stratosphere, however, does improve the impact of atmospheric teleconnections on surface climate, in particular the response to El Niño–Southern Oscillation, the quasi-biennial oscillation, and midwinter stratospheric sudden warmings (i.e., zonal mean wind reversals in the middle stratosphere). Thus, including a well-represented stratosphere could improve climate simulation on intraseasonal to interannual time scales.

scholarly journals The Impact of Air–Sea Interactions on the Simulation of Tropical Intraseasonal Variability

2008 ◽  
Vol 21 (24) ◽  
pp. 6616-6635 ◽  
Author(s):  
Kathy Pegion ◽  
Ben P. Kirtman
Keyword(s):  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Coupled Model ◽  
Coupled Simulation ◽  
Maritime Continent ◽  
Forecast System ◽  
Climate Forecast System ◽  
Environmental Prediction ◽  
The Impact ◽  
The Western Pacific

Abstract The impact of coupled air–sea feedbacks on the simulation of tropical intraseasonal variability is investigated in this study using the National Centers for Environmental Prediction Climate Forecast System. The simulation of tropical intraseasonal variability in a freely coupled simulation is compared with two simulations of the atmospheric component of the model. In one experiment, the uncoupled model is forced with the daily sea surface temperature (SST) from the coupled run. In the other, the uncoupled model is forced with climatological SST from the coupled run. Results indicate that the overall intraseasonal variability of precipitation is reduced in the coupled simulation compared to the uncoupled simulation forced by daily SST. Additionally, air–sea coupling is responsible for differences in the simulation of the tropical intraseasonal oscillation between the coupled and uncoupled models, specifically in terms of organization and propagation in the western Pacific. The differences between the coupled and uncoupled simulations are due to the fact that the relationships between precipitation and SST and latent heat flux and SST are much stronger in the coupled model than in the uncoupled model. Additionally, these relationships are delayed by about 5 days in the uncoupled model compared to the coupled model. As demonstrated by the uncoupled simulation forced with climatological SST, some of the intraseasonal oscillation can be simulated by internal atmospheric dynamics. However, the intraseasonally varying SST appears to be important to the amplitude and propagation of the oscillation beyond the Maritime Continent.

Investigation of the Surface and Circulation Impacts of Cloud-Brightening Geoengineering

2012 ◽  
Vol 25 (21) ◽  
pp. 7527-7543 ◽  
Author(s):  
E. Baughman ◽  
A. Gnanadesikan ◽  
A. Degaetano ◽  
A. Adcroft
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Cloud Condensation Nuclei ◽  
Vertical Wind Shear ◽  
Coupled Model ◽  
Walker Circulation ◽  
Cloud Albedo ◽  
Potential Index ◽  
Marine Stratus ◽  
The Impact

Projected increases in greenhouse gases have prompted serious discussion on geoengineering the climate system to counteract global climate change. Cloud albedo enhancement has been proposed as a feasible geoengineering approach, but previous research suggests undesirable consequences of globally uniform cloud brightening. The present study uses GFDL’s Climate Model version 2G (CM2G) global coupled model to simulate cloud albedo enhancement via increases in cloud condensation nuclei (CCN) to 1000 cm−3 targeted at the marine stratus deck of the Pacific Ocean, where persistent low clouds suggest a regional approach to cloud brightening. The impact of this regional geoengineering on global circulation and climate in the presence of a 1% annual increase of CO2 was investigated. Surface temperatures returned to near preindustrial levels over much of the globe with cloud modifications in place. In the first 40 years and over the 140-yr mean, significant cooling over the equatorial Pacific, continued Arctic warming, large precipitation changes over the western Pacific, and a westward compression and intensification of the Walker circulation were observed in response to cloud brightening. The cloud brightening caused a persistent La Niña condition associated with an increase in hurricane maximum potential intensity and genesis potential index, and decreased vertical wind shear between July and November in the tropical Atlantic, South China Sea, and to the east of Japan. Responses were similar with CCN = 500 cm−3.

scholarly journals Ocean–Atmosphere Coupling in the Monsoon Intraseasonal Oscillation: A Simple Model Study

2008 ◽  
Vol 21 (20) ◽  
pp. 5254-5270 ◽  
Author(s):  
Gilles Bellon ◽  
Adam H. Sobel ◽  
Jerome Vialard
Keyword(s):  
Mixed Layer ◽  
Bay Of Bengal ◽  
Mixed Layer Depth ◽  
Intraseasonal Oscillation ◽  
Thermal Inertia ◽  
Coupled Model ◽  
Boreal Winter ◽  
Quasi Equilibrium ◽  
Layer Depth ◽  
Ocean Atmosphere

Abstract A simple coupled model is used in a zonally symmetric aquaplanet configuration to investigate the effect of ocean–atmosphere coupling on the Asian monsoon intraseasonal oscillation. The model consists of a linear atmospheric model of intermediate complexity based on quasi-equilibrium theory coupled to a simple, linear model of the upper ocean. This model has one unstable eigenmode with a period in the 30–60-day range and a structure similar to the observed northward-propagating intraseasonal oscillation in the Bay of Bengal/west Pacific sector. The ocean–atmosphere coupling is shown to have little impact on either the growth rate or latitudinal structure of the atmospheric oscillation, but it reduces the oscillation’s period by a quarter. At latitudes corresponding to the north of the Indian Ocean, the sea surface temperature (SST) anomalies lead the precipitation anomalies by a quarter of a period, similarly to what has been observed in the Bay of Bengal. The mixed layer depth is in phase opposition to the SST: a monsoon break corresponds to both a warming and a shoaling of the mixed layer. This behavior results from the similarity between the patterns of the predominant processes: wind-induced surface heat flux and wind stirring. The instability of the seasonal monsoon flow is sensitive to the seasonal mixed layer depth: the oscillation is damped when the oceanic mixed layer is thin (about 10 m deep or thinner), as in previous experiments with several models aimed at addressing the boreal winter Madden–Julian oscillation. This suggests that the weak thermal inertia of land might explain the minima of intraseasonal variance observed over the Asian continent.

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