Sensitivity of MJO Simulation and Predictability to Sea Surface Temperature Variability

2008 ◽  
Vol 21 (20) ◽  
pp. 5304-5317 ◽  
Author(s):  
Hye-Mi Kim ◽  
Carlos D. Hoyos ◽  
Peter J. Webster ◽  
In-Sik Kang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Phase Relationship ◽  
Circulation Model ◽  
Forecast Skill ◽  
Sea Surface ◽  
Coupled Processes ◽  
Forecast Lead Time ◽  
Ocean Atmosphere

Abstract The influence of sea surface temperature (SST) on the simulation and predictability of the Madden–Julian oscillation (MJO) is examined using the Seoul National University atmospheric general circulation model (SNU AGCM). Forecast skill was examined using serial climate simulations spanning eight different winter seasons with 30-day forecasts commencing every 5 days, giving a total of 184 thirty-day simulations. The serial runs were repeated using prescribing observed SST with monthly, weekly, and daily temporal resolutions. The mean SST was the same for all cases so that differences between experiments result from the different temporal resolutions of the SST boundary forcing. It is shown that high temporal SST frequency acts to improve 1) the MJO activity of 200-hPa velocity potential field over the entire Asian monsoon region at all lead times; 2) the percentage of filtered variance of the two leading EOF modes that explain the eastward propagation of MJO; 3) the power of the wavenumber 1 eastward propagating mode; and 4) the forecast skill of MJO, maintaining it for longer periods. However, the MJO phase relationship between MJO convection and SST, as is often the case with many atmosphere-only models, although well simulated at the beginning of forecast period becomes distorted rapidly as the forecast lead time increases, even with the daily SST forcing case. Comparison of AGCM simulations with coupled GCM (CGCM) integrations shows that ocean–atmosphere coupling improves considerably the phase relationship between SST and convection. The CGCM results reinforce that the MJO is a coupled phenomenon and suggest strongly the need of the ocean–atmosphere coupled processes to extend predictability.

scholarly journals Impact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments' hydrological responses to heavy precipitation

2020 ◽  
Vol 24 (1) ◽  
pp. 269-291 ◽  
Author(s):  
Alfonso Senatore ◽  
Luca Furnari ◽  
Giuseppe Mendicino
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Sources Of Uncertainty ◽  
Operational Forecasting ◽  
Forecasting System

Abstract. Operational meteo-hydrological forecasting chains are affected by many sources of uncertainty. In coastal areas characterized by complex topography, with several medium-to-small size catchments, quantitative precipitation forecast becomes even more challenging due to the interaction of intense air–sea exchanges with coastal orography. For such areas, which are quite common in the Mediterranean Basin, improved representation of sea surface temperature (SST) space–time patterns can be particularly important. The paper focuses on the relative impact of different resolutions of SST representation on regional operational forecasting chains (up to river discharge estimates) over coastal Mediterranean catchments, with respect to two other fundamental options while setting up the system, i.e. the choice of the forcing general circulation model (GCM) and the possible use of a three-dimensional variational assimilation (3D-Var) scheme. Two different kinds of severe hydro-meteorological events that affected the Calabria region (southern Italy) in 2015 are analysed using the WRF-Hydro atmosphere–hydrology modelling system in its uncoupled version. Both of the events are modelled using the 0.25∘ resolution global forecasting system (GFS) and the 16 km resolution integrated forecasting system (IFS) initial and lateral atmospheric boundary conditions, which are from the European Centre for Medium-Range Weather Forecasts (ECMWF), applying the WRF mesoscale model for the dynamical downscaling. For the IFS-driven forecasts, the effects of the 3D-Var scheme are also analysed. Finally, native initial and lower boundary SST data are replaced with data from the Medspiration project by Institut Français de Recherche pour L'Exploitation de la Mer (IFREMER)/Centre European Remote Sensing d'Archivage et de Traitement (CERSAT), which have a 24 h time resolution and a 2.2 km spatial resolution. Precipitation estimates are compared with both ground-based and radar data, as well as discharge estimates with stream gauging stations' data. Overall, the experiments highlight that the added value of high-resolution SST representation can be hidden by other more relevant sources of uncertainty, especially the choice of the general circulation model providing the boundary conditions. Nevertheless, in most cases, high-resolution SST fields show a non-negligible impact on the simulation of the atmospheric boundary layer processes, modifying flow dynamics and/or the amount of precipitated water; thus, this emphasizes the fact that uncertainty in SST representation should be duly taken into account in operational forecasting in coastal areas.

scholarly journals An objective tropical Atlantic sea surface temperature gradient index for studies of south Amazon dry-season climate variability and change

2008 ◽  
Vol 363 (1498) ◽  
pp. 1761-1766 ◽  
Author(s):  
Peter Good ◽  
Jason A Lowe ◽  
Mat Collins ◽  
Wilfran Moufouma-Okia
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Dry Season ◽  
Sea Surface ◽  
Tropical Atlantic ◽  
Sst Gradient

Future changes in meridional sea surface temperature (SST) gradients in the tropical Atlantic could influence Amazon dry-season precipitation by shifting the patterns of moisture convergence and vertical motion. Unlike for the El Niño-Southern Oscillation, there are no standard indices for quantifying this gradient. Here we describe a method for identifying the SST gradient that is most closely associated with June–August precipitation over the south Amazon. We use an ensemble of atmospheric general circulation model (AGCM) integrations forced by observed SST from 1949 to 2005. A large number of tropical Atlantic SST gradient indices are generated randomly and temporal correlations are examined between these indices and June–August precipitation averaged over the Amazon Basin south of the equator. The indices correlating most strongly with June–August southern Amazon precipitation form a cluster of near-meridional orientation centred near the equator. The location of the southern component of the gradient is particularly well defined in a region off the Brazilian tropical coast, consistent with known physical mechanisms. The chosen index appears to capture much of the Atlantic SST influence on simulated southern Amazon dry-season precipitation, and is significantly correlated with observed southern Amazon precipitation. We examine the index in 36 different coupled atmosphere–ocean model projections of climate change under a simple compound 1% increase in CO 2 . Within the large spread of responses, we find a relationship between the projected trend in the index and the Amazon dry-season precipitation trends. Furthermore, the magnitude of the trend relationship is consistent with the inter-annual variability relationship found in the AGCM simulations. This suggests that the index would be of use in quantifying uncertainties in climate change in the region.

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