Optimal Tropical Sea Surface Temperature Forcing of North American Drought

2010 ◽  
Vol 23 (14) ◽  
pp. 3907-3917 ◽  
Author(s):  
Sang-Ik Shin ◽  
Prashant D. Sardeshmukh ◽  
Robert S. Webb
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North American ◽  
General Circulation ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Sea Surface ◽  
Drought Severity ◽  
Sst Anomaly

Abstract The optimal anomalous sea surface temperature (SST) pattern for forcing North American drought is identified through atmospheric general circulation model integrations in which the response of the Palmer drought severity index (PDSI) is determined for each of 43 prescribed localized SST anomaly “patches” in a regular array over the tropical oceans. The robustness and relevance of the optimal pattern are established through the consistency of results obtained using two different models, and also by the good correspondence of the projection time series of historical tropical SST anomaly fields on the optimal pattern with the time series of the simulated PDSI in separate model integrations with prescribed time-varying observed global SST fields for 1920–2005. It is noteworthy that this optimal drought forcing pattern differs markedly in the Pacific Ocean from the dominant SST pattern associated with El Niño–Southern Oscillation (ENSO), and also shows a large sensitivity of North American drought to Indian and Atlantic Ocean SSTs.

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.

scholarly journals A Verified Estimation of the El Niño Index Niño-3.4 since 1877

2009 ◽  
Vol 22 (14) ◽  
pp. 3979-3992 ◽  
Author(s):  
Lucia Bunge ◽  
Allan J. Clarke
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Correlation Coefficients ◽  
Sea Surface ◽  
Monthly Time Series ◽  
Sst Anomaly

Abstract Decadal and longer time-scale variabilities of the best known El Niño–Southern Oscillation (ENSO) indexes are poorly correlated before 1950, and so knowledge of interdecadal variability and trend in ENSO indexes is dubious, especially before 1950. To address this problem, the authors constructed and compared physically related monthly ENSO indexes. The base index was El Niño index Niño-3.4, the sea surface temperature (SST) anomaly averaged over the equatorial box bounded by 5°N, 5°S, 170°W, and 120°W; the authors also constructed indexes based on the nighttime marine air temperature over the Niño-3.4 region (NMAT3.4) and an equatorial Southern Oscillation index (ESOI). The Niño-3.4 index used the “uninterpolated” sea surface temperature data from the Second Hadley Centre Sea Surface Temperature dataset (HadSST2), a dataset with smaller uncertainty and better geographical coverage than others. In constructing the index, data at each point for a given month were weighted to take into account the typical considerable spatial variation of the SST anomaly over the Niño-3.4 box as well as the number of observations at that point for that month. Missing monthly data were interpolated and “noise” was reduced by using the result that Niño-3.4 has essentially the same calendar month amplitude structure every year. This 12-point calendar month structure from April to March was obtained by an EOF analysis over the last 58 yr and then was fitted to the entire monthly time series using a least squares approach. Equivalent procedures were followed for NMAT3.4 and ESOI. The new ESOI uses Darwin atmospheric pressure in the west and is based on theory that allows for variations of the atmospheric boundary layer depth across the Pacific. The new Niño-3.4 index was compared with NMAT3.4, the new ESOI, and with a record of δ18O from a coral at Palmyra, an atoll inside the region Niño-3.4 (Cobb et al.). Correlation coefficients between Niño-3.4 and the three monthly indexes mentioned above before 1950 are 0.84, 0.87, 0.73 and 0.93, 0.86, 0.73 for decadal time scales. These relatively high correlation coefficients between physically related but independent monthly time series suggest that this study has improved knowledge of low-frequency variability. All four indexes are consistent with a rise in Niño-3.4 SST and the weakening of the equatorial Pacific winds since about 1970.

scholarly journals Nonlinear Modes of North American Winter Climate Variability Derived from a General Circulation Model Simulation

2003 ◽  
Vol 16 (14) ◽  
pp. 2325-2339 ◽  
Author(s):  
Aiming Wu ◽  
William W. Hsieh ◽  
Francis W. Zwiers
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation Model ◽  
North American ◽  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Circulation Model ◽  
Sea Surface ◽  
Sst Anomalies

Abstract Nonlinear principal component analysis (NLPCA), via a neural network (NN) approach, was applied to an ensemble of six 47-yr simulations conducted by the Canadian Centre for Climate Modelling and Analysis (CCCma) second-generation atmospheric general circulation model (AGCM2). Each simulation was forced with the observed sea surface temperature [from the Global Sea Ice and Sea Surface Temperature dataset (GISST)] from January 1948 to November 1994. The NLPCA modes reveal nonlinear structures in both the winter 500-mb geopotential height (Z500) anomalies and surface air temperature (SAT) anomalies over North America, with asymmetric spatial anomaly patterns during the opposite phases of an NLPCA mode. Only during its negative phase is the first NLPCA mode related to the El Niño–Southern Oscillation (ENSO); the positive phase is related to a weakened jet stream. Spatial patterns of the NLPCA mode for the Z500 anomalies generally agree with those for the SAT anomalies. Nonlinear canonical correlation analysis (NLCCA), also via an NN approach, was then applied to the midlatitude winter GCM data and the observed SST of the tropical Pacific. Nonlinearity was detected in both the forcing field (SST) and the response field (Z500 or SAT) at zero time lag. The leading NLCCA mode for the SST anomalies is a nonlinear ENSO mode, with a 30°–40° eastward shift of the positive SST anomalies during El Niño relative to the negative SST anomalies during La Niña. The leading NLCCA mode for the Z500 anomaly field is a nonlinear Pacific–North American (PNA) teleconnection pattern. The ray path of the Rossby waves induced during El Niño is 10°–15° east of that induced during La Niña. The nonlinear atmospheric response to ENSO is also found in the leading NLCCA mode for the SAT anomalies.

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.

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