This article analyses the relations of the Atlantic multidecadal oscillation (AMO) and the El Niño-Southern Oscillation (ENSO) and their influence on the South American rainfall. The ENSO-related precipitation anomalous composites over South America show more (less) organized patterns with the significant anomalies occupying extensive (reduced) areas when ENSO and AMO are in the opposite (same) phase. The El Niño (La Niña) events in the cold (warm) AMO phase are, in general, stronger than those in the warm (cold) AMO phase. The strong El Niño (La Niña) events in the cold (warm) AMO phase are due to the presence of a negative (positive) inter-Pacific-Atlantic sea surface temperature (SST). The negative (positive) SST anomalies in the equatorial Atlantic reinforce the El Niño (La Niña) in the tropical Pacific through an anomalous Atlantic Walker circulation. In consequence, the ENSO-related precipitation anomalies over South America are more intense and with less horizontal structure under the existence of this connection between the climate variability of the tropical Atlantic and Pacific Oceans. As far as the authors know, the results presented here have not been discussed before and have important implications for regional climate monitoring, as well as for modelling studies.
This article describes the main features of the Brazilian Global Atmospheric Model (BAM), analyses of its performance for tropical rainfall forecasting, and its sensitivity to convective scheme and horizontal resolution. BAM is the new global atmospheric model of the Center for Weather Forecasting and Climate Research [Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)], which includes a new dynamical core and state-of-the-art parameterization schemes. BAM’s dynamical core incorporates a monotonic two-time-level semi-Lagrangian scheme, which is carried out completely on the model grid for the tridimensional transport of moisture, microphysical prognostic variables, and tracers. The performance of the quantitative precipitation forecasts (QPFs) from two convective schemes, the Grell–Dévényi (GD) scheme and its modified version (GDM), and two different horizontal resolutions are evaluated against the daily TRMM Multisatellite Precipitation Analysis over different tropical regions. Three main results are 1) the QPF skill was improved substantially with GDM in comparison to GD; 2) the increase in the horizontal resolution without any ad hoc tuning improves the variance of precipitation over continents with complex orography, such as Africa and South America, whereas over oceans there are no significant differences; and 3) the systematic errors (dry or wet biases) remain virtually unchanged for 5-day forecasts. Despite improvements in the tropical precipitation forecasts, especially over southeastern Brazil, dry biases over the Amazon and La Plata remain in BAM. Improving the precipitation forecasts over these regions remains a challenge for the future development of the model to be used not only for numerical weather prediction over South America but also for global climate simulations.
Abstract. The performance of the coupled ocean–atmosphere component of the Brazilian Earth System Model version 2.5 (BESM-OA2.5) was evaluated in simulating the historical period 1850–2005. After a climate model validation procedure in which the main atmospheric and oceanic variabilities were evaluated against observed and reanalysis datasets, the evaluation specifically focused on the mean climate state and the most important large-scale climate variability patterns simulated in the historical run, which was forced by the observed greenhouse gas concentration. The most significant upgrades in the model's components are also briefly presented here. BESM-OA2.5 could reproduce the most important large-scale variabilities, particularly over the Atlantic Ocean (e.g., the North Atlantic Oscillation, the Atlantic Meridional Mode, and the Atlantic Meridional Overturning Circulation), and the extratropical modes that occur in both hemispheres. The model's ability to simulate such large-scale variabilities supports its usefulness for seasonal climate prediction and in climate change studies.
Measurements of ecosystem gas exchange, meteorology, and hydrology (rainfall and soil moisture) were used to assess the seasonal patterns of, and controls on, average diel (24 h) net ecosystem CO2 exchange (NEE), evapotranspiration (E), and bulk canopy water vapor conductance (Gc) of a tropical transitional (ecotonal) forest in the Brazilian Amazon. Diel trends in E and NEE were almost completely explained by the diel variation in photosynthetic photon flux density (QPPFD), and while the QPPFD response of E varied little over the annual cycle, the QPPFD response of NEE declined substantially during the dry season, and the magnitude of hysteresis in the NEE–QPPFD response increased as well. The magnitude of the residuals for the QPPFD versus NEE response was significantly negatively correlated with total monthly rainfall and surface soil moisture and positively correlated with the maximum daily temperature and atmospheric vapor pressure deficit (V). Average daily Gc was also significantly correlated with average daily V (r = −0.72) and soil moisture (r = 0.62), suggesting strong stomatal control of NEE during drought. However, drought reduced ecosystem CO2 efflux relatively more than CO2 assimilation, suggesting that the seasonal variation in NEE was largely driven by seasonal variation in respiration. When compared with other tropical forests, seasonality in NEE was negatively correlated with annual rainfall and positively correlated with dry-season length. The relatively high sensitivity of NEE to seasonal variation in climate and water availability has profound implications for C cycling dynamics under novel climates resulting from climate and/or land-use change in the Amazon basin.
This paper examines the climate variability modes in the South American/Atlantic sector accompanying dry and wet years over north-eastern Brazil (NEB) in which the tropical Pacific and Atlantic oceanic-atmospheric conditions usually associated, respectively, with dryness and wetness are absent. The analyses are for several variables and take into account the warm and cold Atlantic Multidecadal Oscillation (AMO) phases (WAMO and CAMO). Four cases are analysed: DRY-WAMO, DRY-CAMO, WET-WAMO and WET-CAMO. The main difference in the sea surface temperature (SST) anomaly patterns in the tropics between the AMO phases responsible for the differences in the precipitation anomaly patterns is the differential longitude positioning of the warming or cooling of the surface waters in the equatorial Atlantic. In consequence, the anomalous Atlantic Hadley and Walker circulations also show differences between the AMO phases, which justify the observed precipitation anomalies over tropical South America for the analysed cases. The strong anomalous Atlantic Hadley cell determines the dipolar structure of the precipitation anomalies between NEB and northern South America for the DRY-WAMO and WET-WAMO cases. The strong anomalous Atlantic Walker cell defines the dryness over NEB for the DRY-CAMO, and both the strong anomalous Atlantic Hadley and Walker cells act together to yield an anomalous dry condition over NEB and wet condition over northern South America. Therefore, the results here provided clear indications that for climate monitoring and forecasting tasks, the AMO phases should be considered. These are new aspects of the tropical Atlantic variability that might be useful for climate monitoring purposes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.