Breeze Potential Along the Brazilian Northern and Northeastern Coast

<div><p>ABSTRACT The breeze potential along the Brazilian northern and northeastern coast was studied using wind data from the Climate Forecast System Reanalysis for the period between 1980 and 2010. March and September were considered, which are representative of the rainy and dry (or less rainy) periods, respectively. The Brazilian northern and northeastern coast is composed by meridionally oriented coastlines (Amapá State coast and eastern coast of Northeast Brazil) and a zonally oriented coastline (Brazilian northern coast east of Marajó Island). Along the meridionally oriented coastlines, the breeze potential was mainly related to the zonal wind and extended inland over 1 - 2° from the shore. The daily zonal wind cycle maximum (minimum), which represents the land (sea) breeze potential, occurred at ~0700 UTC (~1900 UTC). Along the zonally oriented coastline, the breeze potential was mainly related to the meridional wind and extended inland and offshore over 2 - 3° from the shore. At the shore, the daily meridional wind cycle maximum (minimum), which represents the land (sea) breeze potential, occurred at ~1000 UTC (~2200 UTC). Phase propagation occurred from the shore inland in March and September and also offshore in September. In general, for the entire Brazilian northern and northeastern coast, the breeze potential frequency was higher in September (20 - 25 days per month). In March, while the frequency slightly decreased over the meridionally oriented coastlines (to 15 - 20 days per month), the frequency sharply decreased over the zonally oriented coastlines to 5 - 10 days per month in landside coastal areas and vanished in seaside coastal areas. Higher frequency was generally related to lower interannual variability, and there was significant correlation between the interannual variability of the frequency and oceanic indices, along specific coastal areas. The features of the breeze potential areas obtained in this study complement the results from others and provide a more complete depiction of breeze features along the entire Brazilian northern and northeastern coast.</p></div

Brazilian Annual Precipitation Analysis Simulated by the Brazilian Atmospheric Global Model

The strategy for assessing simulations produced by climate models established as part of the Atmospheric Model Intercomparison Project (AMIP) delivers an outline for model analysis, verification/validation, and intercomparison. Numerical models are continuously being developed to find the best representation for the amount and distribution of precipitation in Brazil to improve the country’s precipitation forecast. This article describes the key features of the Brazilian Global Atmospheric Model (BAM) (developed by the Center for Weather Forecasting and Climate Studies of the National Institute for Space Research (CPTEC/INPE)) and analyses of its performance for annual rainfall climate simulations. This study considered the representation of the annual precipitation in Brazil mainly during the rainy season in the central part of Brazil by the BAM. The model was run over the 1990 to 2015 period using spectral Eulerian model dynamics with a 70-horizontal resolution of approximately 1.0∘× 1.0∘ and 42 vertical sigma levels. The analysis was divided into two stages: the annual precipitation and the rainy season precipitation. Model precipitation analyses were performed using statistical methods, such as the mean and standard deviation, comparing modeled data with observed data from two datasets, data from the XAV (observed data from INMET, ANA, and DAEE), and the Climate Prediction Center (CPC). In general, the BAM model simulations reasonably replicated the configuration of the spatial distribution of precipitation in the Brazilian territory almost entirely, especially compared with the XAV. The accumulated precipitation in the southern region presented great variation, accumulating from 750 mm year−1 in the extreme south to 1750 mm year−1 in the north of this region. Average values of the BAM accumulated precipitation ranged from 1000 to 2000 mm year−1, within the expected average, compared to observed values of 750–1500 mm year−1 (CPC and XAV, correspondingly). Although there was an underestimation of the accumulated precipitation by the model, the model reasonably reproduced the precipitation during the rainy season. The performed assessment identified model aspects that need to be improved

An assessment of land-atmosphere interactions over South America using satellites, reanalysis and two global climate models

In South America, land-atmosphere interactions have an important impact on climate, particularly the regional hydrological cycle, but detailed evaluation of these processes in global climate models has been limited. Focussing on the satellite-era period of 2003–2014, we assess land-atmosphere interactions on annual to seasonal timescales over South America in satellite products, a novel reanalysis (ERA5-Land) and two global climate models: the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) and the UK Hadley Centre Global Environment Model version 3 (HadGEM3). We identify key features of South American land-atmosphere interactions represented in satellite and model datasets, including seasonal variation in coupling strength, large-scale spatial variation in the sensitivity of evapotranspiration to surface moisture, and a dipole in evaporative regime across the continent. Differences between products are also identified, with ERA5-Land, HadGEM3 and BAM-1.2 showing opposite interactions to satellites over parts of the Amazon and the Cerrado, and stronger land-atmosphere coupling along the North Atlantic coast. Where models and satellites disagree on the strength and direction of land-atmosphere interactions, precipitation biases and misrepresentation of processes controlling surface soil moisture are implicated as likely drivers. These results show where improvement of model processes could reduce uncertainty in the modelled climate response to land-use change, and highlight where model biases could unrealistically amplify drying or wetting trends in future climate projections. Finally, HadGEM3 and BAM-1.2 are consistent with the median response of an ensemble of nine CMIP6 models, showing they are broadly representative of the latest generation of climate models

Evaluation of Surface Data Simulation Performance with the Brazilian Global Atmospheric Model (BAM)

In this study, we evaluated the performance of the Brazilian Global Atmospheric Model (BAM), in its version 2.2.1, in the representation of the surface variables solar radiation, temperature (maximum, minimum, and average), and wind speed. Three experiments were carried out for the period from 2016 to 2022 under three different aerosol conditions (constant (CTE), climatological (CLIM), and equal to zero (ZERO)), discarding the first year as a spin-up period. The observations came from a high-resolution gridded analysis that provides Brazil with robust data based on observations from surface stations on a daily scale from 1961 to 2020; therefore, combining the BAM outputs with the observations, our intercomparison period took place from 2017 to 2020, for three timescales: daily, 10-day average, and monthly, targeting different applications. In its different simulations, BAM overestimated solar radiation throughout Brazil, especially in the Amazon; underestimated temperature in most of the northeast, southeast, and south regions; and overestimated in parts of the north and mid-west; while wind speed was only not overestimated in the Amazon region. In relative terms, the simulations with constant aerosol showed better performance than the others, followed by climatological conditions and zero aerosol. The dexterity indices applied in the intercomparison between BAM and observations indicate that BAM needs adjustments and calibration to better represent these surface variables. Where model deficiencies have been identified, these can be used to drive model development and further improve the predictive capabilities