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  1. The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water to the people and environment and are critical to moisture recycling and transport, and represents an important variable for climate models to simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This is done by discussing results from spatial pattern mapping, Taylor diagram analysis and Taylor skill score, annual climatology comparison, cumulative distribution analysis, and empirical orthogonal function (EOF) analysis. Precipitation analysis shows: (1) This region displays higher rainfall in the north-northwest and drier conditions in the south. Models tend to underestimate northern values or overestimate the central to northwest averages. (2) The southern Amazon has a more defined dry season (June, July, and August) and wet season (December, January, and February) and models simulate this well. The northern Amazon dry season tends to occur in August, September, and October and the wet season occurs in March, April, and May, and models are not able to capture the climatology as well. Models tend to produce too much rainfall at the start of the wet season and tend to either over- or under-estimate the dry season, although ensemble meansmore »typically display the overall pattern more precisely. (3) Models struggle to capture extreme values of precipitation except when precipitation values are close to 0. (4) EOF analysis shows that models capture the dominant mode of variability, which was the annual cycle or South American Monsoon System. (5) When all evaluation metrics are considered, the models that perform best are CESM2, MIROC6, MRIESM20, SAM0UNICON, and the ensemble mean. This paper supports research in determining the most up-to-date CMIP6 model performance of precipitation regime for 1981–2014 for the Brazilian Amazon. Results will aid in understanding future projections of precipitation for the selected subset of global climate models and allow scientists to construct reliable model ensembles, as precipitation plays a role in many sectors of the economy, including the ecosystem, agriculture, energy, and water security.« less
    Free, publicly-accessible full text available August 1, 2023
  2. Evapotranspiration (ET) connects the land to the atmosphere, linking water, energy, and carbon cycles. ET is an essential climate variable with a fundamental importance, and accurate assessments of the spatiotemporal trends and variability in ET are needed from regional to continental scales. This study compared eight global actual ET datasets (ETgl) and the average actual ET ensemble (ETens) based on remote sensing, climate reanalysis, land-surface, and biophysical models to ET computed from basin-scale water balance (ETwb) in South America on monthly time scale. The 50 small-to-large basins covered major rivers and different biomes and climate types. We also examined the magnitude, seasonality, and interannual variability of ET, comparing ETgl and ETens with ETwb. Global ET datasets were evaluated between 2003 and 2014 from the following datasets: Breathing Earth System Simulator (BESS), ECMWF Reanalysis 5 (ERA5), Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MOD16, Penman–Monteith–Leuning (PML), Operational Simplified Surface Energy Balance (SSEBop) and Terra Climate. By using ETwb as a basis for comparison, correlation coefficients ranged from 0.45 (SSEBop) to 0.60 (ETens), and RMSE ranged from 35.6 (ETens) to 40.5 mm·month−1 (MOD16). Overall, ETgl estimates ranged from 0 to 150 mm·month−1 in most basins in Southmore »America, while ETwb estimates showed maximum rates up to 250 mm·month−1. ETgl varied by hydroclimatic regions: (i) basins located in humid climates with low seasonality in precipitation, including the Amazon, Uruguay, and South Atlantic basins, yielded weak correlation coefficients between monthly ETgl and ETwb, and (ii) tropical and semiarid basins (areas where precipitation demonstrates a strong seasonality, as in the São Francisco, Northeast Atlantic, Paraná/Paraguay, and Tocantins basins) yielded moderate-to-strong correlation coefficients. An assessment of the interannual variability demonstrated a disagreement between ETgl and ETwb in the humid tropics (in the Amazon), with ETgl showing a wide range of interannual variability. However, in tropical, subtropical, and semiarid climates, including the Tocantins, São Francisco, Paraná, Paraguay, Uruguay, and Atlantic basins (Northeast, East, and South), we found a stronger agreement between ETgl and ETwb for interannual variability. Assessing ET datasets enables the understanding of land–atmosphere exchanges in South America, to improvement of ET estimation and monitoring for water management.« less
    Free, publicly-accessible full text available June 1, 2023
  3. Free, publicly-accessible full text available February 1, 2023