A Multivariate Assessment of Climate Change Projections over South America Using the Fifth Phase of the Coupled Model Intercomparison Project

This study presents results from an assessment of climate change projections over South America using fifth phase of the Coupled Model Intercomparison Project models. Change in near‐surface temperature, precipitation, evapotranspiration, integrated water vapour transport (IVT), sea level pressure (SLP), and wind at three pressure levels is quantified across the multi‐model suite. Additionally, model agreement for the sign and significance of projected change is assessed within the ensemble. Models are in strong agreement that the highest magnitude of projected warming will be over tropical regions. The CMIP5 models project a decrease in precipitation for all seasons over southern South America, especially along the northern portions of the present‐day mid‐latitude storm track. This is consistent with a robustly projected poleward shift of the Pacific extratropical high‐pressure system and mid‐latitude storm track indicated by a systematic increase in SLP and decrease in westerly wind magnitude over the region. Decreased precipitation for the months of September, October, and November is also projected, with strong model agreement, over portions of northern and northeastern Brazil, coincident with decreases in SLP and increases in evapotranspiration. IVT is broadly projected to decrease over southern South America, coincident with the projected poleward shift of the mid‐latitude storm track, with increases projected in the vicinity of the South Atlantic Convergence Zone in spring and summer. Results provide a comprehensive picture of climate change across South America and highlight where model consensus on change is most robust

Characterizing Monthly Temperature Variability States and Associated Meteorology Across Southern South America

Key spatiotemporal patterns of monthly scale temperature variability are characterized over southern South America using k‐means clustering. The resulting clusters reveal patterns of temperature variability, referred to as temperature variability states. Analysis is performed over summer and winter months separately using data covering the period 1980–2015. Results for both seasons show four primary temperature variability states. In both seasons, one state is primarily characterized by warm temperature anomalies across the domain while another is characterized by cold anomalies. The other two patterns tend to be characterized by a warm north–cold south and cold north–warm south feature. This suggests two primary modes of temperature variability over the region. Composites of synoptic‐scale meteorological patterns (wind, geopotential height, and moisture fields) are computed for months assigned to each cluster to diagnose the driving meteorology associated with these variability states. Results suggest that low‐level temperature advection promoted by anomalies in atmospheric circulation patterns is a key process for driving these variability states. Moisture‐related processes also are shown to play a role, especially in summer. The El Niño–Southern Oscillation and the Southern Annular Mode exhibit some relationship with temperature variability state frequency, with some states more common during amplified phases of these two modes than others. However, the climate modes are not a primary driver of the temperature variability states

A Climatology Of Daily Synoptic Circulation Patterns And Associated Surface Meteorology Over Southern South America

Synoptic circulation patterns, defined as anomalies in sea level pressure (SLP), 500 hPa geopotential height (Z500), and 250 hPa wind speed (V250) and referred to as large-scale meteorological patterns (LSMPs), are characterized using the self-organizing maps approach over southern South America. Results show a wide range of possible LSMP types over a 37-year period of study. LSMP type variability can be summarized as a spectrum from patterns dominated by positive SLP and Z500 anomalies with a poleward displacement of the strongest 250 hPa winds, to patterns dominated by similar structures but with anomalies of opposite sign. The LSMPs found are connected with lower tropospheric temperature and wind, precipitation, and the frequency of atmospheric rivers (ARs). This highlights LSMPs more closely associated with anomalous and potentially impactful surface meteorology. Results show ARs as primary drivers of heavy precipitation over some of the region and connect their occurrence to driving synoptic dynamics. Two important low frequency modes of climate variability, the Southern Annular Mode (SAM) and the El Nino Southern Oscillation (ENSO), show some influence on the frequency of LSMP type, with the SAM more directly related to LSMP type modulation than ENSO. This comprehensive climatology of synoptic variability across southern South America has potential to aid in a mechanistic approach to studying climate change projections of temperature, precipitation, and AR frequency in climate models