Relationships among climatological vertical moisture structure, column water vapor, and precipitation over the central Amazon in observations and CMIP5 models

Abstract

Bias and spread in Coupled Model Intercomparison Project Phase 5 simulated vertical specific humidity (q) structure are examined and related to both precipitation and column water vapor (cwv) near Manaus, Brazil, site of the recent Green Ocean Amazon campaign. Simulated seasonal mean q profiles are typically too dry, especially at low levels and during the local dry season, consistent with previously identified surface hydroclimate biases in the Amazon. Multimodel empirical orthogonal function analysis of the models' monthly climatological q profiles indicates two significant modes of ensemble spread in moisture vertical structure, with the leading mode peaked at low levels and the second mode in the lower free troposphere (LFT). While both modes project onto simulated cwv spread, only the first projects on precipitation, suggesting inconsistent sensitivity of simulated rainfall to LFT moisture. Relative to observations, models with high cwv and low‐level moisture errors tend to exhibit high precipitation error.

Why does Amazon precipitation decrease when tropical forests respond to increasing CO2?

“…CMIP models are historically poor at simulating the dry-to-wet transition season over the Amazon as well as dry season moist processes, owing to inaccuracies in the surface energy budget , too little moisture throughout the troposphere [Lintner et al, 2017] and overly strong land-atmosphere coupling in ESMs [Ferguson et al, 2012;Levine et al, 2016]. For the Amazon in particular, the vegetation-driven precipitation activity discussed above plays a central role in the dry-to-wet transition season over the rainforest and is referred to as the "deep convective moisture pump" in Wright et al [2017].…”

On the impact of recent developments of an atmospheric general circulation model on the simulation of CO<sub>2</sub> transport

“…In the Tropics, precipitation is an indicator of the convective activity and we see here that the new physics decreases the mean precipitation (mainly convective) during both periods without showing better agreement with the reference data. The modelling of the precipitation in this region has been shown to be particularly challenging (Lintner et al, 2017). The simulated radon profiles suggest that more radon is detrained above the boundary layers by the thermals in the new physics,…”

Sensitivity of the Amazonian Convective Diurnal Cycle to Its Environment in Observations and Reanalysis

“…The mean state and variability of the CDC is linked to atmospheric state anomalies on various timescales (e.g., Adams et al, ; Betts et al, , ; Derbyshire et al, ; Dodson & Taylor, ; Itterly et al, ; Lintner et al, ; Taylor, , ; Zelinka & Hartmann, ; Zhang & Klein, ; Zhao et al, ). For example, Zhang and Klein () show robust relationships between preconvective environmental parameters and afternoon deep convection in the U.S. Southern Great Plains indicating that higher convective available potential energy (CAPE) is associated with a later onset time and shorter duration of precipitation, whereas higher humidity above the boundary layer leads to an earlier onset time and longer duration of precipitation due to reduced entrainment of developing cumulus clouds (Derbyshire et al, ; Zhang & Klein, ).…”

“…While many studies investigate the relationships between convection and its environment (e.g., Adams et al, 2013Adams et al, , 2015Giangrande et al, 2017;Schiro et al, 2016;Strong et al, 2005;Xie et al, 2014;Zelinka & Hartmann, 2009;Zhang & Klein, 2010), relatively few studies systematically analyze the relationship between the CDC and atmospheric conditions. The mean state and variability of the CDC is linked to atmospheric state anomalies on various timescales (e.g., Adams et al, 2017;Betts et al, 2015Betts et al, , 2017Derbyshire et al, 2004;Itterly et al, 2016;Lintner et al, 2017;Taylor, 2014aTaylor, , 2014bZelinka & Hartmann, 2009;Zhang & Klein, 2010;Zhao et al, 2017). For example, Zhang and Klein (2010) show robust relationships between preconvective environmental parameters and afternoon deep convection in the U.S. Southern Great Plains indicating that higher convective available potential energy (CAPE) is associated with a later onset time and shorter duration of precipitation, whereas higher humidity above the boundary layer leads to an earlier onset time and longer duration of precipitation due to reduced entrainment of developing cumulus clouds (Derbyshire et al, 2004;Zhang & Klein, 2010).…”