Subseasonal prediction performance for South American land–atmosphere coupling in extended austral summer

Abstract

Land-atmosphere feedbacks, through water and energy exchanges, provide subseasonal-to-seasonal predictability of the hydrological cycle. We analyse subseasonal land-atmosphere coupling over South America (SA) during extended austral summer for the soil moisture-to-precipitation and soil moisture-to-air temperature feedback pathways. We evaluate subseasonal hindcasts from global forecasting systems from the UK Met Office, the National Centers for Environmental Prediction (NCEP), the European Centre for Medium Range Weather Forecasts and the Center for Weather Forecast and Climate Studies (CPTEC), for the common period of 1999-2010, against two reanalyses. Biases in landatmosphere states are established in the first week of hindcasts and increase with lead time. By Week 5, all the models only demonstrate good performance over northern, northeastern and southeastern SA for soil moisture and evapotranspiration and over tropical and subtropical SA for temperature. The hindcasts show stronger coupling at longer lead-lag between variables than reanalyses.Our results highlight possible deficiencies in feedbacks between soil moisture and precipitation in CPTEC and NCEP forecasts over the Amazon due to initial dry soil moisture biases, and in feedbacks between soil moisture and temperature for all four investigated models over southeastern SA due to erroneous representations of evapotranspiration.

How morning soil moisture conditions influence afternoon precipitation events in South America

“…(2021a, 2021b, 2021c) and Chevuturi et al . (2022), and an evaluation of multiple reanalysis (including ERA5) in reproducing temperature and precipitation indices over southern South America is presented in Balmaceda‐Huarte et al . (2021).…”

“…In the case of the recent ERA5 reanalysis, as far as we know there are no specific evaluations for this continent at the hourly scale, besides the paper mentioned above (Giles et al, 2021). However, comparisons at seasonal and interannual scales between datasets including ERA5 (or ERA5-Land) are shown in Baker et al (2021aBaker et al ( , 2021bBaker et al ( , 2021c and Chevuturi et al (2022), and an evaluation of…”

Observation‐Driven Characterization of Soil Moisture‐Precipitation Interactions in the Central United States

“…Such soil moisture linkages with atmospheric processes and resultant precipitation or temperature patterns occur on a spectrum of timescales, generally ranging from diurnal to seasonal (Liu et al., 2022; Saini et al., 2016; Talib et al., 2022). At one end of the spectrum, large scale soil moisture patterns can influence subseasonal to seasonal anomalies of precipitation and temperature to varying degrees (Chevuturi et al., 2021; Teng et al., 2016), providing an important form of predictability at those timescales (Prodhomme et al., 2016). On diurnal timescales, soil moisture‐driven anomalies of surface heat fluxes can modify planetary boundary layer (PBL) growth, aiding or impeding local‐ to regional‐scale convection initiation and precipitation (Cioni & Hohenegger, 2017; Ek & Holtslag, 2004).…”

A perspective for advancing climate prediction services in Brazil

“…In a fourth study, Chevuturi et al (2021a) evaluated subseasonal prediction performance for South American land-atmosphere coupling through soil moisture-evapotranspiration-precipitation and soil moisture-sensible heat flux-air temperature feedback pathways (Seneviratne et al, 2010) during extended austral summer in the Brazilian model (Guimarães et al, 2020), as well as the international models assessed by Klingaman et al (2021). This is important because land-atmosphere interactions through water and energy exchanges provide another source of predictability for the hydrological cycle.…”

“…The land surface can affect atmospheric variability when the following conditions are satisfied: (i) the atmosphere is sensitive to land surface state variations (coupling); (ii) the land surface state fluctuates (variability); and (iii) these fluctuations persist (memory). Chevuturi et al (2021a) highlighted deficient representation of feedbacks between soil moisture and precipitation over the Amazon in the Brazilian and American models due to initial dry soil moisture biases. The study also found deficient feedbacks between soil moisture and temperature for all investigated models over southeastern South America, due to erroneous representations of sensible heat flux in the soil moisture to air temperature pathway.…”