Abstract
Abstract. The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the evaporative fraction (EF), i.e., the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by relating the before-noon EF to the frequency of afternoon precipitation over the contiguous US, through statistical analyses of multiple EF and precipitation data sets. We analyze remote-sensing data products (Global Land Evaporation: the Amsterdam Methodology (GLEAM) for EF, and radar precipitation from the NEXt generation weather RADar system (NEXRAD)), FLUXNET station data, and the North American Regional Reanalysis (NARR). Data sets agree on a region of positive relationship between EF and precipitation occurrence in the southwestern US. However, a region of strong positive relationship over the eastern US in NARR cannot be confirmed with observation-derived estimates (GLEAM, NEXRAD and FLUXNET). The GLEAM–NEXRAD data set combination indicates a region of positive EF–precipitation relationship in the central US. These disagreements emphasize large uncertainties in the EF data. Further analyses highlight that much of these EF–precipitation relationships could be explained by precipitation persistence alone, and it is unclear whether EF has an additional role in triggering afternoon precipitation. This also highlights the difficulties in isolating a land impact on precipitation. Regional analyses point to contrasting mechanisms over different regions. Over the eastern US, our analyses suggest that the EF–precipitation relationship in NARR is either atmospherically controlled (from precipitation persistence and potential evaporation) or driven by vegetation interception rather than soil moisture. Although this aligns well with the high forest cover and the wet regime of that region, the role of interception evaporation is likely overestimated because of low nighttime evaporation in NARR. Over the central and southwestern US, the EF–precipitation relationship is additionally linked to soil moisture variations, owing to the soil-moisture-limited climate regime.
Highlights
Soil-moisture–precipitation feedback has been investigated for several decades and, despite some progress in recent years, remains a poorly understood process and a large source of uncertainty in climate models (Seneviratne et al, 2010)
Triggering feedback strength (TFS)∗ is computed at FLUXNET sites from three data set combinations: (i) a reanalysis product (NARR), (ii) direct measurements of surface turbulent heat fluxes at FLUXNET sites for evaporative fraction (EF) in combination with radar precipitation from NEXt generation weather RADar system (NEXRAD), and (iii) EF estimates from a satellite-data-driven evaporation product (GLEAM) in combination with NEXRAD precipitation
(triggering feedback strength), based on data from the North American Regional Reanalysis (NARR), and suggests the existence of an extended region of positive land-surface– precipitation coupling over the eastern US
Summary
Soil-moisture–precipitation feedback has been investigated for several decades and, despite some progress in recent years, remains a poorly understood process and a large source of uncertainty in climate models (Seneviratne et al, 2010). While studies until the 1990s tended to focus on the concept of moisture recycling (i.e., the fraction of precipitation directly contributed by regional evaporation from the land surface; see Seneviratne et al, 2010), more recent studies have emphasized the importance of indirect feedback mechanisms – that is, an influence of soil moisture on atmospheric stability, boundary layer characteristics, and thereby precipitation formation (e.g., Schär et al, 1999; Pal and Eltahir, 2001; Findell and Eltahir, 2003a; Ek and Holtslag, 2004; Betts, 2004; Santanello et al, 2009; Hohenegger et al, 2009; Taylor et al, 2011; Lintner et al, 2013; Gentine et al, 2013).
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