The sensitivity of the West African monsoon circulation to intraseasonal soil moisture feedbacks

Talib, Joshua; Taylor, Christopher M.; Klein, Cornelia; Harris, Bethan L.; Anderson, Seonaid R.; Semeena, V. S.

doi:10.1002/qj.4274

Cited by 12 publications

(23 citation statements)

References 113 publications

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“…The stronger vegetation response to precipitation is expected to dominate any weaker impacts in the opposing direction. Moreover, the impact of intraseasonal surface variability on precipitation may be non-local (Chug & Dominguez, 2019;Talib et al, 2021Talib et al, , 2022. Water controls on transpiration (rather than direct evaporation) provide the dominant pathway for atmospheric feedbacks on these timescales.…”

Section: Discussionmentioning

confidence: 99%

“…We remove data points where both preceding and subsequent VOD changes exceed two standard deviations, as in Talib et al. (2022). This removes a mean of 1% of observed days from each pixel.…”

Section: Methodsmentioning

confidence: 99%

“…However, with such a mask, we still found widespread cases of day-to-day surface water fraction changes affecting VOD responses to rainfall. We therefore developed an alternative inundation mask, using daily SSM from the ESA CCI SM v06.1 combined active-passive microwave product (Dorigo et al, 2017;Gruber et al, 2019), and surface water fraction from the active-passive SWAMPS v3.2 data set (Jensen & Mcdonald, 2019), as in Talib et al (2022), exploiting that artificial decreases in VOD due to inundation tend to coincide with increases in SSM. Further details are included in Text S1 in Supporting Information S1.…”

Section: Datamentioning

confidence: 99%

“…We mask unphysical spikes in the VOD time series by comparing changes in consecutive observations with a monthly climatology for each pixel. We remove data points where both preceding and subsequent VOD changes exceed two standard deviations, as in Talib et al (2022). This removes a mean of 1% of observed days from each pixel.…”

Section: Datamentioning

confidence: 99%

“…Intraseasonal land surface feedbacks impact circulation and rainfall in India (Ferranti et al., 1999; Saha et al., 2012; Unnikrishnan et al., 2017; Webster, 1983), South America (Chug & Dominguez, 2019; Spennemann & Saulo, 2015), Australia (Yu & Notaro, 2020) and West Africa (Lavender et al., 2010; Talib et al., 2022; Taylor, 2008). For example, regional‐scale soil drying and associated vegetation browning can induce an anomalous heat low which enhances rainfall via moisture convergence (Chug & Dominguez, 2019; Taylor, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability

Harris

Taylor

Weedon

et al. 2022

Geophysical Research Letters

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In recent years there has been substantial interest in improving the skill of subseasonal-to-seasonal (S2S; 2-8 weeks) forecasts, which sit between traditional weather and climate forecasts (Brunet et al., 2010;Vitart et al., 2017). A major source of global S2S predictability is provided by tropical intraseasonal oscillations (ISOs: Ding et al., 2011;Waliser et al., 2003), such as the Madden-Julian Oscillation (MJO), which produces rainfall fluctuations with a period of approximately 30-60 days (Madden & Julian, 1994). Accurate representation of the land surface and its interaction with the atmosphere is also key to developing skillful S2S forecasts. The state of the land surface (e.g., root zone soil moisture or leaf area) varies more slowly than the atmospheric state and affects the partitioning of the surface energy budget through changes in evapotranspiration, surface albedo and roughness. The land therefore provides a potential source of S2S predictability to the atmosphere (Dirmeyer

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability

Harris

Taylor

Weedon

et al. 2022

Geophysical Research Letters

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Surface‐driven amplification of Madden–Julian oscillation circulation anomalies across East Africa and its influence on the Turkana jet

Talib

Taylor

Harris

et al. 2023

Quart J Royal Meteoro Soc

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In semi‐arid environments, rainfall‐driven soil moisture fluctuations exert a strong influence on surface turbulent fluxes. Intraseasonal rainfall variability can therefore impact low‐level atmospheric temperatures and influence regional circulations. Using satellite observations and an atmospheric reanalysis, we investigate whether rainfall variability induced by the Madden–Julian oscillation (MJO) triggers land–atmosphere feedbacks across East Africa. We identify that surface fluxes during the East African wet seasons (March–May and October–December) are sensitive to MJO‐induced precipitation variations across low‐lying regions of South Sudan and highland regions of Uganda and southwest Kenya. For example, during MJO phases 6 to 8, when rainfall is suppressed, surface temperatures and sensible heat fluxes increase, whilst evapotranspiration decreases. Spatial variations in the surface flux response to rainfall variability feed back onto the atmosphere through amplifying MJO‐associated pressure anomalies. During dry MJO events for instance, surface warming across the exit region of the Turkana channel increases the low‐tropospheric along‐channel pressure gradient and intensifies the Turkana jet. We conclude that average surface‐driven temperature fluctuations during a single day are responsible for approximately 12% of MJO‐associated variability of the Turkana jet speed. However, we expect that the accumulation of heat over multiple days to the west of the East African Highlands further amplifies anomalies in the pressure gradient and jet intensity. Modelling experiments are required to quantify the accumulated impact of the surface forcing. Surface‐driven Turkana jet variations influence the East African moisture budget and affect the intensity and inland propagation of coastal convection. Not only is this the first study to investigate the importance of intraseasonal land–atmosphere feedbacks across East Africa, but it is also the first to show that Turkana jet characteristics are partly driven by surface conditions. This work motivates an investigation into whether subseasonal forecast models fully harness the predictability from surface‐induced jet variations.

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Representation of land–atmosphere coupling processes over Africa in coupled model intercomparison project Phase 6

Mwanthi

Mutemi²,

Dyer³

et al. 2023

Clim Dyn

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Climate models are useful tools for monthly to decadal prediction of the evolution of climate. This study assesses how CMIP6 models represent soil moisture-latent heat regimes and coupling processes between the land and atmosphere. Metrics considered are terrestrial and atmospheric coupling indices to show the nature and strength of the coupling over Africa, focusing on the March to May (MAM) and June to August (JJA) seasons over East, Central, and West Africa. Characterization of the annual cycle indicates that model biases are highest during the peak of the rainfall season and least during the dry season, while soil moisture biases correspond with rainfall. Models show appreciable sensitivity to regional characteristics; there was model consensus in representing East Africa and the Sahel as regions of limited soil moisture, while major differences were noted in the wet regime over Central Africa. Most CMIP6 models tend to overestimate the strength of the terrestrial and atmospheric coupling pathways over East and Southern Africa. Inter-model differences in coupling indices could be traced to their inter-annual variability rather than the mean biases of the variables considered. These results encourage further advancement of land surface schemes in the next generation of climate models for a better representation of climate over Africa.

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The sensitivity of the West African monsoon circulation to intraseasonal soil moisture feedbacks

Cited by 12 publications

References 113 publications

Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability

Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability

Surface‐driven amplification of Madden–Julian oscillation circulation anomalies across East Africa and its influence on the Turkana jet

Representation of land–atmosphere coupling processes over Africa in coupled model intercomparison project Phase 6

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