Satellite‐based monitoring of intraseasonal variations in tropical Pacific and Atlantic convection

Evans, Jenni L.; Jaskiewicz, Francine A.

doi:10.1029/1999gl011259

Cited by 9 publications

(7 citation statements)

References 18 publications

(13 reference statements)

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“…We use a critical threshold of OLR < 220 W m -2 to diagnose regions of deep convection; this threshold is intermediate between that used by Graham and Barnett (1987) and in other studies of organised convection (e.g. Evans and Shemo 1996;Evans and Jaskiewicz 2001). Sensitivity analyses for the choice of OLR critical threshold were performed using a variety of summary statistics (see below): they confirm that our results are stable across both the range of OLR threshold values used in earlier studies and the choice of reference statistic for identifying the threshold SST.…”

Section: Analysis Methodologymentioning

confidence: 99%

See 1 more Smart Citation

A variable sea surface temperature threshold for tropical convection.

Evans¹,

Webster²

2014

AMOJ

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Sea surface temperatures (SSTs) contribute to modulation of deep convection over tropical oceans. Using a threshold value of outgoing long-wave radiation (OLR) as a proxy for deep tropical convection, regional and temporal relationships between SST and deep convection and its variability are examined.Based on this approach, an SST threshold of 27.5°C for deep convection across the global tropics is identified; this is in agreement with the critical SST of around 27°C for the onset of tropical deep convection identified in previous studies. Monthly and regional variations in the critical SST threshold (SST MON-CRIT ) required for the onset of deep tropical convection are also identified. SST MON-CRIT exhibits interannual and seasonal variations for each of the monsoon regions analysed here. It varies between regions consistent with the mean SST of that region, so is higher in the Pacific than the Atlantic. Further, within a region, the critical SST threshold for convection is cooler in the wet season than the dry. The threshold SST in each region is generally a good proxy for convective activity in the wet season, but this connection breaks down in the dry season. The impact of atmospheric divergence in suppressing convection is much more evident in the dry season. Thus, the applicability of SST as a predictor of convection varies with atmospheric forcing, by region and by season and so we conclude that an absolute SST threshold is not a robust metric for tropical deep convection. Theses results have implications for understanding the distribution of tropical cyclogenesis in varied climate regimes.

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Section: Analysis Methodologymentioning

confidence: 99%

“…Malkus 1963;Evans and Jaskiewicz 2001;Zhou andCui 2008, Hoyos andWebster 2012). Sea surface temperatures (SSTs) play an important role in modulating convection over tropical oceans (e.g.…”

Section: Introductionmentioning

confidence: 99%

A variable sea surface temperature threshold for tropical convection.

Evans¹,

Webster²

2014

AMOJ

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“…Defining an objective standard for the start and end of the wet season is difficult, due to the nature of rainfall in much of the region, which tends to come in the form of large, semi-frequent MCSs, rather than more consistent daily precipitation events (Evans and Jaskiewicz, 2001;Mathon et al, 2002;Núñez Ocasio et al, 2020). A number of different criteria for defining wet seasons have been proposed, including absolute approaches using fixed precipitation values (Stern et al, 1981;Todorov, 1985), relative approaches based of a percentage of the rainfall at the location (Gregory, 1983;Liebmann et al, 2008), and more complex methods, factoring in additional factors, such as evapotranspiration (Hulme, 1987;Boyard-Micheau et al, 2013).…”

Section: Evaluation Metricsmentioning

confidence: 99%

“…Much of the precipitation in the region is convective in nature (Evans and Jaskiewicz, 2001). This precipitation occurs as small-scale convection along the coast, as well as larger and more organized MCSs further inland (Mathon et al, 2002;Núñez Ocasio et al, 2020).…”

Section: Predictor Selectionmentioning

confidence: 99%

Statistical Downscaling for Precipitation Projections in West Africa

Polasky

Evans

Fuentes

2023

Preprint

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The West Africa region (5to 20N and 10E to 20W) is particularly vulnerable to climate change due to a combination of unique geographic features, meteorological conditions, and socio-economic factors. Drastic changes in precipitation (e.g., droughts or floods) in the region can have dramatic impacts on rain-fed agriculture, water availability, and disease risks for the region's population. Quantifying these risks requires localized climate projections at a higher resolution than is generally available from global climate models. Using Self-Organizing Maps, we produce station-based downscaled precipitation projections for medium and high-emission climate scenarios for this region. We find slight increases in precipitation in the coastal areas, and decreases in the interior Sahel region by an average of 10\% by 2100 under the high greenhouse gas-emission scenario of Shared Socioeonomic Pathway 5-8.5. Precipitation decreases in the Sahel are primarily driven by reductions in the number of rainy days during the wet season, rather than by consistent decreases in the magnitude of the precipitation amounts or decreases in the average length of the wet season.

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“…In the second stage, each object at time t is matched to one or more objects at time t + 1 through various methods. The widely used areal overlap method relates objects in consecutive images if they have an area overlap (Boer & Ramanathan, 1997; Evans & Jaskiewicz, 2001; Feng et al., 2021; Huang et al., 2018; Mapes & Houze, 1993; Moseley et al., 2013; Núñez Ocasio et al., 2020b; Tsakraklides & Evans, 2003; Williams & Houze, 1987). The centroid distance method relates objects in consecutive images if the distance between centroids is less than a threshold (Davis et al., 2006b; del Moral et al., 2018; Hayden et al., 2021; Heikenfeld et al., 2019; Woodley et al., 1980).…”

Section: Tracking In Imergmentioning

confidence: 99%

Tracking Mesoscale Convective Systems in IMERG and Regional Variability of Their Properties in the Tropics

Rajagopal,

Russell,

Skok

et al. 2023

JGR Atmospheres

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Mesoscale convective systems (MCSs) constitute only a fraction of convective systems in the tropics but significantly impact tropical weather and global climate. Early studies used satellite infrared (IR) data to track MCSs and study their properties but only for a short period due to computing limitations. Though valuable, the IR brightness temperature (Tb)‐derived precipitation properties have biases. The recent availability of Integrated Multi‐satEllite Retrieval for Global (IMERG) precipitation mission rainfall data of lesser bias than IR Tb‐based rainfall and access to high‐performance computers motivated us to track MCSs over global tropics for 10 years, using the Forward in Time (FiT) algorithm. Though IMERG is advantageous, it poses challenges to tracking MCSs due to convective systems connected by light rain areas and resolution differences between contributing passive microwave sensors. The precipitation field is smoothed and normalized to overcome these problems; then, the FiT algorithm identifies MCSs and tracks them. Our results show that MCSs contribute ∼70% of annual precipitation, though they are only ∼7% of all tracked systems. MCSs occur more often over the Amazon basin and Maritime Continent than in central Africa, known for high thunderstorm frequency, highlighting the contrasting convective regimes. The large, long‐lived, and intensely precipitating MCSs occur more often over the ocean than land, except for the Amazon basin. Fast‐moving MCSs often occur over West Africa, the Amazon basin, and the western Pacific, whereas slow‐moving MCSs are common over Colombia and the Maritime Continent.

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Satellite‐based monitoring of intraseasonal variations in tropical Pacific and Atlantic convection

Cited by 9 publications

References 18 publications

A variable sea surface temperature threshold for tropical convection.

A variable sea surface temperature threshold for tropical convection.

Statistical Downscaling for Precipitation Projections in West Africa

Tracking Mesoscale Convective Systems in IMERG and Regional Variability of Their Properties in the Tropics

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