Precipitation‐Moisture Coupling Over Tropical Oceans: Sequential Roles of Shallow, Deep, and Mesoscale Convective Systems

Chen, Xingchao; Leung, L. Ruby; Feng, Zhe; Yang, Qidong

doi:10.1029/2022gl097836

Cited by 10 publications

(18 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The rapid pickup in MCS lifetime rainfall with the lower-free-tropospheric specific humidity is similar to the observed rapid increase in tropical oceanic precipitation when the environmental column saturation fraction (CSF) is higher than ∼0.7 (Bretherton et al, 2004), which is closely related to the rapid enhancement of MCS rainfall as the environment is near saturation (X. Chen, Leung, Feng, & Yang, 2022;Schiro et al, 2020;Wolding et al, 2020). The observed nonlinear increase in MCS mean area with lower-free-tropospheric specific humidity is also consistent with the observed nonlinear increase in stratiform rain area with CSF as highlighted in Ahmed and Schumacher (2015).…”

Section: Conclusion and Discussionsupporting

confidence: 59%

Environmental Controls on MCS Lifetime Rainfall Over Tropical Oceans

Chen,

Leung,

Feng

et al. 2023

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

Mesoscale convective systems (MCSs) contribute a majority of rainfall over tropical oceans. However, our understanding of the environmental controls on tropical oceanic MCS precipitation remains incomplete. Using 20‐year of satellite observations, reanalysis data, and MCS tracking, we found that MCSs initiating in a mesoscale environment with enhanced lower‐free‐tropospheric moisture, warmer middle troposphere, stronger low‐level ascent, and stronger deep‐layer (surface‐400 hPa) wind shear tend to produce more precipitation during their lifetimes. While most of these environmental factors are correlated with one another, the deep‐layer shear is not. A rapid pickup in MCS lifetime rainfall is found when the lower‐free‐tropospheric specific humidity exceeds 10 g kg−1. This nonlinearity is mostly dominated by the nonlinear increase in MCS area. On the other hand, both MCS area and rain rate increase quasi‐linearly with the deep‐layer shear. The increase in rain rate is related to the enhancement of heavy precipitating convective activity with deep‐layer shear.

show abstract

Section: Conclusion and Discussionsupporting

confidence: 59%

Environmental Controls on MCS Lifetime Rainfall Over Tropical Oceans

Chen,

Leung,

Feng

et al. 2023

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

show abstract

“…(2021) and Chen et al. (2022) is used to investigate the precipitating systems over the BoB. In this method, the hourly 0.1° × 0.1° Integrated Multi‐Satellite Retrievals for Global Precipitation Measurement (GPM) mission (IMERG, Huffman et al., 2019, 2020; Tan et al., 2019) Version 6 precipitation data and the half hourly 4‐km global merged geostationary satellite (Janowiak et al., 2017) infrared brightness temperature ( T b ) data from the National Oceanic and Atmospheric Administration (NOAA) and National Centers for Environmental Prediction (NCEP) are used to identify and track the cloud systems, and subsequently divide them into different types.…”

Section: Methodsmentioning

confidence: 95%

“…Hence, the finding in Table 1 highlights the important role of the lower‐free‐tropospheric moisture in the MCS initiation. Higher lower‐free‐tropospheric moisture limits the negative effects of dry‐air entrainment on the plume buoyancy and facilitates the initiation and organization of tropical MCSs (e.g., Chen et al., 2022; Schiro & Neelin, 2019; Wolding et al., 2020).…”

Section: Physical Mechanisms Responsible For the Diurnal Mcs Initiationmentioning

confidence: 99%

Warm‐Season Afternoon Precipitation Peak in the Central Bay of Bengal: Process‐Oriented Diagnostics

Peng

Chen

2023

JGR Atmospheres

Self Cite

View full text Add to dashboard Cite

Precipitation over the tropical open oceans (i.e., areas at least 200 km away from coastlines) generally shows a diurnal cycle that peaks in the early morning (Dai, 2001;Mapes & Houze, 1993;Yang & Slingo, 2001;Zuidema, 2003). Previous studies have indicated that the early-morning precipitation peak is closely related to diurnal radiative effects (e.g., Gray & Jacobson, 1977;Liu & Moncrieff, 1998;Randall et al., 1991). During the nighttime, net radiative cooling at the cloud top is stronger than that below the cloud base. This process destabilizes the atmosphere and provides a favorable thermodynamical condition for the initiation and development of nocturnal convection (i.e., lapse rate mechanism, Liu & Moncrieff, 1998;Randall et al., 1991). Additionally, different radiative cooling intensities between the cloudy and clear-sky regions enhance the convergence below clouds, thus facilitates the development of nocturnal convection (i.e., differential radiation mechanism, Gray & Jacobson, 1977). Unlike most tropical open oceans with early-morning precipitation peaks, some have a prominent afternoon precipitation peak. Most of these areas are partially enclosed by coastlines, such as the open oceans between northwestern South America and the isthmus of Central America, the Gulf of Guinea, the South China Sea, and the Bay of Bengal (the BoB hereafter; Johnson, 2010). Among these areas, the BoB has been most extensively investigated due to its strong precipitation intensity.

show abstract

“…The unified Noah land surface physics scheme (F. Chen & Dudhia, 2001 ) handles surface process and the Yonsei University (YSU) boundary layer scheme (Hong et al., 2006 ) is employed. No cumulus parameterization is employed because many studies have demonstrated that the 9‐km grid spacing is sufficient to resolve tropical mesoscale convective systems over the region (Chan & Chen, 2022 ; Chan, Zhang, et al., 2020 ; X. Chen, Leung, Feng, & Song, 2021 ; X. Chen, Leung, Feng, Song, & Yang, 2021 ; X. Chen, Pauluis, Leung, & Zhang, 2018 ; X. Chen, Pauluis, & Zhang, 2018 ; X. Chen & Zhang, 2019 ; X. Chen et al., 2020 ; X. Chen et al., 2022 ; S. Wang et al., 2015 ; Ying & Zhang, 2017 , 2018 ; F. Zhang et al., 2017 ).…”

Section: Methodsmentioning

confidence: 99%

The Potential Benefits of Handling Mixture Statistics via a Bi‐Gaussian EnKF: Tests With All‐Sky Satellite Infrared Radiances

Chan

Chen

Anderson

2023

J Adv Model Earth Syst

Self Cite

View full text Add to dashboard Cite

The meteorological characteristics of cloudy atmospheric columns can be very different from their clear counterparts. Thus, when a forecast ensemble is uncertain about the presence/absence of clouds at a specific atmospheric column (i.e., some members are clear while others are cloudy), that column's ensemble statistics will contain a mixture of clear and cloudy statistics. Such mixtures are inconsistent with the ensemble data assimilation algorithms currently used in numerical weather prediction. Hence, ensemble data assimilation algorithms that can handle such mixtures can potentially outperform currently used algorithms. In this study, we demonstrate the potential benefits of addressing such mixtures through a bi-Gaussian extension of the ensemble Kalman filter (BGEnKF). The BGEnKF is compared against the commonly used ensemble Kalman filter (EnKF) using perfect model observing system simulated experiments (OSSEs) with a realistic weather model (the Weather Research and Forecast model). Synthetic all-sky infrared radiance observations are assimilated in this study. In these OSSEs, the BGEnKF outperforms the EnKF in terms of the horizontal wind components, temperature, specific humidity, and simulated upper tropospheric water vapor channel infrared brightness temperatures. This study is one of the first to demonstrate the potential of a Gaussian mixture model EnKF with a realistic weather model. Our results thus motivate future research toward improving numerical Earth system predictions though explicitly handling mixture statistics. Plain Language SummaryThe accuracy of a computer weather forecast often depends on the accuracy of the information inputted into the computer forecast system. The accuracy of the input in turn depends on the accuracy of the input-constructing algorithm. Such algorithms often use probabilistic forecasts from an earlier point in time and current atmospheric measurements to construct the inputs. A common assumption in such algorithms is that the probabilistic forecasts follow a multivariate normal distribution (henceforth called the normality assumption). However, in the frequent situation where the probabilistic forecast is uncertain about the presence/absence of clouds, the normality assumption is violated. This is because clear atmospheric columns and cloudy atmospheric columns have distinctly different thermodynamic and dynamic characteristics. These two types of columns thus have different statistics. As such, when a probabilistic forecast is uncertain about the presence/absence of clouds, it has mixed statistics (henceforth termed mixed probabilistic forecast). Addressing such mixtures can potentially improve forecasts. In this study, we propose a new input-constructing algorithm that can explicitly handle mixed probabilistic forecasts. This new algorithm is nearly as fast as currently available algorithms. More importantly, our experiments demonstrate that our new algorithm can produce more accurate forecast inputs than an existing popular algorithm. Our work thus suggests that...

show abstract

Precipitation‐Moisture Coupling Over Tropical Oceans: Sequential Roles of Shallow, Deep, and Mesoscale Convective Systems

Cited by 10 publications

References 52 publications

Environmental Controls on MCS Lifetime Rainfall Over Tropical Oceans

Environmental Controls on MCS Lifetime Rainfall Over Tropical Oceans

Warm‐Season Afternoon Precipitation Peak in the Central Bay of Bengal: Process‐Oriented Diagnostics

The Potential Benefits of Handling Mixture Statistics via a Bi‐Gaussian EnKF: Tests With All‐Sky Satellite Infrared Radiances

Contact Info

Product

Resources

About