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Samantha Ferrett
,
John Methven
,
Steven J. Woolnough
,
Gui-Ying Yang
,
Christopher E. Holloway
, and
Gabriel Wolf

Abstract

Equatorial waves are a major driver of widespread convection in Southeast Asia and the tropics more widely, a region in which accurate heavy rainfall forecasts are still a challenge. Conditioning rainfall over land on local equatorial wave phases finds that heavy rainfall can be between 2 and 4 times more likely to occur in Indonesia, Malaysia, Vietnam, and the Philippines. Equatorial waves are identified in a global numerical weather prediction ensemble forecast [Met Office Global and Regional Ensemble Prediction System (MOGREPS-G)]. Skill in the ensemble forecast of wave activity is highly dependent on region and time of year, although generally forecasts of equatorial Rossby waves and westward-moving mixed Rossby–gravity waves are substantially more skillful than for the eastward-moving Kelvin wave. The observed statistical relationship between wave phases and rainfall is combined with ensemble forecasts of dynamical wave fields to construct hybrid dynamical–statistical forecasts of rainfall probability using a Bayesian approach. The Brier skill score is used to assess the skill of forecasts of rainfall probability. Skill in the hybrid forecasts can exceed that of probabilistic rainfall forecasts taken directly from MOGREPS-G and can be linked to both the skill in forecasts of wave activity and the relationship between equatorial waves and heavy rainfall in the relevant region. The results show that there is potential for improvements of forecasts of high-impact weather using this method as forecasts of large-scale waves improve.

Open access
Mohd Fadzil Firdzaus Mohd Nor
,
Christopher E. Holloway
, and
Peter M. Inness

Abstract

Severe rainfall events are common in western Peninsular Malaysia. They are usually short and intense, and occasionally cause flash floods and landslides. Forecasting these local events is difficult and understanding the mechanisms of the rainfall events is vital for the advancement of tropical weather forecasting. This study investigates the mechanisms responsible for a local heavy rainfall event on 2 May 2012 that caused flash floods and landslides using both observations and simulations with the limited-area high-resolution Met Office Unified Model (MetUM). Results suggest that previous day rainfalls over Peninsular Malaysia and Sumatra Island influenced the development of overnight rainfall over the Strait of Malacca by low-level flow convergence. Afternoon convection over the Titiwangsa Mountains over Peninsular Malaysia then induced rainfall development and the combination of these two events influenced the development of severe convective storm over western Peninsular Malaysia. Additionally, anomalously strong low-level northwesterlies also contributed to this event. Sensitivity studies were carried out to investigate the influence of the local orography on this event. Flattened Peninsular Malaysia orography causes a lack of rainfall over the central part of Peninsular Malaysia and Sumatra Island and produces a weaker overnight rainfall over the Strait of Malacca. By removing Sumatra Island in the final experiment, the western and inland parts of Peninsular Malaysia would receive more rainfall, as this region is more influenced by the westerly wind from the Indian Ocean. These results suggest the importance of the interaction between landmasses, orography, low-level flow, and the diurnal cycle on the development of heavy rainfall events.

Free access
Xiaoqing Liao
,
Christopher E. Holloway
,
Xiangbo Feng
,
Chunlei Liu
,
Xinyu Lyu
,
Yufeng Xue
,
Ruijuan Bao
,
Jiandong Li
, and
Fangli Qiao

Abstract

There are no well-accepted mechanisms that can explain the annual frequency of tropical cyclones (TCs) both globally and in individual ocean basins. Recent studies using idealized models showed that the climatological frequency of TC genesis (TCG) is proportional to the Coriolis parameter associated with the intertropical convergence zone (ITCZ) position. In this study, we investigate the effect of the ITCZ position on TCG on the interannual time scale using observations over 1979–2020. Our results show that the TCG frequency is significantly correlated with the ITCZ position in the North Atlantic (NA) and western North Pacific (WNP), with more TCG events in years when the ITCZ is farther poleward. The ITCZ–TCG relationship in NA is dominated by TCG events in the tropics (0°–20°N), while the relationship in WNP is due to TCs formed in the east sector (140°E–180°). We further confirmed that ENSO has little effect on the ITCZ–TCG relationship despite the fact that it can affect the ITCZ position and TCG frequency separately. In NA and WNP, a poleward shift of ITCZ is significantly associated with large-scale environment changes favoring TCG in the main development region (MDR). However, the basinwide TCG frequency has a weak relationship with the ITCZ in other ocean basins. We showed that a poleward ITCZ in the eastern North Pacific and South Pacific favors TCG on the poleward flank of the MDR, while it suppresses TCG on the equatorward flank, leading to insignificant change in the basinwide TCG frequency. In the south Indian Ocean, the ITCZ position has weak effect on TCG frequency due to the mixed influences of environmental conditions.

Open access
Godwin Ayesiga
,
Christopher E. Holloway
,
Charles J. R. Williams
,
Gui-Ying Yang
,
Rachel Stratton
, and
Malcolm Roberts

Abstract

Observational studies have shown the link between convectively coupled Kelvin waves (CCKWs) and eastward-propagating rainfall anomalies. We explore the mechanisms in which CCKWs modulate the propagation of precipitation from west to east over equatorial Africa. We examine a multiyear state-of-the-art Africa-wide climate simulation from a convection-permitting model (CP4A) along with a parameterized global driving-model simulation (G25) and evaluate both against observations (TRMM) and ERA-Interim (ERA-I), with a focus on precipitation and Kelvin wave activity. We show that the two important related processes through which CCKWs influence the propagation of convection and precipitation from west to east across equatorial Africa are 1) low-level westerly wind anomalies that lead to increased low-level convergence, and 2) westerly moisture flux anomalies that amplify the lower- to midtropospheric specific humidity. We identify Kelvin wave activity using zonal wind and geopotential height. Using lagged composite analysis, we show that modeled precipitation over equatorial Africa can capture the eastward-propagating precipitation signal that is associated with CCKWs. Composite analysis on strong (high-amplitude) CCKWs shows that both CP4A and G25 capture the connection between the eastward-propagating precipitation anomalies and CCKWs. In comparison to TRMM, however, the precipitation signal is weaker in G25, while CP4A has a more realistic signal. Results show that both CP4A and G25 generally simulate the key horizontal structure of CCKWs, with anomalous low-level westerlies in phase with positive precipitation anomalies. These findings suggest that for operational forecasting, it is important to monitor the day-to-day Kelvin wave activity across equatorial Africa.

Full access
Jian-Feng Gu
,
Robert Stephen Plant
,
Christopher E. Holloway
,
Todd R. Jones
,
Alison Stirling
,
Peter A. Clark
,
Steven J. Woolnough
, and
Thomas L. Webb

Abstract

In this study, bulk mass flux formulations for turbulent fluxes are evaluated for shallow and deep convection using large-eddy simulation data. The bulk mass flux approximation neglects two sources of variability: the interobject variability due to differences between the average properties of different cloud objects, and the intraobject variability due to perturbations within each cloud object. Using a simple cloud–environment decomposition, the interobject and intraobject contributions to the heat flux are comparable in magnitude with that from the bulk mass flux approximation, but do not share a similar vertical distribution, and so cannot be parameterized with a rescaling method. A downgradient assumption is also not appropriate to parameterize the neglected flux contributions because a nonnegligible part is associated with nonlocal buoyant structures. A spectral analysis further suggests the presence of fine structures within the clouds. These points motivate investigations in which the vertical transports are decomposed based on the distribution of vertical velocity. As a result, a “core-cloak” conceptual model is proposed to improve the representation of total vertical fluxes, composed of a strong and a weak draft for both the updrafts and downdrafts. It is shown that the core-cloak representation can well capture the magnitude and vertical distribution of heat and moisture fluxes for both shallow and deep convection.

Open access
Nicholas P. Klingaman
,
Matthew Young
,
Amulya Chevuturi
,
Bruno Guimaraes
,
Liang Guo
,
Steven J. Woolnough
,
Caio A. S. Coelho
,
Paulo Y. Kubota
, and
Christopher E. Holloway

Abstract

Skillful and reliable predictions of week-to-week rainfall variations in South America, two to three weeks ahead, are essential to protect lives, livelihoods, and ecosystems. We evaluate forecast performance for weekly rainfall in extended austral summer (November–March) in four contemporary subseasonal systems, including a new Brazilian model, at 1–5-week leads for 1999–2010. We measure performance by the correlation coefficient (in time) between predicted and observed rainfall; we measure skill by the Brier skill score for rainfall terciles against a climatological reference forecast. We assess unconditional performance (i.e., regardless of initial condition) and conditional performance based on the initial phase of the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO). All models display substantial mean rainfall biases, including dry biases in Amazonia and wet biases near the Andes, which are established by week 1 and vary little thereafter. Unconditional performance extends to week 2 in all regions except for Amazonia and the Andes, but to week 3 only over northern, northeastern, and southeastern South America. Skill for upper- and lower-tercile rainfall extends only to week 1. Conditional performance is not systematically or significantly higher than unconditional performance; ENSO and MJO events provide limited “windows of opportunity” for improved S2S predictions that are region and model dependent. Conditional performance may be degraded by errors in predicted ENSO and MJO teleconnections to regional rainfall, even at short lead times.

Open access
Samantha Ferrett
,
Thomas H. A. Frame
,
John Methven
,
Christopher E. Holloway
,
Stuart Webster
,
Thorwald H. M. Stein
, and
Carlo Cafaro

Abstract

Forecasting rainfall in the tropics is a major challenge for numerical weather prediction. Convection-permitting (CP) models are intended to enable forecasts of high-impact weather events. Development and operation of these models in the tropics has only just been realized. This study describes and evaluates a suite of recently developed Met Office Unified Model CP ensemble forecasts over three domains in Southeast Asia, covering Malaysia, Indonesia, and the Philippines. The fractions skill score is used to assess the spatial scale dependence of skill in forecasts of precipitation during October 2018–March 2019. CP forecasts are skillful for 3-h precipitation accumulations at spatial scales greater than 200 km in all domains during the first day of forecasts. Skill decreases with lead time but varies depending on time of day over Malaysia and Indonesia, due to the importance of the diurnal cycle in driving rainfall in those regions. Skill is largest during daytime when precipitation is over land and is constrained by orography. Comparison of CP ensembles using 2.2-, 4.5-, and 8.8-km grid spacing and an 8.8-km ensemble with parameterized convection reveals that varying resolution has much less effect on ensemble skill and spread than the representation of convection. The parameterized ensemble is less skillful than CP ensembles over Malaysia and Indonesia and more skillful over the Philippines; however, the parameterized ensemble has large drops in skill and spread related to deficiencies in its diurnal cycle representation. All ensembles are underspread indicating that future model development should focus on this issue.

Full access
Peter A. Bieniek
,
Uma S. Bhatt
,
Richard L. Thoman
,
Heather Angeloff
,
James Partain
,
John Papineau
,
Frederick Fritsch
,
Eric Holloway
,
John E. Walsh
,
Christopher Daly
,
Martha Shulski
,
Gary Hufford
,
David F. Hill
,
Stavros Calos
, and
Rudiger Gens

Abstract

Alaska encompasses several climate types because of its vast size, high-latitude location, proximity to oceans, and complex topography. There is a great need to understand how climate varies regionally for climatic research and forecasting applications. Although climate-type zones have been established for Alaska on the basis of seasonal climatological mean behavior, there has been little attempt to construct climate divisions that identify regions with consistently homogeneous climatic variability. In this study, cluster analysis was applied to monthly-average temperature data from 1977 to 2010 at a robust set of weather stations to develop climate divisions for the state. Mean-adjusted Advanced Very High Resolution Radiometer surface temperature estimates were employed to fill in missing temperature data when possible. Thirteen climate divisions were identified on the basis of the cluster analysis and were subsequently refined using local expert knowledge. Divisional boundary lines were drawn that encompass the grouped stations by following major surrounding topographic boundaries. Correlation analysis between station and gridded downscaled temperature and precipitation data supported the division placement and boundaries. The new divisions north of the Alaska Range were the North Slope, West Coast, Central Interior, Northeast Interior, and Northwest Interior. Divisions south of the Alaska Range were Cook Inlet, Bristol Bay, Aleutians, Northeast Gulf, Northwest Gulf, North Panhandle, Central Panhandle, and South Panhandle. Correlations with various Pacific Ocean and Arctic climatic teleconnection indices showed numerous significant relationships between seasonal division average temperature and the Arctic Oscillation, Pacific–North American pattern, North Pacific index, and Pacific decadal oscillation.

Full access