Kevin J. E. Walsh

Prof. Kevin J. E. Walsh


Research Focus & Metrics

Academic Career Length

38Years (1989-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 November 2015 in Wires Climate Change
Verified
Journal Article
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PDF file
KWKevin J. E. Walsh
Kevin J. E. Walsh
JMJohn L. McBride
John L. McBride
PKPhilip J. Klotzbach
Philip J. Klotzbach
SBSethurathinam Balachandran
Sethurathinam Balachandran
SCSuzana J. Camargo
Suzana J. Camargo
MSMasato Sugi
Masato Sugi

15 May 2007 in Journal of Climate
Verified
Journal Article
Open access
KWKevin J. E. Walsh
Kevin J. E. Walsh
MFM. Fiorino
M. Fiorino
CLC. W. Landsea
C. W. Landsea
KMKathleen Mcinnes
Kathleen Mcinnes
Objectively derived resolution-dependent criteria are defined for the detection of tropical cyclones in model simulations and observationally based analyses. These criteria are derived from the wind profiles of observed tropical cyclones, averaged at various resolutions. Both an analytical wind profile model and two-dimensional observed wind analyses are used. The results show that the threshold wind speed of an observed tropical cyclone varies roughly linearly with resolution. The criteria derived here are compared to the numerous different criteria previously employed in climate model simulations. The resulting method provides a simple means of comparing climate model simulations and reanalyses.

1 June 2015 in Bulletin of the American Meteorological Society
Verified
Journal Article
Closed access
KWKevin J. E. Walsh
Kevin J. E. Walsh
SCSuzana J. Camargo
Suzana J. Camargo
GVGabriel A. Vecchi
Gabriel A. Vecchi
ADAnne Sophie Daloz
Anne Sophie Daloz
JEJames Elsner
James Elsner
NHNaomi Henderson
Naomi Henderson
While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results from other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.

1 October 2003 in Natural Hazards
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Journal Article
Closed access
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KMKathleen Mcinnes
Kathleen Mcinnes
KWKevin J. E. Walsh
Kevin J. E. Walsh
GHG. D. Hubbert
G. D. Hubbert
TBT. Beer
T. Beer

15 January 2011 in Journal of Climate
Verified
Journal Article
Open access
SRSurendra P. Rauniyar
Surendra P. Rauniyar
KWKevin J. E. Walsh
Kevin J. E. Walsh
The influence of the MJO on the phase and amplitude of the diurnal cycle of rainfall during Australian summer [December–February (DJF)] over the Maritime Continent (MC) and northern Australia is investigated using the Tropical Rainfall Measuring Mission (TRMM) 3B42 and 3G68 datasets. The gridded rainfall was partitioned into MJO categories (active, suppressed, and weak) based on their longitudinal position and by utilizing the real-time multivariate MJO (RMM) index of Wheeler and Hendon. The diurnal cycles were composited and an empirical orthogonal function (EOF) analysis was applied to extract the spatial and temporal variability. Distinct variations in the rainfall distribution pattern among categories of the MJO over land and ocean are seen. The result of the composite-mean rainfall distribution shows that the average daily rainfall rate over islands is higher during suppressed MJO days, while for surrounding oceans and northern regions of Australia, more rainfall occurs during MJO active days. The normalized relative amplitude (NRA) of the diurnal cycle of rainfall shows that morning rainfall near coastal areas during active days of the MJO is 1.5 times greater than the climatological-mean rainfall but is less than or equal to the climatological mean during other phases of the MJO. Similarly, during the suppressed phase of the MJO evening rainfall is greater over the islands than in other MJO phases. The first two modes of the EOF alone explain more than 88% (65%) of the variance for the 3B42 (3G68) rainfall, and the corresponding principal component time series show a marked diurnal cycle. The results show that both the amplitude and phase of the diurnal cycle of rainfall are modulated by the categories of the MJO. In general, the peak in the diurnal cycle for active (suppressed/weak) days of the MJO lags (leads) the peak in the diurnal cycle for total rainfall by 2 h. Over Darwin and its adjacent regions, the active phase of the MJO is responsible for the occurrence of maximum rainfall after midnight, which is unusual in this region.

1 July 2009 in Quaternary Science Reviews
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Journal Article
Closed access
JNJonathan Nott
Jonathan Nott
SSScott Smithers
Scott Smithers
KWKevin J. E. Walsh
Kevin J. E. Walsh
EREd Rhodes
Ed Rhodes