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Vincent Moron
,
Renaud Barbero
,
Jason P. Evans
,
Seth Westra
, and
Hayley J. Fowler

Abstract

Six weather types (WTs) are computed for tropical Australia during the wet season (November–March 1979–2015) using cluster analysis of 6-hourly low-level winds at 850 hPa. The WTs may be interpreted as a varying combination of at least five distinct phenomena operating at different time scales: the diurnal cycle, fast and recurrent atmospheric phenomena such as transient low pressure, the intraseasonal Madden–Julian oscillation, the annual cycle, and interannual variations mostly associated with El Niño–Southern Oscillation. The WTs are also strongly phase-locked onto the break/active phases of the monsoon; two WTs characterize mostly the trade-wind regime prevalent either at the start and the end of the monsoon or during its breaks, while three monsoonal WTs occur mostly during its core and active phases. The WT influence is strongest for the frequency of wet spells, while the influence on intensity varies according to the temporal aggregation of the rainfall. At hourly time scale, the climatological mean wet intensity tends to be near-constant in space and not systematically larger for the monsoonal WTs compared to other WTs. Nevertheless, one transitional WT, most prevalent around late November and characterized by weak synoptic forcings and overall drier conditions than the monsoonal WTs, is associated with an increased number of high hourly rainfall intensities for some stations, including for the interior of the Cape York Peninsula. When the temporal aggregation exceeds 6–12 h, the mean intensity tends to be larger for some of the monsoonal WTs, in association with more frequent and also slightly longer wet spells.

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C. M. Holgate
,
J. P. Evans
,
A. I. J. M. van Dijk
,
A. J. Pitman
, and
G. Di Virgilio

Abstract

The relative importance of atmospheric advection and local land–atmosphere coupling to Australian precipitation is uncertain. Identifying the evaporative source regions and level of precipitation recycling can help quantify the importance of local and remote marine and terrestrial moisture to precipitation within the different hydroclimates across Australia. Using a three-dimensional Lagrangian back-trajectory approach, moisture from precipitation events across Australia during 1979–2013 was tracked to determine the source of moisture (the evaporative origin) and level of precipitation recycling. We show that source regions vary markedly for precipitation falling in different regions. Advected marine moisture was relatively more important than terrestrial contributions for precipitation in all regions and seasons. For Australia as a whole, contributions from precipitation recycling varied from ~11% in winter up to ~21% in summer. The strongest land–atmosphere coupling was in the northwest and southeast where recycled local land evapotranspiration accounted for an average of 9% of warm-season precipitation. Marine contributions to precipitation in the northwest of Australia increased in spring and, coupled with positive evaporation trends in the key source regions, suggest that the observed precipitation increase is the result of intensified evaporation in the Maritime Continent and Indian and Pacific Oceans. Less clear were the processes behind an observed shift in moisture contribution from winter to summer in southeastern Australia. Establishing the climatological source regions and the magnitude of moisture recycling enables future investigation of anomalous precipitation during extreme periods and provides further insight into the processes driving Australia’s variable precipitation.

Free access
K. J. Evans
,
P. H. Lauritzen
,
S. K. Mishra
,
R. B. Neale
,
M. A. Taylor
, and
J. J. Tribbia

Abstract

The authors evaluate the climate produced by the Community Climate System Model, version 4, running with the new spectral element atmospheric dynamical core option. The spectral element method is configured to use a cubed-sphere grid, providing quasi-uniform resolution over the sphere and increased parallel scalability and removing the need for polar filters. It uses a fourth-order accurate spatial discretization that locally conserves mass and total energy. Using the Atmosphere Model Intercomparison Project protocol, the results from the spectral element dynamical core are compared with those produced by the default finite-volume dynamical core and with observations. Even though the two dynamical cores are quite different, their simulated climates are remarkably similar. When compared with observations, both models have strengths and weaknesses but have nearly identical root-mean-square errors and the largest biases show little sensitivity to the dynamical core. The spectral element core does an excellent job reproducing the atmospheric kinetic energy spectra, including fully capturing the observed Nastrom–Gage transition when running at 0.125° resolution.

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Dynamical Characteristics of Drought in the Caribbean from Observations and Simulations

Dimitris A. Herrera
,
Toby R. Ault
,
Carlos M. Carrillo
,
John T. Fasullo
,
Xiaolu Li
,
Colin P. Evans
,
Marc J. Alessi
, and
Natalie M. Mahowald

Abstract

Climate models consistently project a significant drying in the Caribbean during climate change, and between 2013 and 2016 the region experienced the worst multiyear drought in the historical period. Although dynamical mechanisms have been proposed to explain drought in the Caribbean, the contributions from mass convergence and advection to precipitation minus evaporation (PE) anomalies during drought are unknown. Here we analyze the dynamics of contemporaneous droughts in the Caribbean by decomposing the contributions of mass convergence and advection to PE using observational and simulated data. We find that droughts arise from an anomalous subsidence over the southeastern Caribbean and northeastern South America. Although the contributions from mass convergence and advection vary across the region, it is mass convergence that is the main driver of drought in our study area. A similar dynamical pattern is observed in simulated droughts using the Community Earth System Model (CESM) Large Ensemble (LENS).

Open access
H. W. Barker
,
G. L. Stephens
,
P. T. Partain
,
J. W. Bergman
,
B. Bonnel
,
K. Campana
,
E. E. Clothiaux
,
S. Clough
,
S. Cusack
,
J. Delamere
,
J. Edwards
,
K. F. Evans
,
Y. Fouquart
,
S. Freidenreich
,
V. Galin
,
Y. Hou
,
S. Kato
,
J. Li
,
E. Mlawer
,
J.-J. Morcrette
,
W. O'Hirok
,
P. Räisänen
,
V. Ramaswamy
,
B. Ritter
,
E. Rozanov
,
M. Schlesinger
,
K. Shibata
,
P. Sporyshev
,
Z. Sun
,
M. Wendisch
,
N. Wood
, and
F. Yang

Abstract

The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended?

One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport algorithms, were submitted by 22 groups. Benchmark, domain-averaged irradiance profiles were computed by the MC codes. For the clear and overcast cases, all MC estimates of top-of-atmosphere albedo, atmospheric absorptance, and surface absorptance agree with one of the LBL codes to within ±2%. Most 1D codes underestimate atmospheric absorptance by typically 15–25 W m–2 at overhead sun for the standard tropical atmosphere regardless of clouds.

Depending on assumptions about unresolved clouds, the 1D codes were partitioned into four genres: (i) horizontal variability, (ii) exact overlap of PPH clouds, (iii) maximum/random overlap of PPH clouds, and (iv) random overlap of PPH clouds. A single MC code was used to establish conditional benchmarks applicable to each genre, and all MC codes were used to establish the full 3D benchmarks. There is a tendency for 1D codes to cluster near their respective conditional benchmarks, though intragenre variances typically exceed those for the clear and overcast cases. The majority of 1D codes fall into the extreme category of maximum/random overlap of PPH clouds and thus generally disagree with full 3D benchmark values. Given the fairly limited scope of these tests and the inability of any one code to perform extremely well for all cases begs the question that a paradigm shift is due for modeling 1D solar fluxes for cloudy atmospheres.

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