Please login first
Brian Mapes  - - - 
Top co-authors See all
Christopher S. Velden

2372 shared publications

University of Wisconsin - Madison, Space Science and Engineering Center; Madison WI USA

Axel Timmermann

167 shared publications

Masaki Satoh

148 shared publications

Junko Suzuki

135 shared publications

Robert A. Houze

100 shared publications

University of Washington, USA

Publication Record
Distribution of Articles published per year 
(1987 - 2018)
Total number of journals
published in
Publications See all
Article 0 Reads 0 Citations The Meandering Margin of the Meteorological Moist Tropics Brian E. Mapes, Eui Seok Chung, Walter M. Hannah, Hirohiko M... Published: 28 January 2018
Geophysical Research Letters, doi: 10.1002/2017gl076440
DOI See at publisher website
ABS Show/hide abstract
Bimodally-distributed column water vapor (CWV) indicates a well-defined moist regime in the Tropics, above a margin value near 48 kg m-2 in current climate (about 80% of column saturation). Maps reveal this margin as a meandering, sinuous synoptic contour bounding broad plateaus of the moist regime. Within these plateaus, convective storms of distinctly smaller convective and meso scales occur sporadically. Satellite data composites across the poleward-most moving margin reveal its sharpness, despite the crude averaging: precipitation doubles within 100 km, marked by both enhancement and deepening of cloudiness. Transported patches and filaments of the moist regime cause consequential precipitation events within and beyond the Tropics. Distinguishing synoptic flows that cross the margin from flows that move the margin is made possible by a novel satellite-based Lagrangian CWV tendency estimate. Climate models do not reliably reproduce the observed bimodal distribution, so studying the moist mode's maintenance processes and the margin-zone airmass transformations, guided by the Lagrangian tendency product, might importantly constrain model moist process treatments.
Article 0 Reads 4 Citations The climate response of the Indo-Pacific warm pool to glacial sea level Pedro N. Di Nezio, Axel Timmermann, Jessica E. Tierney, Fei‐... Published: 01 June 2016
Paleoceanography, doi: 10.1002/2015pa002890
DOI See at publisher website
ABS Show/hide abstract
Growing climate proxy evidence suggests that changes in sea level are important drivers of tropical climate change on glacial–interglacial time-scales. These paleodata suggest that rainfall patterns over the Indo-Pacific Warm Pool (IPWP) are highly sensitive to the landmass configuration of the Maritime Continent, and that lowered sea level contributed to large-scale drying during the Last Glacial Maximum (LGM, ca. 21,000 years before present). Using the Community Earth System Model Version 1.2 (CESM1) we investigate the mechanisms by which lowered sea level influenced the climate of the IPWP during the LGM. The CESM1 simulations show that, in agreement with previous hypotheses, changes in atmospheric circulation are initiated by the exposure of the Sunda and Sahul shelves. Ocean dynamical processes amplify the changes in atmospheric circulation by increasing the east-west sea-surface temperature (SST) gradient along the equatorial Indian Ocean. The coupled mechanism driving this response is akin to the Bjerknes feedback, and results in a large-scale climatic reorganization over the Indian Ocean with impacts extending from east Africa to the western tropical Pacific. Unlike exposure of the Sunda shelf, exposure of Sahul shelf and the associated changes in surface albedo play a key role because the positive feedback. This mechanism could explain the pattern of dry (wet) eastern (western) Indian Ocean identified in climate proxies and LGM simulations. However, this response also requires a strengthened SST gradient along the equatorial Indian Ocean, a pattern that is not evident in marine paleoreconstructions. Strategies to resolve this issue are discussed.
Article 0 Reads 4 Citations Gregarious convection and radiative feedbacks in idealized worlds B. E. MAPES Published: 18 May 2016
Journal of Advances in Modeling Earth Systems, doi: 10.1002/2016ms000651
DOI See at publisher website
ABS Show/hide abstract
What role does convection play in cloud feedbacks? What role does convective aggregation play in climate? A flurry of recent studies explores “self-aggregation” of moist convection in diverse simulations using explicit convection and interactive radiation. The implications involve upper-level dry areas as infrared windows – the climate system's “radiator fins” (Pierrehumbert 1995). A positive feedback maintains these: Dry columns undergo radiative cooling which drives descent and further drying. If the resulting clumpiness of vapor and cloud fields depends systematically on global temperature, then convective organization could be a climate system feedback. How reconcilable and how relevant are these interesting but idealized studies? This article is protected by copyright. All rights reserved.
Article 0 Reads 3 Citations Development and evaluation of an objective criterion for the real-time prediction of Indian summer monsoon onset in a co... Susmitha Joseph, A. K. Sahai, S. ABHILASH, R. Chattopadhyay,... Published: 01 August 2015
Journal of Climate, doi: 10.1175/jcli-d-14-00842.1
DOI See at publisher website
Article 0 Reads 5 Citations Improved Spread–Error Relationship and Probabilistic Prediction from the CFS-Based Grand Ensemble Prediction System S. ABHILASH, Atul Kumar Sahai, N. Borah, S. Joseph, R. Chatt... Published: 01 July 2015
Journal of Applied Meteorology and Climatology, doi: 10.1175/jamc-d-14-0200.1
DOI See at publisher website
ABS Show/hide abstract
This study describes an attempt to overcome the underdispersive nature of single-model ensembles (SMEs). As an Indo–U.S. collaboration designed to improve the prediction capabilities of models over the Indian monsoon region, the Climate Forecast System (CFS) model framework, developed at the National Centers for Environmental Prediction (NCEP-CFSv2), is selected. This article describes a multimodel ensemble prediction system, using a suite of different variants of the CFSv2 model to increase the spread without relying on very different codes or potentially inferior models. The SMEs are generated not only by perturbing the initial condition, but also by using different resolutions, parameters, and coupling configurations of the same model (CFS and its atmosphere component, the Global Forecast System). Each of these configurations was created to address the role of different physical mechanisms known to influence error growth on the 10–20-day time scale. Last, the multimodel consensus forecast is developed, which includes ensemble-based uncertainty estimates. Statistical skill of this CFS-based Grand Ensemble Prediction System (CGEPS) is better than the best participating SME configuration, because increased ensemble spread reduces overconfidence errors.
Article 0 Reads 7 Citations The skill of atmospheric linear inverse models in hindcasting the Madden–Julian Oscillation Nicholas Cavanaugh, Teddy Allen, Aneesh Subramanian, Brian M... Published: 25 May 2014
Climate Dynamics, doi: 10.1007/s00382-014-2181-x
DOI See at publisher website
ABS Show/hide abstract
A suite of statistical atmosphere-only linear inverse models of varying complexity are used to hindcast recent MJO events from the Year of Tropical Convection and the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the Madden–Julian Oscillation mission periods, as well as over the 2000–2009 time period. Skill exists for over two weeks, competitive with the skill of some numerical models in both bivariate correlation and root-mean-squared-error scores during both observational mission periods. Skill is higher during mature Madden–Julian Oscillation conditions, as opposed to during growth phases, suggesting that growth dynamics may be more complex or non-linear since they are not as well captured by a linear model. There is little prediction skill gained by including non-leading modes of variability.