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P. B. Duffy
,
R. W. Arritt
,
J. Coquard
,
W. Gutowski
,
J. Han
,
J. Iorio
,
J. Kim
,
L.-R. Leung
,
J. Roads
, and
E. Zeledon

Abstract

In this paper, the authors analyze simulations of present and future climates in the western United States performed with four regional climate models (RCMs) nested within two global ocean–atmosphere climate models. The primary goal here is to assess the range of regional climate responses to increased greenhouse gases in available RCM simulations. The four RCMs used different geographical domains, different increased greenhouse gas scenarios for future-climate simulations, and (in some cases) different lateral boundary conditions. For simulations of the present climate, RCM results are compared to observations and to results of the GCM that provided lateral boundary conditions to the RCM. For future-climate (increased greenhouse gas) simulations, RCM results are compared to each other and to results of the driving GCMs. When results are spatially averaged over the western United States, it is found that the results of each RCM closely follow those of the driving GCM in the same region in both present and future climates. This is true even though the study area is in some cases a small fraction of the RCM domain. Precipitation responses predicted by the RCMs in many regions are not statistically significant compared to interannual variability. Where the predicted precipitation responses are statistically significant, they are positive. The models agree that near-surface temperatures will increase, but do not agree on the spatial pattern of this increase. The four RCMs produce very different estimates of water content of snow in the present climate, and of the change in this water content in response to increased greenhouse gases.

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Hyodae Seo
,
Markus Jochum
,
Raghu Murtugudde
,
Arthur J. Miller
, and
John O. Roads

Abstract

The effects of atmospheric feedbacks on tropical instability waves (TIWs) in the equatorial Atlantic Ocean are examined using a regional high-resolution coupled climate model. The analysis from a 6-yr hindcast from 1999 to 2004 reveals a negative correlation between TIW-induced wind perturbations and TIW-induced ocean currents, which implies damping of the TIWs. On the other hand, the feedback effect from the modification of Ekman pumping velocity by TIWs is small compared to the contribution to TIW growth by baroclinic instability. Overall, the atmosphere reduces the growth of TIWs by adjusting its wind response to the evolving TIWs. The analysis also shows that including ocean current (mean + TIWs) in the wind stress parameterization reduces the surface stress estimate by 15%–20% over the region of the South Equatorial Current. Moreover, TIW-induced perturbation ocean currents can significantly alter surface stress estimations from scatterometers, especially at TIW frequencies. Finally, the rectification effect from the atmospheric response to TIWs on latent heat flux is small compared to the mean latent heat flux.

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Hyodae Seo
,
Markus Jochum
,
Raghu Murtugudde
,
Arthur J. Miller
, and
John O. Roads

Abstract

A regional coupled climate model is configured for the tropical Atlantic to explore the role of synoptic-scale African easterly waves (AEWs) on the simulation of mean precipitation in the marine intertropical convergence zone (ITCZ). Sensitivity tests with varying atmospheric resolution in the coupled model show that these easterly waves are well represented with comparable amplitudes on both fine and coarse grids of the atmospheric model. Significant differences in the model simulations are found in the precipitation fields, however, where heavy rainfall events occur in the region of strong cyclonic shear of the easterly waves only on the higher-resolution grid. This is because the low-level convergence due to the waves is much larger and more realistic in the fine-resolution simulation, which enables heavier precipitation events that skew the rainfall distributions toward longer tails. The variability in rainfall on these time scales accounts for more than 60%–70% of the total variability. As a result, the simulation of mean rainfall in the ITCZ and its seasonal migration improves in the higher-resolution case. This suggests that capturing these transient waves and the resultant strong low-level convergence is one of the key ingredients for improving the simulation of precipitation in global coupled climate models.

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R. G. Lawford
,
R. Stewart
,
J. Roads
,
H.-J. Isemer
,
M. Manton
,
J. Marengo
,
T. Yasunari
,
S. Benedict
,
T. Koike
, and
S. Williams

Over the past 9 years, the Global Energy and Water Cycle Experiment (GEWEX), under the auspices of the World Climate Research Programme (WCRP), has coordinated the activities of the Continental Scale Experiments (CSEs) and other related research through the GEWEX Hydrometeorology Panel (GHP). The GHP contributes to the WCRP'S objective of “developing the fundamental scientific understanding of the physical climate system and climate processes [that is] needed to determine to what extent climate can be predicted and the extent of man's influence on climate.” It also contributes to more specific GEWEX objectives, such as determining the hydrological cycle and energy fluxes, modeling the global hydrological cycle and its impacts, developing a capability to predict variations in global and regional hydrological processes, and fostering the development of observing techniques, data management and assimilation systems. GHP activities include diagnosis, simulation, and experimental prediction of regional water balances and process and modeling studies aimed at understanding and predicting the variability of the global water cycle, with an emphasis on regional coupled land–atmosphere processes. GHP efforts are central to providing a scientific basis for assessing critical science issues, such as the consequences of climate change for the intensification of the global hydrological cycle and its potential impacts on regional water resources. This article provides an overview of the role and evolution of the GHP and describes scientific issues that the GHP is seeking to address in collaboration with the international science community.

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E. S. Takle
,
J. Roads
,
B. Rockel
,
W. J. Gutowski Jr.
,
R. W. Arritt
,
I. Meinke
,
C. G. Jones
, and
A. Zadra

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

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E. S. Takle
,
J. Roads
,
B. Rockel
,
W. J. Gutowski Jr.
,
R. W. Arritt
,
I. Meinke
,
C. G. Jones
, and
A. Zadra
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D. S. Gutzler
,
L. N. Long
,
J. Schemm
,
S. Baidya Roy
,
M. Bosilovich
,
J. C. Collier
,
M. Kanamitsu
,
P. Kelly
,
D. Lawrence
,
M.-I. Lee
,
R. Lobato Sánchez
,
B. Mapes
,
K. Mo
,
A. Nunes
,
E. A. Ritchie
,
J. Roads
,
S. Schubert
,
H. Wei
, and
G. J. Zhang

Abstract

The second phase of the North American Monsoon Experiment (NAME) Model Assessment Project (NAMAP2) was carried out to provide a coordinated set of simulations from global and regional models of the 2004 warm season across the North American monsoon domain. This project follows an earlier assessment, called NAMAP, that preceded the 2004 field season of the North American Monsoon Experiment. Six global and four regional models are all forced with prescribed, time-varying ocean surface temperatures. Metrics for model simulation of warm season precipitation processes developed in NAMAP are examined that pertain to the seasonal progression and diurnal cycle of precipitation, monsoon onset, surface turbulent fluxes, and simulation of the low-level jet circulation over the Gulf of California. Assessment of the metrics is shown to be limited by continuing uncertainties in spatially averaged observations, demonstrating that modeling and observational analysis capabilities need to be developed concurrently. Simulations of the core subregion (CORE) of monsoonal precipitation in global models have improved since NAMAP, despite the lack of a proper low-level jet circulation in these simulations. Some regional models run at higher resolution still exhibit the tendency observed in NAMAP to overestimate precipitation in the CORE subregion; this is shown to involve both convective and resolved components of the total precipitation. The variability of precipitation in the Arizona/New Mexico (AZNM) subregion is simulated much better by the regional models compared with the global models, illustrating the importance of transient circulation anomalies (prescribed as lateral boundary conditions) for simulating precipitation in the northern part of the monsoon domain. This suggests that seasonal predictability derivable from lower boundary conditions may be limited in the AZNM subregion.

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Christopher J. Anderson
,
Raymond W. Arritt
,
Zaitao Pan
,
Eugene S. Takle
,
William J. Gutowski Jr.
,
Francis O. Otieno
,
Renato da Silva
,
Daniel Caya
,
Jens H. Christensen
,
Daniel Lüthi
,
Miguel A. Gaertner
,
Clemente Gallardo
,
Filippo Giorgi
,
René Laprise
,
Song-You Hong
,
Colin Jones
,
H-M. H. Juang
,
J. J. Katzfey
,
John L. McGregor
,
William M. Lapenta
,
Jay W. Larson
,
John A. Taylor
,
Glen E. Liston
,
Roger A. Pielke Sr.
, and
John O. Roads

Abstract

Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.

All RCMs produced positive precipitation minus evapotranspiration (PE > 0), though most RCMs produced PE below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.

Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.

In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

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William J. Gutowski Jr.
,
Raymond W. Arritt
,
Sho Kawazoe
,
David M. Flory
,
Eugene S. Takle
,
Sébastien Biner
,
Daniel Caya
,
Richard G. Jones
,
René Laprise
,
L. Ruby Leung
,
Linda O. Mearns
,
Wilfran Moufouma-Okia
,
Ana M. B. Nunes
,
Yun Qian
,
John O. Roads
,
Lisa C. Sloan
, and
Mark A. Snyder

Abstract

This paper analyzes the ability of the North American Regional Climate Change Assessment Program (NARCCAP) ensemble of regional climate models to simulate extreme monthly precipitation and its supporting circulation for regions of North America, comparing 18 years of simulations driven by the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) reanalysis with observations. The analysis focuses on the wettest 10% of months during the cold half of the year (October–March), when it is assumed that resolved synoptic circulation governs precipitation. For a coastal California region where the precipitation is largely topographic, the models individually and collectively replicate well the monthly frequency of extremes, the amount of extreme precipitation, and the 500-hPa circulation anomaly associated with the extremes. The models also replicate very well the statistics of the interannual variability of occurrences of extremes. For an interior region containing the upper Mississippi River basin, where precipitation is more dependent on internally generated storms, the models agree with observations in both monthly frequency and magnitude, although not as closely as for coastal California. In addition, simulated circulation anomalies for extreme months are similar to those in observations. Each region has important seasonally varying precipitation processes that govern the occurrence of extremes in the observations, and the models appear to replicate well those variations.

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