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Mark A. Miller
,
Virendra P. Ghate
, and
Robert K. Zahn

Abstract

Continuous measurements of the shortwave (SW), longwave (LW), and net cross-atmosphere radiation flux divergence over the West African Sahel were made during the year 2006 using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) and the Geostationary Earth Radiation Budget (GERB) satellite. Accompanying AMF measurements enabled calculations of the LW, SW, and net top of the atmosphere (TOA) and surface cloud radiative forcing (CRF), which quantifies the radiative effects of cloud cover on the column boundaries. Calculations of the LW, SW, and net cloud radiative effect (CRE), which is the difference between the TOA and surface radiative flux divergences in all-sky and clear-sky conditions, quantify the radiative effects on the column itself. These measurements were compared to predictions in four global climate models (GCMs) used in the Intergovernmental Panel for Climate Change Fourth Assessment Report (IPCC AR4). All four GCMs produced wet and dry seasons, but reproducing the SW column radiative flux divergence was problematic in the GCMs and SW discrepancies translated into discrepancies in the net radiative flux divergence. Computing cloud-related quantities from the measurements produced yearly averages of the SW TOA CRF, surface CRF, and CRE of ~−19, −83, and 47 W m−2, respectively, and yearly averages of the LW TOA CRF, surface CRF, and CRE of ~39, 37, and 2 W m−2. These quantities were analyzed in two GCMs and compensating errors in the SW and LW clear-sky, cross-atmosphere radiative flux divergence were found to conspire to produce somewhat reasonable predictions of the net clear-sky divergence. Both GCMs underestimated the surface LW and SW CRF and predicted near-zero SW CRE when the measured values were substantially larger (~70 W m−2 maximum).

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J. Teixeira
,
S. Cardoso
,
M. Bonazzola
,
J. Cole
,
A. DelGenio
,
C. DeMott
,
C. Franklin
,
C. Hannay
,
C. Jakob
,
Y. Jiao
,
J. Karlsson
,
H. Kitagawa
,
M. Köhler
,
A. Kuwano-Yoshida
,
C. LeDrian
,
J. Li
,
A. Lock
,
M. J. Miller
,
P. Marquet
,
J. Martins
,
C. R. Mechoso
,
E. v. Meijgaard
,
I. Meinke
,
P. M. A. Miranda
,
D. Mironov
,
R. Neggers
,
H. L. Pan
,
D. A. Randall
,
P. J. Rasch
,
B. Rockel
,
W. B. Rossow
,
B. Ritter
,
A. P. Siebesma
,
P. M. M. Soares
,
F. J. Turk
,
P. A. Vaillancourt
,
A. Von Engeln
, and
M. Zhao

Abstract

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

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David W. Pierce
,
Daniel R. Cayan
,
Tapash Das
,
Edwin P. Maurer
,
Norman L. Miller
,
Yan Bao
,
M. Kanamitsu
,
Kei Yoshimura
,
Mark A. Snyder
,
Lisa C. Sloan
,
Guido Franco
, and
Mary Tyree

Abstract

Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change. This disagreement is explored in terms of daily precipitation frequency and intensity. It is found that divergent model projections of changes in the incidence of rare heavy (>60 mm day−1) daily precipitation events explain much of the model disagreement on annual time scales, yet represent only 0.3% of precipitating days and 9% of annual precipitation volume. Of the 25 downscaled model projections examined here, 21 agree that precipitation frequency will decrease by the 2060s, with a mean reduction of 6–14 days yr−1. This reduces California's mean annual precipitation by about 5.7%. Partly offsetting this, 16 of the 25 projections agree that daily precipitation intensity will increase, which accounts for a model average 5.3% increase in annual precipitation. Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods [Weather Research and Forecasting (WRF), Regional Spectral Model (RSM), and version 3 of the Regional Climate Model (RegCM3)] and statistical methods [bias correction with spatial disaggregation (BCSD) and bias correction with constructed analogs (BCCA)], although not all downscaling methods were applied to each global model. Model disagreements in the projected change in occurrence of the heaviest precipitation days (>60 mm day−1) account for the majority of disagreement in the projected change in annual precipitation, and occur preferentially over the Sierra Nevada and Northern California. When such events are excluded, nearly twice as many projections show drier future conditions.

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Seiji Kato
,
Bruce A. Wielicki
,
Fred G. Rose
,
Xu Liu
,
Patrick C. Taylor
,
David P. Kratz
,
Martin G. Mlynczak
,
David F. Young
,
Nipa Phojanamongkolkij
,
Sunny Sun-Mack
,
Walter F. Miller
, and
Yan Chen

Abstract

Variability present at a satellite instrument sampling scale (small-scale variability) has been neglected in earlier simulations of atmospheric and cloud property change retrievals using spatially and temporally averaged spectral radiances. The effects of small-scale variability in the atmospheric change detection process are evaluated in this study. To simulate realistic atmospheric variability, top-of-the-atmosphere nadir-view longwave spectral radiances are computed at a high temporal (instantaneous) resolution with a 20-km field-of-view using cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, along with temperature humidity profiles obtained from reanalysis. Specifically, the effects of the variability on the necessary conditions for retrieving atmospheric changes by a linear regression are tested. The percentage error in the annual 10° zonal mean spectral radiance difference obtained by assuming linear combinations of individual perturbations expressed as a root-mean-square (RMS) difference computed over wavenumbers between 200 and 2000 cm−1 is 10%–15% for most of the 10° zones. However, if cloud fraction perturbation is excluded, the RMS difference decreases to less than 2%. Monthly and annual 10° zonal mean spectral radiances change linearly with atmospheric property perturbations, which occur when atmospheric properties are perturbed by an amount approximately equal to the variability of the10° zonal monthly deseasonalized anomalies or by a climate-model-predicted decadal change. Nonlinear changes in the spectral radiances of magnitudes similar to those obtained through linear estimation can arise when cloud heights and droplet radii in water cloud change. The spectral shapes computed by perturbing different atmospheric and cloud properties are different so that linear regression can separate individual spectral radiance changes from the sum of the spectral radiance change. When the effects of small-scale variability are treated as noise, however, the error in retrieved cloud properties is large. The results suggest the importance of considering small-scale variability in inferring atmospheric and cloud property changes from the satellite-observed zonally and annually averaged spectral radiance difference.

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T. Jung
,
M. J. Miller
,
T. N. Palmer
,
P. Towers
,
N. Wedi
,
D. Achuthavarier
,
J. M. Adams
,
E. L. Altshuler
,
B. A. Cash
,
J. L. Kinter III
,
L. Marx
,
C. Stan
, and
K. I. Hodges

Abstract

The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena—an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models.

In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden–Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena.

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