ALBERT

Description: The authors have intercompared the following six surface buoyancy flux estimates, averaged over the years 2005–07: two reanalyses [the recent ECMWF reanalysis (ERA-Interim; hereafter ERA), and the National Centers for Environmental Prediction (NCEP)–NCAR reanalysis 1 (hereafter NCEP1)], two recent flux products developed as an improvement of NCEP1 [the flux product by Large and Yeager and the Southern Ocean State Estimate (SOSE)], and two ad hoc air–sea flux estimates that are obtained by combining the NCEP1 or ERA net radiative fluxes with turbulent flux estimates using the Coupled Ocean–Atmosphere Response Experiment (COARE) 3.0 bulk formulas with NCEP1 or ERA input variables. The accuracy of SOSE adjustments of NCEP1 atmospheric fields (which SOSE uses as an initial guess and a constraint) was assessed by verification that SOSE reduces the biases in the NCEP1 fluxes as diagnosed by the Working Group on Air–Sea Fluxes (Taylor), suggesting that oceanic observations may be a valuable constraint to improve atmospheric variables. Compared with NCEP1, both SOSE and Large and Yeager increase the net ocean heat loss in high latitudes, decrease ocean heat loss in the subtropical Indian Ocean, decrease net evaporation in the subtropics, and decrease net precipitation in polar latitudes. The large-scale pattern of SOSE and Large and Yeager turbulent heat flux adjustment is similar, but the magnitude of SOSE adjustments is significantly larger. Their radiative heat flux adjustments patterns differ. Turbulent heat fluxes determined by combining COARE bulk formulas with NCEP1 or ERA should not be combined with unmodified NCEP1 or ERA radiative fluxes as the net ocean heat gain poleward of 25°S becomes unrealistically large. The other surface flux products (i.e., NCEP1, ERA, Large and Yeager, and SOSE) balance more closely. Overall, the statistical estimates of the differences between the various air–sea heat flux products tend to be largest in regions with strong ocean mesoscale activity such as the Antarctic Circumpolar Current and the western boundary currents.

Description: The Walker circulation (WC) is one of the world’s most prominent and important atmospheric systems. The WC weakened during the twentieth century, reaching record low levels in recent decades. This weakening is thought to be partly due to global warming and partly due to internally generated natural variability. There is, however, no consensus in the literature on the relative contribution of external forcing and natural variability to the observed weakening of the WC. This paper examines changes in the strength of the WC using an index called BoxΔP, which is equal to the difference in mean sea level pressure across the equatorial Pacific. Change in both the observations and in World Climate Research Programme (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3) climate models are examined. The annual average BoxΔP declines in the observations and in 15 out of 23 models during the twentieth century (results that are significant at or above the 95% level), consistent with earlier work. However, the magnitude of the multimodel ensemble mean (MMEM) 1901–99 trend (−0.10 Pa yr−1) is much smaller than the magnitude of the observed trend (−0.52 Pa yr−1). While a wide range of trends is evident in the models with approximately 90% of the model trends in the range (−0.25 to +0.1 Pa yr−1), even this range is too narrow to encompass the magnitude of the observed trend. Twenty-first-century changes in BoxΔP under the Special Report on Emissions Scenarios (SRES) A1B and A2 are also examined. Negative trends (i.e., weaker WCs) are evident in all seasons. However, the MMEM trends for the A1B and A2 scenarios are smaller in magnitude than the magnitude of the observed trend. Given that external forcing linked to greenhouse gases is much larger in the twenty-first-century scenarios than twentieth-century forcing, this, together with the twentieth-century results mentioned above, would seem to suggest that external forcing has not been the primary driver of the observed weakening of the WC. However, 9 of the 23 models are unable to account for the observed change unless the internally generated component of the trend is very large. But indicators of observed variability linked to El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation have modest trends, suggesting that internally variability has been modest. Furthermore, many of the nine “inconsistent” models tend to have poorer simulations of climatic features linked to ENSO. In addition, the externally forced component of the trend tends to be larger in magnitude and more closely matches the observed trend in the models that are better able to reproduce ENSO-related variability. The “best” four models, for example, have a MMEM of −0.2 Pa yr−1 (i.e., approximately 40% of the observed change), suggesting a greater role for external forcing in driving the observed trend. These and other considerations outlined below lead the authors to conclude that (i) both external forcing and internally generated variability contributed to the observed weakening of the WC over the twentieth century and (ii) external forcing accounts for approximately 30%–70% of the observed weakening with internally generated climate variability making up the rest.

Description: The semiannual cycle in zonal wind over the equatorial Indian Ocean is investigated by use of ocean–atmospheric reanalyses, and linear ocean–atmospheric models. In observations, the semiannual cycle in zonal wind is dominant on the equator and confined in the planetary boundary layer (PBL). Results from a momentum budget analysis show that momentum advection generated by the cross-equatorial monsoon circulation is important for the semiannual zonal-wind cycle in the equatorial Indian Ocean. In experiments with a linearized primitive model of the atmosphere, semiannual momentum forcing due to the meridional advection over the central equatorial Indian Ocean is important to simulate the observed maxima of the semiannual cycle in equatorial zonal wind. Off Somalia, diabatic heating and surface friction over land weaken the semiannual response to large momentum forcing there. Results from a linear ocean model suggest that the semiannual zonal wind stress over the central equatorial Indian Ocean generates large semiannual variability in zonal current through a basin-mode resonance.

Description: This study assesses the ability of the Community Climate System Model, version 4 (CCSM4) to represent the Madden–Julian oscillation (MJO), the dominant mode of intraseasonal variability in the tropical atmosphere. The U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group’s prescribed diagnostic tests are used to evaluate the model’s mean state, variance, and wavenumber–frequency characteristics in a 20-yr simulation of the intraseasonal variability in zonal winds at 850 hPa (U850) and 200 hPa (U200), and outgoing longwave radiation (OLR). Unlike its predecessor, CCSM4 reproduces a number of aspects of MJO behavior more realistically. The CCSM4 produces coherent, broadbanded, and energetic patterns in eastward-propagating intraseasonal zonal winds and OLR in the tropical Indian and Pacific Oceans that are generally consistent with MJO characteristics. Strong peaks occur in power spectra and coherence spectra with periods between 20 and 100 days and zonal wavenumbers between 1 and 3. Model MJOs, however, tend to be more broadbanded in frequency than in observations. Broad-scale patterns, as revealed in combined EOFs of U850, U200, and OLR, are remarkably consistent with observations and indicate that large-scale convergence–convection coupling occurs in the simulated MJO. Relations between MJO in the model and its concurrence with other climate states are also explored. MJO activity (defined as the percentage of time the MJO index exceeds 1.5) is enhanced during El Niño events compared to La Niña events, both in the model and observations. MJO activity is increased during periods of anomalously strong negative meridional wind shear in the Asian monsoon region and also during strong negative Indian Ocean zonal mode states, in both the model and observations.

Description: 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.

Description: This study evaluates the capability of coupled global climate models (CGCMs) in simulating the prime examples of the forced response (global monsoon) and internal feedback process (El Niño). Emphases are also placed on the fidelity of the year-to-year variability of global monsoon precipitation that is coordinated by the interannual sea surface temperature (SST) fluctuation over the tropics. The latest version of the Model for Interdisciplinary Research on Climate 5 (MIROC5) with advanced physical schemes is compared with the two previous versions (MIROC3.2, high- and medium-resolution versions) and with the 20 CGCMs participating in the third phase of the Coupled Model Intercomparison Project (CMIP3). The climatological annual mean and cycles of precipitation and 850-hPa winds, the key components to demarcate the global monsoon domain, are reproduced better in MIROC5 than in MIROC3 versions. As a consequence, the former considerably outperforms the latter and is generally superior to the CMIP3 CGCMs in replicating the intensity and domain of global monsoon precipitation and circulations. These results highlight the importance of the improved physical parameterization in a model. Analyses of the monthly Niño-3 index suggest that the amplitude and periodicity of El Niño are simulated better in MIROC5 than in the MIROC3 versions. Yet the reality of nonlinear ENSO dynamics measured indirectly by the SST asymmetricity over the equatorial Pacific is unsatisfactory in the MIROC family as well as in the majority of the CMIP3 models. The maximum covariance analysis shows that a significant fraction of the interannual global monsoon rainfall variability is in concert with El Niño. The multimodel results reveal that such coupling is robust across the current CGCMs. More importantly, the fidelity of the global monsoon precipitation significantly relies on the realism of tropical SST. Comparison among the MIROC models suggests that improved El Niño is likely attributable to the more realistic Bjerknes feedback loop, which results from the intensified convective activity over the equatorial central Pacific Ocean.

Description: This paper evaluates the Weather Research and Forecasting model (WRF) sensitivity to eight different combinations of cumulus, microphysics, and planetary boundary layer (PBL) parameterization schemes over a topographically complex region in southern Spain (Andalusia) for the period 1990–99. The WRF configuration consisted of a 10-km-resolution domain nested in a coarser domain driven by 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) data, with spectral nudging above the PBL employed over the latter domain. The model outputs have been compared at different time scales with an observational dataset that comprises 438 rain gauges and 152 temperature stations with records of both daily maximum and minimum temperatures. To reduce the “representation error,” the validation with observations has been performed using a multistep regionalization that distinguishes five precipitation regions and four temperature regions. The analysis proves that both cumulus and PBL schemes have a crucial impact on the description of precipitation in Andalusia, whereas no noticeable differences between microphysics options were appreciated. Temperature is described similarly by all the configurations, except for the PBL choice affecting minimum values. WRF provides a definite improvement over ERA-40 in the climate description in terms of frequency, spatial distribution, and intensity of extreme events. It also captures more accurately the annual cycle and reduces the biases and the RMSE for monthly precipitation, whereas only a minor enhancement of these features was obtained for monthly-mean maximum and minimum temperatures. The results indicate that WRF is able to correctly reproduce Andalusian climate and produces useful added-value information for climate studies.

Description: Arctic snow presence, absence, properties, and water amount are key components of Earth’s changing climate system that incur far-reaching physical and biological ramifications. Recent dataset and modeling developments permit relatively high-resolution (10-km horizontal grid; 3-h time step) pan-Arctic snow estimates for 1979–2009. Using MicroMet and SnowModel in conjunction with land cover, topography, and 30 years of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) atmospheric reanalysis data, a distributed snow-related dataset was created including air temperature, snow precipitation, snow-season timing and length, maximum snow water equivalent (SWE) depth, average snow density, snow sublimation, and rain-on-snow events. Regional variability is a dominant feature of the modeled snow-property trends. Both positive and negative regional trends are distributed throughout the pan-Arctic domain, featuring, for example, spatially distinct areas of increasing and decreasing SWE or snow season length. In spite of strong regional variability, the data clearly show a general snow decrease throughout the Arctic: maximum winter SWE has decreased, snow-cover onset is later, the snow-free date in spring is earlier, and snow-cover duration has decreased. The domain-averaged air temperature trend when snow was on the ground was 0.17°C decade−1 with minimum and maximum regional trends of −0.55° and 0.78°C decade−1, respectively. The trends for total number of snow days in a year averaged −2.49 days decade−1 with minimum and maximum regional trends of −17.21 and 7.19 days decade−1, respectively. The average trend for peak SWE in a snow season was −0.17 cm decade−1 with minimum and maximum regional trends of −2.50 and 5.70 cm decade−1, respectively.