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Arlindo M. Da Silva

Abstract

We reexamine the coupled lower boundary condition of Chen and Trenberth and show that for consistency the vertical velocity should be corrected from the mountain surface to the lowest computational level. This correction introduces a term of the same order of magnitude as their new term and may have some impact on the results.

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Peter M. Norris and Arlindo M. da Silva

Abstract

General circulation models are unable to resolve subgrid-scale moisture variability and associated cloudiness and so must parameterize grid-scale cloud properties. This typically involves various empirical assumptions and a failure to capture the full range (synoptic, geographic, diurnal) of the subgrid-scale variability. A variational parameter estimation technique is employed to adjust empirical model cloud parameters in both space and time, in order to better represent assimilated International Satellite Cloud Climatology Project (ISCCP) cloud fraction and optical depth and Special Sensor Microwave Imager (SSM/I) liquid water path. The value of these adjustments is verified by much improved cloud radiative forcing and persistent improvement in cloud fraction forecasts.

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Dick P. Dee and Arlindo M. da Silva

Abstract

The maximum-likelihood method for estimating observation and forecast error covariance parameters is described. The method is presented in general terms but with particular emphasis on practical aspects of implementation. Issues such as bias estimation and correction, parameter identifiability, estimation accuracy, and robustness of the method, are discussed in detail. The relationship between the maximum-likelihood method and generalized cross-validation is briefly addressed.

The method can be regarded as a generalization of the traditional procedure for estimating covariance parameters from station data. It does not involve any restrictions on the covariance models and can be used with data from moving observers, provided the parameters to be estimated are identifiable. Any available a priori information about the observation and forecast error distributions can be incorporated into the estimation procedure. Estimates of parameter accuracy due to sampling error are obtained as a by-product.

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Arlindo M. Da Silva and Richard S. Lindzen

Abstract

The establishment of stationary waves in the Northern Hemisphere winter is investigated using stationary and time-dependent linear primitive equation models. Confirming the results of Nigam and Lindzen, we find that small displacements of the subtropical jet can cause significant changes in the stationary-wave response. The time scale for stationary establishment is found to be on the order of 5 days, both in the troposphere and in the lower stratosphere. The exception is for a northward shift of the subtropical jet, in which case the establishment of the new stationary solution in the stratosphere occurs on a longer time scale, which is mainly determined by dissipation. Implications for low-frequency atmospheric variability and mid- and long-range weather forecasting are discussed.

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Dick P. Dee and Arlindo M. da Silva

Abstract

The implications of using different control variables for the analysis of moisture observations in a global atmospheric data assimilation system are investigated. A moisture analysis based on either mixing ratio or specific humidity is prone to large extrapolation errors, due to the high variability in space and time of these parameters and to the difficulties in modeling their error covariances. Using the logarithm of specific humidity does not alleviate these problems, and has the further disadvantage that very dry background estimates cannot be effectively corrected by observations. Relative humidity is a better choice from a statistical point of view, because this field is spatially and temporally more coherent and error statistics are therefore easier to obtain. If, however, the analysis is designed to preserve relative humidity in the absence of moisture observations, then the analyzed specific humidity field depends entirely on analyzed temperature changes. If the model has a cool bias in the stratosphere this will lead to an unstable accumulation of excess moisture there.

A pseudo-relative humidity can be defined by scaling the mixing ratio by the background saturation mixing ratio. A univariate pseudo-relative humidity analysis will preserve the specific humidity field in the absence of moisture observations. A pseudo-relative humidity analysis is shown to be equivalent to a mixing ratio analysis with flow-dependent variance specifications. In the presence of multivariate (temperature–moisture) observations it produces analyzed relative humidity values that are nearly identical to those produced by a relative humidity analysis. Based on a time series analysis of radiosonde observed-minus-background differences it appears to be more justifiable to neglect specific humidity–temperature correlations (in a univariate pseudo-relative humidity analysis) than to neglect relative humidity–temperature correlations (in a univariate relative humidity analysis). A pseudo-relative humidity analysis can be implemented in an existing moisture analysis system simply by scaling the observed-minus-background residuals prior to solving the analysis equation, and rescaling the analyzed increments afterward.

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Arlindo M. da Silva and Richard S. Lindzen

Abstract

Ultralong Rossby waves (low zonal and meridional wavenumbers on the sphere) have been studied for many years. Extensive observational evidence tends to identify these waves with the gravest normal modes of the atmosphere. Due to dissipative processes, these disturbances have to be generated by some forcing mechanism, even though they have phase speeds consistent with free oscillations. In this paper, we consider a mechanism for the excitation of these waves based on temporal changes of the zonal wind in the tropics, in the presence oforography and stationary thermal foming. The waves are excited as a consequence of the adjustment of the quasi-stationary component to the new background configuration.

A barotropic calculation is carried out in order to test the mechanism in a minimal model resolving ultralong Rossby waves, namely, the shallow-water equations over the sphere, including topographic and thermal forcing. Even in this simplified model, the predominance of the 16-day wave is suggested. Our results indicate that thermal foming may be more important than orography, but the limitations of the model do not allow one to assess the relative contributions in the atmosphere with any meaningful accuracy.

The proposed mechanism is quite general and may be tested in more sophisticated models, including effects such as baroclinicity and a more realistic representation of forcing and dissipation.

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Oreste Reale, K. M. Lau, and Arlindo da Silva

Reale et al. (2011) contains a typographical error in the article title in the table of contents and on the title page. The extra word “an” was erroneously inserted. The correct title is “Impact of Interactive Aerosol on the African Easterly Jet in the NASA GEOS-5 Global Forecasting System.”

The staff of Weather and Forecasting regrets any inconvenience this error may have caused.

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Oreste Reale, K. M. Lau, and Arlindo da Silva

Abstract

The real-time treatment of interactive, realistically varying aerosols in a global operational forecasting system, as opposed to prescribed (fixed or climatologically varying) aerosols, is a very difficult challenge that has only recently begun to be addressed. Experiment results from a recent version of the NASA’s Goddard Earth Observing System (GEOS-5) forecasting system, inclusive of interactive-aerosol direct effects, are presented in this work. Five sets of 30 five-day forecasts are initialized from a high quality set of analyses previously produced and documented, to cover the period from 15 August to 16 September 2006, which corresponds to the NASA African Monsoon Multidisciplinary Analysis (NAMMA) observing campaign. Four forecast sets are at two different horizontal resolutions, with and without interactive-aerosol treatment. A fifth forecast set is performed with climatologically varying aerosols. The net impact of the interactive aerosol, associated with a strong Saharan dust outbreak, is a temperature increase at the dust level, and a decrease in the near-surface levels, in agreement with previous observational and modeling studies. Moreover, forecasts in which interactive aerosols are included depict an African easterly jet (AEJ) at slightly higher elevation, and slightly displaced northward, with respect to the forecasts in which aerosols are not included. The shift in the AEJ position goes in the direction of the observations and agrees with previous results.

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Augustus F. Fanning, Richard J. Greatbatch, Arlindo M. Da Silva, and Sydney Levitus

Abstract

A linear, barotropic model of the North Atlantic at 1° ×1° resolution is employed to investigate the effect of using different wind-stress climatologies on the model response at the Florida Straits. The wind-stress climatologies are those of da Silva et al. (DS), Hellerman and Rosenstein (HR), Isemer and Hasse (IH), and Trenberth et al. (TR). For each climatology, the model shows maximum northward transport in the summer and minima in the fall and late winter, in general agreement with transport measurements from cable data (Larsen). However, the amplitude of the model response differs considerably between the climatologies. In the case of DS the range (maximum transport minus minimum transport) is 2.8 Sv (1 Sv=1 × 106 m3 s−1); HR: 3.6 Sv, TR: 5.2 Sv, and IH: 5.9 Sv, compared to a range of 4.6 ± 0.3 Sv derived from cable data. The increased range in the IH case compared to HR is in general agreement with the finding of Böning et al. using the Kiel version of the model that forms the WOCE Community Modelling Effort. However, whereas Böning et al. claim that winds north of 35°N have little influence on the seasonal response of their model at the Florida Straits, it is found that winds north of 35°N play an important role in the model presented here. The reason for the behavior of the community model is not clear but may be associated with advection by the western boundary current, an effect not present in the linear model discussed here. In the case of the present model, the importance of forcing by the meridional component of the wind is shown, although forcing through the zonal component also plays some role in explaining the differences between the cases run under the different climatologies. The importance in the model of forcing associated with the meridional component of the wind along the continental slope region to the north of the straits is emphasized.

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Dick P. Dee, Greg Gaspari, Chris Redder, Leonid Rukhovets, and Arlindo M. da Silva

Abstract

Three different applications of maximum-likelihood estimation of error covariance parameters for atmospheric data assimilation are described. Height error standard deviations, vertical correlation coefficients, and isotropic decorrelation length scales are estimated from rawinsonde height observed-minus-forecast residuals. Sea level pressure error standard deviations and decorrelation length scales are obtained from ship reports, and wind observation error standard deviations and forecast error stream function and velocity potential decorrelation length scales are estimated from aircraft data. These applications serve to demonstrate the ability of the method to estimate covariance parameters using multivariate data from moving observers.

Estimates of the parameter uncertainty due to sampling error can be obtained as a by-product of the maximum-likelihood estimation. By bounding this source of error, it is found that many statistical parameters that are usually presumed constant in operational data assimilation systems in fact vary significantly with time. This may well reflect the use of overly simplistic covariance models that cannot adequately describe state-dependent error components such as representativeness error. The sensitivity of the parameter estimates to the treatment of bias, and to the choice of the model representing spatial correlations, is examined in detail. Several experiments emulate an online covariance parameter estimation procedure using a sliding window of data, and it is shown that such a procedure is both desirable and computationally feasible.

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