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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 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

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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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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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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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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Oreste Reale
,
K. M. Lau
, and
Arlindo da Silva
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Michael G. Bosilovich
,
Jiun-Dar Chern
,
David Mocko
,
Franklin R. Robertson
, and
Arlindo M. da Silva

Abstract

The assimilation of observations in reanalyses incurs the potential for the physical terms of budgets to be balanced by a term relating the fit of the observations relative to a forecast first guess analysis. This may indicate a limitation in the physical processes of the background model or perhaps assimilating data from an inconsistent observing system. In the MERRA reanalysis, an area of long-term moisture flux divergence over land has been identified over the central United States. Here, the water vapor budget is evaluated in this region, taking advantage of two unique features of the MERRA diagnostic output: 1) a closed water budget that includes the analysis increment and 2) a gridded diagnostic output dataset of the assimilated observations and their innovations (e.g., forecast departures).

In the central United States, an anomaly occurs where the analysis adds water to the region, while precipitation decreases and moisture flux divergence increases. This is related more to a change in the observing system than to a deficiency in the model physical processes. MERRA’s Gridded Innovations and Observations (GIO) data narrow the observations that influence this feature to the ATOVS and Aqua satellites during the 0600 and 1800 UTC analysis cycles, when radiosonde information is not prevalent. Observing system experiments further narrow the instruments that affect the anomalous feature to AMSU-A (mainly window channels) and Atmospheric Infrared Sounder (AIRS). This effort also shows the complexities of the observing system and the reactions of the regional water budgets in reanalyses to the assimilated observations.

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Arthur Y. Hou
,
Sara Q. Zhang
,
Arlindo M. da Silva
, and
William S. Olson

Abstract

A global analysis that optimally combines observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the Tropics. In this study it is demonstrated that assimilating precipitation and total precipitable water (TPW) derived from the Tropical Rainfall Measuring Mission Microwave Imager (TMI) can significantly improve the quality of global analysis. It is shown that assimilating the 6-h averaged TMI rainfall and TPW retrievals improves not only the hydrological cycle, but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). Notably, assimilating TMI rain rates improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the Tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Assimilating these data also improves the instantaneous wind and temperature fields in the analysis, leading to better short-range forecasts in the Tropics. Ensemble forecasts initialized with analyses incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day, better 500-hPa geopotential height forecasts up to 5 days, and better 200-hPa divergent winds up to 2 days. These results demonstrate the potential of using high quality spaceborne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications.

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