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Siegfried D. Schubert and Gerald F. Herman

Abstract

A method is demonstrated for evaluating global and zonally averaged heat balance statistics based on a four-dimensional assimilation with an atmospheric general circulation model (GCM). The procedure, which provides observationally constrained model diagnostics, uses the GCM of NASA's Goddard Laboratory for Atmospheric Sciences to evaluate the atmospheric heat balance for the February 1976 Data Systems Test period. The global distribution of the adiabatic and diabatic components of the heat balance are obtained by sampling the continuous GCM assimilation shortly after the insertion of conventional synoptic observations. Sampling times of 6 and 9 h after data insertion were chosen to provide adequate damping of high-frequency oscillations in the vertical velocity field caused by the data insertion.

Salient features of the February 1976 analysis include the following: Maximum rising motion in the mean vertical velocity field at 500 mb over South America, south-central Africa, Australia and the Indonesian archipelago. These regions also were characterized by large values of diabatic heating due to convective latent heat release. The cyclogenetically active regions over the North Atlantic and North Pacific oceans were characterized by maxima in latent heat release due to supersaturation cloud formation, and also maxima in the upward and northward transient eddy heat fluxes. In contrast, the continental west coasts showed a tendency for large downward and southward transient eddy beat fluxes.

Some differences are obtained between the heating rates calculated with the model parameterizations and through a residual method. Other shortcomings of the procedure include data deficiencies in the Southern Hemisphere, which cause the results to be comparatively more model dependent in the high southern latitudes.

The potential applicability of this method of analysis to the recently acquired FGGE data is noted.

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Michael G. Bosilovich and Siegfried D. Schubert

Abstract

Numerous studies suggest that local feedback of surface evaporation on precipitation, known recycling, is a significant source of water for precipitation. Quantitative results on the exact amount of recycling have been difficult to obtain in view of the inherent limitations of diagnostic recycling calculations. The current study describes a calculation of the amount of local and remote geographic sources of surface evaporation for precipitation, based on the implementation of three-dimensional constituent tracers of regional water vapor sources [termed “water vapor tracers” (WVTs)] in a general circulation model. The major limitation on the accuracy of the recycling estimates is the veracity of the numerically simulated hydrological cycle, though it is noted that this approach also can be implemented within the context of a data assimilation system. In the WVT approach, each tracer is associated with an evaporative source region for a prognostic three-dimensional variable that represents a partial amount of the total atmospheric water vapor. The physical processes that act on a WVT are determined in proportion to those that act on the model's prognostic water vapor. In this way, the local and remote sources of water for precipitation can be predicted within the model simulation and validated against the model's prognostic water vapor. As a demonstration of the method, the regional hydrologic cycles for North America and India are evaluated for six summers (June, July, and August) of model simulation. More than 50% of the precipitation in the midwestern United States came from continental regional sources, and the local source was the largest of the regional tracers (14%). The Gulf of Mexico and Atlantic regions contributed 18% of the water for midwestern precipitation, but further analysis suggests that the greater region of the tropical Atlantic Ocean may also contribute significantly. In most North American continental regions, the local source of precipitation is correlated with total precipitation. There is a general positive correlation between local evaporation and local precipitation, but it can be weaker because large evaporation can occur when precipitation is inhibited. In India, the local source of precipitation is a small percentage of the precipitation, owing to the dominance of the atmospheric transport of oceanic water. The southern Indian Ocean provides a key source of water for both the Indian continent and the Sahelian region.

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Siegfried D. Schubert and Man Li Wu

Abstract

The predictability of the 1997 and 1998 south Asian summer monsoon winds is examined from an ensemble of 10 atmospheric general circulation model simulations with prescribed sea surface temperatures (SSTs) and soil moisture. The simulations have no memory of atmospheric initial conditions for the periods of interest.

The model simulations show that the 1998 monsoon is considerably more predictable than the 1997 monsoon. During May and June of 1998 the predictability of the low-level wind anomalies is largely associated with a local response to anomalously warm Indian Ocean SSTs. Predictability increases late in the season (July and August) as a result of the strengthening of the anomalous Walker circulation and the associated development of easterly low-level wind anomalies that extend westward across India and the Arabian Sea. During these months the model is also the most skillful, with the analyses showing a similar late-season westward extension of the easterly wind anomalies.

The model shows little predictability or skill in the monthly mean low-level winds over Southeast Asia during 1997. Predictable wind anomalies do occur over the western Indian Ocean and Indonesia; however, over the Indian Ocean the predictability is artificial, because the model is responding to SST anomalies that were wind driven. The reduced predictability in the low-level winds during 1997 appears to be the result of a weaker (as compared with 1998) simulated anomalous Walker circulation, and the reduced skill is associated with pronounced intraseasonal activity that is not captured well by the model. It is remarkable that the model does produce an ensemble mean Madden–Julian oscillation (MJO) response, though it is approximately in quadrature with, and much weaker than, the observed MJO anomalies during 1997.

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Hailan Wang, Siegfried D. Schubert, Randal D. Koster, and Yehui Chang
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Randal D. Koster, Yehui Chang, Hailan Wang, and Siegfried D. Schubert

Abstract

A series of stationary wave model (SWM) experiments are performed in which the boreal summer atmosphere is forced, over a number of locations in the continental United States, with an idealized diabatic heating anomaly that mimics the atmospheric heating associated with a dry land surface. For localized heating within a large portion of the continental interior, regardless of the specific location of this heating, the spatial pattern of the forced atmospheric circulation anomaly (in terms of 250-hPa eddy streamfunction) is largely the same: a high anomaly forms over west-central North America and a low anomaly forms to the east. In supplemental atmospheric general circulation model (AGCM) experiments, similar results are found; imposing soil moisture dryness in the AGCM in different locations within the U.S. interior tends to produce the aforementioned pattern, along with an associated near-surface warming and precipitation deficit in the center of the continent. The SWM-based and AGCM-based patterns generally agree with composites generated using reanalysis and precipitation gauge data. The AGCM experiments also suggest that dry anomalies imposed in the lower Mississippi River valley have remote surface impacts of particularly large spatial extent, and a region along the eastern half of the U.S.–Canadian border is particularly sensitive to dry anomalies in a number of remote areas. Overall, the SWM and AGCM experiments support the idea of a positive feedback loop operating over the continent: dry surface conditions in many interior locations lead to changes in atmospheric circulation that act to enhance further the overall dryness of the continental interior.

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Randal D. Koster, Max J. Suarez, and Siegfried D. Schubert

Abstract

In an atmospheric general circulation model (AGCM), the physical bounds on soil moisture content and the nonlinear relationship between soil moisture and evaporation lead to distinct geographical patterns in key surface energy and water balance variables. In particular, simple hydrological considerations suggest—and extensive AGCM simulations confirm—that the variance and skew of seasonally averaged [June–August (JJA)] air temperature on the planet should be maximized in specific, and different, regions: a variance maximum should appear on the dry side of the soil moisture variance maximum, and a positive skew maximum should appear on the wet side of the temperature variance maximum. These ideas are tested with multidecade observational temperature data from the Global Historical Climatology Network (GHCN). In the United States, where sufficient data exist, the predicted patterns in the seasonal temperature moments show up where expected. These results suggest that hydrological considerations do indeed control the patterns of seasonal temperature variance and skew in nature.

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Randal D. Koster, Yehui Chang, and Siegfried D. Schubert

Abstract

While the ability of land surface conditions to influence the atmosphere has been demonstrated in various modeling and observational studies, the precise mechanisms by which land–atmosphere feedback occurs are still largely unknown: particularly the mechanisms that allow land moisture state in one region to affect atmospheric conditions in another. Such remote impacts are examined here in the context of atmospheric general circulation model (AGCM) simulations, leading to the identification of one potential mechanism: the phase locking and amplification of a planetary wave through the imposition of a spatial pattern of soil moisture at the land surface. This mechanism, shown here to be relevant in the AGCM, apparently also operates in nature, as suggested by supporting evidence found in reanalysis data.

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Hailan Wang, Siegfried D. Schubert, Randal D. Koster, and Yehui Chang

Abstract

Past modeling simulations, supported by observational composites, indicate that during boreal summer, dry soil moisture anomalies in very different locations within the U.S. continental interior tend to induce the same upper-tropospheric circulation pattern: a high anomaly forms over west-central North America and a low anomaly forms to the east. The present study investigates the causes of this apparent phase locking of the upper-level circulation response and extends the investigation to other land regions in the Northern Hemisphere. The phase locking over North America is found to be induced by zonal asymmetries in the local basic state originating from North American orography. Specifically, orography-induced zonal variations of air temperature, those in the lower troposphere in particular, and surface pressure play a dominant role in placing the soil moisture–forced negative Rossby wave source (dominated by upper-level divergence anomalies) over the eastern leeside of the Western Cordillera, which subsequently produces an upper-level high anomaly over west-central North America, with the downstream anomalous circulation responses phase locked by continuity. The zonal variations of the local climatological atmospheric circulation, manifested as a climatological high over central North America, help shape the spatial pattern of the upper-level circulation responses. Considering the rest of the Northern Hemisphere, the northern Middle East exhibits similar phase locking, also induced by local orography. The Middle Eastern phase locking, however, is not as pronounced as that over North America; North America is where soil moisture anomalies have the greatest impact on the upper-tropospheric circulation.

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Man-Li C. Wu, Oreste Reale, and Siegfried D. Schubert

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This study shows that the African easterly wave (AEW) activity over the African monsoon region and the northern tropical Atlantic can be divided in two distinct temporal bands with time scales of 2.5–6 and 6–9 days. The results are based on a two-dimensional ensemble empirical mode decomposition (2D-EEMD) of the Modern-Era Retrospective Analysis for Research and Applications (MERRA). The novel result of this investigation is that the 6–9-day waves appear to be located predominantly to the north of the African easterly jet (AEJ), originate at the jet level, and are different in scale and structure from the well-known low-level 2.5–6-day waves that develop baroclinically on the poleward flank of the AEJ. Moreover, they appear to interact with midlatitude eastward-propagating disturbances, with the strongest interaction taking place at the latitudes where the core of the Atlantic high pressure system is located. Composite analyses applied to the mode decomposition indicate that the interaction of the 6–9-day waves with midlatitude systems is characterized by enhanced southerly (northerly) flow from (toward) the tropics. This finding agrees with independent studies focused on European floods, which have noted enhanced moist transport from the ITCZ toward the Mediterranean region on time scales of about a week as important precursors of extreme precipitation.

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Siegfried D. Schubert, Max J. Suarez, and Jae-Kyung Schemm

Abstract

The relationship between predictability and persistence is examined using a realistic two-level general circulation model (GCM). Predictability is measured by the average divergence of ensembles of solutions starting from perturbed initial conditions. Persistence is defined in terms of the autocorrelation function based on a single long-term model integration.

The average skill of the dynamical forecasts is compared with the skill of simple persistence-based statistical forecasts. For initial errors comparable in magnitude to present-day analysis errors, the statistical forecast loses all skill after about one week, reflecting the lifetime of the lowest frequency fluctuations in the model. On the other hand, large ensemble mean dynamical forecasts would be expected to remain skillful for about three weeks. The disparity between the skill of the statistical and dynamical forecasts is greatest for the higher frequency modes, which have little memory beyond 1 day, yet remain predictable for about two weeks. For small ensembles, the error of the untempered dynamical forecasts must exceed that of the statistical forecasts for sufficiently long predictions. It is noteworthy, however, that for the low-frequency modes this is found to occur at a time when the GCM error is significantly less than would be obtained by forecasting climatology.

These results are analyzed in terms of two characteristic time scales. A dynamical time scale (Td) is defined as the limiting decay time of a pseudoanomaly correlation and is taken as the measure of predictability. This is compared to the usual statistical time scale (Ts), which is the integrated autocorrelation function and measures the typical time scale of fluctuations. For the dominant low-frequency (Ts ≥ 10 days) modes of fluctuation, the dynamical time scale is between two and three times the statistical time scale. For shorter time scales, the ratio Td/Ts is even greater, reaching six for the shortest time scales considered. This is in contrast to a class of first-order Markov processes with forced-dissipative dynamics for which the two time scales, as defined, are identical.

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