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Scot M. Loehrer, Todd A. Edmands, and James A. Moore

One of the most important datasets to come from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) is the most complete, high-resolution upper-air sounding dataset ever collected in the equatorial western Pacific Ocean. The University Corporation for Atmospheric Research/Office of Field Project Support&UCAR/OFPS (recently combined with the UCAR/Joint International Climate Projects Planning Office and renamed the Joint Office for Science Support); was given the responsibility of processing, quality controlling, and archiving the dataset. OFPS, in consultation with the TOGA COARE scientific community, developed a four-stage process to provide the community with a thoroughly quality controlled dataset.

The TOGA COARE sounding dataset includes over 14 000 soundings, collected from 14 countries, in over 20 different original formats. The first OFPS processing step was the conversion of all soundings to a single, easy to use format, the OFPS quality control format. The second stage was a series of automated internal consistency checks on each sounding. This stage was particularly important as it directly led to the improvement of several of the datasets. The third step was a visual examination of each sounding to provide another layer of internal consistency checks, for dewpoint and wind in particular. The final process used spatial quality control checks to put each station into context with its neighboring stations as well as the network as a whole. These checks provided statistics from which both systematic and individual sounding problems could be determined. Finally, some derived sounding parameters such as convective available potential energy (CAPE) were calculated for each sounding. The CAPE calculations provided a quick method to qualitatively examine the high-resolution sounding data for low-level humidity problems. A composite dataset of all soundings at a uniform vertical resolution of 5 hPa was created to provide the community with a sounding dataset that has been found to be useful in certain modeling studies.

The processed TOGA COARE sounding data, as well as statistical output from the OFPS spatial quality control procedures, are available on-line via the Internet using the World Wide Web (WWW) through the OFPS data management system. Access via the WWW allows a full range of on-line data browsing and ordering capabilities.

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A. M. Moore, N. S. Cooper, and D. L. T. Anderson

Abstract

Numerical experiments have been conducted to investigate the effect of updating models of the Indian Ocean using simulated temperature (mass) and velocity data. Two models are used: a linear reduced gravity model with one active layer, and a nonlinear 12-level general circulation model (GCM). In both cases an “identical twin” approach is adopted, in which the same model is used to generate the “observed” data in a “truth run”, as is used in the assimilation run.

Temperature data is found to be better than velocity data for initializing both models. However, further experiments with the layer model showed that increasing the model diffusion and decreasing the eddy viscosity results in velocity data being better for initializing. These results are ascribed to the energy distribution, with the proportion of kinetic energy being greater in the later experiments.

Simulated data from the proposed TOGA Indian Ocean XBT network were also assimilated into both models using a successive correction interpolation scheme. It is found that for the layer model, which had smooth horizontal variations in thermocline depth, the errors fall to zero within a couple of months. However, in the experiments with the GCM there is little reduction in the assimilation error after the first model update, due to the data analysis scheme not being able to resolve the horizontal temperature structure in the GCM.

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Jann Paul Mattern, Christopher A. Edwards, and Andrew M. Moore

Abstract

A procedure to objectively adjust the error covariance matrices of a variational data assimilation system is presented. It is based on popular diagnostics that utilize differences between observations and prior and posterior model solutions at the observation locations. In the application to a data assimilation system that combines a three-dimensional, physical–biogeochemical ocean model with large datasets of physical and chlorophyll a observations, the tuning procedure leads to a decrease in the posterior model-observation misfit and small improvements in short-term forecasting skill. It also increases the consistency of the data assimilation system with respect to diagnostics, based on linear estimation theory, and reduces signs of overfitting. The tuning procedure is easy to implement and only relies on information that is either prescribed to the data assimilation system or can be obtained from a series of short data assimilation experiments. The implementation includes a lognormal representation for biogeochemical variables and associated modifications to the diagnostics. Furthermore, the effect of the length of the observation window (number and distribution of observations) used to compute the diagnostics and the effect of neglecting model dynamics in the tuning procedure are examined.

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J. Zavala-Garay, C. Zhang, A. M. Moore, and R. Kleeman

Abstract

The possibility that the tropical Pacific coupled system linearly amplifies perturbations produced by the Madden–Julian oscillation (MJO) is explored. This requires an estimate of the low-frequency tail of the MJO. Using 23 yr of NCEP–NCAR reanalyses of surface wind and Reynolds SST, we show that the spatial structure that dominates the intraseasonal band (i.e., the MJO) also dominates the low-frequency band once the anomalies directly related to ENSO have been removed. This low-frequency contribution of the intraseasonal variability is not included in most ENSO coupled models used to date. Its effect in a coupled model of intermediate complexity has, therefore, been studied. It is found that this “MJO forcing” (τ MJO) can explain a large fraction of the interannual variability in an asymptotically stable version of the model. This interaction is achieved via linear dynamics. That is, it is the cumulative effect of individual events that maintains ENSOs in this model. The largest coupled wind anomalies are initiated after a sequence of several downwelling Kelvin waves of the same sign have been forced by τ MJO . The cumulative effect of the forced Kelvin waves is to persist the (small) SST anomalies in the eastern Pacific just enough for the coupled ocean–atmosphere dynamics to amplify the anomalies into a mature ENSO event. Even though τ MJO explains just a small fraction of the energy contained in the stress not associated with ENSO, a large fraction of the modeled ENSO variability is excited by this forcing. The characteristics that make τ MJO an optimal stochastic forcing for the model are discussed. The large zonal extent is an important factor that differentiates the MJO from other sources of stochastic forcing.

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J. Zavala-Garay, C. Zhang, A. M. Moore, A. T. Wittenberg, M. J. Harrison, A. Rosati, Jérôme Vialard, and R. Kleeman

Abstract

A common practice in the design of forecast models for ENSO is to couple ocean general circulation models to simple atmospheric models. Therefore, by construction these models (known as hybrid ENSO models) do not resolve various kinds of atmospheric variability [e.g., the Madden–Julian oscillation (MJO) and westerly wind bursts] that are often regarded as “unwanted noise.” In this work the sensitivity of three hybrid ENSO models to this unresolved atmospheric variability is studied. The hybrid coupled models were tuned to be asymptotically stable and the magnitude, and spatial and temporal structure of the unresolved variability was extracted from observations. The results suggest that this neglected variability can add an important piece of realism and forecast skill to the hybrid models. The models were found to respond linearly to the low-frequency part of the neglected atmospheric variability, in agreement with previous findings with intermediate models. While the wind anomalies associated with the MJO typically explain a small fraction of the unresolved variability, a large fraction of the interannual variability can be excited by this forcing. A large correlation was found between interannual anomalies of Kelvin waves forced by the intraseasonal MJO and the Kelvin waves forced by the low-frequency part of the MJO. That is, in years when the MJO tends to be more active it also produces a larger low-frequency contribution, which can then resonate with the large-scale coupled system. Other kinds of atmospheric variability not related to the MJO can also produce interannual anomalies in the hybrid models. However, when projected on the characteristics of Kelvin waves, no clear correlation between its low-frequency content and its intraseasonal activity was found. This suggests that understanding the mechanisms by which the intraseasonal MJO interacts with the ocean to modulate its low-frequency content may help to better to predict ENSO variability.

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S. B. Power, N. R. Smith, R. Kleeman, A. M. Moore, and D. A. Post

Abstract

A global ocean general circulation model is forced using mixes boundary conditions (i.e., a restoring condition on the upper-level temperature but using a fixed, specified surface salt flux). Freshwater flux anomalies lasting 5 years are then applied over the western half of the subpolar gyre in the northern North Atlantic.

The current climate is found to be stable to anomalies that have salt deficits equivalent to about seven times that estimated for the “great salinity anomaly” of 1968–1982, although this value is a function of the duration over which the anomaly is imposed. Above this level the thermohaline circulation collapses to a state in which the zonally averaged overturning associated with North Atlantic Deep Water formation is only about half its original value, the sea surface temperatures over the North Atlantic are lowered, and both the subpolar and subtropical gyres have weakened horizontal transports. Various atmospheric feedbacks on the momentum and salt flux are then applied under a restorative condition on temperature. The feedbacks on the momentum flux do not have a significant impact on the overturning, other than to increase the Ekman flow, while a modest recovery is possible if the salt flux feedback includes an enhanced divergence of freshwater out of the Atlantic basin.

In contrast, the collapse is critically dependent upon the restorative condition on temperature. This central role suggests that the heat flux feedback maintains the stability exhibited by the collapsed state modeled by Manabe and Stouffer.

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X. W. Quan, P. J. Webster, A. M. Moore, and H. R. Chang

Abstract

The seasonal dependence of atmospheric short-term climate (i.e., seasonal to interannual) predictability is studied. This is accomplished by analyzing the output from ensemble integrations of the European Centre for Medium-Range Weather Forecasts model. The integrations use the observed evolution of sea surface temperature (SST) as prescribed boundary forcing. Forced by the interannual variation of SST, the short-term climate predictability of the atmospheric circulation is geographically and seasonally dependent. In general, the predictability is larger in the Tropics than the extratropics and is greater in the Pacific–Atlantic Ocean sector compared to the Indian Ocean–Asian monsoon region. Predictability is also higher in the winter hemisphere than in the summer hemisphere. On average, the weakest predictability in the Northern Hemisphere occurs during the northern autumn. However, it is noted that the 1982/83 strong El Niño event produced stronger atmospheric predictability than the 1988/89 strong La Niña event during the northern spring, and the predictability pattern is reversed during the northern autumn.

Predictability is further partitioned into its internal and external components. The external component is defined as the interannual variation of ensemble average, and the internal component is the sample-to-sample variance. The temporal and spatial structure in the external variability accounts for most of the structure in the SST-forced atmospheric predictability. However, there are regions in the Tropics, such as over the monsoon region, where the external and internal variabilities show roughly the same magnitude. Overall, internal variability is largest in the extratropics. Specifically, the internal variability is larger in the northern extratropics during the northern autumn and larger in the southern extratropics during the northern spring. In contrast, the external variability is smaller (larger) in the northern extratropics during the northern autumn (spring).

It is concluded that major features of the SST-forced atmospheric predictability are determined by the external variability in the Tropics. In the extratropics, the predictability is determined by seasonal variations in both internal and external variabilities. The weakest predictability that occurs in the northern extratropics during the northern autumn is the result of a conjunction of a local increase in internal variability and a decrease in external variability at the same time.

Furthermore, the external variability is controlled by seasonality in the forcing over the tropical Pacific Ocean, which is largely determined by the following two mechanisms: 1) the annual cycle–ENSO interaction over the tropical Pacific Ocean and 2) nonlinear effects of hydrological processes associated with the annual cycle–ENSO interaction. Also, it is interesting that the annual cycle–ENSO interaction can be summarized into a conceptual model that shows some analogy to the quark model in nuclear physics.

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J. Zavala-Garay, A. M. Moore, C. L. Perez, and R. Kleeman

Abstract

In this work the role that observed intraseasonal atmospheric variability may play in controlling and maintaining ENSO variability is examined. To this end, an asymptotically stable intermediate coupled model of El Niño–Southern Oscillation (ENSO) is forced with observed estimates of stochastic forcing, which are defined to be the part of the atmospheric variability that is apparently independent of the ocean circulation. The stochastic forcing (SF) was estimated from 51 yr (1950–2000) of NCEP–NCAR reanalyses of surface winds and net surface heat flux, 32 yr (1950–81) of reconstructed sea surface temperatures (SST), and 19 yr (1982–2000) of Reynolds SST in the tropical Pacific. The deterministic component of the surface wind and heat flux anomalies that can be linearly related to SST anomalies was estimated using the singular value decomposition of the covariance between the anomaly fields, and was then removed from the atmospheric anomaly fields to recover the stochastic component of the ocean surface forcing. Principal component analysis reveals that the stochastic component has no preferred mode of variability, exhibits decorrelation times of a few days, and has a spectrum that is indistinguishable from red noise. A 19-yr stochastically forced coupled model integration qualitatively shows some similarities with the observed equatorial SST. The robustness of this result is checked by performing different sensitivity experiments. The model mostly exhibits a linear (and nonnormal) response to the low-frequency tail of SF. Using the ideas of generalized linear stability theory, the dynamically important contributions of the SF are isolated, and it is shown that most of the variability in the stochastically forced model solution is produced by stochastically induced Kelvin waves forced in the western and central Pacific. Moreover, the two most dynamically important patterns of stochastic forcing (which account for 71% of the expected variance in the model response) describe eastward propagation of the forcing similar to the MJO. The results of this study support the hypothesis that a significant fraction of ENSO variability may be due to SF, and suggest that a better understanding of the influence of SF on the ocean surface in the western/central Pacific may be required in order to understand the predictability of ENSO.

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Robert S. Pickart, Alison M. Macdonald, G. W. K. Moore, Ian A. Renfrew, John E. Walsh, and William S. Kessler

Abstract

The seasonal change in the development of Aleutian low pressure systems from early fall to early winter is analyzed using a combination of meteorological reanalysis fields, satellite sea surface temperature (SST) data, and satellite wind data. The time period of the study is September–December 2002, although results are shown to be representative of the long-term climatology. Characteristics of the storms were documented as they progressed across the North Pacific, including their path, central pressure, deepening rate, and speed of translation. Clear patterns emerged. Storms tended to deepen in two distinct geographical locations—the Gulf of Alaska in early fall and the western North Pacific in late fall. In the Gulf of Alaska, a quasi-permanent “notch” in the SST distribution is argued to be of significance. The signature of the notch is imprinted in the atmosphere, resulting in a region of enhanced cyclonic potential vorticity in the lower troposphere that is conducive for storm development. Later in the season, as winter approaches and the Sea of Okhotsk becomes partially ice covered and cold, the air emanating from the Asian continent leads to enhanced baroclinicity in the region south of Kamchatka. This corresponds to enhanced storm cyclogenesis in that region. Consequently, there is a seasonal westward migration of the dominant lobe of the Aleutian low. The impact of the wind stress curl pattern resulting from these two regions of storm development on the oceanic circulation is investigated using historical hydrography. It is argued that the seasonal bimodal input of cyclonic vorticity from the wind may be partly responsible for the two distinct North Pacific subarctic gyres.

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Tammy M. Weckwerth, David B. Parsons, Steven E. Koch, James A. Moore, Margaret A. LeMone, Belay B. Demoz, Cyrille Flamant, Bart Geerts, Junhong Wang, and Wayne F. Feltz

The International H2O Project (IHOP_2002) is one of the largest North American meteorological field experiments in history. From 13 May to 25 June 2002, over 250 researchers and technical staff from the United States, Germany, France, and Canada converged on the Southern Great Plains to measure water vapor and other atmospheric variables. The principal objective of IHOP_2002 is to obtain an improved characterization of the time-varying three-dimensional water vapor field and evaluate its utility in improving the understanding and prediction of convective processes. The motivation for this objective is the combination of extremely low forecast skill for warm-season rainfall and the relatively large loss of life and property from flash floods and other warm-season weather hazards. Many prior studies on convective storm forecasting have shown that water vapor is a key atmospheric variable that is insufficiently measured. Toward this goal, IHOP_2002 brought together many of the existing operational and new state-of-the-art research water vapor sensors and numerical models.

The IHOP_2002 experiment comprised numerous unique aspects. These included several instruments fielded for the first time (e.g., reference radiosonde); numerous upgraded instruments (e.g., Wyoming Cloud Radar); the first ever horizontal-pointing water vapor differential absorption lidar (DIAL; i.e., Leandre II on the Naval Research Laboratory P-3), which required the first onboard aircraft avoidance radar; several unique combinations of sensors (e.g., multiple profiling instruments at one field site and the German water vapor DIAL and NOAA/Environmental Technology Laboratory Doppler lidar on board the German Falcon aircraft); and many logistical challenges. This article presents a summary of the motivation, goals, and experimental design of the project, illustrates some preliminary data collected, and includes discussion on some potential operational and research implications of the experiment.

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