Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 77-83). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (p. 123-131).

The Madden-Julian oscillation (MJO) and the quasi-biennial oscillation (QBO) are two key modes of variability in the tropical atmosphere. The MJO, characterized by propagating, planetary-scale signals in convection and winds, is the main source of subseasonal variability and predictability in the tropics. The QBO is a ~28-month cycle in which the tropical stratospheric zonal winds alternate between easterly and westerly regimes. Via thermal wind balance these winds induce temperature anomalies, and both wind and temperature signals reach the tropopause. Recent observational results show a remarkably strong link between the MJO and the QBO during boreal winter: the MJO is stronger and more predictable when QBO winds in the lower stratosphere are easterly than when winds are westerly. Despite its important implications for MJO theory and prediction, the physical processes driving the MJO-QBO interaction are not well-understood. In this thesis, we use a hierarchy of models – including a cloud-resolving model, a forecast model, and a global climate model – to examine whether models can reproduce the MJO-QBO link, and better understand the possible mechanisms driving the connection. Based in part on our modeling findings, we further explore observed QBO temperature signals thought to be important for the MJO-QBO link. After providing necessary background and context in the first two chapters, the third chapter looks at the MJO-QBO link in a small-domain, cloud-resolving model. The model successfully simulates convection associated with two MJO events that occurred during the DYNAMO field campaign. To examine the effect of QBO, we add various QBO temperature and wind anomalies into the model. We find that QBO temperature anomalies alone, without wind anomalies, qualitatively affect the model MJO similarly to the observed MJO-QBO connection. QBO wind anomalies have no clear effect on the modeled MJO. We note however that the MJO response is quite sensitive to the vertical structure of the QBO temperature anomalies, and for realistic temperature signals the model response is very small. In the fourth chapter, we look at the MJO-QBO link in a state-of-the-art global forecast model with a good representation of the MJO. We conduct 84 hind-cast experiments initialized on dates across winters from 1989-2017. For each of these dates, we artificially impose an easterly and a westerly QBO in the stratospheric initial conditions, and examine the resulting changes to the simulated MJO under different stratospheric states. We find that the effect of the QBO on the model MJO is of the same sign as observations, but is much smaller. A large sample size is required to capture any QBO signal, and tropospheric initial conditions seem more important than the stratosphere in determining the behavior of the simulated MJO. Despite the weak signal, we find that simulations with stronger QBO temperature anomalies have a stronger MJO response. In the fifth chapter, we conduct experiments in recent versions of a NASA general circulation model. We find that a version with a high vertical resolution generates a reasonable QBO and MJO, but has no MJO-QBO link. However, this model has weaker-than-observed QBO temperature anomalies, which may explain the lack of an MJO impact. To explore this potential bias, we impose the QBO by nudging the model stratospheric winds towards reanalysis, leading to more realistic simulation of QBO temperature anomalies. Despite this, the model still fails to show a strong MJO-QBO link across several ensemble experiments and sensitivity tests. We conclude with discussion of possible reasons why the model fails to capture the MJO-QBO connection. The sixth chapter examines QBO temperature signals in a range of observational and reanalysis datasets. In particular, we are motivated by two elements of the MJO-QBO relationship which are especially puzzling: the seasonality (i.e. that the MJO-QBO link is only significant in boreal winter) and long-term trend (i.e. that the MJO-QBO link seems to have only emerged since the 1980s). By examining QBO temperature signals around the tropopause, we highlight changes to the strength and structure of QBO temperature anomalies both in boreal winter and in recent decades. Whether these changes are linked to the MJO-QBO relationship, and what more generally might explain them, is not presently clear. Overall, we demonstrate that capturing the MJO-QBO relationship in a variety of models is a difficult task. The majority of evidence indicates that QBO-induced temperature anomalies are a plausible pathway through which the QBO might modulate the MJO, but the theoretical description of precisely how these temperature anomalies may impact convection is lacking and likely more nuanced than the literature to date suggests. Most models show only a weak modulation of the MJO associated with changes in upper-tropospheric temperatures, and even when those temperature signals are artificially enhanced, comprehensive GCMs still fail to show a significant MJO-QBO connection. Our observational study indicates that temperature anomalies associated with the QBO show striking modulations on various timescales of relevance to the MJO-QBO link, but do not conclusively demonstrate a clear connection to the MJO. This difficulty simulating a strong MJO-QBO connection suggests that models may lack a key process in driving the MJO and coupling the tropical stratosphere and troposphere. It is further possible that the observed link may be in some regards different than is currently theorized -- for example statistically not robust, due to non-stratospheric processes, or driven by some mechanism that has not been suitably explored.

O presente trabalho propõe avaliar a habilidade do Modelo Regional Climático, versão 4, (RegCM4) em simular a variabilidade temporal e espacial do sinal associado à propagação da Oscilação de Madden-Julian (OMJ) nos trópicos. A avaliação foi feita através da comparação dos dados observados obtidos do conjunto da Reanálise do ERA-Interim e dos dados simulados pelo RegCM4, para o período de 2005 a 2009. Foram utilizados dados globais diários de precipitação, Radiação de Onda Longa Emergente e componentes zonal do vento em 850 e 200 hPa, provenientes da Reanálise do ERA-Interim, tanto na simulação, quanto nos dados observados. Como condição inicial do modelo, optou-se pela utilização da banda tropical, cujo principal aspecto é o de simular características tanto da circulação quanto dos padrões de precipitação tropicais. Para a validação do modelo, foi utilizada a precipitação diária do Global Precipitation Climatology Project (GPCP). Todos os dados foram filtrados na escala de 30-60 dias a fim de se observar o sinal referente à OMJ. A análise dos padrões globais de precipitação e Radiação de Onda Longa (ROL), após filtragem, permitiu a seleção de cinco áreas, com sinais associados à OMJ, sendo elas: África (AFR), Indonésia (IND), Norte da América do Sul (NAS), Nordeste brasileiro (NEB) e Sudeste brasileiro (SEB). A área NEB, apresentou valores de correlação linear de 0,63 e 0,32 para a anomalia e anomalia de ROL filtrada, respectivamente. Já a área SEB, apresentou valores de correlação linear de 0,30 e 0,54, para a anomalia e anomalia de ROL filtrada. O BIAS calculado entre o modelo e a precipitação do GPCP, para as estações secas (MAI-OUT) e chuvosas (NOV-ABR) mostrou que para a América do Sul, Sul do continente Africano e Índico, o modelo superestima os valores de precipitação do GPCP nas duas estações do ano. Quanto à análise multivariada entre a ROL, vento zonal em 850 e 200 hpa a comparação com o obtido para os dados do Era-Interim, a Empirical Orthogonal Function (EOF1) aplicada aos dados do RegCM4 apresenta convecção e inibição da convecção em áreas distintas da faixa longitudinal entre 15º N e 15º S. Enquanto os valores mínimos de EOF1 para ROL (intensificação da convecção) do Era-Interim são observados próximo a 90º L, os valores mínimos de ROL para os dados do RegCM4 são observados próximos à 120º O, com defasagem longitudinal de 30º. L, enquanto os valores máximos da EOF1 para ROL (inibição de convecção) do Era-Interim são observados próximo a 150º L, os valores máximos para os dados simulados pelo RegCM4 são observados próximos à 60º L, com uma defasagem longitudinal de 90°. / The present work proposes to evaluate the ability of the Regional Climatic Model (RegCM4) to simulate the temporal and spatial variability of the signal associated with the propagation of the Madden-Julian Oscillation in the tropics. The evaluation was done by comparing the observed data obtained from the Reanalysis of the ERA-Interim and the data simulated by RegCM4, for the period from 2005 to 2009. Daily global data were used for precipitation, Emergent Long Wave Radiation and zonal wind components at 850 and 200 hPa from the ERA-Interim Reanalysis, both in the simulation and in the observed data. As initial conditions of the model, we chose to use the tropical band, whose main characteristic is to simulate the circulation and the tropical precipitation patterns. The validation of the model was performed with the daily precipitation of the Global Precipitation Climatology Project (GPCP). All data were filtered in the 30-60 day scale in order to observe the signal concerning the MJO. The analysis of the global precipitation and Outgoing Longwave Radiation (OLR) patterns, after filtration, allowed the selection of five areas, with signs associated to the MJO, being: Africa (AFR), Indonesia (IND), North of South America (NAS), Northeast Brazil (NEB) e Southeast Brazil (SEB). The NEB area presented linear correlation values of 0,63 and 0,32 for the anomaly and filtered anomaly of OLR, respectively. The SEB area presented linear correlation values of 0.30 and 0.54 for the anomaly and anomaly of filtered OLR. The BIAS calculated between the model and GPCP precipitation for the dry (MAY-OCT) and rainy seasons (NOV-APR) showed that for South America, South Africa and Indian continent, the model overestimates precipitation values of GPCP in the two seasons. The multivariate analysis between OLR, zonal wind at 850 and 200 hp compared to that obtained for Era-Interim data, the EOF1 applied to RegCM4 data presents convection and convection inhibition in different areas between 15º N and 15º S. While the minimum Empirical Orthogonal Function (EOF1) values for OLR (convection enhancement) of the Era-Interim are observed close to 90º E, the minimum OLR values for the RegCM4 data are observed close to 120º O, with a longitudinal lag of 30º. And while maximum EOF1 values for OLR (convection inhibition) of the ERA-Interim are observed close to 150º E, the maximum values for the simulated data by RegCM4 are observed close to 60º E, with a longitudinal lag of 90º.

O presente trabalho propõe avaliar a habilidade do Modelo Regional Climático, versão 4, (RegCM4) em simular a variabilidade temporal e espacial do sinal associado à propagação da Oscilação de Madden-Julian (OMJ) nos trópicos. A avaliação foi feita através da comparação dos dados observados obtidos do conjunto da Reanálise do ERA-Interim e dos dados simulados pelo RegCM4, para o período de 2005 a 2009. Foram utilizados dados globais diários de precipitação, Radiação de Onda Longa Emergente e componentes zonal do vento em 850 e 200 hPa, provenientes da Reanálise do ERA-Interim, tanto na simulação, quanto nos dados observados. Como condição inicial do modelo, optou-se pela utilização da banda tropical, cujo principal aspecto é o de simular características tanto da circulação quanto dos padrões de precipitação tropicais. Para a validação do modelo, foi utilizada a precipitação diária do Global Precipitation Climatology Project (GPCP). Todos os dados foram filtrados na escala de 30-60 dias a fim de se observar o sinal referente à OMJ. A análise dos padrões globais de precipitação e Radiação de Onda Longa (ROL), após filtragem, permitiu a seleção de cinco áreas, com sinais associados à OMJ, sendo elas: África (AFR), Indonésia (IND), Norte da América do Sul (NAS), Nordeste brasileiro (NEB) e Sudeste brasileiro (SEB). A área NEB, apresentou valores de correlação linear de 0,63 e 0,32 para a anomalia e anomalia de ROL filtrada, respectivamente. Já a área SEB, apresentou valores de correlação linear de 0,30 e 0,54, para a anomalia e anomalia de ROL filtrada. O BIAS calculado entre o modelo e a precipitação do GPCP, para as estações secas (MAI-OUT) e chuvosas (NOV-ABR) mostrou que para a América do Sul, Sul do continente Africano e Índico, o modelo superestima os valores de precipitação do GPCP nas duas estações do ano. Quanto à análise multivariada entre a ROL, vento zonal em 850 e 200 hpa a comparação com o obtido para os dados do Era-Interim, a Empirical Orthogonal Function (EOF1) aplicada aos dados do RegCM4 apresenta convecção e inibição da convecção em áreas distintas da faixa longitudinal entre 15º N e 15º S. Enquanto os valores mínimos de EOF1 para ROL (intensificação da convecção) do Era-Interim são observados próximo a 90º L, os valores mínimos de ROL para os dados do RegCM4 são observados próximos à 120º O, com defasagem longitudinal de 30º. L, enquanto os valores máximos da EOF1 para ROL (inibição de convecção) do Era-Interim são observados próximo a 150º L, os valores máximos para os dados simulados pelo RegCM4 são observados próximos à 60º L, com uma defasagem longitudinal de 90°. / The present work proposes to evaluate the ability of the Regional Climatic Model (RegCM4) to simulate the temporal and spatial variability of the signal associated with the propagation of the Madden-Julian Oscillation in the tropics. The evaluation was done by comparing the observed data obtained from the Reanalysis of the ERA-Interim and the data simulated by RegCM4, for the period from 2005 to 2009. Daily global data were used for precipitation, Emergent Long Wave Radiation and zonal wind components at 850 and 200 hPa from the ERA-Interim Reanalysis, both in the simulation and in the observed data. As initial conditions of the model, we chose to use the tropical band, whose main characteristic is to simulate the circulation and the tropical precipitation patterns. The validation of the model was performed with the daily precipitation of the Global Precipitation Climatology Project (GPCP). All data were filtered in the 30-60 day scale in order to observe the signal concerning the MJO. The analysis of the global precipitation and Outgoing Longwave Radiation (OLR) patterns, after filtration, allowed the selection of five areas, with signs associated to the MJO, being: Africa (AFR), Indonesia (IND), North of South America (NAS), Northeast Brazil (NEB) e Southeast Brazil (SEB). The NEB area presented linear correlation values of 0,63 and 0,32 for the anomaly and filtered anomaly of OLR, respectively. The SEB area presented linear correlation values of 0.30 and 0.54 for the anomaly and anomaly of filtered OLR. The BIAS calculated between the model and GPCP precipitation for the dry (MAY-OCT) and rainy seasons (NOV-APR) showed that for South America, South Africa and Indian continent, the model overestimates precipitation values of GPCP in the two seasons. The multivariate analysis between OLR, zonal wind at 850 and 200 hp compared to that obtained for Era-Interim data, the EOF1 applied to RegCM4 data presents convection and convection inhibition in different areas between 15º N and 15º S. While the minimum Empirical Orthogonal Function (EOF1) values for OLR (convection enhancement) of the Era-Interim are observed close to 90º E, the minimum OLR values for the RegCM4 data are observed close to 120º O, with a longitudinal lag of 30º. And while maximum EOF1 values for OLR (convection inhibition) of the ERA-Interim are observed close to 150º E, the maximum values for the simulated data by RegCM4 are observed close to 60º E, with a longitudinal lag of 90º.

The Madden-Julian oscillation (MJO), also known as the 30-60day oscillation, is the strongest of the intraseasonal climate oscillations in the tropics and has significant derivative effects on extratropical circulation and intraseasonal climate. It has recently been shown that the stratospheric quasi-biennial oscillation (QBO) modulates the amplitude of the boreal winter MJO such that MJO amplitudes are larger on average during the easterly phase (QBOE) than during the westerly phase (QBOW). A major possible mechanism is the decrease in static stability in the lowermost stratosphere under QBOE conditions resulting from relative upwelling associated with the QBO-induced meridional circulation. Here evidence is presented that tropical upwelling changes related to the 11year solar cycle also modulate the boreal winter MJO. Based on 37.3years of MJO amplitude data, the largest amplitudes and occurrence rates, and the weakest static stabilities in the tropical lower stratosphere, occur during the QBOE phase under solar minimum (SMIN) conditions while the smallest amplitudes and strongest static stabilities occur during the QBOW phase under solar maximum (SMAX) conditions. Conversely, when the QBO and solar forcings are opposed (QBOW/SMIN and QBOE/SMAX), the difference in occurrence rates becomes statistically insignificant. During the coming solar minimum, at least one additional winter in the QBOE/SMIN category should occur (possibly as early as 2017/2018) during which especially large MJO amplitudes are expected and an initial test of these results will be possible. Plain Language Summary An ongoing issue in climate science is the extent to which upper atmospheric processes, including solar forcing, can influence tropospheric climate. It has recently been shown that an internal oscillation of the stratosphere, the quasi-biennial oscillation, can modulate the amplitude and occurrence rate of intraseasonal climate oscillations in the tropical Pacific during northern winter. These intraseasonal oscillations, the most important of which is the 30-60day Madden-Julian oscillation, have significant derivative effects on climate outside of the tropics, including impacts on rainfall events over the continental United States. Here evidence is presented that the amplitude of the Madden-Julian oscillation during northern winter is also modulated by the 11year solar cycle. The modulation is such that amplitudes and occurrence rates are largest under solar minimum conditions when the quasi-biennial oscillation is in its easterly phase and smallest under solar maximum conditions when the quasi-biennial oscillation is in its westerly phase. However, the available time record (37.3years of satellite measurements) is limited. During the coming solar minimum, at least one additional winter in the solar minimum/easterly category should occur (possibly as early as 2017/2018) during which larger-than-average amplitudes are expected and an initial test of the proposed relationship will be possible.

The Shared Mobile Atmospheric Research and Teaching Radar (SMART-R) is a truck-mounted C-band, Doppler radar that was deployed during the Dynamics of the Madden-Julian Oscillation (DYNAMO) / Cooperative Indian Ocean Experiment on interseasonal variability in the year 2011 (CINDY2011) campaign on Addu Atoll, Maldives. One of SMART-R’s objectives was to provide continuous volume scans of precipitating clouds during all phases of the Madden-Julian Oscillation (MJO) for the full duration of the campaign. Data from SMART-R is available for 2 October 2011 through 9 February 2012. Every 10 minutes a full volume scan was produced, which was subsequently run through quality control algorithms that, among other filters, performed a calibration correction, noise filtering, and an attenuation correction. It was observed that data from SMART-R appeared to be slanted towards the WNW, and after analysis, a 0.75◦ tilt correction was applied towards azimuth 285◦. The data was then converted into Cartesian coordinates and an additional noise filter was applied. NETCDF files with radial velocities and corrected reflectivity were produced. From the reflectivity observations, a suite of products including rain maps, echo- top heights and convective/stratiform separations were produced. A modified version of the convective/stratiform separation was developed in an attempt to classify shallow and weak convection more correctly. The modified algorithm utilizes an isolation parameter set to 10 km to the north, south, east, and west, a 10-dBz echo-top height threshold set to 9 km, and a 16-dBz reflectivity threshold at 3 km to ensure only isolated, shallow, and weak rain originally classified as stratiform, is reclassified as convection. Analyses of these products clearly suggest two MJO events occurring in October and November as indicated by the Wheeler and Hendon Multivariate MJO index. While stratiform rain almost always encompassed a larger area of the radar domain, convective rain was the larger producer of rain with the exception of active MJO periods. In addition, echo-top height counts are observed to increase in both vertical structure and frequency as the MJO initiates and becomes active over the radar domain. Possible connections are also made between echo-top height data and humidity retrievals from soundings launched on Addu Atoll. It appears that during MJO initiation, convective echo tops lead the moistening of the mid troposphere, while during suppressed phases, the convective echo tops lag behind the moistening of the mid troposphere. Wind shear also appears to be weaker during an active MJO event, and increase as the active MJO exits the region. From these observations, as well as other rain statistics including the diurnal cycle, indicators for a localized MJO index are proposed that are based on local radar and sounding data, rather than satellite and reanalysis observations of wind and outgoing long-wave radiation.

A census of 24 coupled (CMIP) and 13 uncoupled (AMIP) models from the Intergovernmental Panel on Climate Change (IPCC) fourth assessment report (AR4) were compared with observations and reanalysis to show varied ability of the models to simulate Caribbean precipitation and mechanisms related to precipitation in the region. Not only were errors seen in the annual mean, with CMIP models underestimating both rainfall and sea surface temperature (SST) and AMIP models overestimating rainfall, the annual cycle was also incorrect. Large overestimates of precipitation at all SSTs (and particularly above 28 degrees C) and at vertical circulations less than -10 hPa/day (the deep convective regime) were inherent in the atmospheric models with models using spectral type convective parameterizations performing best. In coupled models, however, errors in the frequency of occurrence of SSTs (the distribution is cold biased) and deep convective vertical circulations (reduced frequency) lead to an underestimation of Caribbean mean precipitation. On daily timescales, the models were shown to produce too frequent light rainfall amounts (especially less than 1 mm/day) and dry extremes and too few heavy rainfall amounts and wet extremes. The simulation of the mid-summer drought (MSD) proved a challenge for the models, despite their ability to produce a Caribbean low-level jet (CLLJ) in the correct location. Errors in the CLLJ, such as too strong magnitude and weak semi-annual cycle, were worse in the CMIP models and were attributed to problems with the location and seasonal evolution of the North Atlantic subtropical high (NASH) in both CMIP and AMIP models. Despite these discrepancies between models and observations, the ability of the models to simulate the correlation between the CLLJ and precipitation varied based on season and region, with the connection with United States precipitation particularly problematic in the AMIP simulations. An observational study of intraseasonal precipitation in the Caribbean showed an explicit connection between the Madden-Julian oscillation (MJO) and Caribbean precipitation for the first time. Precipitation anomalies up to 50 percent above (below) the annual mean are observed in phases 1 and 2 (5 and 6) of the MJO and are related to changes in the CLLJ, that is also modulated by the MJO. Considerable progress has been made on identifying both problems and successes in the simulation of Caribbean climate in general circulation models, but many areas still require investigation.

The intraseasonal Oscillation (ISO) is a very strong and coherent mode of variability observed in the Earths climate. Rainfall variability in the intraseasonal timescale is particularly strong in the Tropics and it directly interacts with the South Asian monsoon during boreal summer and with the Australian monsoon during winter. A detailed analysis of the horizontal and vertical structure of the ISO during both summer and winter is presented in this work considering the coupled ocean-atmosphere system. In addition, the role of the intraseasonal variability of the Southeast Asian monsoon is studied in detail. From the applications point of view, the intraseasonal time scale is arguably the most important period of variability. However, extended forecasting of intraseasonal activity has proven to be a difficult task for the state of the art numerical models. In order to improve the forecasts of the ISO activity over the Southeast Asian monsoon region, a physically based empirical scheme was designed. The scheme uses wavelet banding to separate the predictand and predictors into physically significant bands where linear regression followed by recombination of the bands is used to generate the forecast. Results of the empirical scheme suggest that isolating the evolution of the intraseasonal signal from higher frequency variability and noise improve the skill of the prediction. The hypothesis is that a similar phenomenon occurs in numerical models: The strong intraseasonal signal is eroded by high frequency errors due to the model parameterizations, especially in convection. To evaluate the hypothesis, a coupled ocean-atmosphere model was run in ensemble mode for 30 day periods initialized daily for 20 days before to 20 days after major intraseasonal oscillations, allowing the examination of the skill of the model relative to the phase of the oscillation. The results, which confirm the previous hypothesis, represent well the observations for about 7 days after which the magnitude of the errors is greater than the signal itself. An integration scheme was developed for the coupled ocean-atmosphere general circulation model in order to mimic the philosophy of the empirical scheme and use for 30-day forecasts. The propagation features associated to ISO activity are improved.

Intraseasonal oscillations (ISOs) are important elements of the tropical climate with time-scales of 20-80 day. The ISO is poorly simulated and predicted by numerical models. This work presents a joint diagnostic and modeling study of the ISO that examines the hypothesis that local coupling between the ocean and the atmosphere is essential to the existence and evolution of the ISO in the Indo-Pacific warm pool region. Low-level moistening during the transition phase preconditions the atmosphere for deep convection. The vertical structure of ISO from the ECMWF coupled model during different phases of the oscillation as well as the skill of the model in simulating the processes that occur during the transition phase were studied. The forecast skill of the vertical structure associated with the ISO is greater for winter than for summer events. Predictability of the convective period is poor when initialized before the transitional phase. When initialized within the transition period including lower tropospheric moistening, predictability increases substantially, although the model parameterizations appears to trigger convection quickly without allowing an adequate buildup of CAPE during the transition. The model tends to simulate a more stable atmosphere compared to data, limiting the production of deep convective events. Two different one-dimensional coupled models are used to analyze the role of local ocean-atmosphere coupling in generating ISO. The ocean component is a one-dimensional mixed layer model. In the first model the atmospheric component corresponds to the SCCM. Results suggest that convection in the model tends to be "overactive," inhibiting development of lower frequency oscillations in the atmosphere. In the second case, the atmospheric component is a semi-empirical model that allows reproducing the coupled ISO over long integration periods including only local mechanisms. In the semi-empirical scheme the rate of change of atmospheric variables is statistically related to changes in SST. The stable state of this model is a quasi-periodic oscillation with a time scale between 25 and 80 days that matches well the observed ISO. Results suggest that the period of the oscillation depends on the characteristics of the ocean mixed layer, with a higher frequency oscillation for a shallow mixed layer.