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- Author or Editor: Kingtse Mo x
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Abstract
The NCEP–NCAR reanalysis together with the outgoing longwave radiation anomalies (OLRAs) and a gridded daily precipitation over the United States were used to analyze precipitation over California on intraseasonal timescales. The intraseasonal (10–90 days) filtered OLRAs were subjected to singular spectrum analysis, which identifies nonlinear oscillations in noisy time series. There are two dominant oscillatory modes associated with California rainfall with periods near 36–40 and 20–25 days.
The 36–40-day mode is related to the Madden–Julian Oscillation (MJO) in the Tropics. Enhanced tropical convection propagates from the western Pacific to the central Pacific. A three-cell pattern with negative OLRAs in California and positive anomalies in the eastern Pacific and the Pacific Northwest starts to develop 4 days later and rainfall starts in California.
Anomalies associated with the 20–25-day mode are responsible for alternating wet and dry episodes over California with periods shorter than the timescales of the MJO. The 20–25-day mode is the leading mode in the 7–30-day band and is related to tropical convection in the Pacific. In the extratropics, cloud bands propagate northward along the west coast of North America from the eastern Pacific just north of the ITCZ through California to the Pacific Northwest. The 200-hPa streamfunction anomaly composites associated with the 20–25-day mode reveal a westward propagating wave train dominated by a zonal wavenumber 2. This mode has a spatial structure similar to the traveling pattern described by Branstator.
Abstract
The NCEP–NCAR reanalysis together with the outgoing longwave radiation anomalies (OLRAs) and a gridded daily precipitation over the United States were used to analyze precipitation over California on intraseasonal timescales. The intraseasonal (10–90 days) filtered OLRAs were subjected to singular spectrum analysis, which identifies nonlinear oscillations in noisy time series. There are two dominant oscillatory modes associated with California rainfall with periods near 36–40 and 20–25 days.
The 36–40-day mode is related to the Madden–Julian Oscillation (MJO) in the Tropics. Enhanced tropical convection propagates from the western Pacific to the central Pacific. A three-cell pattern with negative OLRAs in California and positive anomalies in the eastern Pacific and the Pacific Northwest starts to develop 4 days later and rainfall starts in California.
Anomalies associated with the 20–25-day mode are responsible for alternating wet and dry episodes over California with periods shorter than the timescales of the MJO. The 20–25-day mode is the leading mode in the 7–30-day band and is related to tropical convection in the Pacific. In the extratropics, cloud bands propagate northward along the west coast of North America from the eastern Pacific just north of the ITCZ through California to the Pacific Northwest. The 200-hPa streamfunction anomaly composites associated with the 20–25-day mode reveal a westward propagating wave train dominated by a zonal wavenumber 2. This mode has a spatial structure similar to the traveling pattern described by Branstator.
Abstract
Drought indices derived from the North American Land Data Assimilation System (NLDAS) Variable Infiltration Capacity (VIC) and Noah models from 1950 to 2000 are intercompared and evaluated for their ability to classify drought across the United States. For meteorological drought, the standardized precipitation index (SPI) is used to measure precipitation deficits. The standardized runoff index (SRI), which is similar to the SPI, is used to classify hydrological drought. Agricultural drought is measured by monthly-mean soil moisture (SM) anomaly percentiles based on probability distributions (PDs). The PDs for total SM are regionally dependent and influenced by the seasonal cycle, but the PDs for SM monthly-mean anomalies are unimodal and Gaussian.
Across the eastern United States (east of 95°W), the indices derived from VIC and Noah are similar, and they are able to detect the same drought events. Indices are also well correlated. For river forecast centers (RFCs) across the eastern United States, different drought indices are likely to detect the same drought events.
The monthly-mean soil moisture (SM) percentiles and runoff indices between VIC and Noah have large differences across the western interior of the United States. For small areas with a horizontal resolution of 0.5° on the time scales of one to three months, the differences of SM percentiles and SRI between VIC and Noah are larger than the thresholds used to classify drought. For the western RFCs, drought events selected according to SM percentiles or SRI derived from different NLDAS systems do not always overlap.
Abstract
Drought indices derived from the North American Land Data Assimilation System (NLDAS) Variable Infiltration Capacity (VIC) and Noah models from 1950 to 2000 are intercompared and evaluated for their ability to classify drought across the United States. For meteorological drought, the standardized precipitation index (SPI) is used to measure precipitation deficits. The standardized runoff index (SRI), which is similar to the SPI, is used to classify hydrological drought. Agricultural drought is measured by monthly-mean soil moisture (SM) anomaly percentiles based on probability distributions (PDs). The PDs for total SM are regionally dependent and influenced by the seasonal cycle, but the PDs for SM monthly-mean anomalies are unimodal and Gaussian.
Across the eastern United States (east of 95°W), the indices derived from VIC and Noah are similar, and they are able to detect the same drought events. Indices are also well correlated. For river forecast centers (RFCs) across the eastern United States, different drought indices are likely to detect the same drought events.
The monthly-mean soil moisture (SM) percentiles and runoff indices between VIC and Noah have large differences across the western interior of the United States. For small areas with a horizontal resolution of 0.5° on the time scales of one to three months, the differences of SM percentiles and SRI between VIC and Noah are larger than the thresholds used to classify drought. For the western RFCs, drought events selected according to SM percentiles or SRI derived from different NLDAS systems do not always overlap.
Abstract
We have examined systematically oscillatory modes in the Northern Hemisphere and in the tropics. The 700 mb heights were used to analyze extratropical oscillations, and the outgoing longwave radiation to study tropical oscillations in convection. All datasets were band-pass filtered to focus on the intraseasonal (IS) band of 10–120 days. Leading spatial patterns of variability were obtained by applying EOF analysis to these IS data. The leading principal components (PCs) were subjected to singular spectrum analysis (SSA). SSA is a statistical technique related to EOF analysis, but in the time domain, rather than the spatial domain. It helps identify nonlinear oscillations in short and noisy time series.
In the Northern Hemisphere, there are two important modes of oscillation with periods near 48 and 23 days, respectively. The 48-day mode is the most important of the two. It has both traveling and standing components, and is dominated by a zonal wavenumber two. The 23-day mode has the spatial structure and propagation properties described by Branstator and by Kushnir.
In the tropics, the 40–50 day oscillation documented by Madden and Julian, Weickmann, Lau, their colleagues, and many other authors dominates the Indian and Pacific oceans from 60°E to the date line. From 170°W to 90°W, however, a 24–28 day oscillation is equally strong. The extratropical modes are often independent of, and sometimes lead, the tropical modes.
Abstract
We have examined systematically oscillatory modes in the Northern Hemisphere and in the tropics. The 700 mb heights were used to analyze extratropical oscillations, and the outgoing longwave radiation to study tropical oscillations in convection. All datasets were band-pass filtered to focus on the intraseasonal (IS) band of 10–120 days. Leading spatial patterns of variability were obtained by applying EOF analysis to these IS data. The leading principal components (PCs) were subjected to singular spectrum analysis (SSA). SSA is a statistical technique related to EOF analysis, but in the time domain, rather than the spatial domain. It helps identify nonlinear oscillations in short and noisy time series.
In the Northern Hemisphere, there are two important modes of oscillation with periods near 48 and 23 days, respectively. The 48-day mode is the most important of the two. It has both traveling and standing components, and is dominated by a zonal wavenumber two. The 23-day mode has the spatial structure and propagation properties described by Branstator and by Kushnir.
In the tropics, the 40–50 day oscillation documented by Madden and Julian, Weickmann, Lau, their colleagues, and many other authors dominates the Indian and Pacific oceans from 60°E to the date line. From 170°W to 90°W, however, a 24–28 day oscillation is equally strong. The extratropical modes are often independent of, and sometimes lead, the tropical modes.
Abstract
In Part II of this two-part article, we complete the systematic examination of oscillatory modes in the global atmosphere by studying 12 years of 500 mb geopotential heights in the Southern Hemisphere. As in Part I, for the tropics and Northern Hemisphere extratropics, the data were band-pass filtered to focus on intraseasonal (IS) phenomena, and spatial EOFs were obtained. The leading principal components were subjected to singular spectrum analysis (SSA), in order to identify nonlinear IS oscillations with high statistical confidence.
In the Southern Hemisphere, the dominant mode has a period of 23 days, with spatial patterns carried by the second and third winter EOF of the IS band. It has a zonal wavenumber-four structure. The 40-day mode is second, and dominated by wavenumbers three and four, while a 16-day mode is too weak to separate its spatial behavior from the previous two. The IS dynamics in the Southern Hemisphere is more complex and dominated by shorter wavenumbers than the Northern Hemisphere. No statistically significant correlations between the Southern Hemisphere and the tropics or the Northern Hemisphere are apparent in the IS band.
Abstract
In Part II of this two-part article, we complete the systematic examination of oscillatory modes in the global atmosphere by studying 12 years of 500 mb geopotential heights in the Southern Hemisphere. As in Part I, for the tropics and Northern Hemisphere extratropics, the data were band-pass filtered to focus on intraseasonal (IS) phenomena, and spatial EOFs were obtained. The leading principal components were subjected to singular spectrum analysis (SSA), in order to identify nonlinear IS oscillations with high statistical confidence.
In the Southern Hemisphere, the dominant mode has a period of 23 days, with spatial patterns carried by the second and third winter EOF of the IS band. It has a zonal wavenumber-four structure. The 40-day mode is second, and dominated by wavenumbers three and four, while a 16-day mode is too weak to separate its spatial behavior from the previous two. The IS dynamics in the Southern Hemisphere is more complex and dominated by shorter wavenumbers than the Northern Hemisphere. No statistically significant correlations between the Southern Hemisphere and the tropics or the Northern Hemisphere are apparent in the IS band.
Abstract
Data from observations and the Intergovernmental Panel on Climate Change (IPCC) twentieth-century climate change model [phase 3 of the Coupled Model Intercomparison Project (CMIP3)] simulations were analyzed to examine the decadal changes of the impact of ENSO on air temperature T air and precipitation P over the United States. The comparison of composites for the early period (1915–60) and the recent period (1962–2006) indicates that cooling (warming) over the south and warming (cooling) over the north during ENSO warm (cold) winters have been weakening. The ENSO influence on winter P over the Southwest is strengthening, while the impact on P over the Ohio Valley is weakening for the recent decades. These differences are not due to the long-term trends in T air or P; they are attributed to the occurrence of the central Pacific (CPAC) ENSO events in the recent years. The CPAC ENSO differs from the canonical eastern Pacific (EPAC) ENSO. The EPAC ENSO has a sea surface temperature anomaly (SSTA) maximum in the eastern Pacific. Enhanced convection extends from the date line to the eastern Pacific, with negative anomalies in the western Pacific. The atmospheric responses resemble a tropical Northern Hemisphere pattern. The wave train is consistent with the north–south T air contrast over North America during the EPAC ENSO winters. The CPAC ENSO has enhanced convection in the central Pacific. The atmospheric responses show a Pacific–North American pattern. It is consistent with west–east contrast in T air and more rainfall over the Southwest during the CPAC ENSO winters.
Abstract
Data from observations and the Intergovernmental Panel on Climate Change (IPCC) twentieth-century climate change model [phase 3 of the Coupled Model Intercomparison Project (CMIP3)] simulations were analyzed to examine the decadal changes of the impact of ENSO on air temperature T air and precipitation P over the United States. The comparison of composites for the early period (1915–60) and the recent period (1962–2006) indicates that cooling (warming) over the south and warming (cooling) over the north during ENSO warm (cold) winters have been weakening. The ENSO influence on winter P over the Southwest is strengthening, while the impact on P over the Ohio Valley is weakening for the recent decades. These differences are not due to the long-term trends in T air or P; they are attributed to the occurrence of the central Pacific (CPAC) ENSO events in the recent years. The CPAC ENSO differs from the canonical eastern Pacific (EPAC) ENSO. The EPAC ENSO has a sea surface temperature anomaly (SSTA) maximum in the eastern Pacific. Enhanced convection extends from the date line to the eastern Pacific, with negative anomalies in the western Pacific. The atmospheric responses resemble a tropical Northern Hemisphere pattern. The wave train is consistent with the north–south T air contrast over North America during the EPAC ENSO winters. The CPAC ENSO has enhanced convection in the central Pacific. The atmospheric responses show a Pacific–North American pattern. It is consistent with west–east contrast in T air and more rainfall over the Southwest during the CPAC ENSO winters.
Abstract
No abstract available.
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Abstract
Long-term trends and interannual variations of circulation anomalies in the Southern Hemisphere are examined using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis from 1949 to 1998. The changes in planetary circulation regimes are linked to global sea surface temperature anomalies (SSTAs).
Empirical orthogonal function (EOF) analysis was performed on 500-hPa height anomalies. The leading mode EOF1 shows a strong zonal symmetry with a phase reversal between height anomalies in high and midlatitudes. Apart from zonal symmetry, a zonal wavenumber 3 is evident with three centers located in three southern oceans. In the low-frequency band with fluctuations longer than 60 months, EOF1 is associated with the second rotated EOF mode of SSTAs with positive loadings over three southern oceans and negative loadings in the North Pacific and the North Atlantic.
The next two modes are the Pacific–South American (PSA) patterns. They depict wave-3 patterns in quadrature with each other and a well-defined wave train from the tropical Pacific to Argentina with large amplitudes in the Pacific–South American sector. On decadal timescales, the abrupt warming over the central and eastern Pacific is related to the strengthening of PSA1. In the interannual band, PSA1 is associated with the low-frequency part of El Niño–Southern Oscillation (ENSO) variability with the dominant period of 40–48 months. PSA2 is associated with the quasi-biennial component of ENSO variability with a period of 26 months.
Abstract
Long-term trends and interannual variations of circulation anomalies in the Southern Hemisphere are examined using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis from 1949 to 1998. The changes in planetary circulation regimes are linked to global sea surface temperature anomalies (SSTAs).
Empirical orthogonal function (EOF) analysis was performed on 500-hPa height anomalies. The leading mode EOF1 shows a strong zonal symmetry with a phase reversal between height anomalies in high and midlatitudes. Apart from zonal symmetry, a zonal wavenumber 3 is evident with three centers located in three southern oceans. In the low-frequency band with fluctuations longer than 60 months, EOF1 is associated with the second rotated EOF mode of SSTAs with positive loadings over three southern oceans and negative loadings in the North Pacific and the North Atlantic.
The next two modes are the Pacific–South American (PSA) patterns. They depict wave-3 patterns in quadrature with each other and a well-defined wave train from the tropical Pacific to Argentina with large amplitudes in the Pacific–South American sector. On decadal timescales, the abrupt warming over the central and eastern Pacific is related to the strengthening of PSA1. In the interannual band, PSA1 is associated with the low-frequency part of El Niño–Southern Oscillation (ENSO) variability with the dominant period of 40–48 months. PSA2 is associated with the quasi-biennial component of ENSO variability with a period of 26 months.
Abstract
The ensemble canonical correlation (ECC) prediction method is used to predict summer (July–September) and winter (January–March) seasonal mean surface temperature (T surf) over the United States. The predictors are the global sea surface temperature (SST), sea level pressure over the Northern Hemisphere T surf, and soil moisture over the United States from one to two seasons lead, as well as the model outputs from the NCEP seasonal forecast model. The canonical correlation analysis (CCA) prediction is performed for each variable separately. The predicted T surf fields form an ensemble. The ensemble forecast is the weighted average of its members. Both the simple ensemble forecast and the superensemble forecast are tested. The simple ensemble mean is the equally weighted average of its members. The weighting function for the superensemble forecast is determined by linear regression analysis.
Overall, both ensemble forecasts improve skill. On average, the superensemble gives the best performance. For summer, both ensemble forecasts improve skill substantially in comparison with the CCA forecasts based on the SST alone. Different variables recognize different forcing. They have forecast skills over different regions of the United States. Therefore, the ensemble forecasts are skillful.
For summer, the leading SST modes that contribute to the sources of skill are associated with the long-term decadal trends, ENSO, and variability in the North Atlantic. In addition to SSTs, soil moisture in March–May also plays an important role in forecasting T surf in summer. For winter, SSTs in the tropical Pacific associated with the decadal and ENSO variability dominate the contribution.
Abstract
The ensemble canonical correlation (ECC) prediction method is used to predict summer (July–September) and winter (January–March) seasonal mean surface temperature (T surf) over the United States. The predictors are the global sea surface temperature (SST), sea level pressure over the Northern Hemisphere T surf, and soil moisture over the United States from one to two seasons lead, as well as the model outputs from the NCEP seasonal forecast model. The canonical correlation analysis (CCA) prediction is performed for each variable separately. The predicted T surf fields form an ensemble. The ensemble forecast is the weighted average of its members. Both the simple ensemble forecast and the superensemble forecast are tested. The simple ensemble mean is the equally weighted average of its members. The weighting function for the superensemble forecast is determined by linear regression analysis.
Overall, both ensemble forecasts improve skill. On average, the superensemble gives the best performance. For summer, both ensemble forecasts improve skill substantially in comparison with the CCA forecasts based on the SST alone. Different variables recognize different forcing. They have forecast skills over different regions of the United States. Therefore, the ensemble forecasts are skillful.
For summer, the leading SST modes that contribute to the sources of skill are associated with the long-term decadal trends, ENSO, and variability in the North Atlantic. In addition to SSTs, soil moisture in March–May also plays an important role in forecasting T surf in summer. For winter, SSTs in the tropical Pacific associated with the decadal and ENSO variability dominate the contribution.
Abstract
Two sets of experiments were performed. The first set, denoted SSTA, consisted of 90-day forecasts with sea surface temperature anomalies updated with observed values daily during the entire integration. For the summers 1987 and 1988, three SSTA experiments were made using three different initial conditions centered on 1 June of that year, separated by 1 day. The second set of experiments, denoted CSST, used the same initial conditions as the first set, but the integrations were performed using climatological SSTs. All numerical experiments were done using the NMC T80 spectral model of 1990, which is the same model used in making operational medium-range forecasts.
Simulated seasonal ensemble-mean rainfall was compared with satellite estimates of precipitation and observed station rainfall data. Overall agreement between them is good. Two centers of maximum rainfall, over the Arabian Sea and the Bay of Bengal, are captured by the model, but it fails to capture the movement of the rainfall associated with the Indian monsoon. The model is able to simulate the interannual variability of rain in India and over the Sahel, although the simulated convection in the central Pacific associated with the 1987 warm episode is not realistic.
When the model is able to simulate the convection associated with the SSTAs, then the updated SSTs have a large positive impact on tropical impact seasonal forecasts. The impact on the extratropical forecasts is, in general, positive but small.
Abstract
Two sets of experiments were performed. The first set, denoted SSTA, consisted of 90-day forecasts with sea surface temperature anomalies updated with observed values daily during the entire integration. For the summers 1987 and 1988, three SSTA experiments were made using three different initial conditions centered on 1 June of that year, separated by 1 day. The second set of experiments, denoted CSST, used the same initial conditions as the first set, but the integrations were performed using climatological SSTs. All numerical experiments were done using the NMC T80 spectral model of 1990, which is the same model used in making operational medium-range forecasts.
Simulated seasonal ensemble-mean rainfall was compared with satellite estimates of precipitation and observed station rainfall data. Overall agreement between them is good. Two centers of maximum rainfall, over the Arabian Sea and the Bay of Bengal, are captured by the model, but it fails to capture the movement of the rainfall associated with the Indian monsoon. The model is able to simulate the interannual variability of rain in India and over the Sahel, although the simulated convection in the central Pacific associated with the 1987 warm episode is not realistic.
When the model is able to simulate the convection associated with the SSTAs, then the updated SSTs have a large positive impact on tropical impact seasonal forecasts. The impact on the extratropical forecasts is, in general, positive but small.
Abstract
No abstract available.
Abstract
No abstract available.
