• Becker, E. J., , E. H. Berbery, , and R. W. Higgins, 2009: Understanding the characteristics of daily precipitation over the United States using the North American Regional Reanalysis. J. Climate, 22, 62686286.

    • Search Google Scholar
    • Export Citation
  • Berbery, E. H., , and C. S. Vera, 1996: Characteristics of the Southern Hemisphere winter storm track with filtered and unfiltered data. J. Atmos. Sci., 53, 468481.

    • Search Google Scholar
    • Export Citation
  • Bjerknes, J., 1951: Extratropical cyclones. Compendium of Meteorology, T. F. Malone, Ed., Amer. Meteor. Soc., 577–598.

  • Bond, N. A., , and G. A. Vecchi, 2003: The influence of the Madden–Julian oscillation on precipitation in Oregon and Washington. Wea. Forecasting, 18, 600613.

    • Search Google Scholar
    • Export Citation
  • Cassou, C., 2008: Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation. Nature, 455, 523527.

    • Search Google Scholar
    • Export Citation
  • Chang, E. K. M., 1993: Downstream development of baroclinic waves as inferred from regression analysis. J. Atmos. Sci., 50, 20382053.

    • Search Google Scholar
    • Export Citation
  • Cressman, J. E., 1959: An operational objective analysis system. Mon. Wea. Rev., 87, 367374.

  • Ek, M., , K. Mitchell, , Y. Lin, , E. Rogers, , P. Grunmann, , V. Koren, , G. Gayno, , and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation
  • Hendon, H. H., , and M. L. Salby, 1994: The life cycle of the Madden–Julian Oscillation. J. Atmos. Sci., 51, 22252237.

  • Higgins, R. W., , A. Leetmaa, , Y. Xue, , and A. Barnston, 2000a: Dominant factors influencing the seasonal predictability of U.S. precipitation and surface air temperature. J. Climate, 13, 39944017.

    • Search Google Scholar
    • Export Citation
  • Higgins, R. W., , W. Shi, , E. Yarosh, , and R. Joyce, 2000b: Improved United States Precipitation Quality Control System and Analysis. NCEP/Climate Prediction Center Atlas 7, National Oceanic and Atmospheric Administration, 40 pp.

    • Search Google Scholar
    • Export Citation
  • Higgins, R. W., , V. E. Kousky, , H.-K. Kim, , W. Shi, , and D. Unger, 2002: High Frequency and Trend Adjusted Composites of United States Temperature and Precipitation by ENSO Phase. NCEP/Climate Prediction Center Atlas 10, 22 pp.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., , and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38, 11791196.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., , and K. I. Hodges, 2002: New perspectives on the Northern Hemisphere winter storm tracks. J. Atmos. Sci., 59, 10411061.

    • Search Google Scholar
    • Export Citation
  • Jones, C., 2000: Occurrence of extreme precipitation events in California and relationships with the Madden–Julian oscillation. J. Climate, 13, 35763587.

    • Search Google Scholar
    • Export Citation
  • Jones, C., , D. E. Waliser, , K. M. Lau, , and W. Stern, 2004: Global occurrences of extreme precipitation and the Madden–Julian oscillation: Observations and predictability. J. Climate, 17, 45754589.

    • Search Google Scholar
    • Export Citation
  • Knutson, T. R., , and K. M. Weickmann, 1987: 30–60 day atmospheric oscillations: Composite life cycles of convection and circulation anomalies. Mon. Wea. Rev., 115, 14071436.

    • Search Google Scholar
    • Export Citation
  • L’Heureux, M. L., , and R. W. Higgins, 2008: Boreal winter links between the Madden–Julian oscillation and the Arctic Oscillation. J. Climate, 21, 30403050.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., , and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 12751277.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., , and P. R. Julian, 1971: Description of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., , and P. R. Julian, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 11091123.

    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360.

  • Mo, K. C., , and W. R. Higgins, 1998a: Tropical influences on California precipitation. J. Climate, 11, 412430.

  • Mo, K. C., , and W. R. Higgins, 1998b: Tropical convection and precipitation regimes in the western United States. J. Climate, 11, 24042423.

    • Search Google Scholar
    • Export Citation
  • Reichler, T., , and J. O. Roads, 2005: Long-range predictability in the tropics. Part II: 30–60-day variability. J. Climate, 18, 634650.

    • Search Google Scholar
    • Export Citation
  • Silva, V. B. S., , and E. H. Berbery, 2006: Intense rainfall events affecting the La Plata Basin. J. Hydrometeor., 7, 769787.

  • Uccellini, L. W., , and P. J. Kocin, 1987: The interaction of jet streak circulations during heavy snow events along the East Coast of the United States. Wea. Forecasting, 2, 289308.

    • Search Google Scholar
    • Export Citation
  • Waliser, D. E., , K. M. Lau, , W. Stern, , and C. Jones, 2003: Potential predictability of the Madden–Julian oscillation. Bull. Amer. Meteor. Soc., 84, 3350.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M. C., , and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 19171932.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 2005: Madden–Julian Oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158.

  • View in gallery

    November–March composite OLR anomalies (W m−2) indexed by MJO phase, from NOAA OLR data. Enhanced convection, indicated by a negative anomaly in OLR (blue), moves eastward across the tropics during an MJO event.

  • View in gallery

    MJO events during the cold season (November–March), 1979–2005. The events were determined using the CPC’s MJO event criteria: the MJO index must have a magnitude greater than 1 for consecutive pentads, the phases must be in numerical order, and the MJO must meet the first two criteria for more than five pentads and not remain stationary (in one phase) for more than four pentads. In this figure, each dot represents one pentad. The vertical axis shows the phase, and phases 5, 6, and 7 are indicated in blue.

  • View in gallery

    Mean precipitation rate (mm day−1) during November–March, from CPC unified rain gauge database for 1979–2005.

  • View in gallery

    Composite cold season (November–March, 1979–2005) precipitation rate anomaly (mm day−1) for each of the eight MJO phases defined by the Wheeler–Hendon index. Precipitation data are from the CPC’s Unified Raingauge Dataset (URD).

  • View in gallery

    Composite precipitation rate anomaly for MJO (top) phases 2–4 (when MJO-related enhanced convection is located in Indian Ocean) and (bottom) phases 5–7 (convection in western and central Pacific). Areas where the anomaly is significant at the 95% level are indicated with hatching. Black overlay shows the Mississippi River basin and its subbasins.

  • View in gallery

    Composite change in (top) precipitation frequency and (bottom) intensity during phases 5–7 of the MJO. Values are normalized by local November–March mean.

  • View in gallery

    Composite vertically integrated moisture flux convergence anomaly during cold season MJO phases 5–7 (mm day−1) from NARR.

  • View in gallery

    (top) 200-hPa zonal wind mean (contours) and anomaly during MJO phases 5–7 (shaded; in m s−1) illustrating the jet stream. (middle) The storm track can be detected using the 200-hPa meridional wind standard deviation during November–March (contours) and anomalies in the standard deviation during MJO phases 5–7 (shaded). (bottom) Anomalies in the 200-hPa meridional wind (m s−1). Wind data from NARR.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 86 86 24
PDF Downloads 40 40 17

Modulation of Cold-Season U.S. Daily Precipitation by the Madden–Julian Oscillation

View More View Less
  • 1 NOAA/NWS/NCEP, Climate Prediction Center, Camp Springs, Maryland
  • | 2 Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland
  • | 3 NOAA/NWS/NCEP, Climate Prediction Center, Camp Springs, Maryland
© Get Permissions
Full access

Abstract

This study examines the characteristics of cold-season (November–March) daily precipitation over the contiguous United States during active periods of the Madden–Julian oscillation (MJO). A large response in the precipitation rate anomaly is found over the eastern United States when MJO-related enhanced tropical convection is moving through the far western to central Pacific (conventionally known as phases 5, 6, and 7 of the MJO). Positive anomalies occur in the region of the eastern Mississippi River basin, and negative anomalies occur in the Southeast. The relative stability of this pattern throughout the three phases suggests that they can be considered together. During phases 5–7, the central United States has a daily precipitation rate between 110% and 150% of normal, while the precipitation rate over much of Florida is less than 70% of normal. Much of the lower Mississippi River basin region receives somewhat more frequent daily precipitation during MJO phases 5–7, but a greater increase is found in the daily precipitation intensity, suggesting more intense storms. On the other hand, Florida has substantially fewer daily precipitation events, with a smaller decrease in the intensity.

To understand the atmospheric mechanisms related to the above shifts in daily precipitation, elements of the atmospheric circulation were examined. Positive moisture flux convergence anomalies, which have been linked to increased precipitation rate and intensity, are found in the region of increased precipitation rate during MJO phases 5–7. During those phases, the North American jet stream is shifted northward, likely leading to a higher incidence of storms over the lower Mississippi River basin and fewer storms over Florida. This is supported by the fact that the storm track also shows increased activity over the central United States during MJO phases 5–7.

Corresponding author address: E. H. Berbery, Department of Atmospheric and Oceanic Science/ESSIC, University of Maryland, College Park, 3427 Computer and Space Sciences Bldg., College Park, MD 20742-2425. E-mail: berbery@atmos.umd.edu

Abstract

This study examines the characteristics of cold-season (November–March) daily precipitation over the contiguous United States during active periods of the Madden–Julian oscillation (MJO). A large response in the precipitation rate anomaly is found over the eastern United States when MJO-related enhanced tropical convection is moving through the far western to central Pacific (conventionally known as phases 5, 6, and 7 of the MJO). Positive anomalies occur in the region of the eastern Mississippi River basin, and negative anomalies occur in the Southeast. The relative stability of this pattern throughout the three phases suggests that they can be considered together. During phases 5–7, the central United States has a daily precipitation rate between 110% and 150% of normal, while the precipitation rate over much of Florida is less than 70% of normal. Much of the lower Mississippi River basin region receives somewhat more frequent daily precipitation during MJO phases 5–7, but a greater increase is found in the daily precipitation intensity, suggesting more intense storms. On the other hand, Florida has substantially fewer daily precipitation events, with a smaller decrease in the intensity.

To understand the atmospheric mechanisms related to the above shifts in daily precipitation, elements of the atmospheric circulation were examined. Positive moisture flux convergence anomalies, which have been linked to increased precipitation rate and intensity, are found in the region of increased precipitation rate during MJO phases 5–7. During those phases, the North American jet stream is shifted northward, likely leading to a higher incidence of storms over the lower Mississippi River basin and fewer storms over Florida. This is supported by the fact that the storm track also shows increased activity over the central United States during MJO phases 5–7.

Corresponding author address: E. H. Berbery, Department of Atmospheric and Oceanic Science/ESSIC, University of Maryland, College Park, 3427 Computer and Space Sciences Bldg., College Park, MD 20742-2425. E-mail: berbery@atmos.umd.edu

1. Introduction

The Madden–Julian oscillation (MJO) is a large-scale pattern of coupled atmospheric circulation and deep convection. First documented by Madden and Julian (1971, 1972), it features a prominent area of enhanced deep convection and rainfall that propagates eastward along the equator through the Indian and Pacific Oceans at the relatively slow speed of about 5 m s−1, with an intraseasonal period of between 30 and 90 days (see Zhang 2005, and references therein). The enhanced convection signal can be identified through satellite outgoing longwave radiation (OLR), velocity potential, and upper- and lower-level winds (Knutson and Weickmann 1987).

Remote effects of the MJO have been detected at higher latitudes due to indirect mechanisms. These mechanisms include modulation of the Hadley cell by the MJO-related enhanced convection, leading to stronger 200-hPa divergence in the tropics and stronger 200-hPa convergence in higher latitudes (Mo and Higgins 1998b, see their Fig. 12). This leads to midlatitude divergence and negative Rossby wave vorticity source anomalies in the central Pacific. As the enhanced convection system moves eastward, anomalous divergent outflow generates an anomalous Rossby wave vorticity source in the subtropics, the Pacific jet extends eastward, and the North American jet moves northward (Mo and Higgins 1998b).

Several studies have tied MJO activity to altered precipitation patterns in North America (e.g., Mo and Higgins 1998a,b; Jones 2000; Bond and Vecchi 2003). An increased frequency of extreme precipitation during active MJO has been identified in areas of Africa, the Middle East, eastern China, eastern South America, and parts of North America (Jones et al. 2004). Jones et al. (2004) found that, for areas with an MJO signal, the number of extreme precipitation events occurring during the active MJO was about 40% higher than the number occurring during the quiescent phase. Some differences exist in the results of these studies, possibly due to different methods of MJO identification. For example, Jones (2000) found a slight tendency for increased extreme events in California when enhanced convection is located over the Indian Ocean, while Mo and Higgins (1998b) found no significant precipitation anomaly over the United States for this condition.

Most previous studies of MJO effects on the continental United States have focused on the western United States. The findings of these include dry conditions in the southwest and wet conditions in the Pacific Northwest during winter when enhanced convection is located in the western Pacific (Mo and Higgins 1998b), and a link between MJO-related enhanced convection in Indonesia and the western Pacific and extreme 3-day precipitation events along the West Coast (Higgins et al. 2000a). Bond and Vecchi (2003), looking at Oregon and Washington State during early winter, found as much as a 200% difference between precipitation rates, depending on the location of MJO-related westerly wind anomalies.

Dynamical forecasting of the MJO suggests a potential for predictability out to three or four weeks (Waliser et al. 2003; Reichler and Roads 2005), and an understanding of MJO-related modulation of precipitation over the United States can contribute to improved forecasting of weather and climate. This forecasting range of one to four weeks, often thought of as the bridge between “weather” and “climate,” is an area in need of research. Here we examine the teleconnections between MJO-related enhanced tropical convection and daily precipitation in the central and eastern United States, and explore possible mechanisms for the patterns that are found. Section 2 of this paper presents the indexing methods used to determine an MJO event, as well as the data used in this study. Section 3 discusses the main results, that is, the MJO-related modulation of regional circulation during November–March and its links to changes in precipitation over the United States. A summary and conclusions are presented in section 4.

2. MJO indices and data

Over the past few decades, many different methods have been used to identify the presence, strength, and phase of the MJO, often relying on simultaneous or lagged OLR and wind measurements. Wheeler and Hendon (2004) proposed an MJO-indexing method that is based on the first two empirical orthogonal functions (EOFs) of the combined fields of near-equatorially-averaged 850-hPa zonal wind, 200-hPa zonal wind, and OLR data. In this method, and before the EOFs are computed, ENSO variability and the 120-day mean of the most recent 120 days at each point are removed. The magnitude of the index indicates the amplitude of the MJO: a magnitude greater than 1 is considered a strong index. The two EOFs make up the x and y axis of a phase space, and the state of the MJO is diagnosed as a point in this space. The phase space is divided into 8 regions (phases 1–8), mapping the approximate location of the enhanced convective signal of the MJO around the global tropics. The enhanced convection signal of the MJO generally develops in the Indian Ocean, propagates across the Maritime Continent, and weakens as it crosses the date line (Hendon and Salby 1994), but MJO-related enhanced convection can also develop elsewhere in the tropics, and can pass from the Western Hemisphere into Africa and the Indian Ocean (i.e., from phase 8 into phase 1).

While the Wheeler and Hendon (2004) MJO index identifies the strength and location of enhanced tropical convection, it is necessary to apply further criteria to identify “MJO events” (i.e., when the tropical convection is propagating eastward on time scales congruent with the MJO). The Climate Prediction Center (CPC) has recently developed an MJO event classification following Wheeler and Hendon (2004)’s approach, but applied to pentad-averaged data. The CPC classification system sets 3 criteria for an MJO event (L’Heureux and Higgins 2008; M. L’Heureux 2009, personal communication): the MJO index must have a magnitude greater than 1 for consecutive pentads, the phases must be in numerical order (to indicate eastward propagation; e.g., 5, 6, 7, 8, 1, 2), and the MJO must meet the first two criteria for more than five pentads and not remain stationary (in one phase) for more than four pentads. As the indexing method relies on satellite-derived OLR, the event classification includes the satellite era only (1979–present). The CPC index was used in our study to build the composites and their time evolution.

Figure 1 presents the OLR anomalies [derived from the National Oceanic and Atmospheric Administration (NOAA) interpolated OLR; Liebmann and Smith 1996] composited for November–March 1979–2008 using the CPC’s MJO event classification. This figure is similar to those of earlier MJO studies, for example Bond and Vecchi (2003, their Fig. 1) and Cassou (2008, their Fig. 2). The eastward movement of the enhanced convection through the eight phases is readily noticed: phases 1–3 reveal the developmental stages of MJO-related enhanced convection (negative OLR anomalies) over the Indian Ocean. This anomaly grows and progresses through the Pacific Ocean in phases 5–8. As the MJO propagates into the Western Hemisphere, the enhanced convection signal decreases (Fig. 1, phase 7). The MJO is still identifiable in the velocity potential and upper- and lower-level winds, however, and continues to move eastward at an increased rate of approximately 10 m s−1 (Hendon and Salby 1994). Using the CPC’s event classification, the MJO is in an “active” state approximately 60% of days during November–March in the 1979–2005 record (Fig. 2). Figure 2, which depicts all of the MJO events examined in this study, also illustrates the progression through the phases of an MJO event.

Fig. 1.
Fig. 1.

November–March composite OLR anomalies (W m−2) indexed by MJO phase, from NOAA OLR data. Enhanced convection, indicated by a negative anomaly in OLR (blue), moves eastward across the tropics during an MJO event.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

Fig. 2.
Fig. 2.

MJO events during the cold season (November–March), 1979–2005. The events were determined using the CPC’s MJO event criteria: the MJO index must have a magnitude greater than 1 for consecutive pentads, the phases must be in numerical order, and the MJO must meet the first two criteria for more than five pentads and not remain stationary (in one phase) for more than four pentads. In this figure, each dot represents one pentad. The vertical axis shows the phase, and phases 5, 6, and 7 are indicated in blue.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

A gridded daily precipitation analysis obtained from the CPC (available online at ftp://ftp.cpc.ncep.noaa.gov/precip/CPC_UNI_PRCP/GAUGE_GLB/) is employed to examine MJO-related modulation of precipitation over the United States. The gridded daily analysis (Higgins et al. 2000b) was produced using the CPC’s Unified Rain Gauge Database, which contains precipitation information from over 8000 stations across the United States. The station data was used to make a 1200–1200 UTC daily analysis, and gridded to a 0.25° × 0.25° latitude–longitude grid using a Cressman (1959) interpolation scheme. The quality control of the dataset is discussed by Higgins et al. (2000b).

To explore the mechanisms related to the modulation of precipitation, a complementary analysis was performed using the North American Regional Reanalysis (NARR). NARR is a long-term, dynamically consistent, high-resolution (32 km, 45 layers), high-frequency (3 h), atmospheric and land surface hydrology dataset for the North American domain (Mesinger et al. 2006). The regional reanalysis was developed with the 2003 version of the Eta model and its associated Eta data assimilation system. The Eta model is coupled to the Noah land surface model (Ek et al. 2003) that simulates land surface temperature, the components of the surface energy balance and the surface water balance, and the evolution of soil temperature and soil moisture, both liquid and frozen. In NARR, precipitation is converted to latent heat and then assimilated. In the assimilation process all variables reach equilibrium, and thus precipitation is allowed to affect other dynamical variables [further details can be found in Mesinger et al. (2006)].

3. MJO modulation of U.S. precipitation during the cold season

a. Precipitation patterns

The mean U.S. November–March precipitation rate (average over all days in the sample) from the gridded observations (Fig. 3) features the highest precipitation rate over the West Coast and the mountains of the Pacific Northwest and California. Another region of high precipitation rate is found in the southeastern United States. To better understand the modulation of this pattern by the MJO, composite precipitation anomalies during each of the eight MJO phases were examined (Fig. 4). The anomalies are created by indexing the daily precipitation data using the CPC’s MJO indexing method, averaging the precipitation rate over all days in each phase, and subtracting the mean November–March precipitation rate. Looking first at the West Coast, some correspondence to earlier studies is seen, including high precipitation in California during MJO phase 3, when enhanced convection is located in the Indian Ocean (Jones 2000). We also see the tendency for higher precipitation in California when enhanced convection is located in the western Pacific (Mo and Higgins 1998a) and the modulation of the precipitation rate in the Pacific Northwest (Bond and Vecchi 2003).

Fig. 3.
Fig. 3.

Mean precipitation rate (mm day−1) during November–March, from CPC unified rain gauge database for 1979–2005.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

Fig. 4.
Fig. 4.

Composite cold season (November–March, 1979–2005) precipitation rate anomaly (mm day−1) for each of the eight MJO phases defined by the Wheeler–Hendon index. Precipitation data are from the CPC’s Unified Raingauge Dataset (URD).

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

Bond and Vecchi (2003) found a sharp difference between early winter (October–December) and late winter (January–March) in MJO-modulated Oregon and Washington precipitation rates. According to these authors, the region has a positive precipitation anomaly during MJO phase 7 in early winter and a negative precipitation anomaly for the same phase during late winter. In the current study, a similar switch in sign is found for West Coast precipitation anomalies between the first and second halves of the cold season, but not shown.

The precipitation rate anomaly exhibits a large response in the eastern half of the United States (Fig. 4) during phases 5, 6, and 7 of the MJO, when the enhanced tropical convection is moving through the far western to central Pacific (see Fig. 1). Positive anomalies occur in the region of the eastern Mississippi River basin, and negative anomalies in the Southeast. While the anomalies are not identical, the relative stability of this pattern throughout the three phases suggests they can be combined (Fig. 5). Statistical significance was assessed using a resampling test with 10 000 permutations, and areas above the 95th level are indicated with crosshatching. During phases 5–7, the southern central United States has a precipitation rate between 110% and 150% of normal, while the precipitation rate in much of Florida is less than 70% of normal (Fig. 5, top, shows the anomaly in mm day−1; the percentage change in precipitation is not shown, but was calculated for description). In contrast, precipitation anomalies during phases 2–4 (Fig. 5, bottom), do not show a coherent large-scale pattern, suggesting weaker teleconnections between the central United States and MJO-related enhanced tropical convection in the Indian Ocean. The precipitation anomaly during MJO phases 5–7 is present in both the early and late halves of the November–March cold season, unlike the differences seen in West Coast precipitation (not shown).

Fig. 5.
Fig. 5.

Composite precipitation rate anomaly for MJO (top) phases 2–4 (when MJO-related enhanced convection is located in Indian Ocean) and (bottom) phases 5–7 (convection in western and central Pacific). Areas where the anomaly is significant at the 95% level are indicated with hatching. Black overlay shows the Mississippi River basin and its subbasins.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

The frequency of precipitation (number of days with 1.0 mm or greater) and intensity (average over days only with recorded precipitation of 1.0 mm or greater; Fig. 6) provide additional insight into the characteristics of the precipitation rate anomaly. Much of the lower Mississippi River basin region exhibits an increase of the precipitation frequency during MJO phases 5–7, but a greater increase is found in the intensity (i.e., it rains/snows slightly more often during these phases of the MJO, but the average 1-day total is substantially higher than the seasonal mean). On the other hand, the precipitation decrease in Florida is primarily due to fewer daily precipitation events, with a smaller decrease in the intensity.

Fig. 6.
Fig. 6.

Composite change in (top) precipitation frequency and (bottom) intensity during phases 5–7 of the MJO. Values are normalized by local November–March mean.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

This study focuses on contemporaneous MJO phase and teleconnection responses. Since an MJO event, using the identification method detailed in section 2, progresses through phases in numerical order, remaining in each phase for one to four pentads (usually fewer; see Fig. 2), the lag responses generally resembled the simultaneous response for the next phase. For example, the phase 4 response at a lag of 1 pentad resembled the no-lag phase 5 response. Hence, while the teleconnection may be the result of the enhanced convection during the previous phase, the effect is manifest during the current phase. This question of the lag between the forcing in the tropics and the response in the eastern United States is an interesting point that deserves further investigation in a separate study.

b. Mechanisms

To understand the possible mechanisms that may lead to the above shifts in daily precipitation, the atmospheric circulation is examined during periods when MJO-related enhanced convection is active. As several fields from NARR were used for this part of the study, the composite anomalies in NARR precipitation during active MJO phases (not shown) were compared to the anomalies in observed precipitation (Figs. 4 and 5). The anomalies in NARR precipitation were found to be very similar to those in the observed precipitation.

A comparison of observed precipitation patterns with those of the NARR vertically integrated moisture flux convergence (viMFC) gives a sense of the forcing of precipitation. In general, positive viMFC anomalies are linked to increased precipitation rate and intensity (Silva and Berbery 2006; Becker et al. 2009). As most atmospheric water vapor is contained in the lower troposphere, viMFC composites give a picture of the lower-tropospheric circulation and water vapor content. The composite NARR viMFC anomalies during MJO phases 5–7 (Fig. 7) feature a strong positive anomaly, indicating anomalous convergence and more moisture availability than the average, over the central United States in the area of the positive precipitation anomaly (Fig. 5) and increased precipitation intensity (Fig. 6). In other words, the collocation of the precipitation and viMFC anomalies strongly hints at the dynamical nature of the precipitation forcing. In the Southeast and Florida, the relationship between weaker precipitation during MJO phases 5–7 and negative viMFC anomalies is not as clear (Fig. 7). This is not surprising, as the MJO-related modulation of precipitation over Florida is mainly through changes in the frequency rather than in the intensity (see Fig. 6), and viMFC appears to predominantly affect changes in intensity.

Fig. 7.
Fig. 7.

Composite vertically integrated moisture flux convergence anomaly during cold season MJO phases 5–7 (mm day−1) from NARR.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

Mo and Higgins (1998a,b) have shown that enhanced convection in the tropical western Pacific relates to shifts in the extratropical winter jet stream and storm track on daily time scales, leading to precipitation anomalies over North America. During MJO phases 5–7, when the enhanced tropical convection is moving eastward through the western Pacific, the mean 200-hPa zonal wind over North America (Fig. 8, top, shaded area) indicates that the jet core is shifted northward from its November–March climatological position (Fig. 8, top, contours). Upper-level divergence is found along the southern side of a jet entrance region, where flow is accelerating (Bjerknes 1951; Uccellini and Kocin 1987). When the jet moves northward, this area of divergence is displaced northward from its mean position over the Gulf of Mexico. This shifts the large upper-level divergence and associated ascending motion, likely contributing to more and stronger daily precipitation events over the Mississippi River basin and fewer events over Florida. Cassou (2008) observed similar shifts to the jet and upper-level divergence during and after phase 6 of the MJO.

Fig. 8.
Fig. 8.

(top) 200-hPa zonal wind mean (contours) and anomaly during MJO phases 5–7 (shaded; in m s−1) illustrating the jet stream. (middle) The storm track can be detected using the 200-hPa meridional wind standard deviation during November–March (contours) and anomalies in the standard deviation during MJO phases 5–7 (shaded). (bottom) Anomalies in the 200-hPa meridional wind (m s−1). Wind data from NARR.

Citation: Journal of Climate 24, 19; 10.1175/2011JCLI4018.1

This is further supported by the changes in the storm track, computed as the standard deviation of the unfiltered 200-hPa meridional wind (Chang 1993; Berbery and Vera 1996; Hoskins and Hodges 2002). The average storm track during November–March in the 27-yr record (Fig. 8, middle, contours), shows peaks of storm activity in the northeast Pacific and the central United States. During MJO phases 5–7, the anomaly in the standard deviation of the 200-hPa meridional wind (Fig. 8, middle, shaded) is positive over the northern half of the United States, and in particular the Midwest region, indicating a more active storm track in this area. Negative anomalies are seen over the northern Gulf of Mexico, suggesting that fewer storms would impact Florida. Consistent with the above picture, the anomalies in the 200-hPa mean meridional wind during phases 5–7 (Fig. 8, lower) also indicate a deeper synoptic wave pattern with an upper-level anticyclonic rotation over the central United States. Taken in consideration with Fig. 7, which indicates convergence in the lower-level circulation, these conditions suggest more, stronger storms affect the area of the lower Mississippi River basin.

c. MJO-related precipitation anomalies compared to ENSO

It is desirable to place the precipitation anomalies associated with the MJO in the context of anomalies due to other sources of precipitation variability. The El Niño–Southern Oscillation (ENSO) also modulates the characteristics of daily precipitation over the United States through tropical–extratropical teleconnections (e.g., Higgins et al. 2002; Becker et al. 2009), and enhanced tropical convection in the Pacific basin is a feature of both the MJO and ENSO. (Although, importantly, MJO-related enhanced convection propagates eastward along the equator on intraseasonal time scales, and ENSO-related convection is stationary, and develops on seasonal to interannual time scales.) To understand the magnitude of precipitation anomalies during some phases of the MJO and during ENSO phases, the composite anomalies over two boxes of 2° longitude by 2° latitude were examined (Table 1). The two locations, one in the lower Mississippi River basin (34°–36°N, 94°–92°W) and one in Florida (27°–29°N, 81°–83°W), are both areas with a strong signal during MJO phases 5–7 (see Fig. 5). The precipitation rates were area averaged over the land grid points in each box (64 in the Mississippi River basin box and 58 in the Florida box). ENSO phase was identified using the oceanic Niño index (ONI), compiled by the CPC (see online at http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml). For the purposes of this study, we focused on stronger ENSO events, and El Niño (La Niña) is characterized by an ONI greater than or equal to 0.9°C (less than or equal to −0.9°C).

Table 1.

Mean precipitation rate for two 2° latitude by 2° longitude boxes: one located in the lower Mississippi River basin and one in the Southeast. The boundaries of the boxes are listed in the second row of the table. Mean precipitation rates (mm day−1) are given for the November–March average and for 5 temporal subsets: when the MJO is in phases 5–7, MJO phases 2–4, El Niño, La Niña, and ENSO-neutral. Mean values that represent anomalies significant at the 95% level are in bold. All units are (mm day−1).

Table 1.

First, tests carried out by dividing the data sample into El Niño, La Niña, and neutral conditions (not shown) indicate that the presence of wet anomalies in the south-central United States and dry anomalies in Florida during MJO phases 5–7 was robust for all ENSO phases. Next, five composites were created for each location: MJO phases 5–7 (889 days total in composite), MJO phases 2–4 (927 days), strong El Niño (905 days), strong La Niña (544 days), and ENSO-neutral days (2061 days). The full 1979–2005 November–March time series comprises 4084 days. The MJO and ENSO composites are not exclusive, that is, a specific day may be included in both an MJO composite and an ENSO composite (while it is tempting to further subdivide the sample, the time series is insufficient to provide significant results). For reference, the November–March daily mean precipitation rate is included in the table. Precipitation rates that deviate significantly from the seasonal mean are indicated in bold; significance was assessed using the t test.

Table 1 shows that in the lower Mississippi basin, during MJO phases 5–7 the precipitation rate is 4.40 mm day−1 (i.e., a significant anomaly that reaches 123% of the seasonal mean). The precipitation rate during MJO phases 2–4 and ENSO phases does not show statistically significant differences. In Florida, the precipitation rate is well below normal during MJO phases 5–7 (58% of the seasonal mean), as well as during La Niña (57% of the seasonal mean), while El Niño brings an increased precipitation rate to this region (149% of the seasonal mean). The results presented in Table 1 show that in Florida the effect on precipitation due to MJO phases 5–7 is similar to that due to La Niña. The shifts in the characteristics of precipitation, namely the intensity and frequency of precipitation (see section 3a above), are also similar during MJO phases 5–7 and La Niña in Florida. While both frequency and intensity decrease over this area, the decrease in frequency is greater than that of intensity (Fig. 6, for MJO, not shown for La Niña). Note, however, that despite having similar structure, the precipitation anomalies may respond to different mechanisms, with the MJO-related anomalies responding to changes as those described in section 3b, while ENSO anomalies respond to stationary teleconnection patterns (e.g., Hoskins and Karoly 1981). This may be the reason why over the lower Mississippi River basin, the rate and characteristics of precipitation during MJO phases 5–7 do not resemble those during any of the ENSO phases. On a related note, this study includes all MJO events during the cold season in the period 1979–2005, regardless of duration, which can vary from around 30 to around 60 days. Also, an event can linger in a particular phase for up to 4 pentads. It is likely that events of different durations would have different tropical–extratropical teleconnections. It would be interesting to look at this as a function of MJO duration in a separate study.

4. Summary and discussion

An understanding of the modulation of precipitation by large-scale climate modes is necessary for improved forecasting in the range of 1–4 weeks. This study examined MJO-related modulation of the characteristics of daily precipitation during the cold season (November–March) over the central and eastern United States. The contemporary circulation changes were then explored using the NARR dataset.

A prominent MJO-related anomaly in the U.S. cold season precipitation occurs over the central and southern United States during MJO phases 5–7, when enhanced tropical convection is moving eastward from the far western Pacific into the central Pacific. During this period, the precipitation rate over the southern Mississippi River basin is between 110% and 150% of normal, while the Florida precipitation rate is reduced to less than 70% of normal. The magnitude of these anomalies is on the order of those attributed to ENSO in the southeastern United States, but significant MJO-related anomalies exist over the lower Mississippi River basin, an area where significant ENSO-related anomalies are not found.

Much of the positive precipitation anomaly in the southern Mississippi River basin is accounted for by increased precipitation intensity, with a small increase in the frequency of precipitation. On the other hand, the negative precipitation anomaly in Florida during MJO phases 5–7 is due to a decrease in the frequency of events rather than to a decrease in intensity. These features, and the overall pattern of a drier Southeast and a wetter south-central United States, will be useful for short-term climate prediction, which is often implemented as an increased probability of an anomaly over a geographical region.

The changes in precipitation are consistent with the changes in circulation due to the evolution of the MJO. The lower atmosphere shows strong moisture flux convergence over the southern Mississippi River basin, in the region of the positive precipitation anomaly during MJO phases 5–7. Also during these phases, the North American jet core is shifted farther north than the winter mean. This likely leads to northward displacement of the area of upper-level divergence, anticyclonic circulation, and rising motion that forms on the southern flank of a jet entrance region, leading to more precipitation over this region. Additionally, anomalies in the storm track indicate increased storminess over the central United States during this period.

The slow eastward progression of the MJO and its modulation of precipitation over higher latitudes make it a potential contributor to the predictability of climate over the United States. An understanding of the relationship between phases 5–7 of the MJO and altered precipitation rate, intensity, and frequency over regions of the eastern United States will hopefully contribute to forecasts in the range of 1–4 weeks.

Acknowledgments

The comments of three anonymous reviewers helped clarify many aspects of this article. NARR and interpolated OLR data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, and are available online at http://www.esrl.noaa.gov/psd/. This work was supported by NOAA Grant NA09OAR4310189.

REFERENCES

  • Becker, E. J., , E. H. Berbery, , and R. W. Higgins, 2009: Understanding the characteristics of daily precipitation over the United States using the North American Regional Reanalysis. J. Climate, 22, 62686286.

    • Search Google Scholar
    • Export Citation
  • Berbery, E. H., , and C. S. Vera, 1996: Characteristics of the Southern Hemisphere winter storm track with filtered and unfiltered data. J. Atmos. Sci., 53, 468481.

    • Search Google Scholar
    • Export Citation
  • Bjerknes, J., 1951: Extratropical cyclones. Compendium of Meteorology, T. F. Malone, Ed., Amer. Meteor. Soc., 577–598.

  • Bond, N. A., , and G. A. Vecchi, 2003: The influence of the Madden–Julian oscillation on precipitation in Oregon and Washington. Wea. Forecasting, 18, 600613.

    • Search Google Scholar
    • Export Citation
  • Cassou, C., 2008: Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation. Nature, 455, 523527.

    • Search Google Scholar
    • Export Citation
  • Chang, E. K. M., 1993: Downstream development of baroclinic waves as inferred from regression analysis. J. Atmos. Sci., 50, 20382053.

    • Search Google Scholar
    • Export Citation
  • Cressman, J. E., 1959: An operational objective analysis system. Mon. Wea. Rev., 87, 367374.

  • Ek, M., , K. Mitchell, , Y. Lin, , E. Rogers, , P. Grunmann, , V. Koren, , G. Gayno, , and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation
  • Hendon, H. H., , and M. L. Salby, 1994: The life cycle of the Madden–Julian Oscillation. J. Atmos. Sci., 51, 22252237.

  • Higgins, R. W., , A. Leetmaa, , Y. Xue, , and A. Barnston, 2000a: Dominant factors influencing the seasonal predictability of U.S. precipitation and surface air temperature. J. Climate, 13, 39944017.

    • Search Google Scholar
    • Export Citation
  • Higgins, R. W., , W. Shi, , E. Yarosh, , and R. Joyce, 2000b: Improved United States Precipitation Quality Control System and Analysis. NCEP/Climate Prediction Center Atlas 7, National Oceanic and Atmospheric Administration, 40 pp.

    • Search Google Scholar
    • Export Citation
  • Higgins, R. W., , V. E. Kousky, , H.-K. Kim, , W. Shi, , and D. Unger, 2002: High Frequency and Trend Adjusted Composites of United States Temperature and Precipitation by ENSO Phase. NCEP/Climate Prediction Center Atlas 10, 22 pp.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., , and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38, 11791196.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., , and K. I. Hodges, 2002: New perspectives on the Northern Hemisphere winter storm tracks. J. Atmos. Sci., 59, 10411061.

    • Search Google Scholar
    • Export Citation
  • Jones, C., 2000: Occurrence of extreme precipitation events in California and relationships with the Madden–Julian oscillation. J. Climate, 13, 35763587.

    • Search Google Scholar
    • Export Citation
  • Jones, C., , D. E. Waliser, , K. M. Lau, , and W. Stern, 2004: Global occurrences of extreme precipitation and the Madden–Julian oscillation: Observations and predictability. J. Climate, 17, 45754589.

    • Search Google Scholar
    • Export Citation
  • Knutson, T. R., , and K. M. Weickmann, 1987: 30–60 day atmospheric oscillations: Composite life cycles of convection and circulation anomalies. Mon. Wea. Rev., 115, 14071436.

    • Search Google Scholar
    • Export Citation
  • L’Heureux, M. L., , and R. W. Higgins, 2008: Boreal winter links between the Madden–Julian oscillation and the Arctic Oscillation. J. Climate, 21, 30403050.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., , and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 12751277.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., , and P. R. Julian, 1971: Description of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., , and P. R. Julian, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 11091123.

    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360.

  • Mo, K. C., , and W. R. Higgins, 1998a: Tropical influences on California precipitation. J. Climate, 11, 412430.

  • Mo, K. C., , and W. R. Higgins, 1998b: Tropical convection and precipitation regimes in the western United States. J. Climate, 11, 24042423.

    • Search Google Scholar
    • Export Citation
  • Reichler, T., , and J. O. Roads, 2005: Long-range predictability in the tropics. Part II: 30–60-day variability. J. Climate, 18, 634650.

    • Search Google Scholar
    • Export Citation
  • Silva, V. B. S., , and E. H. Berbery, 2006: Intense rainfall events affecting the La Plata Basin. J. Hydrometeor., 7, 769787.

  • Uccellini, L. W., , and P. J. Kocin, 1987: The interaction of jet streak circulations during heavy snow events along the East Coast of the United States. Wea. Forecasting, 2, 289308.

    • Search Google Scholar
    • Export Citation
  • Waliser, D. E., , K. M. Lau, , W. Stern, , and C. Jones, 2003: Potential predictability of the Madden–Julian oscillation. Bull. Amer. Meteor. Soc., 84, 3350.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M. C., , and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 19171932.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 2005: Madden–Julian Oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158.

Save