Annual Variation of Midlatitude Precipitation

Tsing-Chang Chen Atmospheric Science Program, Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

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Wan-Ru Huang Atmospheric Science Program, Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

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Eugene S. Takle Atmospheric Science Program, Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

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Abstract

Annual variation of midlatitude precipitation and its maintenance through divergent water vapor flux were explored by the use of hydrological variables from three reanalyses [(NCEP–NCAR, ECMWF Re-Analysis (ERA), and Goddard Earth Observing System (GEOS-1)] and two global precipitation datasets [Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and Global Precipitation Climatology Project (GPCP)]. Two annual variation patterns of midlatitude precipitation were identified:

  1. Tropical–midlatitude precipitation contrast: Midlatitude precipitation along storm tracks over the oceans attains its maximum in winter and its minimum in summer opposite to that over the tropical continents.

  2. Land–ocean precipitation contrast: The annual precipitation variation between the oceans and the continent masses exhibits a pronounced seesaw.

The annual variation of precipitation along storm tracks of both hemispheres follows that of the convergence of transient water vapor flux. On the other hand, the land–ocean precipitation contrast in the Northern Hemisphere midlatitudes is primarily maintained by the annual seesaw between the divergence of stationary water vapor flux over the western oceans and the convergence of this water vapor flux over the eastern oceans during winter. The pattern is reversed during the summer. This divergence–convergence exchange of stationary water vapor flux is coupled with the annual evolution of upper-level ridges over continents and troughs over the oceans.

Corresponding author address: Dr. Tsing-Chang (Mike) Chen, Atmospheric Science Program, Department of Geological and Atmospheric Sciences, 3010 Agronomy Hall, Iowa State University, Ames, IA 50011. Email: tmchen@iastate.edu

Abstract

Annual variation of midlatitude precipitation and its maintenance through divergent water vapor flux were explored by the use of hydrological variables from three reanalyses [(NCEP–NCAR, ECMWF Re-Analysis (ERA), and Goddard Earth Observing System (GEOS-1)] and two global precipitation datasets [Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and Global Precipitation Climatology Project (GPCP)]. Two annual variation patterns of midlatitude precipitation were identified:

  1. Tropical–midlatitude precipitation contrast: Midlatitude precipitation along storm tracks over the oceans attains its maximum in winter and its minimum in summer opposite to that over the tropical continents.

  2. Land–ocean precipitation contrast: The annual precipitation variation between the oceans and the continent masses exhibits a pronounced seesaw.

The annual variation of precipitation along storm tracks of both hemispheres follows that of the convergence of transient water vapor flux. On the other hand, the land–ocean precipitation contrast in the Northern Hemisphere midlatitudes is primarily maintained by the annual seesaw between the divergence of stationary water vapor flux over the western oceans and the convergence of this water vapor flux over the eastern oceans during winter. The pattern is reversed during the summer. This divergence–convergence exchange of stationary water vapor flux is coupled with the annual evolution of upper-level ridges over continents and troughs over the oceans.

Corresponding author address: Dr. Tsing-Chang (Mike) Chen, Atmospheric Science Program, Department of Geological and Atmospheric Sciences, 3010 Agronomy Hall, Iowa State University, Ames, IA 50011. Email: tmchen@iastate.edu

1. Introduction

The empirical orthogonal function (EOF) analyses of outgoing longwave radiation (OLR) by Heddinghaus and Krueger (1981) and analyses of the potential function of water vapor flux by Chen and Tzeng (1990) showed that positive convective and convergence centers of water vapor flux of the annual mode were located over the three tropical continents in the summer hemisphere and three centers of opposite phase in the winter hemisphere. Chen et al. (1995) analyzed the annual component of the global atmospheric hydrological cycle using data generated by the global data assimilation system of the National Meteorological Center [predecessor of the National Centers for Environmental Prediction (NCEP)] and the Goddard precipitation estimation (Susskind et al. 1997). They found that the hemispheric-mean divergence of water vapor flux (which is equivalent to the total cross-equator water vapor flux) and precipitation exhibit an amplitude of 0.5–0.7 mm day−1 in their annual components, as indicated in Fig. 1 [time series of hemispheric mean precipitation and its annual component in Chen et al.'s (1995) Fig. 4 added to the direction of the annual component of Southern Hemisphere (SH) water vapor flux across the equator]. These two hydrological variables vary annually in a coherent manner: water vapor diverges from the winter hemisphere, where hemispheric mean precipitation reaches its minimum, to the summer hemisphere, where hemispheric mean precipitation attains its maximum. Since precipitation is coupled with convection, maximum centers of the annual precipitation component coincide with minimum centers of the annual OLR component and the minimum centers of annual precipitation component with maximum centers of annual OLR. Thus, the positive centers of the annual precipitation component over the three tropical continents in the summer hemisphere are maintained by the convergence of water vapor flux, and the negative centers of the annual precipitation variation in the winter hemisphere by the divergence of water vapor flux.

Annual variations of the global atmospheric hydrological processes presented by Chen et al. (1995) were primarily contributions from the tropical–subtropical region. In midlatitudes, synoptic cyclones are effective agents in producing precipitation (e.g., Chen et al. 1996a). Because the major cyclone activity occurs along storm tracks in both hemispheres (e.g., Blackmon et al. 1977; Sinclair et al. 1997), the major precipitation areas in midlatitudes could occur along these storm tracks. In view of the possible role played by the storm tracks in midlatitude precipitation, several questions concerning the annual variation of midlatitude precipitation and associated hydrological processes are raised:

  1. Does precipitation along midlatitude storm tracks exhibit an annual variation?

  2. If so, does annual precipitation along the midlatitude storm tracks vary in concert with tropical precipitation?

  3. How are the precipitation zones along the storm tracks in both hemispheres maintained?

Despite the fact that the combined areas north of 30°N and south of 30°S cover half of the earth's surface, these areas contribute only 39% of the total global precipitation [estimated with Jaeger's (1976) latitudinal distribution of global precipitation]. Therefore, the annual variation of midlatitude precipitation is often obscurred by the tropical regions within 30°S and 30°N in the global/hemispheric mean atmospheric hydrological cycle. However, midlatitude precipitation is not only critical to societal activities in this region, but also vital to the climate system. A number of regional field experiments in the midlatitudes [e.g., Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP), GEWEX Asian Monsoon Experiment (GAME), GEWEX Americans Prediction Project (GAPP), etc.] were recently conducted under GEWEX to explore and better understand the regional hydrological cycle related to land surface interaction. The questions we have raised, however, are beyond the scope of these experiments. To answer these questions, we analyzed three reanalysis datasets and two sets of global precipitation, as described in section 2. Ensemble averages of results obtained with different datasets were used to depict the annual variation of midlatitude atmospheric hydrological processes in section 3, and concluding remarks are offered in section 4.

2. Data and analysis

In this study, we use the NCEP–National Center for Atmospheric Research (NCAR) (Kalnay et al. 1996), European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA; Gibson et al. 1994), and Goddard Earth Observing System (GEOS-1) (Schubert et al. 1993) reanalysis datasets and global precipitation fields assembled by Huffman et al. (1996) and Xie and Arkin (1997). Although the three reanalyses provided data at four synoptic times, the daily mean data were used to avoid the possible effect of the semidiurnal mode (e.g., Chen and Schubert 2000). These data cover the period of 1979–2000, but each dataset has a different time period and its own bias caused either by the assimilation system or the analysis scheme. In order to reduce this possible bias, the ensemble average of results obtained from different datasets is presented. The robustness of the ensemble average was verified by a variance ratio between departure of each dataset's result and the ensemble average. The ratio of any hydrological variable analyzed in this study is smaller than 10%. In other words, the analysis results presented are robust.

The water vapor budget equation is
i1520-0442-17-21-4291-e1
where W = g−1p00 q dp, Q = g−1p00 υq dp, E, and P are precipitable water, water vapor flux, evaporation, and precipitation, respectively. According to Chen (1985), the water vapor flux may be split into rotational (QR) and divergent (QD) components; that is, Q = QR + QD. Equation (1) can then be rewritten as
i1520-0442-17-21-4291-e2
where QD is evaluated through the gradient of the potential function of water vapor flux (χQ), that is, QD = ∇χQ, and χQ is obtained by solving the Poisson equation, ∇2χQ = ∇ · QD, in terms of spherical harmonics with a triangular-31 resolution. The divergent water vapor flux consists of both stationary (QSD) and transient (QTD) components,
QDQSDQTD
The seasonal mean value of any first-moment variable is defined as the stationary component, while departure from this seasonal-mean value is defined as the transient component. Because results of the analysis are expressed in terms of seasonal averages, all variables presented hereinafter are seasonal mean values. Therefore, Eq. (2) may be expressed as
QSDQTDEP.
Since observations of evaporation are not available, our analysis primarily focuses on QSD, QTD, and P.

3. Results

a. Annual variation

Three continents in each hemisphere have tropical– subtropical landmasses: Asia, Central/North America, and West Africa in the Northern Hemisphere (NH) and Australia, South America, and Africa in the Southern Hemisphere (SH). Regions of intense precipitation (stippled areas in Fig. 2) lie along the intertropical convergence zone (ITCZ) and over these continents. In the NH midlatitudes, major precipitation bands coincide with locations of the East Asian and North American jets, while in the SH midlatitudes regions of intense precipitation map onto the three SH convergence zones [i.e., South Pacific convergence zone (SPCZ), South American convergence zone (SACZ), and South Indian Ocean convergence zone (SICZ)] and the circumpolar cyclone activity zone. The midlatitude precipitation zones coincide with storm tracks in the winter Northern Hemisphere depicted by Blackmon et al. (1977) and in the winter Southern Hemisphere by Sinclair et al. (1997). Because cyclones are effective precipitation producers and are more active in winter following the intensification of midlatitude jets, it is likely that the precipitation along the midlatitude storm tracks reaches a maximum in winter. This inference is supported by the global distribution of maximum precipitation months, which is contoured in Fig. 2 (when the amplitude of annual precipitation component is larger/equal to 30 mm month−1).

The annual oscillation of precipitation between the tropical continents of the two hemispheres was shown by Chen et al. (1995). In addition to this interhemispheric seesaw of maximum and minimum precipitation, two other distinct patterns of the contrast between precipitation centers are identified in Fig. 2:

  1. Tropics–midlatitude contrast: Precipitation over the three tropical continents and along the ITCZ reaches its maximum in the NH summer but also along the two major midlatitude storm tracks in the North Pacific and the North Atlantic in the NH winter.

  2. Land–ocean contrast: Maximum precipitation appears over land in summer and over oceans in winter. This land–ocean contrast of maximum rainfall exists only in the NH midlatitudes. This unique precipitation contrast is a result of some special features of the NH circulation, which will be illustrated in section 3b.

These two precipitation patterns can be further clarified by the precipitation difference between the NH winter [December–February (DJF)] and NH summer [June– August (JJA)], ΔP [≡P(DJF) − P(JJA)], shown in Fig. 3a, and precipitation histograms (Fig. 3b) at the ΔP centers (marked in Fig. 3a). The first pattern is revealed from the contrast between precipitation centers at locations 7, 8, 9, 10, and 11 in the NH tropical continents and 4, 5, and 6 in the NH storm tracks and between those at locations 12, 13, 14, and 15 in the SH tropical continents and 16, 17, and 18 in the SH storm tracks. The second pattern is illustrated by the contrast of precipitation centers between land locations 1, 2, and 3 and ocean locations 4, 5, and 6. It is noteworthy that, regardless of its small geographical size compared to the two major NH oceans, the annual variation of Mediterranean precipitation (histogram 6 in Fig. 3b) behaves in the same way as the annual variation of precipitation along the oceanic storm tracks (histograms 4 and 5 in Fig. 3b).

b. Maintenance of precipitation

Precipitation is always generated by updraft air masses. This upward motion, which is coupled with the low-level convergence, is an integral part of the divergent circulation. Water vapor needed to generate precipitation is furnished by the low-level convergence of water vapor. Because observations of evaporation (E) are not available, a complete water vapor budget analysis was not possible. Therefore, factors maintaining these two precipitation patterns are illustrated by the following relationship:
PQSDQTD
Equation (5) indicates that precipitation is maintained by convergence of the water vapor flux, which may be contributed by the stationary (QSD) and the transient (QTD) components. Annual variations of P and −∇ · QD[= −∇ · (QSD + QTD)] are related to local hydrological processes in response to the annual evolution of the atmospheric circulation. The coupling of these local hydrological processes with the global-scale circulation may be inferred through comparison of the ΔP distribution with both ΔQSD and ΔQTD, which reflects the annual variation of the low-tropospheric stationary and transient divergent circulation. According to Chen (1985), QSD is several times larger in magnitude than QTD. Therefore, QSD is a good approximation of QD. On the other hand, transients that contribute to maintaining storm tracks and producing rainfall in midlatitudes cannot be ignored. Thus, Δ(QSD, −∇ · QSD) and Δ(QTD, −∇ · QTD) superimposed with ΔP are presented in the discussion of our analysis results.

1) Stationary mode

The maintenance of the annual variation in global precipitation ΔP contributed by the stationary component, Δ(QSD, −∇ · QSD), is illustrated in Fig. 4a. Two salient features are revealed in this figure.

(i) Interhemispheric exchange

Patterns of P, QSD, and −∇ · QSD indicate that water vapor diverges from the three tropical continents in the winter Northern Hemisphere to maintain intense precipitation over the three tropical continents in the summer Southern Hemisphere. The pattern in Fig. 4a reverses in the northern summer. The interhemispheric exchange of water vapor through an annual seesaw between the hemispheres is clearly shown by Δ(QSD, −∇ · QSD).

(ii) Land–ocean exchange in the NH midlatitudes

Recall that NH midlatitude precipitation reaches its maximum over land in summer and over the ocean in winter (e.g., East Asia versus the northeast Pacific, northeast North America versus northeast Atlantic– western Europe, and Eurasia versus the Mediterranean Sea). In essence, water vapor diverges from the cold/ dry continent to maintain precipitation along ocean storm tracks during the northern winter, while during the NH summer divergence over the oceans feeds continental precipitation. The land–ocean exchange of water vapor is a result of the clear contrast between the west and east centers of −∇ · QSD across the oceans in NH midlatitudes (Fig. 4a). This exchange of water vapor does not appear in the Southern Hemisphere.

The interhemispheric exchanges of water vapor and the interhemispheric alternation of maximum precipitation centers across the equator were analyzed by previous studies (e.g., Chen et al. 1995), but the annual seesaw of precipitation and the exchange of water vapor flux between land and ocean in the NH midlatitudes have not been explored. As illustrated below, the latter annual variations are coupled with the annual evolution of stationary waves. Lau (1979, his Figs. 1 and 2) reported that the major troughs in the NH winter are located over the western oceans and major ridges are situated over land and the eastern oceans. In the NH summer, stationary waves migrate eastward and become weaker (White 1982, his Figs. 4 and 5). These waves were depicted in terms of eddy geopotential height (ZE) in which the zonally averaged component was removed. The difference in eddy geopotential height at 45°N between winter and summer, ΔZE(45°N) (Fig. 5a), clearly shows ridge development over continents and trough deepening over eastern oceans. This amplification of wintertime stationary waves is coupled with the vertical motion and divergent circulation. As indicated by −Δω(45°N) imposed on the ΔZE(45°N) cross section, upward motion is enhanced ahead of the deepening trough over the eastern oceans, and downward motion is intensified ahead of a developing ridge over the continent. These enhanced vertical motions, which form a well-organized east–west circulation across the oceans, are linked with the lower-tropospheric divergence center in the west and convergence center in the east. Ultimately, the low-level divergence and convergence centers of the east–west circulation are revealed by the divergence and convergence centers of water vapor flux over the western and eastern oceans (Fig. 4a), respectively. One may argue that these lower-tropospheric divergence and convergence centers are just the result of the land–ocean contrast. Actually, it is more appropriate to argue that they are formed by the annual evolution of the NH midlatitude stationary waves from summer to winter. This argument can be strengthened by the fact that a significant land–ocean exchange cannot be established in the Southern Hemisphere because of the weak stationary waves (e.g., van Loon 1983).

2) Transient mode

Following Blackmon et al. (1977), we use the variance of the 2–7-day bandpass-filtered meridional motion at 500 mb, υ̃2(500 mb), to portray winter storm tracks in both hemispheres. Because strong baroclinicity is generally associated with jet streams, transients are expected to be active along these jets. Northern Hemisphere storm tracks are anchored in the North Pacific, the North Atlantic, and the Mediterranean Sea (Blackmon et al. 1977), while the SH tracks are located along the circumpolar zone of 30°–50°S over the three oceans (Sinclair et al. 1997). It was pointed out previously that magnitudes of ΔQSD (Fig. 4a) are generally much larger than those of ΔQTD (Fig. 4b). Regardless of this disparity in magnitude, it is revealed from the contrast between ΔQTD and Δυ̃2(500 mb; Fig. 5b) that the former is generally significant along storm tracks. Since cyclones are effective precipitation producers, the relationship between ΔQTD and Δυ̃2(500 mb) indicates that transients contribute to the maintenance of the precipitation along the storm tracks, particularly in the Southern Hemisphere. In addition to this function of transients, we also observe the following relationship among ΔQSD, ΔQTD, and ΔP in both hemispheres.

(i) Northern Hemisphere

As indicated by the north–south juxtaposition of negative and positive zones of −∇ · QTD in Fig. 4b, the transient component contributes notable convergence of water vapor flux toward the storm tracks. However, the divergent water vapor flux produced by the stationary component (ΔQSD) exhibits an east–west differentiation: divergence in the west and convergence in the east across the North Pacific in midlatitudes. Consequently, the precipitation decrease (from summer to winter) over land is related to the stationary water vapor divergence but cannot be compensated by the transient water vapor convergence. In contrast, oceanic precipitation over the downstream side of storm tracks is maintained primarily by convergence of the stationary water vapor flux but cannot be altered by divergence of the transient water vapor flux.

(ii) Southern Hemisphere

Since the two extreme seasons in the Southern Hemisphere are opposite to those in the Northern Hemisphere, we explore the difference of the transient divergent water vapor flux and precipitation between JJA (southern winter) and DJF (southern summer), Δ(P, QTD, −∇ ·  QTD), for the Southern Hemisphere. For Fig. 4b, we reverse the directions of ΔQSD and signs of ΔP from Fig. 4a and find that the stationary component does not noticeably support precipitation along the SH storm tracks. The contrast between the lower halves of Figs. 4b and 5b reveals that precipitation along the SH storm tracks is basically maintained by the convergence of the transient water vapor flux. In spite of the cyclone passage across the three SH continents (Fig. 5b), convergence of transient water vapor flux may not supply sufficient water vapor to counterbalance the reduction in precipitation caused by the divergence of stationary water vapor flux, as seen in the NH continents.

4. Concluding remarks

The global/hemispheric mean water vapor budget is primarily contributed by the tropical–subtropical region (Chen et al. 1995, 1996b). Consequently, annual variations in the midlatitude precipitation and the associated hydrological processes are masked by low-latitude processes. However, we are able to identify underlying reasons behind annual variations of midlatitude precipitation and the hydrological process maintaining this precipitation in both hemispheres with the reanalysis data generated by three operational/research centers (NCEP, ECMWF, and GEOS) and two global precipitation datasets (CMAP and GPCP). Major findings of this study may be summarized as follows.

a. Precipitation

In the NH midlatitudes, precipitation reaches its maximum over the continents in summer but along ocean storm tracks in winter. This land–ocean contrast forms an annual east–west precipitation seesaw. Because of the lack of any significant landmass in the SH midlatitudes, precipitation attains its maximum along the storm tracks only in winter. Comparison of low and middle latitudes for both hemispheres clearly shows that midlatitude precipitation along storm tracks varies annually out of phase with tropical precipitation.

b. Maintenance

The maintenance of the precipitation difference between the two extreme seasons (ΔP) is illustrated by the spatial patterns of changes in the divergent water vapor flux and its convergence/divergence between these two seasons contributed through stationary [Δ(QSD, −∇ · QSD)] and transient [Δ(QTD, −∇ · QSD)] components.

  1. In the NH midlatitudes, an east–west seesaw of stationary divergent water vapor flux between the two sides of the oceans is revealed from Δ(QSD, −∇ ·  QSD): Divergence exists in the west, while convergence appears in the east. This east–west seesaw of stationary divergent water vapor flux is coupled with the development of the east–west circulation following the annual evolution of stationary waves: amplification of ridges over land and deepening of troughs in the oceans accompanied with the westward shift of stationary waves in winter. Migrating southward in winter, transient activity along storm tracks intensifies and convergence of transient water vapor flux toward these storm tracks is enhanced. The contrast between stationary and transient components of water vapor flux convergence reveals that these two contribute to maintaining ΔP almost in an opposite way both upstream and downstream of the storm tracks. Since convergence of transient water vapor flux is much smaller than its stationary counterpart, it cannot balance the latter in maintaining the annual variation in precipitation over land. The land–ocean annual seesaw of precipitation is primarily maintained by the stationary component with an almost opposite contribution from the transient component.

  2. Due to the lack of major landmasses in the SH, stationary waves here are much weaker compared to those in the NH (van Loon 1983) and do not significantly impact the divergent water vapor transport at midlatitudes. Precipitation along the SH storm tracks is largely maintained by convergence of transient water vapor flux. Thus, the SH ΔP follows the SH Δ(QTD, −∇ · QTD).

The findings summarized above enable us to better understand annual variations of midlatitude hydrological processes, but two remarks concerning this study are in order. First, analysis of a complete atmospheric hydrological cycle and water vapor budget cannot be accomplished without observations of evaporation. Indirect methods may be explored to resolve this limitation in our study, such as using residual methods with the water vapor budget. However, this approach may introduce computational errors and data bias caused by the data assimilation system. Perhaps, the evaporation generated by a global climate model [e.g., the NCAR Community Climate Model, version 3 (CCM3; Hack et al. 1998)] may offer an alternative, although it is not a real observation. Model-generated evaporation contains model bias due to parameterizations related to hydrological processes. In view of these possible biases, we did not attempt to evaluate the contribution of evaporation to the annual variations of the atmospheric hydrological cycle and water vapor budget. Second, the most pronounced climate signal is the annual variation of the atmospheric circulation. If this climate signal cannot be accurately simulated by a global climate model, we will have less confidence in the validity of the simulated interannual variation of the global climate system (e.g., the midlatitude response to the ENSO cycle). Coupling of the annual precipitation seesaw between land and oceans in NH midlatitudes with the annual evolution of stationary waves and storm tracks, illustrated in section 3b(1), provides a powerful validity check for global climate simulations. In addition, the importance of the midlatitude hydrological cycle and its feedbacks to the climate system as a basis for understanding future climates cannot be overlooked.

Acknowledgments

This study is partially supported by NSF Grant ATM-9906454, NASA Grant NAG5-8293, and the Baker Endowment Fund, ENDOW-D11-CHEN. Comments and suggestions offered by reviewers were very helpful in improving this paper.

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Fig. 1.
Fig. 1.

Time series of the hemispheric-mean ([ ]) precipitation (thin solid line) over the Northern ([P]NH) and Southern ([P]SH) Hemisphere for 1979–80 using the Goddard precipitation index (GPI) generated by Susskind et al. (1997). The [P]NH and [P]SH values larger and smaller than their own annual mean values (dashed line) are heavily and lightly stippled, respectively. Time series of the annual harmonic ( ˆ ) component (thick solid line) are added. Thick arrows represent the direction of [∇ · ]SH (the annual component of hemispheric mean ∇ · Q over the Southern Hemisphere). This figure is a modification of the [P] and [] time series shown in Fig. 4 of Chen et al. (1995)

Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1

Fig. 2.
Fig. 2.

Distribution of the annual-mean precipitation (P) superimposed with the month of maximum in the annual precipitation variation. Values of P larger than 2(4) mm day−1 are lightly (heavily) stippled. The months that have maximum precipitation in the year (contoured with the month, each represented by its numerical value) falls within the northern summer (winter) are denoted by large (small) dots. The contour interval of maximum precipitation months is 1 month

Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1

Fig. 3.
Fig. 3.

(a) Difference in precipitation between the two extreme seasons, ΔP, and (b) precipitation histograms at the ΔP centers marked in (a). Positive (negative) values of ΔP are heavily (lightly) stippled. The contour interval of ΔP is 1 mm day−1

Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1

Fig. 4.
Fig. 4.

(a) Differences in precipitation, stationary water vapor flux, and its convergence/divergence between NH winter (DJF) and NH summer (JJA), Δ(P, QSD, −∇ · QSD). (b) As in (a) but for the Northern Hemisphere, except for Δ(P, QTD, −∇ · QTD). In the Southern Hemisphere of (b), the order of the two extreme seasons is reversed. Therefore, Δ(P, QTD, −∇ · QTD) between the SH winter (JJA) and summer (DJF) is displayed. Magnitudes of ΔQSD and ΔQTD are shown by vectors on the right side of each panel. Positive values of ΔP are lightly stippled on the scale shown in the right bottom side of each panel while those of −∇ · QSD and −∇ · QTD are dotted. Contour intervals of the latter two quantities are 10−5 and 4 × 10−6 kg m−2 s−1, respectively

Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1

Fig. 5.
Fig. 5.

(a) Cross section of (a) differences in eddy geopotential height (ZE) and east–west circulation (uD, −ω) at 45°N between winter and summer, Δ[ZE, (uD, −ω)] (45°N) and (b) the difference in variance of 2–7-day filtered meridional wind Δυ̃2(500 mb) between winter and summer in the Northern Hemisphere (upper half) and Southern Hemisphere (lower half). The contour interval in (a) is 25 m, while that in (b) is 4 m2 s−2. Magnitudes of Δ(uD, −ω) are scaled by arrows shown on the right-hand side of (a). Values of Δυ̃2(500 mb) larger than 12 m2 s−2 are stippled in (b)

Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1

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  • Fig. 1.

    Time series of the hemispheric-mean ([ ]) precipitation (thin solid line) over the Northern ([P]NH) and Southern ([P]SH) Hemisphere for 1979–80 using the Goddard precipitation index (GPI) generated by Susskind et al. (1997). The [P]NH and [P]SH values larger and smaller than their own annual mean values (dashed line) are heavily and lightly stippled, respectively. Time series of the annual harmonic ( ˆ ) component (thick solid line) are added. Thick arrows represent the direction of [∇ · ]SH (the annual component of hemispheric mean ∇ · Q over the Southern Hemisphere). This figure is a modification of the [P] and [] time series shown in Fig. 4 of Chen et al. (1995)

  • Fig. 2.

    Distribution of the annual-mean precipitation (P) superimposed with the month of maximum in the annual precipitation variation. Values of P larger than 2(4) mm day−1 are lightly (heavily) stippled. The months that have maximum precipitation in the year (contoured with the month, each represented by its numerical value) falls within the northern summer (winter) are denoted by large (small) dots. The contour interval of maximum precipitation months is 1 month

  • Fig. 3.

    (a) Difference in precipitation between the two extreme seasons, ΔP, and (b) precipitation histograms at the ΔP centers marked in (a). Positive (negative) values of ΔP are heavily (lightly) stippled. The contour interval of ΔP is 1 mm day−1

  • Fig. 4.

    (a) Differences in precipitation, stationary water vapor flux, and its convergence/divergence between NH winter (DJF) and NH summer (JJA), Δ(P, QSD, −∇ · QSD). (b) As in (a) but for the Northern Hemisphere, except for Δ(P, QTD, −∇ · QTD). In the Southern Hemisphere of (b), the order of the two extreme seasons is reversed. Therefore, Δ(P, QTD, −∇ · QTD) between the SH winter (JJA) and summer (DJF) is displayed. Magnitudes of ΔQSD and ΔQTD are shown by vectors on the right side of each panel. Positive values of ΔP are lightly stippled on the scale shown in the right bottom side of each panel while those of −∇ · QSD and −∇ · QTD are dotted. Contour intervals of the latter two quantities are 10−5 and 4 × 10−6 kg m−2 s−1, respectively

  • Fig. 5.

    (a) Cross section of (a) differences in eddy geopotential height (ZE) and east–west circulation (uD, −ω) at 45°N between winter and summer, Δ[ZE, (uD, −ω)] (45°N) and (b) the difference in variance of 2–7-day filtered meridional wind Δυ̃2(500 mb) between winter and summer in the Northern Hemisphere (upper half) and Southern Hemisphere (lower half). The contour interval in (a) is 25 m, while that in (b) is 4 m2 s−2. Magnitudes of Δ(uD, −ω) are scaled by arrows shown on the right-hand side of (a). Values of Δυ̃2(500 mb) larger than 12 m2 s−2 are stippled in (b)

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