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:
Does precipitation along midlatitude storm tracks exhibit an annual variation?
If so, does annual precipitation along the midlatitude storm tracks vary in concert with tropical precipitation?
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.
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:
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.
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.
b. Maintenance of precipitation
1) Stationary mode
The maintenance of the annual variation in global precipitation ΔP contributed by the stationary component, Δ(
(i) Interhemispheric exchange
Patterns of P,
(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 −∇ ·
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,
(i) Northern Hemisphere
As indicated by the north–south juxtaposition of negative and positive zones of −∇ ·
(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,
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(
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 ): 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.QSD 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.
REFERENCES
Blackmon, M. L., J. M. Wallace, N-C. Lau, and S. L. Mullen, 1977: An observational study of the Northern Hemisphere wintertime circulation. J. Atmos. Sci, 34 , 1040–1053.
Chen, T-C., 1985: Global water vapor flux and maintenance during FGGE. Mon. Wea. Rev, 113 , 1801–1819.
Chen, T-C., and R-Y. Tzeng, 1990: Global-scale intraseasonal and annual variation of divergent water-vapor flux. Meteor. Atmos. Phys, 44 , 133–151.
Chen, T-C., and S. Schubert, 2000: Aliasing of the semidiurnal cycle in the depiction of global atmospheric circulation. Bull. Amer. Meteor. Soc, 81 , 95–100.
Chen, T-C., J-M. Chen, and J. Pfaendtner, 1995: Low-frequency variations in the atmospheric branch of the global hydrological cycle. J. Climate, 8 , 92–107.
Chen, T-C., M-C. Yen, and S. Schubert, 1996a: Hydrological processes associated with cyclone systems over the United States. Bull. Amer. Meteor. Soc, 77 , 1557–1567.
Chen, T-C., M-C. Yen, J. Pfaendtner, and Y. C. Sud, 1996b: Annual variation of the global precipitable water and its maintenance: Observation and climate simulation. Tellus, 48A , 1–16.
Gibson, J. K., P. Kallberg, A. Nomura, and S. Uppala, 1994: The ECMWF Re-analysis (ERA) Project—Plans and current status. Preprints, 10th Int. Conf. on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Nashville, TN, Amer. Meteor. Soc., 164–167.
Hack, J. J., J. T. Kiehl, and J. W. Hurrell, 1998: The hydrological and thermodynamic characteristics of the NCAR CCM3. J. Climate, 11 , 1179–1206.
Heddinghaus, T. R., and A. Krueger, 1981: Annual and interannual variations in outgoing longwave radiation over the tropics. Mon. Wea. Rev, 109 , 1208–1218.
Huffman, G. J., and Coauthors, 1996: The Global Precipitation Climatology Project (GPCP) combined precipitation dataset. Bull. Amer. Meteor. Soc, 77 , 5–20.
Jaeger, L., 1976: Monthly precipitation maps for the entire earth. Ber. Dtsch. Wetterdienstes, 18 (139) 1–38.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc, 77 , 437–471.
Lau, N-C., 1979: The observed structure of tropospheric stationary waves and local balances of vorticity and heat. J. Atmos. Sci, 36 , 996–1016.
Schubert, S., R. B. Rood, and J. Pfaendtner, 1993: An assimilated dataset for earth science applications. Bull. Amer. Meteor. Soc, 74 , 2331–2342.
Sinclair, M. R., J. A. Renwick, and J. W. Kidson, 1997: Low-frequency variability of Southern Hemisphere sea level pressure and weather system activity. Mon. Wea. Rev, 125 , 2531–2543.
Susskind, J., P. Piraino, L. Rokke, L. Iredell, and A. Metha, 1997: Characteristics of the TOVS Pathfinder Path A dataset. Bull. Amer. Meteor. Soc, 78 , 1446–1472.
van Loon, H., 1983: A comparison of the quasi-stationary waves on the Northern and Southern Hemispheres. Proc. First Int. Southern Hemisphere Conf., Sao Jose dos Campos, Brazil, Amer. Meteor. Soc., 77–84.
White, G. H., 1982: An observational study of the Northern Hemisphere extratropical summertime general circulation. J. Atmos. Sci, 38 , 28–40.
Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based upon gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc, 78 , 2539–2558.
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 [∇ · Q̂]SH (the annual component of hemispheric mean ∇ · Q over the Southern Hemisphere). This figure is a modification of the [P] and [P̂] time series shown in Fig. 4 of Chen et al. (1995)
Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1
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
(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
(a) Differences in precipitation, stationary water vapor flux, and its convergence/divergence between NH winter (DJF) and NH summer (JJA), Δ(P,
Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1
(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 Δ
Citation: Journal of Climate 17, 21; 10.1175/JCLI3201.1