Abstract

The zonal-mean meridional transport of water vapor across the globe is evaluated using the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis for 1948–97. The shape of the meridional profile of the climatological mean transport closely resembles that of previous mean climate descriptions, but values tend to be notably larger than in climatologies derived from radiosonde-only-based analyses. The unprecedented length of the NCEP–NCAR dataset invites a focus on interannual variations in the zonal-mean moisture transport, and these results for northern winter are highlighted here. Although interannual variability in the transport is typically small at most latitudes, a significant ENSO signal is present, marked by a strengthening of water vapor transports over much of the winter hemisphere during warm events. Because of an increase in tropical sea surface temperatures and in the frequency of warm events relative to cold events in the latter half of the 50-yr record, this interannual signal projects onto an overall trend toward enhanced meridional moisture transports in the global hydrological cycle.

1. Introduction

Of the total energy typically carried by the atmosphere across midlatitudes toward the poles, nearly half is in the form of latent heat associated with the meridional flux of water vapor (Rosen 1999, his Fig. 1.4). Variations in this flux on interannual or longer timescales may, therefore, have important consequences for weather and climate. For example, it is currently of considerable interest to determine how the meridional moisture flux might change if the planet were to warm from the rise in greenhouse gases. Presumably, the moisture content of the atmosphere would increase in such a scenario (Sun and Oort 1995; Trenberth 1998), but whether a moister atmosphere would generate larger, more intense storms or smaller ones that carry energy poleward more efficiently remains a matter of speculation (Held 1993). In addition to its (latent) energy content, water vapor transported to the poles represents a flux of freshwater that contributes importantly to the buoyancy forces driving the thermohaline circulation. Changes in the meridional moisture flux may, therefore, have an impact on climate also by affecting the formation of global deep water and hence the dynamics of the oceanic “conveyor belt” (Wang et al. 1999), although again there is much uncertainty about this possibility.

Predicting the behavior of water vapor and its meridional transport is, therefore, key to successfully modeling changes in climate from anthropogenic or other forcings. State-of-the-art climate models, however, appear to overestimate the observed poleward transport of both total energy (Gleckler et al. 1995) and its latent heat component (Gaffen et al. 1997), and work to correct such deficiencies is needed before predictions of future climate can be better trusted. Part of this work will entail the ongoing assessment of simulations of the current climate through comparisons with observed moisture-flux datasets. Diagnoses of such datasets also provide a context for determining whether future changes in moisture transport rise above the “noise” of natural variability. In this regard, lengthy datasets of moisture transport attain special value because they better sample that variability. Indeed, this note is motivated by the availability of a multidecadal set of tropospheric analyses that can be used to document year-to-year variability and trends in the meridional transport of moisture to an extent not previously possible.

Unfortunately, measuring and analyzing water vapor and its transport across the globe have proven to be notoriously difficult (National Research Council 1999). Standard humidity sensors carried by radiosondes are prone to error, changes in these sensors can introduce important discontinuities into the record (Elliott 1995), and the network of radiosonde stations is strongly biased to locations on land. Satellite measurements provide global coverage, but their vertical resolution in the lower troposphere, where virtually all vapor transport takes place, is poor (Randel et al. 1996). As a consequence of such measurement shortcomings, operational or other analyses of large-scale moisture fields are typically model dependent and differ notably from each other. Such disagreements are especially large over the data-sparse Southern Hemisphere, where estimates of the zonally averaged meridional moisture transport can vary by as much as 100% (Slonaker and Van Woert 1999).

The moisture-flux dataset examined in this note, derived from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay et al. 1996), is certainly not free from these difficulties. Only radiosonde observations were used to produce the moisture fields in the NCEP–NCAR reanalysis, but even over a data-rich region like the central United States, estimates of the mean moisture-flux convergence from this product differ significantly from that needed to balance independent, reliable streamflow data (Gutowski et al. 1997). On the other hand, Gutowski et al. demonstrate that the temporal variability of this convergence is more realistic. Large-scale meridional transports of water vapor from the NCEP–NCAR reanalysis were computed by Mo and Higgins (1996) for an 8-yr period and were compared with results from another reanalysis effort. Significant differences in the climatological mean zonally averaged transports between the two reanalyses exist, particularly in the Tropics in association with differences in the strength and location of winds in the lower levels of the mean Hadley cell, despite both reanalyses’ use of wind information there from satellites and other systems besides radiosondes. Nevertheless, Mo and Higgins (1996) conclude that the NCEP–NCAR moisture-flux products are “able to depict interannual variability related to the ENSO cycle quite well.” Waliser et al. (1999) investigated the signals associated with the El Niño–Southern Oscillation (ENSO) in the NCEP–NCAR estimates of Hadley cell strength, and they compare these signals with ones derived from in situ (radiosonde) analyses and from subsampling the NCEP–NCAR product at radiosonde locations. Waliser et al. conclude that the “in situ and subsampled estimates significantly overestimate the effects of ENSO” on the meridional mass transport because of their “reliance on sparsely distributed data,” whereas the ENSO signal in the reanalysis is more realistic. Diagnoses of precipitable water by Trenberth and Guillemot (1998) indicate that an ENSO signal in the NCEP–NCAR moisture fields is present, although interannual variability is smaller in the reanalysis than in the composite observational database of Randel et al. (1996). In summary, the studies cited here suggest that results for climatological mean values presented below should be viewed cautiously, but that aspects of interannual variability will be qualitatively correct.

Here the study of Mo and Higgins (1996) is extended to incorporate 50 yr of NCEP–NCAR reanalysis output, although our focus is limited to the meridional transport of water vapor, and especially its zonal average, for the reasons noted at the outset. Our main interest is in the interannual variability of the zonal-mean transport, but for completeness, the trends in this quantity depicted in the reanalysis are also considered.

2. Data and methodology

The meridional transport of water vapor during the period 1948–97 is analyzed using monthly mean data available from the NCEP–NCAR reanalysis products (Kalnay et al. 1996; Basist and Chelliah 1997). Monthly means of the meridional vapor transport at up to eight levels in the mid- and lower troposphere and at each grid point (2.5° lat × 2.5° long) have been created by multiplying daily values of the meridional wind υ and the specific humidity q. To assess the total meridional flux crossing a grid point, these fields are then integrated from the monthly mean surface pressure to a pressure p of 300 hPa:

 
formula

where g is gravitational acceleration and the overbar denotes a monthly mean. Last, to compute the mean meridional water vapor transport across each latitude, {Qϕ} is averaged around the entire latitude circle and the result is multiplied by the length of the circle:

 
QΦ = 2πa cosϕ[{Qϕ}],

where a is the earth’s radius, ϕ is latitude, and the square brackets denote a zonal mean.

3. Climatology

Figure 1 depicts QΦ as a function of latitude for annual and solstitial seasonal means during 1948–97. Also shown is the range between the largest and smallest of the 50 values during the period. As can be seen from the figure, the annual meridional vapor transport is predominantly poleward in the eddy-dominated extratropics. Within the Tropics, however, the flow is dominated by the mean meridional circulation (i.e., the Hadley cell), and, because most of the water vapor is contained in the lower troposphere, the transport converges near the “meteorological” equator near 5°N (Philander et al. 1996).

Fig. 1.

Mean meridional flux of water vapor QΦ from NCEP–NCAR reanalysis as a function of latitude for (a) annual, (b) DJF, and (c) JJA means. Shading indicates the range between the largest and smallest of the individual values during the 50-yr (1948–97) reanalysis period. Units: 108 kg s−1.

Fig. 1.

Mean meridional flux of water vapor QΦ from NCEP–NCAR reanalysis as a function of latitude for (a) annual, (b) DJF, and (c) JJA means. Shading indicates the range between the largest and smallest of the individual values during the 50-yr (1948–97) reanalysis period. Units: 108 kg s−1.

Outside the Tropics, QΦ undergoes relatively small seasonal changes, but its seasonality is much greater within the Tropics because of the shifting position and strength of the Hadley cells in each hemisphere, as shown, for example, by Chen (1985). During DJF (December, January, and February) the transport is still generally out of the Tropics toward the poles, but northward transport of water vapor only occurs poleward of about 30°N. In JJA (June, July, and August) the picture is reversed: northward transport of water vapor occurs from about 20°S to the North Pole, and poleward of 20°S, the transport is southward. In both seasons, therefore, the winter hemisphere supplies moisture to the summer hemisphere.

The shape of the profiles in Fig. 1 closely resembles that of earlier QΦ profiles derived from radiosonde-only-based analyses, such as those produced by Peixoto et al. (1978) for the International Geophysical Year of 1958 and more recently by Peixoto and Oort (1992) for the decade starting in May 1963. As remarked by Mo and Higgins (1996), however, the magnitude of QΦ tends to be systematically lower in the radiosonde-based analyses than in reanalysis products, at least in the midlatitudes. A similar bias was noted by Bromwich et al. (1995) in their comparison of moisture transports across Southern Hemisphere midlatitudes between radiosonde-based analyses and operational analyses from the National Meteorological Center (now NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The size of this bias can be significant; for example, in Fig. 2 the annual-mean QΦ from Fig. 1 is compared with the profile derived by Gaffen et al. (1997) for the decade of 1979–88 using the radiosonde-based analyses of Oort and Liu (1993). The transport across 40°N, where the peak in the flux across Northern Hemisphere midlatitudes occurs in the NCEP–NCAR reanalysis, is more than one-third smaller in the radiosonde-based analysis. Radiosonde-based estimates of QΦ are also smaller than estimates from NCEP–NCAR and ECMWF reanalyses in northern high latitudes, according to Cullather et al. (2000).

Fig. 2.

The 50-yr mean and range of QΦ from NCEP–NCAR reanalysis (solid line and shading from Fig. 1a) along with an independent estimate of the same quantity for 1979–88 from a radiosonde-based analysis by Oort [dashed line, from Gaffen et al. (1997)]. Units:108 kg s−1.

Fig. 2.

The 50-yr mean and range of QΦ from NCEP–NCAR reanalysis (solid line and shading from Fig. 1a) along with an independent estimate of the same quantity for 1979–88 from a radiosonde-based analysis by Oort [dashed line, from Gaffen et al. (1997)]. Units:108 kg s−1.

4. Interannual variability

The year-to-year variability of the annual QΦ shown in Fig. 1 is generally small for all latitudes. The greatest variability is in the Tropics, where one standard deviation (not shown) is on the order of 15% of the maximum mean value. In the extratropics, the range between the highest and lowest values is only on the order of 20%, but between 10°N and 10°S, extreme values can vary by as much as 50%. Similar results appear for year-to-year differences within the two solstitial seasons shown in Fig. 1.

Although the interannual variability depicted in Fig. 1 is, by and large, relatively modest, it is worth exploring the extent to which it may be systematic, that is, associated with a known signal of interannual variability like ENSO. To this end, we divided the 49 DJFs during 1948–97 into warm-event (El Niño), cold-event (La Niña), and neutral years. Of the 49, 14 are warm events, 13 are cold events, and 22 are neutral (Table 1).

Table 1.

List of El Niño (warm event) and La Niña (cold event) DJFs during 1948–97. DJFs are listed under the same year as their December component (e.g., DJF 1951/52 is listed under calendar year 1951). Warm and cold events are defined based largely on Trenberth (1997) but also incorporate information from other sources, including Noel and Changnon (1998).

List of El Niño (warm event) and La Niña (cold event) DJFs during 1948–97. DJFs are listed under the same year as their December component (e.g., DJF 1951/52 is listed under calendar year 1951). Warm and cold events are defined based largely on Trenberth (1997) but also incorporate information from other sources, including Noel and Changnon (1998).
List of El Niño (warm event) and La Niña (cold event) DJFs during 1948–97. DJFs are listed under the same year as their December component (e.g., DJF 1951/52 is listed under calendar year 1951). Warm and cold events are defined based largely on Trenberth (1997) but also incorporate information from other sources, including Noel and Changnon (1998).

Figure 3 contrasts QΦ during ENSO warm and cold events. Differences between warm- and cold-event composites are most apparent within the deep Tropics, where they explain about one-third to one-half of the spread among all 49 values. The most notable impact of warm events during DJF is the increased southward transport of water vapor between 15°N and the equator. On average, during a warm event, this southward transport is 10% larger than the climatic mean. Outside of the Tropics the impact of ENSO warm events is small, although in the Northern Hemisphere extratropics, at least, the tendency is toward larger poleward fluxes during warm events. The signature of ENSO cold events is largely the reverse of that associated with warm events, so that, in general, during northern winter, there are decreased transports of water vapor across the Northern Hemisphere during ENSO cold events. The mean difference in QΦ between warm and cold events is illustrated at the bottom of Fig. 3; in the Northern Hemisphere, these differences are statistically significant at the 5% level between approximately the equator and 15°N, and between 20° and 35°N, according to a set of Student’s t tests. (A test of this relationship for the portions of the record before and after the introduction of satellite-based wind and temperature data in 1979 demonstrates that the result in Fig. 3 is independent of this change in data input to the reanalysis.) During southern winter (JJA, not shown) a similar scenario exists: increased (decreased) transports of water vapor occur across much of the Southern Hemisphere during ENSO warm (cold) events.

Fig. 3.

(top) The mean and range, by latitude, of QΦ from NCEP–NCAR reanalysis for DJF during 1948–97 (solid thick line and shading from Fig. 1b). Also shown are DJF means during warm-event (dashed line) and cold-event (solid thin line) years composited according to the list in Table 1. (bottom) Difference between warm- and cold-event composites. Units: 108 kg s−1.

Fig. 3.

(top) The mean and range, by latitude, of QΦ from NCEP–NCAR reanalysis for DJF during 1948–97 (solid thick line and shading from Fig. 1b). Also shown are DJF means during warm-event (dashed line) and cold-event (solid thin line) years composited according to the list in Table 1. (bottom) Difference between warm- and cold-event composites. Units: 108 kg s−1.

Regionally, during DJF (Fig. 4) the average ENSO warm event is associated with large increases in southward transport across much of the tropical North Pacific, with the strong anomalies near 10°N across the Pacific accounting for most of the signal in QΦ evident in Fig. 3. In the tropical South Pacific, these anomalies turn positive, especially west of 170°W or so, yielding the less negative QΦ warm-event transports between 5° and 20°S in Fig. 3, despite enhanced southward fluxes elsewhere in this belt. The enhanced meridional moisture convergence over the tropical Pacific near and west of the date line during warm events is particularly striking. The strong resemblance between the anomalies in Fig. 4 and those in Fig. 13 of Waliser et al. (1999) for the meridional mass flux suggests that enhanced lower-tropospheric winds contribute significantly to shaping the ENSO signal in the moisture flux of Fig. 3. In the northern extratropics, enhanced poleward fluxes during warm events occur in the North Atlantic storm track and in the U.S. Pacific Northwest, but these fluxes are nearly balanced in the zonal mean by negative anomalies over much of the central North Pacific.

Fig. 4.

(top) Map of the {Qϕ} climate mean for all DJFs from the NCEP–NCAR reanalysis during 1948–97. Contours are shown every 50 kg s−1 m−1. Shaded areas are negative, and zero contours are omitted for clarity. (bottom) Map of {Qϕ} anomaly from climate mean of the composite of 14 warm-event DJFs. Values are plotted as in top panel but are contoured every 10 kg s−1 m−1.

Fig. 4.

(top) Map of the {Qϕ} climate mean for all DJFs from the NCEP–NCAR reanalysis during 1948–97. Contours are shown every 50 kg s−1 m−1. Shaded areas are negative, and zero contours are omitted for clarity. (bottom) Map of {Qϕ} anomaly from climate mean of the composite of 14 warm-event DJFs. Values are plotted as in top panel but are contoured every 10 kg s−1 m−1.

5. Trends

Given the lengthy record provided by the NCEP–NCAR reanalysis, some consideration of the trends present in QΦ is warranted. To this end, we present a Hovmöller diagram of QΦ anomalies for DJFs during 1948–97 in Fig. 5. Also included in the figure is the trend in QΦ as a function of latitude. The largest trend signal is in the deep Tropics, with a tendency toward stronger southward fluxes. North of the equator, at least, this trend is consistent with the recent change in the relative frequency of ENSO warm and cold events (Table 1) and a related, general warming of the tropical Pacific since around 1976 (Trenberth and Hoar 1996, 1997; Trenberth 1999), recalling from Fig. 3 the enhancement of QΦ in the northern Tropics during warm conditions. The trend in Northern (and Southern) Hemisphere extratropics toward increased poleward fluxes similarly appears to be associated with warm events (Fig. 3) and the tendency for higher-than-normal tropical sea surface temperatures (SSTs) at the end of the record (Hurrell and Trenberth 1999). Sun and Trenberth (1998) suggest that an increase in poleward energy fluxes out of the Tropics may well be a fundamental response of the atmosphere–ocean system to warming of the Pacific during El Niños. Our results hint that the component of the poleward energy flux associated with the transport of water vapor contributes to this process.

Fig. 5.

Anomalies from climate mean of QΦ as a function of latitude and time for DJFs from the NCEP–NCAR reanalysis during 1948–97. Contours are every 1 × 108 kg s−1. Shaded areas are negative, and zero contours are omitted for clarity. At right is the trend, by latitude, of QΦ (108 kg s−1 decade−1).

Fig. 5.

Anomalies from climate mean of QΦ as a function of latitude and time for DJFs from the NCEP–NCAR reanalysis during 1948–97. Contours are every 1 × 108 kg s−1. Shaded areas are negative, and zero contours are omitted for clarity. At right is the trend, by latitude, of QΦ (108 kg s−1 decade−1).

The extent to which the trends in vapor transport shown in Fig. 5 are due to secular changes in the atmosphere’s water vapor content, in the meridional component of the wind, or in some combination of the two remains to be quantified. Increases during the last one to several decades have been detected in surface humidity over most of the United States (Gaffen and Ross 1999) and in precipitable water over most of North America (Ross and Elliott 1996), China (Zhai and Eskridge 1997), and the global ocean (Wentz and Schabel 2000). A trend in tropical meridional winds would be consistent with the strengthened Hadley circulation during ENSO warm events found by Waliser et al. (1999). The amplitude of the trends in specific humidity and/or the meridional wind in the NCEP–NCAR reanalysis has yet to be determined, however.

6. Summary and concluding remarks

In this note, a 50-yr climate description of the meridional water vapor transport derived from the NCEP–NCAR reanalysis is presented, the lengthiest such climatology evaluated to date. Based on the product examined here, interannual variability in the meridional water vapor transport is relatively small: at the latitude of peak transport in the Northern Hemisphere, values range only between 7.7 × 108 and 9.0 × 108 kg s−1. Interannual variability is larger in the Tropics, but even there, where the magnitude of the peak annual fluxes varies by some 50%, the location of these peaks is highly reproducible.

The phenomenon with the largest known influence on interannual variability, ENSO, imparts a small but detectable signal on the meridional vapor transport. In the winter hemisphere during El Niño, there is a tendency for increased equatorward transport of water vapor in the Tropics and poleward vapor transport in midlatitudes, that is, a strengthening of water vapor transports. The opposite, or a general weakening of water vapor transports, occurs during La Niña winters.

Finally, we considered whether trends in the meridional flux of water vapor during the 50-yr period are related to the increase in El Niño events relative to La Niña events during the latter half of the record. An increase was found in meridional transports during DJFs that is consistent, over most of the globe, with the secular signal in ENSO and in SSTs across the Tropics. Independent evidence suggests that the global hydrological cycle may be accelerating (Chahine et al. 1997;Trenberth 1998); in this context, our result of a trend toward larger moisture transports does not seem surprising.

Acknowledgments

Partial support for this research was obtained from the NASA Global Modeling and Analysis Program under Contract NAS5-98179. We thank Peter Nelson of AER for data processing and producing the figures, and the editor for his thoughtful recommendations to improve the manuscript.

REFERENCES

REFERENCES
Basist, A. N., and M. Chelliah, 1997: Comparison of tropospheric temperatures derived from the NCEP/NCAR reanalysis, NCEP operational analysis, and the Microwave Sounding Unit. Bull. Amer. Meteor. Soc., 78, 1431–1447.
Bromwich, D. H., F. M. Robasky, R. L. Cullather, and M. L. Van Woert, 1995: The atmospheric hydrologic cycle over the Southern Ocean and Antarctica from operational numerical analyses. Mon. Wea. Rev., 123, 3518–3538.
Chahine, M. T., R. Haskins, and E. Fetzer, 1997: Observation of the recycling rate of moisture in the atmosphere: 1988–1994. GEWEX News, 7, 1–4.
Chen, T.-C., 1985: Global water vapor flux and maintenance during FGGE. Mon. Wea. Rev., 113, 1801–1819.
Cullather, R. I., D. H. Bromwich, and M. C. Serreze, 2000: The atmospheric hydrologic cycle over the Arctic basin from reanalyses. Part I. Comparison with observations and previous studies. J. Climate, 13, 923–937.
Elliott, W. P., 1995: On detecting long-term changes in atmospheric moisture. Climatic Change, 31, 349–367.
Gaffen, D. J., and R. J. Ross, 1999: Climatology and trends of U.S. surface humidity and temperature. J. Climate, 12, 811–828.
——, R. D. Rosen, D. A. Salstein, and J. S. Boyle, 1997: Evaluation of tropospheric water vapor simulations from the Atmospheric Model Intercomparison Project. J. Climate, 10, 1648–1661.
Gleckler, P. J., and Coauthors, 1995: Cloud-radiative effects on implied oceanic energy transports as simulated by atmospheric general circulation models. Geophys. Res. Lett., 22, 791–794.
Gutowski, W. J., Y. Chen, and Z. Otles, 1997: Atmospheric water vapor transport in NCEP–NCAR reanalyses: Comparison with river discharge in the central United States. Bull. Amer. Meteor. Soc., 78, 1957–1969.
Held, I. M., 1993: Large-scale dynamics and global warming. Bull. Amer. Meteor. Soc., 74, 228–241.
Hurrell, J. W., and K. E. Trenberth, 1999: Global sea surface temperature analyses: Multiple problems and their implications for climate analysis, modeling, and reanalysis. Bull. Amer. Meteor. Soc., 80, 2661–2678.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.
Mo, K. C., and R. W. Higgins, 1996: Large-scale atmospheric moisture transport as evaluated in the NCEP/NCAR and the NASA/DAO reanalyses. J. Climate, 9, 1531–1545.
National Research Council, 1999: The GEWEX Global Water Vapor Project (GVaP)—U.S. Opportunities. National Academy Press, 17 pp.
Noel, J., and D. Changnon, 1998: A pilot study examining U.S. winter cyclone frequency patterns associated with three ENSO parameters. J. Climate, 11, 2152–2159.
Oort, A. H., and H. Liu, 1993: Upper-air temperature trends over the globe, 1958–1989. J. Climate, 6, 292–307.
Peixoto, J. P., and A. H. Oort, 1992: Physics of Climate. American Institute of Physics, 520 pp.
——, R. D. Rosen, and D. A. Salstein, 1978: Seasonal variability in the pole-to-pole modes of water vapor transport during the IGY. Arch. Meteor. Geophys. Bioklimatol., A27, 233–255.
Philander, S. G. H., D. Gu, D. Halpern, G. Lambert, N.-C. Lau, T. Li, and R. C. Pacanowski, 1996: Why the ITCZ is mostly north of the equator. J. Climate, 9, 2958–2972.
Randel, D. L., T. H. Vonder Haar, M. A. Ringerud, G. L. Stephens, T. J. Greenwald, and C. L. Combs, 1996: A new global water vapor dataset. Bull. Amer. Meteor. Soc., 77, 1233–1246.
Rosen, R. D., 1999: The global energy cycle. Global Energy and Water Cycles, K. A. Browning and R. J. Gurney, Eds., Cambridge University Press, 1–9.
Ross, R. J., and W. P. Elliott, 1996: Tropospheric water vapor climatology and trends over North America: 1973–93. J. Climate, 9, 3561–3574.
Slonaker, R. L., and M. L. Van Woert, 1999: Atmospheric moisture transport across the Southern Ocean via satellite observations. J. Geophys. Res., 104, 9229–9249.
Sun, D.-Z., and A. H. Oort, 1995: Humidity–temperature relationships in the tropical troposphere. J. Climate, 8, 1974–1987.
——, and K. E. Trenberth, 1998: Coordinated heat removal from the equatorial Pacific during the 1986–87 El Niño. Geophys. Res. Lett., 25, 2659–2662.
Trenberth, K. E., 1997: The definition of El Niño. Bull. Amer. Meteor. Soc., 78, 2771–2777.
——, 1998: Atmospheric moisture residence times and cycling: Implications for rainfall rates and climate change. Climatic Change, 39, 667–694.
——, 1999: The extreme weather events of 1997 and 1998. Consequences, 5, 3–15.
——, and T. J. Hoar, 1996: The 1990–1995 El Niño–Southern Oscillation event: Longest on record. Geophys. Res. Lett, 23, 57–60.
——, and ——, 1997: El Niño and climate change. Geophys. Res. Lett., 24, 3057–3060.
——, and C. J. Guillemot, 1998: Evaluation of the atmospheric moisture and hydrological cycle in the NCEP/NCAR reanalyses. Climate Dyn., 14, 213–231.
Waliser, D. E., Z. Shi, J. R. Lanzante, and A. H. Oort, 1999: The Hadley circulation: Assessing NCEP/NCAR reanalysis and sparse in-situ estimates. Climate Dyn., 15, 719–735.
Wang, X., P. H. Stone, and J. Marotzke, 1999: Global thermohaline circulation. Part I: Sensitivity to atmospheric moisture transport. J. Climate, 12, 71–82.
Wentz, F. J., and M. Schabel, 2000: Precise climate monitoring using complementary satellite data sets. Nature, 403, 414–416.
Zhai, P., and R. E. Eskridge, 1997: Atmospheric water vapor over China. J. Climate, 10, 2643–2652.

Footnotes

Corresponding author address: Dr. Richard D. Rosen, Atmospheric and Environmental Research, Inc., 131 Hartwell Ave., Lexington, MA 02421.