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Michael G. Bosilovich, Siegfried D. Schubert, and Gregory K. Walker

Abstract

In this study, numerical simulations of the twentieth-century climate are evaluated, focusing on the changes in the intensity of the global water cycle. A new model diagnostic of atmospheric water vapor cycling rate is developed and employed that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values with more variability.

Climate simulations were performed using SSTs of the early (1902–21) and late (1979–98) twentieth century along with the appropriate CO2 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-yr climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the simulated hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend, while the oceanic precipitation has an upward trend consistent with previous studies and the available observations. The decreasing continental trend in precipitation is located primarily over tropical land regions, with some other regions, such as North America, experiencing an increasing trend. Precipitation trends are diagnosed further using the water tracers to delineate the precipitation that occurs because of continental evaporation, as opposed to oceanic evaporation. These model diagnostics show that over global land areas, the recycling of continental moisture is decreasing in time. However, the recycling changes are not spatially uniform so that some regions, most notably over the United States, experience continental recycling of water that increases in time.

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Siegfried D. Schubert, Max J. Suarez, Yehui Chang, and Grant Branstator

Abstract

This study examines the variability in forecasts of the January–February–March (JFM) mean extratropical circulation and how that variability is modulated by the El Niño–Southern Oscillation. The analysis is based on ensembles of seasonal simulations made with an atmospheric general circulation model (AGCM) forced with sea surface temperatures observed during the 1983 El Niño and 1989 La Niña events. The AGCM produces pronounced interannual differences in the magnitude of the extratropical seasonal mean noise (intraensemble JFM variability). The North Pacific, in particular, shows extensive regions in which the 1989 seasonal mean noise kinetic energy (SKE), which is dominated by a “Pacific–North American (PNA)–like” spatial structure, is more than 2 times that of the 1983 forecasts. The larger SKE in 1989 is associated with a larger-than-normal barotropic conversion of kinetic energy from the mean Pacific jet to the seasonal mean noise. The generation of SKE by submonthly transients also shows substantial interannual differences, though these are much smaller than the differences in the mean flow conversions. An analysis of the generation of monthly mean noise kinetic energy and its variability suggests that the seasonal mean noise is predominantly a statistical residue of variability resulting from dynamical processes operating on monthly and shorter timescales.

A stochastically forced barotropic model (linearized about the AGCM's 1983 and 1989 seasonal and ensemble mean states) is used to further assess the role of the basic state, submonthly transients, and tropical forcing in modulating the uncertainties in the seasonal AGCM forecasts. When forced globally with spatially white noise, the linear model generates much larger variance for the 1989 basic state, consistent with the AGCM results. The extratropical variability for the 1989 basic state is dominated by a single eigenmode and is strongly coupled with forcing over the tropical western Pacific and the Indian Ocean. Linear calculations that include forcing from the AGCM variance of the tropical forcing and submonthly transients show a small impact on the variability over the PNA region as compared with that of the basic-state differences.

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Chung-Kyu Park, Max J. Suarez, and Siegfried D. Schubert

Abstract

An atmospheric general circulation model is used to study the impact of idealized zonally propagating tropical heating anomalies on the low-frequency variability in the North Pacific region. The propagating heating is designed to mimic the thermal forcing associated with the Madden–Julian oscillation (MJO). Results are examined by separating the forced response from other variability and by comparing with runs employing fixed-phase (stationary) heating anomalies.

For both the forced and free circulations, the main modes of variability consist of a zonal expansion and retraction of the East Asian jet. The effective Rossby wave forcing associated with the heating is dominated by the advection term and located in the subtropics in the regions of strong absolute vorticity gradients.

Compared with cases using stationary forcing, the response to the propagating forcing is weaker and of different phase, indicating that the 40-day period used for the propagating anomalies is too short to allow the development of the steady-state response in the extratropics.

The model's total low-frequency variability in the North Pacific sector is dominated by the free oscillations that are the result of local processes uncorrelated with tropical variability. The relatively small forced response appear to be partly the result of the simplicity of the propagating heating anomaly that propagates at a constant phase speed and the simplification introduced into the GCM that do not allow transient feedback in the diabatic heating.

It is suggested that the lack of a significant Rossby wave stretching term in the subtropics is a distinguishing feature of the east–west dipole heating anomalies of the MJO and may contribute to the weakness of the response compared to interannual tropical heating anomalies.

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Stefan Liess, Duane E. Waliser, and Siegfried D. Schubert

Abstract

Our ability to predict active and break periods of the Asian summer monsoon is intimately tied to our ability to predict the intraseasonal oscillation (ISO). The present study analyzes the upper limit of potential predictability of the northern summer ISO, as it is simulated by the ECHAM5 atmospheric general circulation model forced with climatological SSTs. The leading extended empirical orthogonal functions of precipitation, computed from a 10-yr control simulation, are used to define four different phases of the ISO. Fourteen-member ensembles of 90-day hindcasts are run for each phase of the three strongest ISO events identified in the 10-yr control run. Initial conditions for each ensemble are created from the control simulation using a breeding method.

The signal-to-noise ratio is analyzed over a region that covers the core of the Asian summer monsoon activity. Over Southeast Asia, the upper limit for predictability of precipitation and 200-hPa zonal wind is about 27 and 33 days, respectively. Over India, values of more than 15 days occur for both variables. A spatial analysis of the different phases of the ISO reveals that the predictability follows the eastward- and northward-propagating ISO during the active and break phases of the monsoon. Precipitation reveals increased predictability at the end of the convective phase. Analogous, 200-hPa zonal wind shows strongest predictability during low and easterly anomalies. This potential predictability is considerably higher than for numerical forecasts of typical weather variations, particularly for the Tropics, indicating that useful forecasts of monsoon active and break events may be possible with lead times of more than two weeks for precipitation and the dynamics. A closer look at the breeding method used here to initialize the hindcasts shows the importance of appropriate ensemble experiment designs.

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Siegfried D. Schubert, Richard B. Rood, and James Pfaendtner

The Data Assimilation Office at NASA's Goddard Space Flight Center is currently producing a multiyear gridded global atmospheric dataset for use in climate research, including tropospheric chemistry applications. The data, which are being made available to the scientific community, are well suited for climate research since they are produced by a fixed assimilation system designed to minimize the spinup in the hydrological cycle. By using a nonvarying system, the variability due to algorithm change is eliminated and geophysical variability can be more confidently isolated.

The analysis incorporates rawinsonde reports, satellite retrievals of geopotential thickness, cloud-motion winds, and aircraft, ship, and rocketsonde reports. At the lower boundary, the assimilating atmospheric general circulation model is constrained by the observed sea surface temperature and soil moisture derived from observed surface air temperature and precipitation fields. The available output data include all prognostic variables and a large number of diagnostic quantities such as heating rates, precipitation, surface fluxes, cloud fraction, and the height of the planetary boundary layer. These variables were chosen to assure a complete budget of the energy and moisture cycles. The assimilated data should also be useful for estimating transport by cumulus processes. The analysis increments (observation minus first guess) and the estimated analysis errors are provided to help the user assess the quality of the data. All quantities are made available every 6 h at the full resolution of the assimilating general circulation model. Selected surface quantities are made available every 3 h.

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Young-Kwon Lim, Siegfried D. Schubert, Yehui Chang, and Hailan Wang

Abstract

This study examines the within-season monthly variation of the El Niño response over North America during December–March using the NASA/GEOS model. In agreement with previous studies, the skill of 1-month-lead GEOS coupled model forecasts of precipitation over North America is largest (smallest) for February (January), with similar results in uncoupled mode. A key finding is that the relatively poor January skill is the result of the model placing the main circulation anomaly over the northeast Pacific slightly to the west of the observed, resulting in precipitation anomalies that lie off the coast instead of over land as observed. In contrast, during February the observed circulation anomaly over the northeast Pacific shifts westward, lining up with the predicted anomaly, which is essentially unchanged from January, resulting in both the observed and predicted precipitation anomalies remaining off the coast. Furthermore, the largest precipitation anomalies occur along the southern tier of states associated with an eastward extended jet—something that the models capture reasonably well. Simulations with a stationary wave model indicate that the placement of January El Niño response to the west of the observed over the northeast Pacific is the result of biases in the January climatological stationary waves, rather than errors in the tropical Pacific El Niño heating anomalies in January. Furthermore, evidence is provided that the relatively poor simulation of the observed January climatology, characterized by a strengthened North Pacific jet and enhanced ridge over western North America, can be traced back to biases in the January climatology heating over the Tibet region and the tropical western Pacific.

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Siegfried D. Schubert, Yehui Chang, Anthony M. DeAngelis, Hailan Wang, and Randal D. Koster

Abstract

Much of the southeast United States experienced record dry conditions during September of 2019, with the area in abnormally dry to exceptional drought conditions growing from 25% at the beginning of the month to 80% by the end of the month. The drought ended just as abruptly due to above-normal rain that fell during the second half of October. In this study we employed MERRA-2 and the GEOS-5 AGCM to diagnose the underlying causes of the drought’s onset, maintenance, and demise. The basic approach involves performing a series of AGCM simulations in which the model is constrained to remain close to MERRA-2 over prespecified areas that are external to the drought region. The start of the drought appears to have been forced by anomalous heating in the central/western tropical Pacific that resulted in low-level anticyclonic flow and a tendency for descending motion over much of the Southeast. An anomalous ridge associated with a Rossby wave train (emanating from the Indian Ocean region) is found to be the main source of the most intense temperature and precipitation anomalies that develop over the Southeast during the last week of September. A second Rossby wave train (emanating from the same region) is responsible for the substantial rain that fell during the second half of October to end the drought. The links to the Indian Ocean dipole (with record positive values) as well as a waning El Niño allow some speculation as to the likelihood of similar events occurring in the future.

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Siegfried D. Schubert, Max J. Suarez, Philip J. Pegion, Randal D. Koster, and Julio T. Bacmeister

Abstract

The U.S. Great Plains experienced a number of multiyear droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long-term (1930–2000) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multiyear) variations in precipitation in the Great Plains region (30°–50°N, 95°–105°W) that are similar to those observed.

A correlative analysis suggests that the ensemble-mean low-frequency (time scales longer than about 6 yr) rainfall variations in the Great Plains are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low-frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the two polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influences the Great Plains. As such, the Great Plains tend to have above-normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper-tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally symmetric component in which U.S. Great Plains pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extratropics.

The potential predictability of rainfall in the Great Plains associated with SSTs is rather modest, with about one-third of the total low-frequency rainfall variance being forced by SST anomalies. Further idealized experiments with climatological SST suggest that the remaining low-frequency variance in the Great Plains precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a fivefold increase in the variance in annual Great Plains precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce a year-to-year memory in the hydrological cycle. The impact of soil memory is consistent with a red noise process, in which the deep soil is forced by white noise and damped with a time scale of about 1.5 yr. As such, the role of low-frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

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Randal D. Koster, Rolf H. Reichle, Siegfried D. Schubert, and Sarith P. Mahanama

Abstract

Hydrological variability at a given location is characterized in part by a horizontal length scale—a measure of how far one can travel from that location and still see similar time variations of a hydrological variable of interest. Here, using Level-2 soil moisture retrievals produced by the NASA Soil Moisture Active Passive (SMAP) mission, we compute global distributions of these length scales for the Northern Hemisphere warm and cold seasons (May–September and November–March, respectively). The length scales show significant spatial and seasonal variability, with, as expected, much larger values (e-folding scales of greater than 500 km) often seen in the cold season, when convective rainfall is less prominent. The SMAP-derived length scales are found to be largely consistent with those derived directly, where possible, from precipitation measurements. This suggests a unique value of the retrievals: outside of well-instrumented areas, satellite-based soil moisture datasets have the potential to provide otherwise unattainable estimates of the horizontal length scales of hydrological variability.

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Siegfried D. Schubert, Hailan Wang, Randal D. Koster, Max J. Suarez, and Pavel Ya. Groisman

Abstract

This article reviews the understanding of the characteristics and causes of northern Eurasian summertime heat waves and droughts. Additional insights into the nature of temperature and precipitation variability in Eurasia on monthly to decadal time scales and into the causes and predictability of the most extreme events are gained from the latest generation of reanalyses and from supplemental simulations with the NASA Goddard Earth Observing System model, version 5 (GEOS-5). Key new results are 1) the identification of the important role of summertime stationary Rossby waves in the development of the leading patterns of monthly Eurasian surface temperature and precipitation variability (including the development of extreme events such as the 2010 Russian heat wave); 2) an assessment of the mean temperature and precipitation changes that have occurred over northern Eurasia in the last three decades and their connections to decadal variability and global trends in SST; and 3) the quantification (via a case study) of the predictability of the most extreme simulated heat wave/drought events, with some focus on the role of soil moisture in the development and maintenance of such events. A literature survey indicates a general consensus that the future holds an enhanced probability of heat waves across northern Eurasia, while there is less agreement regarding future drought, reflecting a greater uncertainty in soil moisture and precipitation projections. Substantial uncertainties remain in the understanding of heat waves and drought, including the nature of the interactions between the short-term atmospheric variability associated with such extremes and the longer-term variability and trends associated with soil moisture feedbacks, SST anomalies, and an overall warming world.

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