The Global Water Cycle
USGCRP Fiscal Year 2006 Accomplishments

USGCRP
Program Elements

Atmospheric Composition

Ecosystems

Global Carbon Cycle

Decision-Support Resources Development and Related Research on Human Contributions and Responses

Climate Variability and Change

Global
Water Cycle

The following are selected highlights of recent research supported by CCSP participating agencies (as reported in the fiscal year 2007 edition of the annual report, Our Changing Planet).

These research results address the strategic research questions on the global water cycle identified in the CCSP Strategic Plan. Due to the overlap between the global water cycle and other CCSP elements, some themes such as water vapor-radiation feedback, an important component of global water cycle research, are elaborated in other chapters of this publication rather than here.

Modeling and Simulation of Cloud Processes and Cloud Systems [11, 12, 15, 18, 23]

Multi-Scale Simulations of Clouds

Researchers have been experimenting with a global atmospheric model in which the conventional cloudparameterizations are replaced, in each grid column, by a two-dimensional cloud-resolving model. Figure 12 shows that the modelproduces a simulation of uppertropospheric cloudiness that is much more realistic than a control run.

New Shallow Cloud Convection Scheme

By comparing regional model simulations with the observations collected at the Atmospheric Radiation Measurement (ARM) Southern Great Plains and Tropical Western Pacific sites, scientistsevaluated the overall performance of a recently developed shallowcumulus parameterization scheme under different meteorological conditions (see Figure 13). The simulations indicate that the shallow cumulus scheme can accurately simulate both marine shallow cumuli and the observed diurnal cycle of continental shallow cumuli. Sub-grid cloud properties, the resolved thermodynamic structures, and the surface energy budget are simulated well by the model.

Diagnostic Simulations of Arctic Cloud Systems

Scientists used measurements made as part of the ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) to evaluate the performance of the Community Atmosphere Model (CAM3) of the National Corporation for Atmospheric Research (NCAR), the Atmosphere Model (AM2) of NOAA’s Geophysical Fluid Dynamics Laboratory, and the weather forecast model of the European Centre for Medium-Range Weather Forecasts (ECMWF) in simulating Arctic cloud systems. The two climate models were evaluated under the framework developed through a joint effort between DOE’s Climate Change Prediction Program (CCPP) and the ARM program, the CCPP-ARM Parameterization Testbed, which is a diagnostic tool for evaluating climate models using weather prediction techniques. As revealed in the study, the models simulate the occurrence of clouds fairly well, but there are substantial errors in cloud microphysical properties. ARM data will be used to suggest improvements for these models (see Figure 14).

New Model of Cloud Drop Distribution that Simulates Drop Clustering

CCSPscientists have developed size-dependent models of the spatial distribution of cloud drops that simulate the observed clustering of drops. Understanding of spatialdistribution and small-scale fluctuations in cloud droplets is essential for both cloud physics and atmospheric radiation. For cloud physics, the coalescence growth ofraindrops depends upon size distribution while, for radiation, the spatial distribution of cloud drops has a strong impact on cloud radiative properties. In contrast tocurrently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, the new models show strong drop clustering, which increases with larger drop size. Clustering has vital consequences for rain physics, explaining how rain can form more quickly in the new models than simulations made with the former, homogenous models. The new models also help to explain why remotely sensed cloud drop size distributions are generally biased.

Improved Understanding and Modeling of Cloud Aerosol Interaction, Cloud Organization, and Radiative Properties [17]

Studying Stratus, Radiation, Aerosol, and Drizzle

The DOE’s ARM and Atmospheric Science Programs and the U.S. Office of Naval Research conducted a joint extensive field experiment at Pt. Reyes, California. The objectives were to
collect data from cloud-aerosol interactions and to improve understanding of cloud organization that is often associated with patches of drizzle.

Simulating Radiative Properties of Ice Clouds

Scientists developed a model that provides a means of predicting the radiative properties of ice clouds in terms of explicit microphysical properties, such as the parameters describing a bimodal size distribution that accounts for the smallest ice crystals and the various ice crystal shapes in the size distribution. The ice radiative properties predicted by the model code are being used in a development version of the NCAR CAM/Community Climate System Model (CCSM), and it will be a candidate for inclusion in CAM4/CCSM4. The explicit coupling between ice particle microphysical properties and radiative properties also provides a better opportunity for investigating the role of aerosol-ice nucleation processes in global climate processes.

Percentage of Global Land Areas Affected by Serious Drought Increases [2]

Global Palmer Drought Severity Index data and offline simulations with the NCAR land-surface model were used to study the potential drying over global land areas associated with the warming during the last several decades. This study found that the percentage of the global land area affected by serious drought more than doubled from about 15% during the 1970s to about 30% in the early 2000s. Widespread drying occurred over much of Europe and Asia, Canada, western and southern Africa, and eastern Australia. The warming-induced drying has occurred over most land areas with the largest effects in northern mid- and high latitudes. In contrast, rainfall deficits alone were the main factor behind expansion of dry soils in Africa’s Sahel and East Asia. Figure 15 illustrates these trends.

Mass Decrease in the Greenland Ice Sheet [13, 19, 21]

Greenland hosts the largest reservoir of freshwater in the Northern Hemisphere, and any substantial changes in the mass of its ice sheet will affect global sea level, the meridional overturning circulation of the ocean, and therefore the climate system. The Greenland glaciers cover an area of about 1.7 million km2 (a little smaller than Mexico) and are up to 3-km thick in spots. In the first direct, comprehensive mass survey of the entire Greenland Ice Sheet, scientists using data from the NASA/German Aerospace Center Gravity Recovery and Climate Experiment (GRACE) measured a significant decrease in the mass of the Greenland ice cap resulting from a speeding up of the flow of Greenland glaciers and accelerated ice discharge. GRACE detected a volume reduction in the Greenland ice sheet of 162 ± 22 km3 (39 ± 5.4 mi3) per year between 2002 and 2005. This is higher than all previously published estimates, and represents a contribution of about 0.4 mm (0.016 in) per year to globalsea-level rise as shown in Figure 16. The identical twin GRACE satellites track minute changes in Earth’s gravity field resulting from regional changes in Earth’s mass such as masses of ice, air, water, and solid earth that shift due to weather patterns, seasonal change, climate change, and even tectonic events. GRACE has the unique ability to measure monthly mass changes for an entire ice sheet—a breakthrough in our ability to monitor such changes.

Interannual Variability of the Hydrologic Cycle over North America [1, 5, 6, 22]

Recent research findings indicate that dominant winter modes in the hydrologic cycle are due to moisture fluxes associated with extreme precipitation events over the west coast of the United States, and are controlled by strong El Niño Southern Oscillation (ENSO) events, such as those of 1982-1983 and 1997-1998 (El Niño) and 1989(La Niña). In the central United States, moisture transport is associated with high-precipitation events and with moisture flux variability related to the droughts of 1983 and 1988. These research results are important because they point to a moisture storage component. The results have been incorporated in a new precipitation-recycling model that includes a soil moisture storage pool. The new recycling model was used to study the variability of monthly precipitation recycling over the conterminous United States from 1979 to 2000. Specific drought or flood years do not completely account for observed variability, pointing to a storage or “memory” term response, which subsequently affects interannual precipitation variability. To explore this soil moisture control, a novel method is being developed to use energy fluxes estimated from remote-sensing platforms to show that differences in energy fluxes (which drive moisture fluxes) are related to soil moisture through deep soil layer moisture effects on surface moisture fluxes. Deep soil influences on the uptake of moisture by plant roots result in high transpiration variability and changes in the overall energy balance. This potential vegetation response to a moisture storage pool plays a crucial role in land-atmosphere interactions through water transport in the form of evapotranspiration and root uptake, and carbon transport in the form of photosynthesis and respiration. Results show explicit correlations between vegetation variability, as controlled by topography, and the ENSO and North Pacific oceanic signals. Areas of vegetation variability found to be associated with the ENSO signal are uncommon to previous studies relating precipitation and temperature to ENSO, thus indicating a novel result and pointing to the hypothesized moisture “storage” memory. The focus of the initial phase of the analysis is on the continental United States to gain insight into general, wide-ranging relationships, yet focusing on particular ecological regions with greater vegetation variability. This will give further insight into influential mechanisms linking vegetation, climate, and physiography at small scales.

Changes in the Global Water/Energy Cycle Associated with Changes in the Carbon Cycle [10]

Afforestation is the process of converting open land into forest by planting trees or their seeds. It is generally considered beneficial for carbon sequestration (at certain time scales), ecosystem protection, soil moisture retention, reducing excessive surface runoff, improving replenishment of the groundwater table, andpossibly increasing local precipitation by increasing surface boundary layer moisture convergence, among other benefits. However, these benefits need to be balanced against the adverse impacts that afforestation may have in certain regions, depending on local and regional climate conditions. In this particular study, a global analysis of 504 annual catchment observations showed that afforestation dramatically decreased streamflow within a few years of planting. Across all plantation ages in the database, afforestation of grasslands, shrublands, or croplands decreased streamflow by180 mm yr-1 and 38% on average. After a slight initial increase in some cases,substantial annual decreases of 155 mm and 42% were observed on average for 6- to 10-year old plantations, and average losses for 10- to 20-year-old plantations were even greater (227 mm yr-1 and 52% of streamflow). Perhaps most important, 13% of the studied streams dried up completely for at least 1 year, with eucalyptus more likely to dry up streams than pines. Afforestation in drier regions (<1000 mm mean annual rainfall) was more likely to eliminate stream flow completely than in wetter regions. Mean annual renewable freshwater (percentage of annual precipitation lost as runoff) decreased about 20% with afforestation. For many nations whose total annual renewable freshwater is less than 30% of precipitation, afforestation is likely to have large impacts on water resources. These results suggest that afforestation and carbon cycle issues such as carbon sequestration need to be viewed together with their interfaces with the water cycle.

Evidence for Positive Trends in Moisture Recycling at High Northern Latitudes Leading to Vegetation Increases [3, 4]

Most observational indicators of global climate change have been found directly in the temperature record or in physical and ecological processes that respond to changing temperature. Researchers used a tracer approach to examine the atmospheric branch of the hydrologic cycle by following the moisture in global rainfall back to its evaporative sources over the last 25 years. Along with the first detailed analysis and climatology of the global atmospheric water cycle, their study shows evidence of trends in recycling at high northern latitudes driven by changes in circulation as well as surface temperature. These trends are consistent with observed vegetation-related changes and most evident where the density of meteorological data influencing the atmospheric analyses is high (see Figure 17).

New Land-Surface Schemes in Climate Models that Include Photosynthesis Show Improved Climate Simulations of Water-Cycle Parameters [8]

A new physiology-based model of canopy stomatal conductance and photosynthesis was included in the latest version of the Goddard Institute for Space Studies (GISS) general circulation model (GCM), Model E1. The sub-model includes responses to atmospheric humidity and CO2 concentration, which were missing from previous GISS GCM land-surface schemes. Measurements of moisture, energy, and CO2 fluxes over four vegetation types were used to test and calibrate the sub-model. Photosynthetic leaf nitrogen was calibrated for each vegetation type from flux measurements. The new sub-model resulted in surface cooling over many regions that were too warm in previous simulations. Some warm biases of over 2°C cooled by more than 0.5°C, including over central Eurasia, South America, the western United States, and Australia. Some regions that were previously too cool warmed, such as the Tibetan plateau. A number of precipitation biases were reduced, particularly over South America (by up to 1 mm day-1) and the oceanic inter-tropical convergence zone (by ± 1 mm day-1), while coastal West Africa became significantly wetter. Cloud cover increased over many land areas previously too clear. Higher absolute canopy conductances and positive feedbacks with atmospheric humidity were largely responsible for the simulated vegetation influence on the atmosphere. High-latitude climate changes through the remote effects of increased tropical latent heating (heat released by precipitating clouds) resulted directly from improved characterization of tropical forest canopy conductance. The realistic representation of stomatal control of land evaporation and evapotranspiration is critical for the accurate simulation of atmospheric dynamics in climate models. Figure 18 shows seasonal maps of mean precipitation bias.

Correspondence between Observations and Streamflow Simulations by Climate Models, and Future Streamflow Projections [ 16]

CCSP scientists analyzed the long-term streamflow characteristics in an ensemble of recent climate simulations and projections by 12 different global climate models. They found encouraging correspondences between observed historical and simulated patterns of 20th-century regional streamflow variations on multi-decadal time scales. The same models project 10 to 40% increases in runoff in eastern equatorial Africa, the La Plata basin, and high-latitude America and Eurasia, and 10 to 30% decreases in southern Africa, southern Europe, the Middle East, and mid-latitude western North America by 2050 under a mid-range scenario of greenhouse gas emissions leading to an atmospheric CO2 concentration of approximately 530 ppm by the mid-21st-century.

Linking the Time Scales and Amplitudes of Groundwater and Surface Water Flows to Global Climate Variations [9]

The time scales and amplitude of the hydrologic responses to climate variations depend on the time scales and mechanisms of the climate forcings, on how closely the groundwater and surface water systems are coupled to each other and to climate variations, and whether the overall hydrologic responses in a given setting depend more on slower aquifer responses or more rapid streamflow responses. An innovative study used a global GCM (ECHAM-T42) coupled to a regional groundwater model (RGWM) of the Santa Clara-Calleguas Basin to examine the simulated precipitation rates from the GCM for the period 1950 to 1993. The study found that interannual to interdecadal time scales of ENSO and Pacific Decadal Oscillation climate variations are imparted to the simulated climate-driven recharge (and discharge) variations. For example, the simulated response of average groundwater level to ENSO variations at a key observation well in the basin is 1.2 m per °C compared to 0.9 m per °C in the observations. This close agreement shows that the GCM-RGWM combination can translate global-scale climate variations into realistic groundwater responses. Figure 19 illustrates the spatial relationships and groundwater budgets of components of the water resource extraction and distribution systems for the Santa Clara-Calleguas Basin.

The Groundwater Connection in the Amplification of Seasonal- to Century-scale Oscillations in Closed Basins [7, 20]

A recent study shows that the space-time components of runoff have a complex relationship with orography, where the balance of precipitation and evapotranspiration interacts with the mountain-front watershed to filter and amplify runoff to the Great Salt Lake. The study examined the space-time patterns of annual,interannual, and decadal components of precipitation, temperature, and runoff using long-record time series across the steep topographic gradient of the Wasatch Front in northern Utah. This region forms the major drainage area to the Great Salt Lake. The approach used multi-channel singular spectrum analysis as a means of detecting dominant oscillations and spatial patterns in the data (see Figure 20 for a depiction of the spatial patterns). Results showed that high-elevation runoff is dominated by the annual and seasonal harmonics, while low-elevation runoff exhibits strong interannual to decadal oscillations. In particular,significant low-frequency components are found at intermediate and low elevations of the Wasatch Range. The research suggests that these results are due to mountain-front hydrologic conditions supporting groundwater storage and base flow. The transmission zone, or the zone of streamflow loss to groundwater, was identified as affecting annual, interannual, and decadal runoff components. Overall, the groundwater-streamflow relation represents a “low-pass” filter for the precipitation/evaporation input signal. The filtering effect is likely to be proportional to the scale of volumetric groundwater storage in the mountain blocks and basin sediments.

Collaborative Research: Development of Informatics Infrastructure for Hydrologic Sciences [14]

Scientists associated with the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI) have developed a Hydrologic Information System (HIS) that combines point data (on-site measurements), spatial data (GIS-based geographical data), remotely sensed (satellite) data, and meteorological data. HIS provides a “digital watershed” with access through a common portal to a wide variety of hydrologic and water quality data collected by many agencies, and with a “translator” that makes seamless connections. HIS will later be expanded to provide hydrologic representations and analyses. With this hydrologic digital library, users can find desired items through web-based searches and acquire them through automated data acquisition systems. The goal is to allow the scientific community and resource managers to access information needed to define fluxes and flow paths, residence times, and mass balances—key elements for testing hydrologic hypotheses. HIS provides data fusion for mating and communication among different formats to form a coherent framework in space and time.

References

1)   Amenu, G.G., P. Kumar, and X.-Z. Liang, 2005: Interannual variability of deep-layer hydrologic memory and mechanisms of its influence on surface energy fluxes. Journal of Climate, 18, 5024-5045.

2)   Dai, A., K.E. Trenberth, and T. Qian, 2004: A global dataset of Palmer Drought Severity Index for 1870-2002: Relationship with soil moisture and effects of surface warming. Journal of Hydrometeorology, 5(6), 1117-1130.

3)   Dirmeyer, P.A. and K.L. Brubaker, 2006a: Global characterization of the hydrologic cycle from a quasi-isentropic back-trajectory analysis of atmospheric water vapor. Journal of Hydrometeorology (accepted).

4)   Dirmeyer, P.A. and K.L. Brubaker, 2006b: Evidence for trends in the Northern Hemisphere water cycle. Geophysical Research Letters, 33, L14712, doi:10.1029/2006GL026359.

5)   Dominguez, F. and P. Kumar, 2005: Dominant modes of moisture flux anomalies over North America and their relationship to extreme hydrologic events. Journal of Hydrometeorology, 6, 194-209.

6)   Dominguez, F., P. Kumar, X.-Z. Liang, and M.Ting, 2006: Impact of atmospheric moisture storage on precipitation recycling. Journal of Climate, 19, 1513-1530.

7)   Duffy, C., 2005: The groundwater connection: amplification of seasonal to century scale oscillations in closed basins. In: Geological Society of America Annual Meeting Abstracts with Programs, 37(7), 162. Geological Society of America, Salt Lake City, Paper No. 64-8.

8)   Friend, A.D. and N.Y. Kiang, 2005: Land surface model development for the GISS GCM: Effects of improved canopy physiology on simulated climate. Journal of Climate, 18(15), 2883-2902.

9)   Hanson, R.T. and M.D. Dettinger, 2005: Ground water/surface water responses to global climate simulations, Santa Clara-Calleguas Basin, Ventura, California. Journal of the American Water Resources Association, 41(3), 517-536.

10) Jackson, R.B., E.G. Jobbagy, R. Avissar, S. Baidya Roy, D.J. Barret, C.W. Cook, K.A. Farley, D.C. le Maitre, B.A. McCarl, B.C. Murray, 2005: Trading water for carbon with biological carbon sequestration. Science, 310, 1944-1947.

11) Khairoutdinov, M., D.A. Randall, and C. DeMott, 2005: Simulation of the atmospheric general circulation using a cloud-resolving model as a super-parameterization of physical processes. Journal of the Atmospheric Sciences, 62, 2136-2154.

12) Knyazikhin, Y., A. Marshak, M. Larsen, W. Wiscombe, J. Martonchik, and R. Myneni, 2005: Small-scale drop size variability: Impact on estimation of cloud optical properties. Journal of the Atmospheric Sciences, 62, 2555-2567.

13) Levi, B.G., 2006: Is there a slowing in the Atlantic Ocean’s overturning circulation? Physics Today, 59(4), 26-28.

14) Maidment, D.R. (ed.), 2005: CUAHSI Hydrologic Information System Status Report [PDF] . Consortium for the Advancement of Hydrologic Science, Inc., Washington, DC, USA, 214 pp.

15) Marshak, A., Y. Knyazikhin, M. Larsen, and W. Wiscombe, 2005: Small-scale drop size variability: Empirical models for drop-size-dependent clustering in clouds. Journal of the Atmospheric Sciences, 62, 551-558.

16) Milly, P.C.D., K.A. Dunne, and A.V. Vecchio, 2005: Global pattern of trends in streamflow and water availability in a changing climate. Nature, 438, 347-350.

17) Mitchell, D.L., A.J. Baran, W.P. Arnott, and C. Schmitt, 2006: Testing and comparing the modified diffraction approximation. Journal of the Atmospheric Sciences (in press).

18) Ping Z. and C. S. Bretherton, 2004: A simulation study of shallow moist convection and its impact on the atmospheric boundary layer. Monthly Weather Review, 132(10), 2391-2409.

19) Rignot, E. and P. Kanagaratnam, 2006: Changes in the velocity structure of the Greenland Ice Sheet. Science, 311, 986-990.

20) Shun, T. and C. Duffy, 1999: Low-frequency oscillations in precipitation, temperature, and runoff on a west facing mountain front: A hydrological interpretation. Water Resources Research, 35, 191-201.

21) Velicogna, I. and J. Wahr, 2005: Greenland mass balance from GRACE. Geophysical Research Letters, 32, L18505, doi:10.1029/2005GRL023955.

22) White, A.B., P. Kumar, and D. Tcheng, 2005: A data mining approach for understanding topographic control on climate-induced inter-annual vegetation variability over the United States. Remote Sensing of Environment, 98, 1-20.

23) Xie, S., S. Klein, J. Yio, A. Beljarrs, C. Long, and M. Zhang: 2005. An assessment of ECMWF analyses and model forecasts over the North Slope of Alaska using observations from the ARM Mixed-Phase Arctic Cloud Experiment. Journal of Geophysical Research, 111, D05107, doi:10.1029/2005JD006509