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Xing Yuan and Xin-Zhong Liang

Abstract

This study presents a comprehensive evaluation on a Conjunctive Surface–Subsurface Process Model (CSSP) in predicting soil temperature–moisture distributions, terrestrial hydrology variations, and land–atmosphere exchanges against various in situ measurements and synthetic observations at regional–local scales over the contiguous United States. The CSSP, rooted in the Common Land Model (CoLM) with a few updates from the Community Land Model version 3.5 (CLM3.5), incorporates significant advances in representing hydrology processes with realistic surface (soil and vegetation) characteristics. These include dynamic surface albedo based on satellite retrievals, subgrid soil moisture variability of topographic controls, surface–subsurface flow interactions, and bedrock constraint on water table depths. As compared with the AmeriFlux tower measurements, the CSSP and CLM3.5 reduce surface sensible and latent heat flux errors from CoLM by 10 W m−2 on average, and have much higher correlations with observations for daily latent heat variations. The CSSP outperforms the CLM3.5 over the crop, grass, and shrub sites in depicting the latent heat annual cycles. While retaining the improvement for soil moisture in deep layers, the CSSP shows further advantage over the CLM3.5 in representing seasonal and interannual variations in root zones. The CSSP reduces soil temperature errors from the CLM3.5 (CoLM) by 0.2 (0.7) K at 0.1 m and 0.3 (0.6) K at 1 m; more realistically captures seasonal–interannual extreme runoff and streamflow over most regions and snow depth anomalies in high latitude (45°–52°N); and alleviates climatological water table depth systematic bias (absolute error) by about 1.2 (0.4) m. Clearly, the CSSP performance is overall superior to both the CoLM and CLM3.5. The remaining CSSP deficiencies and future refinements are also discussed.

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Jinhong Zhu and Xin-Zhong Liang

Abstract

The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)-based regional climate model (CMM5) capability in simulating the interannual variations of U.S. precipitation and surface air temperature during 1982–2002 is evaluated with a continuous baseline integration driven by the NCEP–Department of Energy (DOE) Second Atmospheric Model Intercomparison Project Reanalysis (R-2). It is demonstrated that the CMM5 has a pronounced downscaling skill for precipitation and temperature interannual variations. The EOF and correlation analyses illustrate that, for both quantities, the CMM5 captures the spatial pattern, temporal evolution, and circulation teleconnections much better than the R-2. In particular, the CMM5 more realistically simulates the precipitation pattern centered in the Northwest, where the representation of the orographic enhancement by the forced uplifting during winter (rainy season) is greatly improved over the R-2.

The downscaling skill, however, is sensitive to the cumulus parameterization. This sensitivity is studied by comparing the baseline with a branch summer integration replacing the Grell with the Kain–Fritsch cumulus scheme in the CMM5. The dominant EOF mode of the U.S. summer precipitation interannual variation, identified with the out-of-phase relationship between the Midwest and Southeast in observations, is reproduced more accurately by the Grell than the Kain–Fritsch scheme, which largely underestimates the variation in the Midwest. This pattern is associated with east–west movement of the Great Plains low-level jet (LLJ): a more western position corresponds to a stronger southerly flow bringing more moisture and heavier rainfall in the Midwest and less in the Southeast. The second EOF pattern, which describes the consistent variation over the southern part of the Midwest and the South in observations, is captured better by the Kain–Fritsch scheme than the Grell, whose pattern systematically shifts southward.

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Xiaoqing Wu and Xin-Zhong Liang

Abstract

The representation of subgrid horizontal and vertical variability of clouds in radiation schemes remains a major challenge for general circulation models (GCMs) due to the lack of cloud-scale observations and incomplete physical understanding. The development of cloud-resolving models (CRMs) in the last decade provides a unique opportunity to make progress in this area of research. This paper extends the study of Wu and Moncrieff to quantify separately the impacts of cloud horizontal inhomogeneity (optical property) and vertical overlap (geometry) on the domain-averaged shortwave and longwave radiative fluxes at the top of the atmosphere and the surface, and the radiative heating profiles. The diagnostic radiation calculations using the monthlong CRM-simulated tropical cloud optical properties and cloud fraction show that both horizontal inhomogeneity and vertical overlap of clouds are equally important for obtaining accurate radiative fluxes and heating rates. This study illustrates an objective approach to use long-term CRM simulations to separate cloud overlap and inhomogeneity effects, based on which GCM representation (such as mosaic treatment) of subgrid cloud–radiation interactions can be evaluated and improved.

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Shuyan Liu and Xin-Zhong Liang

Abstract

An observational climatology of the planetary boundary layer height (PBLH) diurnal cycle, specific to surface characteristics, is derived from 58 286 fine-resolution soundings collected in 14 major field campaigns around the world. An objective algorithm determining PBLH from sounding profiles is first developed and then verified by available lidar and sodar retrievals. The algorithm is robust and produces realistic PBLH as validated by visual examination of several thousand additional soundings. The resulting PBLH from all existing data is then subject to various statistical analyses. It is demonstrated that PBLH occurrence frequencies under stable, neutral, and unstable regimes follow a narrow, intermediate, and wide Gamma distribution, respectively, over both land and oceans. Over ice all exhibit a narrow distribution. The climatological PBLH diurnal cycle is strong over land and oceans, with a distinct peak at 1500 and 1200 LT, whereas the cycle is weak over ice. Relative to midlatitude land, the PBLH variability over tropical oceans is larger during the morning and at night but much smaller in the afternoon. This study provides a unique observational database for critical model evaluation on the PBLH diurnal cycle and its temporal/spatial variability.

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Jinhong Zhu and Xin-Zhong Liang

Abstract

Observations reveal that, in summer, westward extension of the Bermuda high enhances the Great Plains low-level jet (LLJ) that transports more moisture northward, causing precipitation increases in the Midwest and decreases in the Gulf States. Meanwhile, more warm air advection from the Gulf of Mexico to the southern Great Plains and stronger clear-sky radiative heating under high pressures over the Southeast result in warmer surface temperatures across the Gulf states. The enhanced LLJ transport of cleaner marine air from the Gulf reduces surface ozone across the southern Great Plains–Midwest. In contrast, larger transport of more polluted air from the Midwest to New England and more frequent air stagnation under high pressures in the Southeast increase ozone over most of the eastern coastal states. This Bermuda high–induced ozone change reversal between the southern Great Plains–Midwest and eastern coastal states, with a magnitude of 6 and 13.5 ppb, respectively, in summer-mean maximum daily 8-h average, exhibits strong decadal variations that should be considered in the U.S. air quality dynamic management.

The observed Bermuda high signatures over the Gulf states can be well captured by regional climate and air quality models. Notable model deficiencies exist over the northern Great Plains–Midwest that are more remote to the Bermuda high and LLJ control. The regional models largely reduce these deficiencies from general circulation models (GCMs). Only 7 out of 51 GCMs can represent all key regional signatures of the Bermuda high, while none can simulate its strong association with planetary sea surface temperature anomalies. The result indicates a great challenge for GCMs to predict Bermuda high variability and change.

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Hyun I. Choi and Xin-Zhong Liang

Abstract

This study addresses several deficiencies in the existing formulations for terrestrial hydrologic processes in the Common Land Model (CLM) and presents improved solutions, focusing on runoff prediction. In particular, this paper has 1) incorporated a realistic geographic distribution of bedrock depth to improve estimates of the actual soil water capacity; 2) replaced an equilibrium approximation with a dynamic prediction of the water table to produce more reasonable variations of the saturated zone depth; 3) used an exponential decay function with soil depth for the saturated hydraulic conductivity to consider the effect of macropores near the ground surface; 4) formulated an effective hydraulic conductivity of the liquid part at the frozen soil interface and imposed a maximum surface infiltration limit to eliminate numerically generated negative or excessive soil moisture solution; and 5) examined an additional contribution to subsurface runoff from saturation lateral runoff or baseflow controlled by topography. To assess the performance of these modifications, runoff results from a set of offline simulations are validated at a catchment-scaled study domain around the Ohio Valley region. Together, these new schemes enable the CLM to capture well the major characteristics of the observed total runoff variations. The improvement is especially significant at peak discharges under high flow conditions.

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Xiaoqing Wu, Xin-Zhong Liang, and Sunwook Park

Abstract

This study aims to combine the cloud-resolving model (CRM) simulations with the Department of Energy’s Atmospheric Radiation Measurement Program (ARM) observations to provide long-term comprehensive and physically consistent data that facilitate quantifying the effects of subgrid cloud–radiation interactions and ultimately to develop physically based parameterization of these interactions in general circulation models. The CRM is applied here to simulate the midlatitude cloud systems observed at the ARM southern Great Plains (SGP) site during the 1997 intensive observation period. As in the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE), the CRM-simulated ensemble mean quantities such as cloud liquid water, cloud fraction, precipitation, and radiative fluxes are generally in line with the surface measurements, satellite, and radar retrievals. The CRM differences from the ARM estimates, when averaged over the entire period, are less than 5 W m−2 in both longwave and shortwave radiative fluxes at the top of the atmosphere and surface. Because of the different large-scale forcing and surface heat fluxes in ARM and TOGA COARE, the CRM produces different cloud distributions over the midlatitude continent and tropical ocean. However, diagnostic analyses show that the subgrid cloud variability has similar impact on the domain-averaged radiative fluxes and heating rates in ARM as in TOGA COARE.

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Kenneth E. Kunkel and Xin-Zhong Liang

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A diagnostic analysis of relationships between central U.S. climate characteristics and various flow and scalar fields was used to evaluate nine global coupled ocean–atmosphere general circulation models (CGCMs) participating in the Coupled Model Intercomparison Project (CMIP). To facilitate identification of physical mechanisms causing biases, data from 21 models participating in the Atmospheric Model Intercomparison Project (AMIP) were also used for certain key analyses.

Most models reproduce basic features of the circulation, temperature, and precipitation patterns in the central United States, although no model exhibits small differences from the observationally based data for all characteristics in all seasons. Model ensemble means generally produce better agreement with the observationally based data than any single model. A fall precipitation deficiency, found in all AMIP and CMIP models except the third-generation Hadley Centre CGCM (HadCM3), appears to be related in part to slight biases in the flow on the western flank of the Atlantic subtropical ridge. In the model mean, the ridge at 850 hPa is displaced slightly to the north and to the west, resulting in weaker southerly flow into the central United States.

The CMIP doubled-CO2 transient runs show warming (1°–5°C) for all models and seasons and variable precipitation changes over the central United States. Temperature (precipitation) changes are larger (mostly less) than the variations that are observed in the twentieth century and the model variations in the control simulations.

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Xin-Zhong Liang, Wei-Chyung Wang, and Michael P. Dudek

Abstract

Observed and general circulation climate model (GCM) simulated interannual teleconnection patterns in the Northern Hemisphere are compared on a monthly basis. The study was based on 1946–1991 observations and two separate 100-year simulations corresponding to the present climate and a greenhouse warming climate. The teleconnection patterns are characterized by action centers and composite extreme anomaly (CEA) distributions. The definition and comparison of observed and simulated patterns include examination of time persistence, spatial coherence as well as consistent signatures between 500-mb height, sea level pressure, and surface air temperature.

For the present climate simulation, the GCM reproduces observed spatial and temporal variations of the action centers of four principal teleconnection patterns: the North Atlantic oscillation, the North Pacific oscillation, the Pacific/North American pattern, and the Eurasian pattern. Substantial model biases exist in the magnitude, regional structure as well as monthly transition of anomalies. The CEA regional characteristics are better simulated over land than over the oceans. For example, the model most accurately simulates the Eurasian pattern, which has its dominant action centers over Eurasia. In addition, all three climate variables exhibit substantial anomalies for each land-based action center. In contrast, over the oceans, the model systematically underestimates sea level pressure and 500-mb height CEAs, while it produces small surface temperature responses. It is suggested that atmospheric dynamics associated with flow instability is likely to be the dominant mechanism that generates these teleconnections, while the lack of interactive ocean dynamics may be responsible for small responses over the oceans.

In the greenhouse warming climate, the GCM continues to simulate the four interannual teleconnection patterns. Systematic changes, however, are found for the Pacific/North American and Eurasian patterns in winter, where the action centers shift to the east and the CEAs weaken over land. These results must be considered to be exploratory because of the use of a mixed layer ocean that does not include oceanic dynamics.

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Xin-Zhong Liang, Kenneth E. Kunkel, and Arthur N. Samel

Abstract

A regional climate model (RCM) is being developed for U.S. Midwest applications on the basis of the newly released Pennsylvania State University–NCAR Fifth-Generation Mesoscale Model (MM5), version 3.3. This study determines the optimal RCM domain and effective data assimilation technique to accurately integrate lateral boundary conditions (LBCs) across the buffer zones. The LBCs are constructed from both the NCEP–NCAR and ECMWF reanalyses to depict forcing uncertainties. The RCM domain was chosen to correctly represent the governing physical processes while minimizing LBC errors. Sensitivity experiments are conducted for the Midwest 1993 summer flood to investigate buffer zone treatment impacts on RCM performance.

The results demonstrate the superiority of the buffer zone treatment that consists of the physically based domain choice and revised assimilation technique. Given this treatment, the RCM realistically simulates both temporal variations and spatial distributions in the major flood area (MFA). This success is identified with the accurate representation of both the midlatitude upper-level jet stream and Great Plains low-level jet (LLJ). The RCM reproduces different climate regimes, where observed rainfall was identified with the periodic (5 day) passage of midlatitude cyclones in June and persistent synoptic circulations in July. The model also correctly simulates the MFA rainfall diurnal cycle (with the peak amount at 0900 UTC), which follows the LLJ cycle by approximately 3 h. On the other hand, RCM performance is substantially reduced when the southern buffer zone extends to the Tropics, where large forcing errors exist. In particular, the RCM generates a weaker LLJ and, as a consequence, a decreased amount and delayed diurnal cycle of the MFA rainfall. In addition, the MM5 default LBC data assimilation technique produces considerable model biases, whereas the revised technique improves overall RCM performance and reduces sensitivity to domain size.

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