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Featured researches published by Xiquan Dong.


Journal of Geophysical Research | 2001

A new retrieval for cloud liquid water path using a ground‐based microwave radiometer and measurements of cloud temperature

James C. Liljegren; Eugene E. Clothiaux; Gerald G. Mace; Seiji Kato; Xiquan Dong

A new method to retrieve cloud liquid water path using 23.8 and 31.4 GHz microwave radiometer brightness temperature measurements is developed. This method does not depend on climatological estimates of either the mean radiating temperature of the atmosphere Tmr or the mean cloud liquid water temperature Tcloud. Rather, Tmr is estimated from surface temperature and relative humidity measurements, while Tcloud is estimated using millimeter-wave cloud radar data, together with atmospheric temperature profiles obtained from either radiosonde or rapid update cycle (RUC) model output. Simulations demonstrate that the new retrieval method significantly reduces the biases in the liquid water path estimates that are apparent in a site-specific retrieval based on monthly stratified, local climatology. An analysis of the liquid water path estimates produced by the two retrievals over four case study days illustrates trends and retrieval performances consistent with the model simulations.


Journal of the Atmospheric Sciences | 2002

Comparison of Stratus Cloud Properties Deduced from Surface, GOES, and Aircraft Data during the March 2000 ARM Cloud IOP

Xiquan Dong; Patrick Minnis; Gerald G. Mace; William L. Smith; Michael R. Poellot; Roger T. Marchand; Anita D. Rapp

Low-level stratus cloud microphysical properties derived from surface and Geostationary Operational Environmental Satellite (GOES) data during the March 2000 cloud intensive observational period (IOP) at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site are compared with aircraft in situ measurements. For the surface retrievals, the cloud droplet effective radius and optical depth are retrieved from a d2-stream radiative transfer model with the input of ground-based measurements, and the cloud liquid water path (LWP) is retrieved from ground-based microwave-radiometer-measured brightness temperature. The satellite results, retrieved from GOES visible, solar-infrared, and infrared radiances, are averaged in a 0.5 8 3 0.58 box centered on the ARM SGP site. The forward scattering spectrometer probe (FSSP) on the University of North Dakota Citation aircraft provided in situ measurements of the cloud microphysical properties. During the IOP, four low-level stratus cases were intensively observed by the ground- and satellite-based remote sensors and aircraft in situ instruments resulting in a total of 10 h of simultaneous data from the three platforms. In spite of the large differences in temporal and spatial resolution between surface, GOES, and aircraft, the surface retrievals have excellent agreement with the aircraft data overall for the entire 10-h period, and the GOES results agree reasonably well with the surface and aircraft data and have similar trends and magnitudes except for the GOES-derived effective radii, which are typically larger than the surface- and aircraft-derived values. The means and standard deviations of the differences between the surface and aircraft effective radius, LWP, and optical depth are 24% 6 20.1%, 21% 6 31.2%, and 8% 6 29.3%, respectively; while their correlation coefficients are 0.78, 0.92, and 0.89, respectively, during the 10-h period. The differences and correlations between the GOES-8 and aircraft results are of a similar magnitude, except for the droplet sizes. The averaged GOES-derived effective radius is 23% or 1.8 mm greater than the corresponding aircraft values, resulting in a much smaller correlation coefficient of 0.18. Additional surface‐satellite datasets were analyzed for time periods when the aircraft was unavailable. When these additional results are combined with the retrievals from the four in situ cases, the means and standard deviations of the differences between the satellite-derived cloud droplet effective radius, LWP, and optical depth and their surface-based counterparts are 16% 6 31.2%, 4% 6 31.6%, and 26% 6 39.9%, respectively. The corresponding correlation coefficients are 0.24, 0.88, and 0.73. The frequency distributions of the two datasets are very similar indicating that the satellite retrieval method should be able to produce reliable statistics of boundary layer cloud properties for use in climate and cloud process models.


IEEE Transactions on Geoscience and Remote Sensing | 2011

CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part II: Examples of Average Results and Comparisons With Other Data

Patrick Minnis; Szedung Sun-Mack; Yan Chen; M. M. Khaiyer; Yuhong Yi; J. K. Ayers; Ricky R. Brown; Xiquan Dong; Sharon Gibson; P. W. Heck; Bing Lin; Michele L. Nordeen; Louis Nguyen; Rabindra Palikonda; William L. Smith; Douglas A. Spangenberg; Qing Z. Trepte; Baike Xi

Cloud properties were retrieved by applying the Clouds and Earths Radiant Energy System (CERES) project Edition-2 algorithms to 3.5 years of Tropical Rainfall Measuring Mission Visible and Infrared Scanner data and 5.5 and 8 years of MODerate Resolution Imaging Spectroradiometer (MODIS) data from Aqua and Terra, respectively. The cloud products are consistent quantitatively from all three imagers; the greatest discrepancies occur over ice-covered surfaces. The retrieved cloud cover (~59%) is divided equally between liquid and ice clouds. Global mean cloud effective heights, optical depth, effective particle sizes, and water paths are 2.5 km, 9.9, 12.9 μm , and 80 g·m-2, respectively, for liquid clouds and 8.3 km, 12.7, 52.2 μm, and 230 g·m-2 for ice clouds. Cloud droplet effective radius is greater over ocean than land and has a pronounced seasonal cycle over southern oceans. Comparisons with independent measurements from surface sites, the Ice Cloud and Land Elevation Satellite, and the Aqua Advanced Microwave Scanning Radiometer-Earth Observing System are used to evaluate the results. The mean CERES and MODIS Atmosphere Science Team cloud properties have many similarities but exhibit large discrepancies in certain parameters due to differences in the algorithms and the number of unretrieved cloud pixels. Problem areas in the CERES algorithms are identified and discussed.


Journal of Geophysical Research | 1997

Microphysical and radiative properties of boundary layer stratiform clouds deduced from ground‐based measurements

Xiquan Dong; Thomas P. Ackerman; Eugene E. Clothiaux; Peter Pilewskie; Yong Han

Two methods for retrieving the microphysical and radiative properties of marine and continental boundary layer stratiform clouds from ground-based measurements are implemented. The first method uses measurements of the cloud liquid water path and the cloud nadir radiance at 1 μm to infer the cloud optical depth, cloud droplet effective radius, and cloud droplet concentration. In the second method a <52-stream radiative transfer model is used to retrieve the microphysical and radiative properties of stratiform clouds from measurements of the cloud liquid water path, the cloud geometric thickness, the downward shortwave irradiance at the surface, and atmospheric profiles of temperature, pressure, and relative humidity. In all of the retrievals the cloud droplets are assumed to have a lognormal size distribution with a logarithmic width of 0.35; the cloud droplet modal radius and cloud droplet concentration are free parameters. Data obtained in the Azores and Oklahoma from marine and continental boundary layer stratiform clouds, respectively, are used in the study. Results of the analysis demonstrated that the retrieved cloud droplet effective radii from the marine clouds (13 μm) were generally larger than the values from continental clouds (7 μm), while cloud droplet number concentrations were much less in marine clouds (150 cm−3) than in continental clouds (500 cm−3). The retrieved cloud droplet effective radius had a strong negative correlation with the cloud droplet concentration. The effects of uncertainties in the measurements, the cloud droplet distribution width, and the surface albedo on the retrieved properties were evaluated by using the 52-stream model. The errors in the retrieved cloud radiative properties were generally less than 5%, while the errors in the retrieved cloud microphysical properties were considerably larger.


Journal of Climate | 2003

Arctic Stratus Cloud Properties and Radiative Forcing Derived from Ground-Based Data Collected at Barrow, Alaska

Xiquan Dong; Gerald G. Mace

Abstract A record of single-layer and overcast low-level Arctic stratus cloud properties has been generated using data collected from May to September 2000 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) (71.3°N, 156.6°W) site near Barrow, Alaska. The record includes liquid-phase and liquid dominant mixed-phase Arctic stratus macrophysical, microphysical, and radiative properties, as well as surface radiation budget and cloud radiative forcing. The macrophysical properties consist of cloud fractions, cloud-base/top heights and temperatures, and cloud thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding. The microphysical properties include cloud liquid water path and content, and cloud-droplet effective radius and number concentration obtained from microwave radiometer brightness temperature measurements, and the new cloud parameterization. The radiative properties contain cloud optical depth, effective solar transmission, and surface/cloud/top-of-...


Journal of Climate | 2011

A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data

Aaron Kennedy; Xiquan Dong; Baike Xi; Shaocheng Xie; Yunyan Zhang; Junye Chen

AbstractAtmospheric states from the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the North American Regional Reanalysis (NARR) are compared with data from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site, including the ARM continuous forcing product and Cloud Modeling Best Estimate (CMBE) soundings, during the period 1999–2001 to understand their validity for single-column model (SCM) and cloud-resolving model (CRM) forcing datasets. Cloud fraction, precipitation, and radiation information are also compared to determine what errors exist within these reanalyses. For the atmospheric state, ARM continuous forcing and the reanalyses have good agreement with the CMBE sounding information, with biases generally within 0.5 K for temperature, 0.5 m s−1 for wind, and 5% for relative humidity. Larger disagreements occur in the upper troposphere (p 800 hPa) for meri...


Journal of Climate | 2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II: Cloud Fraction and Surface Radiative Forcing

Xiquan Dong; Baike Xi; Patrick Minnis

Abstract Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0–3 km), middle (3–6 km), and high clouds (>6 km) using ARM SCF ground-based paired lidar–radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of ∼10 W m−2. The annual averages of total and single-layered low-, middle-, and high-cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total- and low-cloud amounts peak during January and February and reach a minimum during July and August; high clouds occur more frequently than other types of clouds with a peak in summer. The average annual ...


Journal of Atmospheric and Oceanic Technology | 2003

Profiles of Low-Level Stratus Cloud Microphysics Deduced from Ground-Based Measurements

Xiquan Dong; Gerald G. Mace

The microwave radiometer‐derived cloud liquid water path (LWP) and a profile of radar reflectivity are used to derive a profile of cloud liquid water content (LWC). Two methods (M1 and M2) have been developed for inferring the profile of cloud-droplet effective radius (re) in liquid phase or liquid dominant mixed phase stratocumulus clouds. The M1-inferred re profile is proportional to a previously derived layer-mean re and to the ratio of the radar reflectivity to the integrated radar reflectivity. This algorithm is independent of the radar calibration and is applicable to overcast low-level stratus clouds that occur during the day because it is dependent on solar transmission observations. In order to extend the retrieval algorithm to a wider range of conditions, a second method is described that uses an empirical relationship between effective radius and radar reflectivity based on theory and the results of M1. Sensitivity studies show that the surface-retrieved re is more sensitive to the variation of radar reflectivity when the radar reflectivity is large, and the uncertainties of retrieved re related to the assumed vertically constant cloud-droplet number concentration and shape of the size distribution are about 9% and 2%, respectively. For validation, a total of 10 h of aircraft data and 36 h of surface data were collected over the Atmospheric Radiation Measurement (ARM) program’s Southern Great Plains (SGP) site during the March 2000 cloud intensive observational period (IOP). More detailed comparisons in two cases quantify the agreement between the aircraft data and the surface retrievals. When the temporal averages of the two datasets increase from 1 min to 30 min, the means and standard deviations of differences between the two datasets decrease from 22.5% 6 84% to 1.3% 6 42.6% and their corresponding correlation coefficients increase from 0.47 to 0.8 for LWC; and decrease from 24.8% 6 36.4% to 23.3% 6 22.5% with increased coefficients from 0.64 to 0.94 for re (both M1 and M2). The agreement between the aircraft and surface data in the 30-min averages suggests that the two platforms are capable of characterizing the cloud microphysics over this temporal scale. On average, the surface retrievals are unbiased relative to the aircraft in situ measurements. However, when only the 1-min averaged aircraft data within 3 km of the surface site were selected, the means and standard deviations of differences between the two datasets are larger (23.4% 6 113% for LWC and 28.3% 6 60.7% for re) and their correlation coefficients are smaller (0.32 for LWC and 0.3 for re) than those from all 1-min samples. This result suggests that restricting the comparison to the samples better matched in space and time between the surface and aircraft data does not result in a better comparison.


Journal of Climate | 2005

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility: Part I: Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties

Xiquan Dong; Patrick Minnis; Baike Xi

Abstract A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 h of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant mixed-phase low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (re) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (τ), effective solar transmission (γ), and cloud/top-of-atmosphere albedos (Rcldy/RTOA) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations...


Journal of Geophysical Research | 2000

A 25-month database of stratus cloud properties generated from ground-based measurements at the Atmospheric Radiation Measurement Southern Great Plains Site

Xiquan Dong; Patrick Minnis; Thomas P. Ackerman; Eugene E. Clothiaux; Gerald G. Mace; Charles N. Long; James C. Liljegren

A 25-month database of the macrophysical, microphysical, and radiative properties of isolated and overcast low-level stratus clouds has been generated using a newly developed parameterization and surface measurements from the Atmospheric Radiation Measurement central facility in Oklahoma. The database (5-min resolution) includes two parts: measurements and retrievals. The former consist of cloud base and top heights, layer-mean temperature, cloud liquid water path, and solar transmission ratio measured by a ground-based lidar/ceilometer and radar pair, radiosondes, a microwave radiometer, and a standard Eppley precision spectral pyranometer, respectively. The retrievals include the cloud-droplet effective radius and number concentration and broadband shortwave optical depth and cloud and top-of-atmosphere albedos. Stratus without any overlying mid or high-level clouds occurred most frequently during winter and least often during summer. Mean cloud-layer altitudes and geometric thicknesses were higher and greater, respectively, in summer than in winter. Both quantities are positively correlated with the cloud-layer mean temperature. Mean cloud-droplet effective radii range from 8.1 μm in winter to 9.7 μm during summer, while cloud-droplet number concentrations during winter are nearly twice those in summer. Since cloud liquid water paths are almost the same in both seasons, cloud optical depth is higher during the winter, leading to greater cloud albedos and lower cloud transmittances.

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Baike Xi

University of North Dakota

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Aaron Kennedy

University of North Dakota

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Sunny Sun-Mack

Science Applications International Corporation

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Zhe Feng

Pacific Northwest National Laboratory

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Jingyu Wang

University of North Dakota

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Erica K. Dolinar

University of North Dakota

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Ryan E. Stanfield

University of North Dakota

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