Search Results

You are looking at 1 - 10 of 15 items for :

  • Author or Editor: F. K. Li x
  • Refine by Access: All Content x
Clear All Modify Search
F. Li
,
W. Large
,
W. Shaw
,
K. Davidson
, and
E. J. Walsh

Abstract

A case study of ocean radar backscatter dependence on near-surface wind and wind stress is presented using the data obtained on 18 February 1986 during the Frontal Air-Sea Interaction Experiment. Our interest in this case stems from the particular wind-wave conditions and their variations across a sharp sea surface temperature front. These are described. Most importantly, the small change in wind speed across the front cannot account for the large change in wind stress implying significant changes in the drag coefficient and surface roughness length. When compared with previous results, the corresponding changes in radar backscatter cross-section at 50° and 20° angles of incidence were consistent with the observed variations in wind stress, but inconsistent with both the mean wind and the equivalent neutral wind. Although not definitive, the results strengthen the hypothesis that radar backscatter is closely correlated to wind stress, and therefore, could be used for remote sensing of the wind stress itself over the global oceans.

Full access
S. L. Durden
,
E. Im
,
F. K. Li
,
W. Ricketts
,
A. Tanner
, and
W. Wilson

Abstract

A new airborne rain-mapping radar (ARMAR) has been developed by NASA and the Jet Propulsion Laboratory for operation on the NASA Ames DC-8 aircraft. The radar operates at 13.8 GHz, the frequency to be used by the radar on the Tropical Rainfall Measuring Mission (TRMM). ARMAR simulates the TRMM radar geometry by looking downward and scanning its antenna in the cross-track direction. This basic compatibility between ARMAR and TRMM allows ARMAR to provide information useful for the TRMM radar design, for rain retrieval algorithm development, and for postlaunch calibration. ARMAR has additional capabilities, including multiple polarization, Doppler velocity measurement, and a radiometer channel for brightness temperature measurement. The system has been tested in both ground-based and airborne configurations. This paper describes the design of the system and shows results of field tests.

Full access
S. L. Durden
,
Z. S. Haddad
,
A. Kitiyakara
, and
F. K. Li

Abstract

The Tropical Rainfall Measuring Mission (TRMM) will carry the first spaceborne radar for rainfall observation. Because the TRMM Precipitation Radar (PR) footprint size of 4.3 km is greater than the scale of some convective rainfall events, there is concern that nonuniform filling of the PR antenna beam may bias the retrieved rain-rate profile. The authors investigate this effect theoretically and then observationally using data from the NASA Jet Propulsion Laboratory Airborne Rain Mapping Radar (ARMAR), acquired during Tropical Oceans Global Atmosphere Coupled Ocean–Atmosphere Response Experiment in early 1993. The authors’ observational approach is to simulate TRMM PR data using the ARMAR data and compare the radar observables and retrieved rain rate from the simulated PR data with those corresponding to the high-resolution radar measurements. The authors find that the path-integrated attenuation and the resulting path-averaged rain rate are underestimated. The reflectivity and rain rate near the top of the rainfall column are overestimated. The near-surface reflectivity can be overestimated or underestimated, with a mean error very close to zero. The near-surface rain rate, however, is usually underestimated, sometimes severely.

Full access
Zhijun Huang
,
Huan Wu
,
Guojun Gu
,
Xiaomeng Li
,
Nergui Nanding
,
Robert F. Adler
,
Koray K. Yilmaz
,
Lorenzo Alfieri
, and
Sirong Chen

Abstract

Precipitation data are known to be the key driver of hydrological simulations. Hence, reliable quantitative precipitation estimates and forecasts are vital for accurate hydrological forecasting. Satellite-based precipitation estimates from Integrated Multi-satellitE Retrievals for GPM Early Run (IMERG-E) and forecasted precipitation from NASA’s Goddard Earth Observing System Forward Processing (GEOS-FP) have shown values in global flood nowcasting and forecasting. However, few studies have comprehensively evaluated their hydrological performance let alone explored the potential value of combining them. Therefore, this study undertakes a quasi-global evaluation of their utility in real-time hydrological monitoring and 1–5-day forecasting with the Dominant River Tracing-Routing Integrated with Variable Infiltration Capacity (VIC) Environment (DRIVE) model. The gauge-corrected IMERG Final Run precipitation estimates and corresponding hydrological simulation are used as the references. Results showed that the hit bias is the dominant error source of IMERG-E, while the false precipitation is more noticeable in GEOS-FP. In terms of hydrological performance, the GEOS-FP-driven model (DRIVE-FP) performance is close to the IMERG-E-driven model (DRIVE-E) performance on day 1, indicating that GEOS-FP could nicely fill the gap of nowcasting caused by the IMERG-E time latency. For longer lead-time forecasts, the bias tends to diminish in most regions, likely because the under- or overestimation in IMERG-E is generally offset by the distinct types of misestimation in GEOS-FP. The skillful initial hydrological conditions present outperformed forecasts in most regions, except for tropical areas where the accuracy of GEOS-FP prevails. Overall, this study provides a valuable view of the combined use of IMERG-E and GEOS-FP precipitation in the context of hydrological nowcasts and forecasts.

Restricted access
Z. Q. Li
,
H. Xu
,
K. T. Li
,
D. H. Li
,
Y. S. Xie
,
L. Li
,
Y. Zhang
,
X. F. Gu
,
W. Zhao
,
Q. J. Tian
,
R. R. Deng
,
X. L. Su
,
B. Huang
,
Y. L. Qiao
,
W. Y. Cui
,
Y. Hu
,
C. L. Gong
,
Y. Q. Wang
,
X. F. Wang
,
J. P. Wang
,
W. B. Du
,
Z. Q. Pan
,
Z. Z. Li
, and
D. Bu

Abstract

An overview of Sun–Sky Radiometer Observation Network (SONET) measurements in China is presented. Based on observations at 16 distributed SONET sites in China, atmospheric aerosol parameters are acquired via standardization processes of operational measurement, maintenance, calibration, inversion, and quality control implemented since 2010. A climatology study is performed focusing on total columnar atmospheric aerosol characteristics, including optical (aerosol optical depth, ÅngstrÖm exponent, fine-mode fraction, single-scattering albedo), physical (volume particle size distribution), chemical composition (black carbon; brown carbon; fine-mode scattering component, coarse-mode component; and aerosol water), and radiative properties (aerosol radiative forcing and efficiency). Data analyses show that aerosol optical depth is low in the west but high in the east of China. Aerosol composition also shows significant spatial and temporal variations, leading to noticeable diversities in optical and physical property patterns. In west and north China, aerosols are generally affected by dust particles, while monsoon climate and human activities impose remarkable influences on aerosols in east and south China. Aerosols in China exhibit strong light-scattering capability and result in significant radiative cooling effects.

Full access
Michael F. Jasinski
,
Jordan S. Borak
,
Sujay V. Kumar
,
David M. Mocko
,
Christa D. Peters-Lidard
,
Matthew Rodell
,
Hualan Rui
,
Hiroko K. Beaudoing
,
Bruce E. Vollmer
,
Kristi R. Arsenault
,
Bailing Li
,
John D. Bolten
, and
Natthachet Tangdamrongsub

Abstract

Terrestrial hydrologic trends over the conterminous United States are estimated for 1980–2015 using the National Climate Assessment Land Data Assimilation System (NCA-LDAS) reanalysis. NCA-LDAS employs the uncoupled Noah version 3.3 land surface model at 0.125° × 0.125° forced with NLDAS-2 meteorology, rescaled Climate Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth, and irrigation products. Mean annual trends are reported using the nonparametric Mann–Kendall test at p < 0.1 significance. Results illustrate the interrelationship between regional gradients in forcing trends and trends in other land energy and water stores and fluxes. Mean precipitation trends range from +3 to +9 mm yr−1 in the upper Great Plains and Northeast to −1 to −9 mm yr−1 in the West and South, net radiation flux trends range from +0.05 to +0.20 W m−2 yr−1 in the East to −0.05 to −0.20 W m−2 yr−1 in the West, and U.S.-wide temperature trends average about +0.03 K yr−1. Trends in soil moisture, snow cover, latent and sensible heat fluxes, and runoff are consistent with forcings, contributing to increasing evaporative fraction trends from west to east. Evaluation of NCA-LDAS trends compared to independent data indicates mixed results. The RMSE of U.S.-wide trends in number of snow cover days improved from 3.13 to 2.89 days yr−1 while trend detection increased 11%. Trends in latent heat flux were hardly affected, with RMSE decreasing only from 0.17 to 0.16 W m−2 yr−1, while trend detection increased 2%. NCA-LDAS runoff trends degraded significantly from 2.6 to 16.1 mm yr−1 while trend detection was unaffected. Analysis also indicated that NCA-LDAS exhibits relatively more skill in low precipitation station density areas, suggesting there are limits to the effectiveness of satellite data assimilation in densely gauged regions. Overall, NCA-LDAS demonstrates capability for quantifying physically consistent, U.S. hydrologic climate trends over the satellite era.

Open access
Sid-Ahmed Boukabara
,
Isaac Moradi
,
Robert Atlas
,
Sean P. F. Casey
,
Lidia Cucurull
,
Ross N. Hoffman
,
Kayo Ide
,
V. Krishna Kumar
,
Ruifang Li
,
Zhenglong Li
,
Michiko Masutani
,
Narges Shahroudi
,
Jack Woollen
, and
Yan Zhou

Abstract

A modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.

Full access
D. A. Knopf
,
K. R. Barry
,
T. A. Brubaker
,
L. G. Jahl
,
K. A. Jankowski
,
J. Li
,
Y. Lu
,
L. W. Monroe
,
K. A. Moore
,
F. A. Rivera-Adorno
,
K. A. Sauceda
,
Y. Shi
,
J. M. Tomlin
,
H. S. K. Vepuri
,
P. Wang
,
N. N. Lata
,
E. J. T. Levin
,
J. M. Creamean
,
T. C. J. Hill
,
S. China
,
P. A. Alpert
,
R. C. Moffet
,
N. Hiranuma
,
R. C. Sullivan
,
A. M. Fridlind
,
M. West
,
N. Riemer
,
A. Laskin
,
P. J. DeMott
, and
X. Liu

Abstract

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

Full access
Gerhard Theurich
,
C. DeLuca
,
T. Campbell
,
F. Liu
,
K. Saint
,
M. Vertenstein
,
J. Chen
,
R. Oehmke
,
J. Doyle
,
T. Whitcomb
,
A. Wallcraft
,
M. Iredell
,
T. Black
,
A. M. Da Silva
,
T. Clune
,
R. Ferraro
,
P. Li
,
M. Kelley
,
I. Aleinov
,
V. Balaji
,
N. Zadeh
,
R. Jacob
,
B. Kirtman
,
F. Giraldo
,
D. McCarren
,
S. Sandgathe
,
S. Peckham
, and
R. Dunlap IV

Abstract

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users.

The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.

Full access
H. W. Barker
,
G. L. Stephens
,
P. T. Partain
,
J. W. Bergman
,
B. Bonnel
,
K. Campana
,
E. E. Clothiaux
,
S. Clough
,
S. Cusack
,
J. Delamere
,
J. Edwards
,
K. F. Evans
,
Y. Fouquart
,
S. Freidenreich
,
V. Galin
,
Y. Hou
,
S. Kato
,
J. Li
,
E. Mlawer
,
J.-J. Morcrette
,
W. O'Hirok
,
P. Räisänen
,
V. Ramaswamy
,
B. Ritter
,
E. Rozanov
,
M. Schlesinger
,
K. Shibata
,
P. Sporyshev
,
Z. Sun
,
M. Wendisch
,
N. Wood
, and
F. Yang

Abstract

The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended?

One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport algorithms, were submitted by 22 groups. Benchmark, domain-averaged irradiance profiles were computed by the MC codes. For the clear and overcast cases, all MC estimates of top-of-atmosphere albedo, atmospheric absorptance, and surface absorptance agree with one of the LBL codes to within ±2%. Most 1D codes underestimate atmospheric absorptance by typically 15–25 W m–2 at overhead sun for the standard tropical atmosphere regardless of clouds.

Depending on assumptions about unresolved clouds, the 1D codes were partitioned into four genres: (i) horizontal variability, (ii) exact overlap of PPH clouds, (iii) maximum/random overlap of PPH clouds, and (iv) random overlap of PPH clouds. A single MC code was used to establish conditional benchmarks applicable to each genre, and all MC codes were used to establish the full 3D benchmarks. There is a tendency for 1D codes to cluster near their respective conditional benchmarks, though intragenre variances typically exceed those for the clear and overcast cases. The majority of 1D codes fall into the extreme category of maximum/random overlap of PPH clouds and thus generally disagree with full 3D benchmark values. Given the fairly limited scope of these tests and the inability of any one code to perform extremely well for all cases begs the question that a paradigm shift is due for modeling 1D solar fluxes for cloudy atmospheres.

Full access