Search Results

You are looking at 1 - 4 of 4 items for :

  • Author or Editor: Yi Huang x
  • Journal of Atmospheric and Oceanic Technology x
  • Refine by Access: All Content x
Clear All Modify Search
Jing Feng
and
Yi Huang

Abstract

This study examines the feasibility of retrieving lower-stratospheric water vapor using a nadir infrared hyperspectrometer, with the focus on the detectability of small-scale water vapor variability. The feasibility of the retrieval is examined using simulation experiments that model different instrument settings. These experiments show that the infrared spectra, measured with sufficient spectral coverage, resolution, and noise level, contain considerable information content that can be used to retrieve lower-stratospheric water vapor. Interestingly, it is found that the presence of an opaque cloud layer at the tropopause level can substantially improve the retrieval performance, as it helps remove the degeneracy in the retrieval problem. Under this condition, elevated lower-stratospheric water vapor concentration—for instance, caused by convective moistening—can be detected with an accuracy of 0.09 g m−2 using improved spaceborne hyperspectrometers. The cloud-assisted retrieval is tested using the measurements of the Atmospheric Infrared Sounder (AIRS). Validation against collocated aircraft data shows that the retrieval can detect the elevated water vapor concentration caused by convective moistening.

Full access
Maziar Bani Shahabadi
and
Yi Huang

Abstract

This study examines the ability of an infrared spectral sensor flying at the tropopause level for retrieving stratospheric H2O. Synthetic downwelling radiance spectra simulated by the line-by-line radiative transfer model are used for this examination. The potential of high-sensitivity water vapor retrieval is demonstrated by an ideal sensor with low detector noise, high spectral resolution, and full infrared coverage. A suite of hypothetical sensors with varying specifications is then examined to determine the technological requirements for a satisfactory retrieval. This study finds that including far infrared in the sensor’s spectral coverage is essential for achieving accurate H2O retrieval with an accuracy of 0.4 ppmv (1-sigma). The uncertainties in other gas species such as CH4, N2O, O3, and CO2 do not significantly affect the H2O retrieval. Such a hyperspectral instrument may afford an advantageous tool, especially for detecting small-scale lower-stratospheric moistening events.

Full access
Yi Huang
,
Steven Siems
,
Michael Manton
,
Alain Protat
,
Leon Majewski
, and
Hanh Nguyen

Abstract

Cloud-top height (CTH) and cloud-top temperature (CTT) retrieved from the Himawari-8 observations are evaluated using the active shipborne radar–lidar observations derived from the 31-day Clouds, Aerosols, Precipitation Radiation and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment in 2016 and 1-yr observations from the spaceborne Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud product over a large sector of the Southern Ocean. The results show that the Himawari-8 CTH (CTT) retrievals agree reasonably well with both the shipborne estimates, with a correlation coefficient of 0.837 (0.820), a mean bias error of 0.226 km (−2.526°C), and an RMSE of 1.684 km (10.069°C). In the comparison with CALIOP, the corresponding quantities are found to be 0.786 (0.480), −0.570 km (1.343°C), and 2.297 km (25.176°C). The Himawari-8 CTH (CTT) generally falls between the physical CTHs observed by CALIOP and the shipborne radar–lidar estimates. However, major systematic biases are also identified. These errors include (i) a low (warm) bias in CTH (CTT) for warm liquid cloud type, (ii) a cold bias in CTT for supercooled liquid water cloud type, (iii) a lack of CTH at ~3 km that does not have a corresponding gap in CTT, (iv) a tendency of misclassifying some low-/mid-top clouds as cirrus and overlap cloud types, and (v) a saturation of CTH (CTT) around 10 km (−40°C), particularly for cirrus and overlap cloud types. Various challenges that underpin these biases are also explored, including the potential of parallax bias, low-level inversion, and cloud heterogeneity.

Full access
Vidhi Bharti
,
Eric Schulz
,
Christopher W. Fairall
,
Byron W. Blomquist
,
Yi Huang
,
Alain Protat
,
Steven T. Siems
, and
Michael J. Manton

Abstract

Given the large uncertainties in surface heat fluxes over the Southern Ocean, an assessment of fluxes obtained by European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) product, the Australian Integrated Marine Observing System (IMOS) routine observations, and the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project hybrid dataset is performed. The surface fluxes are calculated using the COARE 3.5 bulk algorithm with in situ data obtained from the NOAA Physical Sciences Division flux system during the Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment on board the R/V Investigator during a voyage (March–April 2016) in the Australian sector of the Southern Ocean (43°–53°S). ERA-Interim and OAFlux data are further compared with the Southern Ocean Flux Station (SOFS) air–sea flux moored surface float deployed for a year (March 2015–April 2016) at ~46.7°S, 142°E. The results indicate that ERA-Interim (3 hourly at 0.25°) and OAFlux (daily at 1°) estimate sensible heat flux H s accurately to within ±5 W m−2 and latent heat flux H l to within ±10 W m−2. ERA-Interim gives a positive bias in H s at low latitudes (<47°S) and in H l at high latitudes (>47°S), and OAFlux displays consistently positive bias in H l at all latitudes. No systematic bias with respect to wind or rain conditions was observed. Although some differences in the bulk flux algorithms are noted, these biases can be largely attributed to the uncertainties in the observations used to derive the flux products.

Full access