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Yong Han and E. R. Westwater

Abstract

A technique is presented for deriving tropospheric water vapor and cloud liquid water, as well as temperature, from a suite of ground-based sensors. Included in the suite are a dual-channel microwave radiometer, a ceilometer, a radio acoustic sounding system (RASS), and conventional surface meteorological instruments. A linear statistical inversion algorithm, combined with a data classification technique, is applied to retrieve water vapor and cloud liquid water profiles. The linear statistical inversion algorithm is also applied to derive temperature profiles from RASS virtual temperature measurements and surface meteorological parameters. A physical retrieval algorithm is then applied to retrieve integrated water vapor and liquid water. Finally, these two algorithms are coupled in a two-step iteration process. The technique is evaluated by comparing retrieved quantities with radiosonde measurements and by comparing this technique with the traditional technique based solely on dual-channel microwave radiometric measurements. Significant improvement is achieved in retrieving dominant structures in the water vapor profile when liquid clouds are present. This evaluation also predicts significant improvement in measuring integrated liquid water, but lack of ground truth prevented experimental verification.

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Yong Han and Dennis W. Thomson

Abstract

To estimate mesoscale variations in integrated water vapor, cloud liquid water, and temperature in a tropical region, multiwavelength microwave radiometric observations were carried out over a seven-week period on the island of Saipan during the 1990 Tropical Cyclone Motion Experiment. Methods to combine radiometric and ceilometer measurements were developed to improve both the retrieval accuracies of integrated water vapor and liquid water. The rms difference between the retrieved and radiosonde-measured integrated water vapor was 6% relative to the mean. Compared to radiosondes the temperature profiles retrieved using a linear statistical inversion technique were accurate to 1.28°C. However, since the radiometric temperature profiles were no more accurate than profiles obtained from climatology, the surface-based radiometer provided essentially no new information regarding the environmental temperature profiles.

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Yong Chen, Yong Han, Paul van Delst, and Fuzhong Weng

Abstract

The nadir-viewing satellite radiances at shortwave infrared channels from 3.5 to 4.6 μm are not currently assimilated in operational numerical weather prediction data assimilation systems and are not adequately corrected for applications of temperature retrieval at daytime. For satellite observations over the ocean during the daytime, the radiance in the surface-sensitive shortwave infrared is strongly affected by the reflected solar radiance, which can contribute as much as 20.0 K to the measured brightness temperatures (BT). The nonlocal thermodynamic equilibrium (NLTE) emission in the 4.3-μm CO2 band can add a further 10 K to the measured BT. In this study, a bidirectional reflectance distribution function (BRDF) is developed for the ocean surface and an NLTE radiance correction scheme is investigated for the hyperspectral sensors. Both effects are implemented in the Community Radiative Transfer Model (CRTM). The biases of CRTM simulations to Infrared Atmospheric Sounding Interferometer (IASI) observations and the standard deviations of the biases are greatly improved during daytime (about a 1.5-K bias for NLTE channels and a 0.3-K bias for surface-sensitive shortwave channels) and are very close to the values obtained during the night. These improved capabilities in CRTM allow for effective uses of satellite data at short infrared wavelengths in data assimilation systems and in atmospheric soundings throughout the day and night.

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Yong Chen, Fuzhong Weng, Yong Han, and Quanhua Liu

Abstract

The line-by-line radiative transfer model (LBLRTM) is used to derive the channel transmittances. The channel transmittance from a level to the top of the atmosphere can be approximated by three methods: Planck-weighted transmittance 1 (PW1), Planck-weighted transmittance 2 (PW2), and non-Planck-weighted transmittance (ORD). The PW1 method accounts for a radiance variation across the instrument’s spectral response function (SRF) and the Planck function is calculated with atmospheric layer temperature, whereas the PW2 method accounts for the variation based on the temperatures at the interface between atmospheric layers. For channels with broad SRFs, the brightness temperatures (BTs) derived from the ORD are less accurate than these from either PW1 or PW2. Furthermore, the BTs from PW1 are more accurate than these from PW2, and the BT differences between PW1 and PW2 increase with atmospheric optical thickness.

When the band correction is larger than 1, the PW1 method should be used to account for the Planck radiance variation across the instrument’s SRF. When considering the solar contribution in daytime, the correction of the solar reflection has been made for near-infrared broadband channels (~3.7 μm) when using PW1 transmittance. The solar transmittance is predicted by using explanatory variables, such as PW1 transmittance, the secant of zenith angle, and the surface temperature. With this correction, the errors can be significantly reduced.

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Ge Chen, Jun Ma, Chaoyang Fang, and Yong Han

Abstract

A detailed study on global oceanic precipitation is carried out using the simultaneous TOPEX and TMR (TOPEX Microwave Radiometer) data. It is motivated by the success of a series of feasibility studies based on a few years of TOPEX–TMR data, and the availability of a decade-long new dataset that spans 1992–2002. In this context, a previously proposed rain probability index is improved by taking into account the difference of the dynamic range of the TOPEX-measured backscatter coefficients at the Ku and C bands and the latitudinally complementary sensitivities of the TOPEX and TMR rain detections, leading to a refined joint precipitation index, which is generally consistent and quantitatively comparable with existing precipitation climatologies from the Global Precipitation Climatology Project (GPCP) and the Comprehensive Ocean–Atmosphere Data Set (COADS). The new TOPEX–TMR precipitation climatology, on the one hand, confirms the fundamental features of global oceanic rainfall with additional details, and, on the other hand, reveals a number of interesting characteristics that are previously unknown or poorly defined. 1) The spatial variability of the western Pacific “rain pool” (the atmospheric counterpart of the oceanic warm pool) is characterized by an interannual zonal migration, an annual cycle of meridional seesaw, and a semiannual cycle of expansion and shrinking. 2) The Pacific, Atlantic, and Indian Ocean intertropical convergence zones (ITCZs) all have an annual cycle of cross-basin oscillation with east and west stops in JJA and DJF, respectively. 3) A well-defined prominent rainy zone is observed in the southeast China Seas around Taiwan Island, connecting with the Pacific rain pool in the south. 4) Between El Niño and La Niña years, there is a systematic sign reversal of the geographical distribution of precipitation anomaly, which exists globally rather than in the tropical oceans only. 5) On a global basis, interannual and annual precipitation variabilities are of the same magnitude, but the interannual (annual) component is more important for the Southern (Northern) Hemisphere. 6) For the tropical oceans, “season” defined by rainfall usually has a one-quarter delay with respect to the corresponding meteorological season. For the “marine deserts” in the subtropical oceans, however, the rain-based season is found to be anticorrelated with the meteorological season. In addition, the annual cycle of the Atlantic precipitation is nearly 180° out of phase with respect to that of the Pacific and Indian Ocean for the same hemisphere.

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Quanhua Liu, Xingming Liang, Yong Han, Paul van Delst, Yong Chen, Alexander Ignatov, and Fuzhong Weng

Abstract

The Community Radiative Transfer Model (CRTM) developed at the Joint Center for Satellite Data Assimilation (JCSDA) is used in conjunction with a daily sea surface temperature (SST) and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) atmospheric data and surface wind to calculate clear-sky top-of-atmosphere (TOA) brightness temperatures (BTs) in three Advanced Very High Resolution Radiometer (AVHRR) thermal infrared channels over global oceans. CRTM calculations are routinely performed by the sea surface temperature team for four AVHRR instruments on board the National Oceanic and Atmospheric Administration (NOAA) satellites NOAA-16, NOAA-17, and NOAA-18 and the Meteorological Operation (MetOp) satellite MetOp-A, and they are compared with clear-sky TOA BTs produced by the operational AVHRR Clear-Sky Processor for Oceans (ACSPO). It was observed that the model minus observation (M−O) bias in the NOAA-16 AVHRR channel 3b (Ch3b) centered at 3.7 μm experienced a discontinuity of ∼0.3 K when a new CRTM version 1.1 (v.1.1) was implemented in ACSPO processing in September 2008. No anomalies occurred in any other AVHRR channel or for any other platform. This study shows that this discontinuity is caused by the out-of-band response in NOAA-16 AVHRR Ch3b and by using a single layer to the NCEP GFS temperature profiles above 10 hPa for the alpha version of CRTM. The problem has been solved in CRTM v.1.1, which uses one of the six standard atmospheres to fill in the missing data above the top pressure level in the input NCEP GFS data. It is found that, because of the out-of-band response, the NOAA-16 AVHRR Ch3b has sensitivity to atmospheric temperature at high altitudes. This analysis also helped to resolve another anomaly in the absorption bands of the High Resolution Infrared Radiation Sounder (HIRS) sensor, whose radiances and Jacobians were affected to a much greater extent by this CRTM inconsistency.

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Yong Chen, Yong Han, Quanhua Liu, Paul Van Delst, and Fuzhong Weng

Abstract

To better use the Stratospheric Sounding Unit (SSU) data for reanalysis and climate studies, issues associated with the fast radiative transfer (RT) model for SSU have recently been revisited and the results have been implemented into the Community Radiative Transfer Model version 2. This study revealed that the spectral resolution for the sensor’s spectral response functions (SRFs) calculations is very important, especially for channel 3. A low spectral resolution SRF results, on average, in 0.6-K brightness temperature (BT) errors for that channel. The variations of the SRFs due to the CO2 cell pressure variations have been taken into account. The atmospheric transmittance coefficients of the fast RT model for the Television and Infrared Observation Satellite (TIROS)-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-11, and NOAA-14 have been generated with CO2 and O3 as variable gases. It is shown that the BT difference between the fast RT model and line-by-line model is less than 0.1 K, but the fast RT model is at least two orders of magnitude faster. The SSU measurements agree well with the simulations that are based on the atmospheric profiles from the Earth Observing System Aura Microwave Limb Sounding product and the Sounding of the Atmosphere using Broadband Emission Radiometry on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. The impact of the CO2 cell pressures shift for SSU has been evaluated by using the Committee on Space Research (COSPAR) International Reference Atmosphere (CIRA) model profiles. It is shown that the impacts can be on an order of 1 K, especially for SSU NOAA-7 channel 2. There are large brightness temperature gaps between observation and model simulation using the available cell pressures for NOAA-7 channel 2 after June 1983. Linear fittings of this channel’s cell pressures based on previous cell leaking behaviors have been studied, and results show that the new cell pressures are reasonable. The improved SSU fast model can be applied for reanalysis of the observations. It can also be used to address two important corrections in deriving trends from SSU measurements: CO2 cell leaking correction and atmospheric CO2 concentration correction.

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Yong Han, Yiwen Zhou, Jianping Guo, Yonghua Wu, Tijian Wang, Bingliang Zhuang, and Mengmeng Li

Abstract

The planetary boundary layer (PBL) controls the exchange of momentum and energy between the ground surface and the free troposphere, but few studies have been involved in the connection of the PBL with the development and extinction of tropical cyclones (TCs). Studies on the PBL usually need high-resolution soundings in the lowest troposphere that are otherwise quite rare with traditional technology. Here, 1-s resolution L-band radiosonde data are acquired to study the variations in PBL characteristics associated with the development of TCs in eastern China. The strong variations in the vertical profiles of temperature, relative humidity, and wind speed in the PBL during the landfall of a TC are revealed. In addition, four typical methods, including the virtual potential temperature method, Holzworth method, bulk Richardson number method, and potential temperature gradient method, are applied to estimate the PBL height (PBLH). The results indicate that the PBLHs derived by these methods vary by several hundred meters, which may be related to their different definitions of kinetic or thermodynamic theories. Furthermore, the PBLH was found to display a slight upward tendency during the landfall of TC.

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Yong Hyun Kim, Sungshin Kim, Hye-Young Han, Bok-Haeng Heo, and Cheol-Hwan You

Abstract

In countries with frequent aerial military exercises, chaff particles that are routinely spread by military aircraft represent significant noise sources for ground-based weather radar observation. In this study, a cost-effective procedure is proposed for identifying and removing chaff echoes from single-polarization Doppler radar readings in order to enhance the reliability of observed meteorological data. The proposed quality control procedure is based on three steps: 1) spatial and temporal clustering of decomposed radar image elements, 2) extraction of the clusters’ static and time-evolution characteristics, and 3) real-time identification and removal (or censoring) of target echoes from radar data. Simulation experiments based on this procedure were conducted on site-specific ground-echo-removed weather radar data provided by the Korea Meteorological Administration (KMA), from which three-dimensional (3D) reflectivity echoes covering hundreds of thousands of square kilometers of South Korean territory within an altitude range of 0.25–10 km were retrieved. The algorithm identified and removed chaff clutter from the South Korean data with a novel decision support system at an 81% accuracy level under typical cases in which chaff and weather clusters were isolated from one another with no overlapping areas.

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Edgeworth R. Westwater, B. Boba Stankov, Domenico Cimini, Yong Han, Joseph A. Shaw, Barry M. Lesht, and Carles N. Long

Abstract

During June–July 1999, the NOAA R/V Ron H. Brown (RHB) sailed from Australia to the Republic of Nauru where the Department of Energy's Atmospheric Radiation Measurement (ARM) Program operates a long-term climate observing station. During July, when the RHB was in close proximity to the island of Nauru, detailed comparisons of ship- and island-based instruments were possible. Essentially identical instruments were operated from the ship and the island's Atmospheric Radiation and Cloud Station (ARCS)-2. These instruments included simultaneously launched Vaisala RS80-H radiosondes, the Environmental Technology Laboratory's (ETL) Fourier transform infrared radiometer (FTIR), and ARM's atmospheric emitted radiance interferometer (AERI), as well as cloud radars/ceilometers to identify clear conditions.

The ARM microwave radiometer (MWR) operating on Nauru provided another excellent dataset for the entire Nauru99 experiment. The calibration accuracy was verified by a liquid nitrogen blackbody target experiment and by consistent high quality tipping calibrations throughout the experiment. Comparisons were made for calculated clear-sky brightness temperature (T b) and for precipitable water vapor (PWV). These results indicate that substantial errors, sometimes of the order of 20% in PWV, occurred with the original radiosondes. When a Vaisala correction algorithm was applied, calculated T bs were in better agreement with the MWR than were the calculations based on the original data. However, the improvement in T b comparisons was noticeably different for different radiosonde lots and was not a monotonic function of radiosonde age. Three different absorption algorithms were compared: Liebe and Layton, Liebe et al., and Rosenkranz. Using AERI spectral radiance observations as a comparison standard, scaling of radiosondes by MWR data was compared with both original and corrected soundings.

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