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Shi-Keng Yang and G. Louis Smith

Abstract

Lapse rate, moist adiabatic lapse rate and the critical lapse rate for baroclinic adjustment are calculated as was done by Stone and Carlson using a different data set covering both hemispheres. Results show very good agreement in low latitudes, where temperature lapse rate can be approximated by the moist adiabatic lapse rate. In midlatitudes of the Northern Hemisphere, the lapse rate agrees with the critical lapse rate for baroclinic adjustment. In midlatitudes of the Southern Hemisphere, the lapse rate follows the critical lapse rate for baroclinic adjustment with a 15° lag.

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Larry McMillin, Si-Song Zhou, and Shi-Keng Yang

Abstract

Cloud-top heights and cloud amounts are produced as part of the operational processing of polar-satellite data at the National Environmental Satellite Data and Information Service (NESDIS). These products were compared with similar products from the air force's real-time nephanalysis (RTNEPH), from the International Satellite Cloud Climatology Project, and from NASA Goddard's processing of satellite data. It was found that the amount of high-level cloud was too small in the NESDIS results, while the amount of low-level cloud was too large. An examination of the NESDIS algorithm revealed that the differences in cloud distributions were caused by the selection of channels used for the cloud retrievals. Cloud retrievals are most accurate at the levels at which the channels that are used are most sensitive. In addition, it was found that no one pair of channels was best at all levels. A new procedure was developed that varied the channels as a function of an initial estimate of the cloud height. This procedure produced improved cloud retrievals that were then compared with the RTNEPH results. The comparison showed that the two methods provide similar retrievals of cloud height and amount.

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Shi-Keng Yang, G. Louis Smith, and Fred L. Bartman

Abstract

An Earth outgoing longwave radiation (OLWR) climate model was constructed for radiation budget studies. The model consists of the upward radiative transfer parameterization of Thompson and Warren, the cloud cover model of Sherr et al., and a monthly average climatology defined by the data from Crutcher and Meserve, and Taljaard et al. The required water vapor climatology was developed by Yang et al. Cloud top temperature was adjusted so that the calculation agreed with NOAA scanning radiometer measurements. Cloudy sky cases were calculated and discussed for global average, zonal average and worldwide distributed cases. The results agreed well with the satellite observations.

Although the zonally averaged OLWR has a minimum in the tropics, this minimum is essentially contributed by a few very low flux regions. There are regions in the tropics where the OLWR is as large as that in the subtropics. Gradients of OLWR occur in the tropics that are as large as those from the tropics to the poles. In the high latitudes, where cold air contains less water vapor, OLWR is basically modulated by the surface temperature. Thus, the topographical heat capacity becomes a dominant factor in determining the seasonal variation. The two very different regimes of OLWR can be easily identified using the time history of the zonal average OLWR.

Clouds enhance the water vapor modulation of OLWR. Tropical clouds have very cold cloud top temperatures, which increases the longitudinal variation in the region. However, in the polar region, where temperature inversion is prominent, cloud top temperature is warmer than surface temperature. Hence, clouds have the effect of increasing OLWR. The implications of this are that the latitudinal gradient of net radiation is further increased, and that the forcing of the general simulation is substantially different due to the increased additional available energy. A set of cloud top temperature maps were compiled using the cloud region classification of Sherr et al. (1968), with the aid of the LW radiation measurement by NOAA sunning radiometer.

The results also suggest that a simple parameterization of the longwave cooling should include a water vapor absorbing term.

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Shi-Keng Yang, G. Louis Smith, and Fred L. Bartman

Abstract

An Earth outgoing longwave radiation (OLWR) climate model has been constructed for a monthly average radiation budget study. The model consists of the upward radiative transfer parameterization of Thompson and Warren and a monthly average climatology defined by the data from Crutcher and Meserve and Taljaard et al. Additional required information is provided by the empirical 100-mb water vapor mixing ratio equation of Harries and the mixing ratio interpolation scheme of Briegleb and Ramanathan.

Clear sky cases are calculated and discussed for the global average, zonal averages and global distributions. The results agree well with some satellite observations. The clear-sky case shows that the OLWR field is highly modulated by water vapor, especially in the tropics, where the strongest longitudinal variations in OLWR occur. These variations can be primarily explained by the strong water vapor gradient. Although in the zonal-average case the tropics have a minimum of OLWR, the minimum is essentially contributed to by a few very low flux regions, such as the Amazon, Indonesia and the Congo. There are regions in the tropics such that their OLWR is as large as that of the subtropics. In the high latitudes where cold air contains less water vapor, OLWR is basically modulated by the surface temperature.

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Shi-Keng Yang, Si-Song Zhou, Larry M. Mcmillin, and Ken A. Campana

Abstract

A cloud retrieval algorithm using NOAA/National Environmental Satellite, Data and Information Service High-Resolution Infrared Radiation Sounder 2 Microwave Sounding Unit measurements from a polar-orbiting satellite, described in McMillin et al., uses multiple channel pairs with a two-pass procedure for enhancing accuracies. The current paper complements McMillin et al. in several ways. First, it describes the characteristics of the channel pairs used in the algorithm while documenting the logic of the channel selection. It shows that the cloud-top heights and cloud fractions are dependent on the sensing channel pairs. The higher the altitude of the weighting function, the smaller the cloud fractions. Second, it adds an atmospheric attenuation correction and displays its effect on cloud-top heights. Without the attenuation correction, the cloud-top distributions are separated into two bands, possibly as a result of the distance between the heights of the weighting functions of the sensing channel pair. The attenuation correction effectively eliminates the gap, both by lowering the upper band and by elevating the lower band. The cloud fractions from this experimental operation are compared with Air Force Real-Time Nephanalysis for 3 months, and they reveal its strength in detecting low-level stratus.

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Sundar A. Christopher, Min Wang, Todd A. Berendes, Ronald M. Welch, and Shi-Keng Yang

Abstract

Using satellite imagery, more than five million square kilometers of the forest and cerrado regions over South America are extensively studied to monitor fires and smoke during the 1985 biomass burning season. The results are characterized for four major ecosystems, namely, 1) tropical rain forest, 2) tropical broadleaf seasonal, 3) savanna/grass and seasonal woods (SGW), and 4) mild/warm/hot grass/shrub (MGS). The spatial and temporal distribution of fires are examined from two different methods using the multispectral Advanced Very High Resolution Radiometer Local Area Coverage data. Using collocated measurements from the instantaneous scanner Earth Radiation Budget Experiment data, the direct regional radiative forcing of biomass burning aerosols is computed. The results show that more than 70% of the fires occur in the MGS and SGW ecosystems due to agricultural practices. The smoke generated from biomass burning has negative instantaneous net radiative forcing values for all four major ecosystems within South America. The smoke found directly over the fires has mean net radiative forcing values ranging from −25.6 to −33.9 W m−2. These results confirm that the regional net radiative impact of biomass burning is one of cooling. The spectral and broadband properties for clear-sky and smoke regions are also presented that could be used as input and/or validation for other studies attempting to model the impact of aerosols on the earth–atmosphere system.

These results have important applications for future instruments from the Earth Observing System (EOS) program. Specifically, the combination of the Visible Infrared Scanner and Clouds and the Earth’s Radiant Energy System (CERES) instruments from the Tropical Rainfall Measuring Mission and the combination of Moderate Resolution Imaging Spectrometer and CERES instruments from the EOS morning crossing mission could provide reliable estimates of the direct radiative forcing of aerosols on a global scale, thereby reducing the uncertainties in current global aerosol radiative forcing values.

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Yu-Tai Hou, Kenneth A. Campana, Kenneth E. Mitchell, Shi-Keng Yang, and Larry L. Stowe

Abstract

CLAVR [cloud from AVHRR (Advanced Very High Resolution Radiometer)] is a global cloud dataset under development at NOAA/NESDIS (National Environmental Satellite, Data, and Information Service). Total cloud amount from two experimental cases, 9 July 1986 and 9 February 1990, are intercompared with two independent products, the Air Force Real-Time Nephanalysis (RTNEPH), and the International Satellite Cloud Climatology Project (ISCCP). The ISCCP cloud database is a climate product processed retrospectively some years after the data are collected. Thus, only CLAVR and RTNEPH can satisfy the real-time requirements for numerical weather prediction (NWP) models. Compared with RTNEPH and ISCCP, which only use two channels in daytime retrievals and one at night, CLAVR utilizes all five channels in daytime and three at night from AVHRR data. That gives CLAVR a greater ability to detect certain cloud types, such as thin cirrus and low stratus. Designed to be an operational product, CLAVR is also compared with total cloud forecasts from the National Meteorological Center (NMC) Medium Range Forecast (MRF) Model. The datasets are mapped to the orbits of NOAA polar satellites, such that errors from temporal sampling are minimized. A set of statistical scores, histograms, and maps are used to display the characteristics of the datasets. The results show that the CLAVR data can realistically resolve global cloud distributions. The spatial variation is, however, less than that of RTNEPH and ISCCP, due to current constraints in the CLAVR treatment of partial cloudiness. Results suggest that if the satellite cloud data is available in real time, it can be used to improve the cloud parameterization in numerical forecast models and data assimilation systems.

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Shi-Keng Yang, Yu-Tai Hou, Alvin J. Miller, and Kenneth A. Campana

Abstract

This study presents an evaluation of the NCEP–NCAR Reanalysis (the reanalysis) by comparing its components of the earth radiation budget to satellite data. Monthly mean clear sky (CS) and total sky of outgoing longwave radiation (OLR), as well as reflected solar radiation (RSW) for 1985 and 1986, are compared to the top-of-the-atmosphere (TOA) measurements from the Earth Radiation Budget Experiment (ERBE). The ERBE-derived data of Staylor and Wilbur are also utilized to validate surface albedo. There are two objectives to this study: (i) to document the general quality of the reanalysis radiation budget, and (ii) to identify some of the general problem areas in the reanalysis global data assimilation system (GDAS).

The OLR comparisons show that the global annual mean from the reanalysis is approximately 1.5% higher than that of ERBE. The zonal-average differences are strongly seasonal, which is particularly evident at high latitudes for the CS OLR, and at most latitudes for total-sky OLR. For the geographical distribution, the synoptic patterns from the reanalysis are in good agreement with the observations. Yet many regions in the Tropics and subtropics pose significant systematic biases. Possible causes are from shortcomings in the the cloud/moisture parameterizations of the reanalysis GDAS. The complex topography unresolvable by the T62 model could also be the cause for the biases in tall mountain regions.

The global RSW comparisons show that the CS data from the reanalysis is in very good agreement with ERBE, while the total-sky RSW data overestimate ERBE by 12.6 W m−2 (∼10%) globally. Persistent overestimates of RSW throughout the period indicate that the global energy budget for the reanalysis is not balanced. This result also is consistent with the finding in OLR suggesting that the reanalysis GDAS contains shortcomings in the cloud/moisture parameterizations. Another possibility for the difference in RSW is deficiencies in the GDAS shortwave parameterizations.

Over the Sahara Desert, the reanalysis underestimates RSW, and overestimates OLR, both in the clear-sky and total-sky conditions. Comparison with the Staylor and Wilber ERBE-derived surface albedo suggests that GDAS surface albedo in this region should be increased by up to 0.1 (in albedo units). A comparison with the interannual variations of the satellite data for the boreal summer illustrates that the radiation budget data of the reanalysis contains a realistic climate signal.

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Masao Kanamitsu, Wesley Ebisuzaki, Jack Woollen, Shi-Keng Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter

The NCEP–DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the “50-year” (1948–present) NCEP–NCAR Reanalysis Project. NCEP–DOE AMIP-II re-analysis covers the “20-year” satellite period of 1979 to the present and uses an updated forecast model, updated data assimilation system, improved diagnostic outputs, and fixes for the known processing problems of the NCEP–NCAR reanalysis. Only minor differences are found in the primary analysis variables such as free atmospheric geopotential height and winds in the Northern Hemisphere extratropics, while significant improvements upon NCEP–NCAR reanalysis are made in land surface parameters and land–ocean fluxes. This analysis can be used as a supplement to the NCEP–NCAR reanalysis especially where the original analysis has problems. The differences between the two analyses also provide a measure of uncertainty in current analyses.

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