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K. Aydin and J. Singh

Abstract

Two algorithms are presented for ice crystal classification using 95-GHz polarimetric radar observables and air temperature (T). Both are based on a fuzzy logic scheme. Ice crystals are classified as columnar crystals (CC), planar crystals (PC), mixtures of PC and small- to medium-sized aggregates and/or lightly to moderately rimed PC (PSAR), medium- to large-sized aggregates of PC, or densely rimed PC, or graupel-like snow or small lumpy graupel (PLARG), and graupel larger than about 2 mm (G). The 1D algorithm makes use of Z h, Z dr, LDRhv, and T, while the 2D algorithm incorporates the three radar observables in pairs, (Z dr, Z h), (LDRhv, Z h), and (Z dr, LDRhv), plus the temperature T. The range of values for each observable or pair of observables is derived from extensive modeling studies conducted earlier. The algorithms are tested using side-looking radar measurements from an aircraft, which was also equipped with particle probes producing simultaneous and nearly collocated shadow images of cloud ice crystals. The classification results from both algorithms agreed very well with the particle images. The two algorithms were in agreement by 89% in one case and 97% in the remaining three cases considered here. The most effective observable in the 1D algorithm was Z dr, and in the 2D algorithm the pair (Z dr, Z h). LDRhv had negligible effect in the 1D classification algorithm for the cases considered here. The temperature T was mainly effective in separating columnar crystals from the rest. The advantage of the 2D algorithm over the 1D algorithm was that it significantly reduced the dependence on T in two out of the four cases.

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Siri Jodha Singh Khalsa and Ellen J. Steiner

Abstract

Temperature and moisture data from the TIROS Operational Vertical Sounder (TOVS) archives are examined for applicability to studies of the tropical atmosphere on time scales ranging from intraseasonal to interannual. Comparisons with monthly mean radiosonde data from island stations confirm the ability of TOVS to track short- and long-term atmospheric variability. Biases and rms errors are generally different for near-equatorial and subtropical stations. Inclusion of soundings derived under cloudy conditions increases negative temperature bias while improving or leaving unchanged the rms temperature error at all levels.

The large volume of TOVS data (up to 16 000 soundings per day) is reduced to manageable form by the creation of a gridded product. A structure function analysis is performed to assist in the choice of gridding parameters. The objective analysis routines used are designed to handle data voids common in satellite data fields.

A time-longitude diagram of 5-day mean precipitable water (PW) in the 1000–700 mb layer shows a strong interannual (El Niño) signal as well as time variability in the 30–60 day range in the western Pacific and Indian oceans. On the shorter time scales, maximum PW is generally coincident with axes of minimum 250 mb velocity potential.

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J. M. Rosen, D. J. Hofmann, and S. P. Singh

Abstract

This paper deals with the development of a one-dimensional steady-state stratospheric aerosol model and the subsequent perturbations caused by including the expected space shuttle particulate effluents in the model. Two approaches to the basic modeling effort have been made: in one, enough simplifying assumptions were introduced so that a more or less exact solution to the descriptive equations could be obtained; in the other, very few simplifications were made and a computer technique was used to solve the equations. The most complete form of the model contains the effects of sedimentation, diffusion, particle growth and coagulation. The results indicate that the model is capable of describing many aspects of the stratospheric aerosol layer, such as size distribution and the vertical profile of particles >0.3 μm diameter.

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Someshwar Das, A. K. Mitra, G. R. Iyengar, and J. Singh

Abstract

The operational global spectral model of the National Center for Medium Range Weather Forecasting (NCMRWF) at T80 resolution and 18 vertical levels has been used to study the skill of medium-range forecasts using three different parameterizations of deep convection namely, a Kuo–Anthes-type cumulus parameterization scheme referred to as “KUO” scheme, the relaxed Arakawa–Schubert (RAS) scheme, and the simplified Arakawa–Schubert (SAS) scheme, during an active phase of the Indian summer monsoon. Several medium-range forecasts (up to 5 days) have been made using the initial conditions of July and August of 1999, when the monsoon was active over the Indian region. Skill scores of predicted rainfall, rmse of wind and temperature, systematic errors, and genesis and tracks of the monsoon depressions predicted by the three schemes have been studied. Results indicate that, in general, the areas of light (heavy) rainfall are overestimated (underestimated) by KUO, which also fails to predict the rain-shadow effect observed over southern peninsular India. RAS and SAS produce fairly good forecasts of the observed rainfall; however, the best forecast is produced by SAS in most of the rainfall categories over the Indian region. The rmse of wind and temperature do not show significant differences among the three schemes over the global domain; however, they indicate considerable differences over the Indian region. The rmse of wind is slightly higher in RAS and SAS because of overestimation of the strength of the low-level westerly jet and upper-level tropical easterly jet. Errors in temperature forecasts are considerably reduced by RAS and SAS on all days. Systematic errors of the forecasts indicate that KUO tries to weaken the observed southwesterly flow and the low-level jet during the monsoon. RAS and SAS try to intensify the easterlies over the north Indian plains and to strengthen the monsoon trough. They shift the core of the tropical easterly jet stream to the south of its normal position. SAS reduces the cold bias almost everywhere over the Indian region. The improved simulation of temperature by SAS results in the reduction of rmse. The reduction of cold bias and improved simulated temperature by SAS indicate a proper redistribution of heat by deep convective clouds over the region by this scheme. Study of the lows and monsoon depressions indicated that the best forecast of the location of the genesis was produced by RAS. All three schemes were able to predict the tracks of the depression fairly well in the 24 h, but SAS produced relatively fewer errors when compared with the other two schemes. In most of the cases, SAS was also able to maintain the system up to 72 h, whereas the other two schemes weakened the systems.

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Xianmian Wu, John J. Bates, and Sirijodha Singh khalsa

Abstract

Measurements of brightness temperature from the water vapor band channels of the National Oceanic and Atmospheric Administration polar satellites from 1981 through 1988 are analyzed. Only clear and cloud-cleared measurements from the operational sounding product are used to produce averages for bins of 2.5° latitude by 2.5° longitude and 5 days. The standard deviations of random errors for these bins are estimated. A unique feature of this dataset is its ability to identify the dry regions in the middle and upper troposphere with unprecedented detail. Results agree with the known climatology in the tropics.

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Shekhar Gupta, R. T. McNider, Michael Trainer, Robert J. Zamora, Kevin Knupp, and M. P. Singh

Abstract

Theoretical plume growth rates depend upon the atmospheric spatial energy spectrum. Current grid-based numerical models generally resolve large-scale (synoptic) energy, while planetary boundary layer turbulence is parameterized. Energy at intermediate scales is often neglected. In this study, boundary layer radar profilers are used to examine the temporal energy spectrum, which can provide information about the atmospheric structure affecting plume growth rates. A boundary layer model (BLM) into which the radar information has been assimilated is used to drive a Lagrangian particle model (LPM) that is subsequently employed to examine plume growth rates. Profiler and aircraft data taken during the 1995 Southern Oxidants Study in Nashville, Tennessee, are used in the model study for assimilation and evaluation. The results show that the BLM without assimilation significantly underestimates the strength of the diurnal–inertial spectral peak, which in turn causes an underestimate of plume spread. Comparison with measures of plume width from aircraft data also shows that assimilation of radar information greatly improves plume spread rates predicted by the LPM.

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Hansi K. A. Singh, Cecilia M. Bitz, Aaron Donohoe, and Philip J. Rasch

Abstract

Numerical water tracers implemented in a global climate model are used to study how polar hydroclimate responds to CO2-induced warming from a source–receptor perspective. Although remote moisture sources contribute substantially more to polar precipitation year-round in the mean state, an increase in locally sourced moisture is crucial to the winter season polar precipitation response to greenhouse gas forcing. In general, the polar hydroclimate response to CO2-induced warming is strongly seasonal: over both the Arctic and Antarctic, locally sourced moisture constitutes a larger fraction of the precipitation in winter, while remote sources become even more dominant in summer. Increased local evaporation in fall and winter is coincident with sea ice retreat, which greatly augments local moisture sources in these seasons. In summer, however, larger contributions from more remote moisture source regions are consistent with an increase in moisture residence times and a longer moisture transport length scale, which produces a robust hydrologic cycle response to CO2-induced warming globally. The critical role of locally sourced moisture in the hydrologic cycle response of both the Arctic and Antarctic is distinct from controlling factors elsewhere on the globe; for this reason, great care should be taken in interpreting polar isotopic proxy records from climate states unlike the present.

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Michael J. Kavaya, Jeffrey Y. Beyon, Grady J. Koch, Mulugeta Petros, Paul J. Petzar, Upendra N. Singh, Bo C. Trieu, and Jirong Yu

Abstract

The first airborne wind measurements of a pulsed, 2-μm solid-state, high-energy, wind-profiling lidar system for airborne measurements are presented. The laser pulse energy is the highest to date in an eye-safe airborne wind lidar system. This energy, the 10-Hz laser pulse rate, the 15-cm receiver diameter, and dual-balanced coherent detection together have the potential to provide much-improved lidar sensitivity to low aerosol backscatter levels compared to earlier airborne-pulsed coherent lidar wind systems. Problems with a laser-burned telescope secondary mirror prevented a full demonstration of the lidar’s capability, but the hardware, algorithms, and software were nevertheless all validated. A lidar description, relevant theory, and preliminary results of flight measurements are presented.

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Yang Yang, Lynn M. Russell, Sijia Lou, Maryam A. Lamjiri, Ying Liu, Balwinder Singh, and Steven J. Ghan

Abstract

Two 150-yr preindustrial simulations with and without interactive sea salt emissions from the Community Earth System Model (CESM) are performed to quantify the interactions between sea salt emissions and El Niño–Southern Oscillation (ENSO). Variations in sea salt emissions over the tropical Pacific Ocean are affected by changing wind speed associated with ENSO variability. ENSO-induced interannual variations in sea salt emissions result in decreasing (increasing) aerosol optical depth (AOD) by 0.03 over the equatorial central-eastern (western) Pacific Ocean during El Niño events compared to those during La Niña events. These changes in AOD further increase (decrease) radiative fluxes into the atmosphere by +0.2 (−0.4) W m−2 over the tropical eastern (western) Pacific. Thereby, sea surface temperature increases (decreases) by 0.2–0.4 K over the tropical eastern (western) Pacific Ocean during El Niño compared to La Niña events and enhances ENSO variability by 10%. The increase in ENSO amplitude is a result of systematic heating (cooling) during the warm (cold) phase of ENSO in the eastern Pacific. Interannual variations in sea salt emissions then produce the anomalous ascent (subsidence) over the equatorial eastern (western) Pacific between El Niño and La Niña events, which is a result of heating anomalies. Owing to variations in sea salt emissions, the convective precipitation is enhanced by 0.6–1.2 mm day−1 over the tropical central-eastern Pacific Ocean and weakened by 0.9–1.5 mm day−1 over the Maritime Continent during El Niño compared to La Niña events, enhancing the precipitation variability over the tropical Pacific.

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Fabien Gibert, Grady J. Koch, Jeffrey Y. Beyon, Timothy W. Hilton, Kenneth J. Davis, Arlyn Andrews, Pierre H. Flamant, and Upendra N. Singh

Abstract

The vertical profiling of CO2 turbulent fluxes in the atmospheric boundary layer (ABL) is investigated using a coherent differential absorption lidar (CDIAL) operated nearby a tall tower in Wisconsin during June 2007. A CDIAL can perform simultaneous range-resolved CO2 DIAL and velocity measurements. The lidar eddy covariance technique is presented. The aims of the study are (i) an assessment of performance and current limitation of available CDIAL for CO2 turbulent fluxes and (ii) the derivation of instrument specifications to build a future CDIAL to perform accurate range-resolved CO2 fluxes. Experimental lidar CO2 mixing ratio and vertical velocity profiles are successfully compared with in situ sensors measurements. Time and space integral scales of turbulence in the ABL are addressed that result in limitation for time averaging and range accumulation. A first attempt to infer CO2 fluxes using an eddy covariance technique with currently available 2-μm CDIAL dataset is reported.

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