Errors In Temperature Profiles Research Articles

Effects of auxiliary atmospheric state parameters on the aerosol optical properties retrieval errors of high-spectral-resolution lidar.

A detailed assessment is carried out in relation to the influence of the uncertainties associated with the input auxiliary atmospheric state parameters on retrieving aerosol optical properties from high-spectral-resolution lidar (HSRL) observations. The study starts from a review of the main spectral structure of the Rayleigh backscattering followed by evaluating the temperature effects on a backscattering cross section of atmospheric molecules based on numerical simulation. It shows that the transmittance of the background interference filter should be taken into account, depending on the full width at half maximum, although overall temperature dependence is negligible. Based on the Taylor expansion of the Tenti S6 model, the systematic errors arising from input temperature and pressure profiles are analyzed. It is demonstrated that the atmospheric pressure profiles have limited effects on the inversion results of aerosol optical parameters, as the atmospheric pressure is usually quite stable. The relative errors of the aerosol backscatter coefficient mainly stem from temperature profile errors and highly depend on the aerosol concentration. Quantitatively, the aerosol backscatter coefficient error could be larger than 5% with a 3 K deviation of temperature when the backscatter ratio is larger than 1.1. The accuracy of aerosol extinction coefficient retrieval is affected not only by the error in temperature, but also by the error in temperature lapse rate; the retrieval accuracy is more sensitive to the latter than the former. Further analysis based on the sounding temperature data shows that the variation of the temperature inversion layer during the night could induce a bias larger than 0.04 km-1 on the aerosol extinction coefficient retrieval. Therefore, the time resolution of temperature measurement from sounding balloons twice per day is too low to obtain an accurate retrieval of the aerosol optical properties from the HSRL.

Validation of eight atmospheric reanalyses in the Antarctic Peninsula region

AbstractEight atmospheric reanalyses were compared against observed vertical profiles of temperature, specific humidity and wind speed collected by two research aircraft in February–March 2010 in the Antarctic Peninsula region. These data offered a rare possibility to validate reanalyses against independent in situ data which have not been assimilated into the reanalyses. The reanalyses had generally too moist profiles with too low wind speeds, but otherwise the errors in the reanalyses had large spatial differences. On the eastern side of the peninsula, the near‐surface temperatures were largely overestimated. None of the reanalyses outperformed the others in all variables, at all altitudes and on both sides of the peninsula. Generally, NCEP‐CFSR and MERRA had the smallest errors in temperature profiles, JRA‐55 had marginally the most accurate specific humidity profiles and NCEP‐CFSR had the best wind profiles. The reanalyses were coherent, although biased, on the western side of the Antarctic Peninsula, but on the eastern side the spread was large. All the reanalyses underestimated the variability between the individual profiles of temperature and wind speed. The modern reanalyses with a sufficient spatial resolution and an adequate data assimilation method outperformed the others, especially on the eastern side.

Retrieval of atmospheric parameters from NOAA-16 AMSU data over Indian region - Preliminary results

With the establishment of a new High Resolution Picture Transmission (HRPT) reception system at IMD, New Delhi, the real time data from microwave sounding instruments onboard the NOAA-K, L, M and N series of satellites has also become available. The raw HRPT data is being interfaced with the recently acquired new ‘ATOVS and AVHRR Preprocessing Package (AAPP)’ to perform temperature and moisture retrievals from AMSU data of NOAA-16 satellite using two separate schemes: Inversion Coupled Imager (ICI) and Neural Network (NN) approach. In this study, NOAA-16 satellite data over Indian region were used for retrieving temperature and moisture profiles for the month of January, 2002. The temperature and moisture retrieval results are evaluated by computing the bias and root mean square (RMS) difference using collocated ECMWF analysis. The results based on the analysis of data set for the month of January, 2002 shows that ICI approach yields better results for all atmospheric levels. The RMS errors in temperature profiles are found to be less than 4oC at all pressure levels. The RMS errors in relative humidity are found to be less than 20% at all pressure levels. C Intercomparison of the results revealed that bias and RMS error are less for ICI scheme using forecast field compared to ICI without using forecast field and Neural Network approach.

Systematic errors in atmospheric profiles obtained from Abelian inversion of radio occultation data: Effects of large‐scale horizontal gradients

Reduction of radio occultation data to retrieve atmospheric profiles (T‐p(r)) requires knowledge or assumption of the horizontal structure of the atmosphere. In the case of terrestrial planets the atmosphere in the vicinity of ray periapsides usually is assumed to be spherically symmetric. This assumption leads to an integral transform relationship between the profiles of refractivity versus radius and the total bending angle versus the asymptotic closest approach of rays, where the latter is directly obtainable from occultation frequency data and trajectory information. Occultation studies of the giant planets have demonstrated that departures from spherical symmetry, if not accounted for, can result in serious errors in derived T‐p(r) profiles. We analyze errors in atmospheric profiles due to large‐scale departures from spherical symmetry. For analytic convenience we represent departures from spherical symmetry as locally spherical structures with center of curvature offset in three dimensions from the center of mass, from which follow analytic expressions for errors in bending angle and impact parameter as functions of the offset and trajectory parameters. Since these expressions are not restricted to any specific occultation type, it is easy to identify the geometrical configurations and the specific trajectory parameters that enhance or suppress these errors. Errors in bending angle and impact parameter carry over into the refractivity and radius profiles, while at the same time, new errors are introduced because the bending angle versus impact parameter profile is integrated along a nonvertical path in the presence of large‐scale departures from spherical symmetry, to obtain refractivity and radius profiles. Similarly, refractivity and radius errors propagate into the temperature and pressure profiles, while a nonvertical path of integration in the presence of horizontal gradients provides another opportunity for new errors to be introduced. We estimate that fractional errors in temperature profiles can be as large as a few percent for the Martian atmosphere above 20 km, decreasing in magnitude closer to the surface. For Earth, such errors are estimated to be less than 1% above 30 km. In the lower parts of Earth's atmosphere, however, and especially in the lower troposphere, these errors can be very sensitive to horizontal gradients and hence highly variable; typically, the error magnitude remains less than 2% for the dry regions of Earth's troposphere. We have not addressed the effect on errors of water vapor gradients, or of more extreme structures such as sharp weather fronts. A small variation on this approach can incorporate errors due to imprecise knowledge of the transmitter and receiver trajectories.

Analysis of stellar occultation data: Effects of photon noise and initial conditions

A new inversion technique for obtaining temperature, pressure, and number density profiles of a planetary atmosphere from an occultation light curve is described. This technique employs an improved boundary condition to begin the numerical inversion and permits the computation of errors in the profiles caused by photon noise in the light curve. We present our assumptions about the atmosphere, optics, and noise and develop the equations for temperature, pressure, and number density and their associated errors. By inverting in equal increments of altitude, Δh, rather than in equal increments of time, Δt, the inversion need not be halted at the first negative point on the light curve as required by previous methods. The importance of the boundary condition is stressed, and a new initial condition is given. Numerical results are presented for the special case of inversion of a noisy isothermal light curve. From these results, simple relations are developed which can be used to predict the noise quality of an occultation. It is found that fractional errors in temperature profiles are comparable to those of pressure and number density profiles. An example of the inversion method is shown. Finally, we discuss the validity of our assumptions. In an appendix we demonstrate that minimum fractional errors in scale height determined from the inversion are comparable to those from an isothermal fit to a noisy isothermal light curve.