This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.

/pdf/the-hitran-2008-molecular-spectroscopic-database-1ud8clpej3.pdf

The HITRAN 2008 molecular spectroscopic database

The paper motivates, presents, demonstrates in use, and evaluates a methodology for conducting design science (DS) research in information systems (IS). DS is of importance in a discipline oriented to the creation of successful artifacts. Several researchers have pioneered DS research in IS, yet over the past 15 years, little DS research has been done within the discipline. The lack of a methodology to serve as a commonly accepted framework for DS research and of a template for its presentation may have contributed to its slow adoption. The design science research methodology (DSRM) presented here incorporates principles, practices, and procedures required to carry out such research and meets three objectives: it is consistent with prior literature, it provides a nominal process model for doing DS research, and it provides a mental model for presenting and evaluating DS research in IS. The DS process includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication. We demonstrate and evaluate the methodology by presenting four case studies in terms of the DSRM, including cases that present the design of a database to support health assessment methods, a software reuse measure, an Internet video telephony application, and an IS planning method. The designed methodology effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.

A Design Science Research Methodology for Information Systems Research

The Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the Humidity Sounder for Brazil (HSB) form an integrated cross-track scanning temperature and humidity sounding system on the Aqua satellite of the Earth Observing System (EOS). AIRS is an infrared spectrometer/radiometer that covers the 3.7-15.4-/spl mu/m spectral range with 2378 spectral channels. AMSU is a 15-channel microwave radiometer operating between 23 and 89 GHz. HSB is a four-channel microwave radiometer that makes measurements between 150 and 190 GHz. In addition to supporting the National Aeronautics and Space Administration's interest in process study and climate research, AIRS is the first hyperspectral infrared radiometer designed to support the operational requirements for medium-range weather forecasting of the National Ocean and Atmospheric Administration's National Centers for Environmental Prediction (NCEP) and other numerical weather forecasting centers. AIRS, together with the AMSU and HSB microwave radiometers, will achieve global retrieval accuracy of better than 1 K in the lower troposphere under clear and partly cloudy conditions. This paper presents an overview of the science objectives, AIRS/AMSU/HSB data products, retrieval algorithms, and the ground-data processing concepts. The EOS Aqua was launched on May 4, 2002 from Vandenberg AFB, CA, into a 705-km-high, sun-synchronous orbit. Based on the excellent radiometric and spectral performance demonstrated by AIRS during prelaunch testing, which has by now been verified during on-orbit testing, we expect the assimilation of AIRS data into the numerical weather forecast to result in significant forecast range and reliability improvements.

http://www.atmos.berkeley.edu/~inez/MSRI-NCAR_CarbonDA/papers/barnet_refs/Aumann_IEEE8big15aug02.pdf

AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems

. The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980–2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003–2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011–2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land–atmosphere feedbacks.

/pdf/gleam-v3-satellite-based-land-evaporation-and-root-zone-soil-rk15enx2ox.pdf

GLEAM v3: satellite-based land evaporation and root-zone soil moisture

[1] Objective measures of climate model performance are proposed and used to assess simulations of the 20th century, which are available from the Coupled Model Intercomparison Project (CMIP3) archive. The primary focus of this analysis is on the climatology of atmospheric fields. For each variable considered, the models are ranked according to a measure of relative error. Based on an average of the relative errors over all fields considered, some models appear to perform substantially better than others. Forming a single index of model performance, however, can be misleading in that it hides a more complex picture of the relative merits of different models. This is demonstrated by examining individual variables and showing that the relative ranking of models varies considerably from one variable to the next. A remarkable exception to this finding is that the so-called “mean model” consistently outperforms all other models in nearly every respect. The usefulness, limitations and robustness of the metrics defined here are evaluated 1) by examining whether the information provided by each metric is correlated in any way with the others, and 2) by determining how sensitive the metrics are to such factors as observational uncertainty, spatial scale, and the domain considered (e.g., tropics versus extra-tropics). An index that gauges the fidelity of model variability on interannual time-scales is found to be only weakly correlated with an index of the mean climate performance. This illustrates the importance of evaluating a broad spectrum of climate processes and phenomena since accurate simulation of one aspect of climate does not guarantee accurate representation of other aspects. Once a broad suite of metrics has been developed to characterize model performance it may become possible to identify optimal subsets for various applications.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2007JD008972

Performance metrics for climate models

Absorption of Microwaves by Atmospheric Gases

The NOAA-15 weather satellite carries the Advanced Microwave Sounding Units-A and -B (AMSU-A, AMSU-B) which measure thermal emission from an atmospheric oxygen band, two water lines, and several window frequencies An iterated minimum-variance algorithm retrieves profiles of temperature and humidity in the atmosphere from this data Relative humidity is converted into absolute humidity with use of the retrieved temperature profile Two important issues in the retrieval problem are modeling of the surface and clouds An a priori surface emissivity is computed on the basis of a preliminary classification, and the surface brightness spectrum is subsequently adjusted simultaneously with the moisture profile retrieval Cloud liquid water is constrained by a condensation model that uses an extended definition of relative humidity as a parameter

Retrieval of temperature and moisture profiles from AMSU-A and AMSU-B measurements

Interference coefficients describe the non-Lorentzian effect that arises as pressure broadening causes lines to overlap. These coefficients, one for each line, are at moderate pressures related linearly to absorption and dispersion. They are determined here for the 5-mm wavelength oxygen lines broadened by air. The method includes four a priori constraints on off-diagonal elements of the relaxation matrix, which produce the interference effect: (1) detailed balance; (2) intra-branch submatrices are assumed to be identical; (3) coupling between the + and - branches is ignored; (4) coupling between the (positive-frequency) resonances and the nonresonant and negative-resonant branches is represented by a small bias term in the interference coefficients. The linear equations relating measured dispersion to the interference coefficients are solved by the Twomey-Tikhonov method, which minimizes a cost function, subject to the condition of constant measurement-error variance. The cost function is chosen to minimize the variation of elements along diagonals of the intra-branch relaxation submatrix. Implications for atmospheric radiative transfer are briefly discussed.

Interference coefficients for overlapping oxygen lines in air

http://radiometrics.com/data/uploads/2012/11/Tretyakova_JMS_05.pdf

60-GHz oxygen band: precise broadening and central frequencies of fine-structure lines, absolute absorption profile at atmospheric pressure, and revision of mixing coefficients

Absorption of electromagnetic waves by rotational transitions of molecules is formulated for the case in which the wave frequency is displaced from resonance by an amount large compared to the reciprocal duration of a typical binary collision, and also large compared to the differences between frequencies of the strong resonances of the gas. In this far-wing limit, Fano's relaxation operator is reduced to a scalar parameter which depends on the frequency displacement. This relaxation parameter is not symmetric with respect to reflection about resonance, but becomes symmetric when multiplied by the factor exp (h/2pi) (omega sub d)/2kT where omega sub d is the frequency displacement. The theory applies to dipolar molecules of any shape, in collisions with either dipolar or quadrupolar molecules.

Philip W. Rosenkranz

Papers

Absorption of Microwaves by Atmospheric Gases

Retrieval of temperature and moisture profiles from AMSU-A and AMSU-B measurements

Interference coefficients for overlapping oxygen lines in air

60-GHz oxygen band: precise broadening and central frequencies of fine-structure lines, absolute absorption profile at atmospheric pressure, and revision of mixing coefficients

Pressure broadening of rotational bands. I - A statistical theory