Cooperative Institute for Research in the Atmosphere

About: Cooperative Institute for Research in the Atmosphere is a based out in . It is known for research contribution in the topics: Snow & Data assimilation. The organization has 332 authors who have published 997 publications receiving 38835 citations. The organization is also known as: CIRA.

Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions

Abstract: . Recent successes in passive remote sensing of far-red solar-induced chlorophyll fluorescence (SIF) have spurred the development and integration of canopy-level fluorescence models in global terrestrial biosphere models (TBMs) for climate and carbon cycle research. The interaction of fluorescence with photochemistry at the leaf and canopy scales provides opportunities to diagnose and constrain model simulations of photosynthesis and related processes, through direct comparison to and assimilation of tower, airborne, and satellite data. TBMs describe key processes related to the absorption of sunlight, leaf-level fluorescence emission, scattering, and reabsorption throughout the canopy. Here, we analyze simulations from an ensemble of process-based TBM–SIF models (SiB3 – Simple Biosphere Model, SiB4, CLM4.5 – Community Land Model, CLM5.0, BETHY – Biosphere Energy Transfer Hydrology, ORCHIDEE – Organizing Carbon and Hydrology In Dynamic Ecosystems, and BEPS – Boreal Ecosystems Productivity Simulator) and the SCOPE (Soil Canopy Observation Photosynthesis Energy) canopy radiation and vegetation model at a subalpine evergreen needleleaf forest near Niwot Ridge, Colorado. These models are forced with local meteorology and analyzed against tower-based continuous far-red SIF and gross-primary-productivity-partitioned (GPP) eddy covariance data at diurnal and synoptic scales during the growing season (July–August 2017). Our primary objective is to summarize the site-level state of the art in TBM–SIF modeling over a relatively short time period (summer) when light, canopy structure, and pigments are similar, setting the stage for regional- to global-scale analyses. We find that these models are generally well constrained in simulating photosynthetic yield but show strongly divergent patterns in the simulation of absorbed photosynthetic active radiation (PAR), absolute GPP and fluorescence, quantum yields, and light response at the leaf and canopy scales. This study highlights the need for mechanistic modeling of nonphotochemical quenching in stressed and unstressed environments and improved the representation of light absorption (APAR), distribution of light across sunlit and shaded leaves, and radiative transfer from the leaf to the canopy scale.

Assimilating Coherent Doppler Lidar Measurements into a Model of the Atmospheric Boundary Layer. Part I: Algorithm Development and Sensitivity to Measurement Error

Abstract: A four-dimensional variational data assimilation (4DVAR) algorithm for retrieval of spatially and temporally resolved velocity and thermodynamic fields within the atmospheric boundary layer (ABL) is described and applied to a coherent Doppler lidar dataset. The adjoint method is used to find the initialization of an ABL model that gives the best fit to radial velocity measurements from the Doppler lidar. The adjoint equations are derived by assuming that subgrid-scale fluxes can be represented as general functions of the resolved-scale rates of strain and potential temperature gradients. For this study, particular attention is paid to the treatment of real measurement error. Radial velocity precision as a function of the signal-to-noise ratio (SNR) is estimated from time series analysis of real fixed beam data, and this information is used in the evaluation of the cost function. The cost function is evaluated by interpolating the model output to the observation coordinates. As a result, the error...

An Example of Temperature Structure Differences in Two Cyclone Systems Derived from the Advanced Microwave Sounder Unit

Abstract: The Advanced Microwave Sounding Unit (AMSU) has better horizontal resolution and vertical temperature sounding abilities than its predecessor, the Microwave Sounding Unit (MSU). Those improved capabilities are demonstrated with observations of two cyclonic weather systems located in the South Pacific Ocean on 1 March 1999. These weather systems appear quite similar in conventional infrared satellite imagery, suggesting that they are comparable in structure and intensity. However, an analysis using temperature retrievals created from the AMSU shows that their vertical thermal structure is quite different. This is just one example of an application highlighting the improved sounding capabilities available with the AMSU instrument suite. A preliminary look at what the AMSU can provide in data-void regions and a discussion of future plans to create AMSU-based products to better diagnose synoptic-scale weather systems are presented.

Objective Identification of Annular Hurricanes

Abstract: Annular hurricanes are a subset of intense tropical cyclones that have been shown in previous work to be significantly stronger, to maintain their peak intensities longer, and to weaken more slowly than average tropical cyclones. Because of these characteristics, they represent a significant forecasting challenge. This paper updates the list of annular hurricanes to encompass the years 1995–2006 in both the North Atlantic and eastern–central North Pacific tropical cyclone basins. Because annular hurricanes have a unique appearance in infrared satellite imagery, and form in a specific set of environmental conditions, an objective real-time method of identifying these hurricanes is developed. However, since the occurrence of annular hurricanes is rare (4% of all hurricanes), a special algorithm to detect annular hurricanes is developed that employs two steps to identify the candidates: 1) prescreening the data and 2) applying a linear discriminant analysis. This algorithm is trained using a dependent dataset (1995–2003) that includes 11 annular hurricanes. The resulting algorithm is then independently tested using datasets from the years 2004–06, which contained an additional three annular hurricanes. Results indicate that the algorithm is able to discriminate annular hurricanes from tropical cyclones with intensities greater than 84 kt (43.2 m s 1 ). The probability of detection or hit rate produced by this scheme is shown to be 96% with a false alarm rate of 6%, based on 1363 six-hour time periods with a tropical cyclone with an intensity greater than 84 kt (1995–2006).

Comparison of cloud products within IASI footprints for the assimilation of cloudy radiances

Abstract: This article compares different methods of deriving cloud properties in the footprint of the Infrared Atmospheric Sounding Interferometer (IASI), onboard the European MetOp satellite. Cloud properties produced by ten operational schemes are assessed and an intercomparison of the products for a 12 h global acquisition is presented. Clouds cover a large part of the Earth, contaminating most of the radiance data. The estimation of cloud top height and effective amount within the sounder footprint is an important step towards the direct assimilation of cloud-affected radiances. This study first examines the capability of all the schemes to detect and characterize the clouds for all complex situations and provides some indications of confidence in the data. Then the dataset is restricted to thick overcast single layers and the comparison shows a significant agreement between all the schemes. The impact of the retrieved cloud properties on the residuals between calculated cloudy radiances and observations is estimated in the long-wave part of the spectrum. Copyright © 2011 Royal Meteorological Society, Crown in the right of Canada, and British Crown copyright, the Met Office