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.

Ocean reflectance spectra at the red, near‐infrared, and shortwave infrared from highly turbid waters: A study in the Bohai Sea, Yellow Sea, and East China Sea

Abstract: Normalized water-leaving radiance spectra nLw(λ) at the red, near-infrared (NIR), and shortwave infrared (SWIR) are quantified and characterized in highly turbid waters of the western Pacific using 3 yr (2009–2011) observations from the Moderate Resolution Imaging Spectroradiometer on the satellite Aqua. nLw(645; red), nLw(859; NIR), and nLw(1240; SWIR) were higher in the coastal region and river estuaries, with SWIR nLw(1240) reaching up to ∼ 0.2 mW cm−2 µm−1 sr−1 in Hangzhou Bay during winter. The NIR ocean-reflectance spectral shape represented by the ratio of the normalized water-leaving reflectance ρwN(λ) at the two NIR bands ρwN(748) : ρwN(869) is highly dynamic and region-dependent. The NIR spectral feature associated with the sediment source from the Yellow River and Ancient Yellow River is noticeably different from that of the Yangtze River. There are non-negligible SWIR nLw(1240) contributions for waters with the NIR nLw(859) > ∼ 2.5 mW cm−2 µm−1 sr−1. Estimation of the NIR ocean reflectance with iterative approaches might only be accurate for turbid waters with nLw(859) < ∼ 1.5 mW cm−2 µm−1 sr−1. Thus, the SWIR atmospherics correction algorithm for satellite ocean-color data processing is indispensable to derive accurate nLw(λ) for highly turbid waters. Current existing satellite algorithms for chlorophyll a, diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), total suspended matter, and inherent optical properties (IOPs) using nLw(λ) at the red band for coastal waters are limited and can only be applied to turbid waters with nLw(859) < ∼ 1.5 mW cm−2 µm−1 sr−1. Thus, the NIR nLw(λ) measurements are required to characterize water properties for highly turbid waters. Based on the fact that pure water absorption is significantly larger than other absorption components in the NIR wavelengths, we show that it is feasible to analytically derive accurate IOP data for turbid waters with combined satellite-measured visible-NIR nLw(λ) spectra data.

Concentric gravity waves over northern China observed by an airglow imager network and satellites

Abstract: The first no-gap OH airglow all-sky imager network was established in northern China in February 2012. The network is composed of six all-sky airglow imagers that make observations of OH airglow gravity waves and cover an area of about 2000 km east and west and about 1400 km south and north. An unusual outbreak of Concentric Gravity Wave (CGW) events were observed by the network nearly every night during the first half of August 2013. These events were coincidentally observed by satellite sensors from Fengyun-2 (FY-2), Atmospheric Infrared Sounder (AIRS)/Aqua, and Visible Infrared Imaging Radiometer Suite (VIIRS)/Suomi National Polar-orbiting Partnership (NPP). Combination of the ground imager network with satellites provides multilevel observations of the CGWs from the stratosphere to the mesopause region. In this paper, two representative CGW events in August 2013 are studied in detail: first is the CGW on the night of 13 August 2013, likely launched by a single thunderstorm. The temporal and spatial analyses indicate that the CGW horizontal wavelengths follow freely propagating waves based on a GW dispersion relation within 300 km from the storm center. In contrast, the more distant observed gravity wave field exhibits a smaller horizontal wavelength of ~20 km, and our analysis strongly suggest this wave field represents a ducted wave. A second event, exhibiting multiple CGWs, was induced by two very strong thunderstorms on 9 August 2013. Multiscale waves with horizontal wavelengths ranging from less than 10 km to 200 km were observed.

Improvements to the Operational Tropical Cyclone Wind Speed Probability Model

Abstract: The National Hurricane Center Hurricane Probability Program, which estimated the probability of a tropical cyclone passing within a specific distance of a selected set of coastal stations, was replaced by the more general Tropical Cyclone Surface Wind Speed Probabilities in 2006. A Monte Carlo (MC) method is used to estimate the probabilities of 34-, 50-, and 64-kt (1 kt = 0.51 m s−1) winds at multiple time periods through 120 h. Versions of the MC model are available for the Atlantic, the combined eastern and central North Pacific, and the western North Pacific. This paper presents a verification of the operational runs of the MC model for the period 2008–11 and describes model improvements since 2007. The most significant change occurred in 2010 with the inclusion of a method to take into account the uncertainty of the track forecasts on a case-by-case basis, which is estimated from the spread of a dynamical model ensemble and other parameters. The previous version represented the track uncertai...

Integrating snow science and wildlife ecology in Arctic-boreal North America

Abstract: Snow covers Arctic and boreal regions (ABRs) for approximately 9months of the year, thus snowscapes dominate the form and function of tundra and boreal ecosystems. In recent decades, Arctic warming has changed the snowcover’s spatial extent and distribution, as well as its seasonal timing and duration, while also altering the physical characteristics of the snowpack. Understanding the little studied effects of changing snowscapes on its wildlife communities is critical. The goal of this paper is to demonstrate the urgent need for, and suggest an approach for developing, an improved suite of temporally evolving, spatially distributed snowproducts to help understand howdynamics in snowscape properties impact wildlife, with a specific focus onAlaska and northwesternCanada. Via consideration of existing knowledge of wildlife-snow interactions, currently available snowproducts for focus region, and results of three case studies, we conclude that improving snow science in the ABR will be best achieved by focusing efforts on developing data-model fusion approaches to produce fitfor-purpose snowproducts that include, but are not limited to, wildlife ecology. The relativewealth of coordinated in situmeasurements, airborne and satellite remote sensing data, andmodeling tools being collected and developed as part ofNASA’s Arctic Boreal Vulnerability Experiment and SnowEx campaigns, for example, provide a data rich environment for developing and testing new remote sensing algorithms and retrievals of snowscape properties.

Carbon flux estimation for Siberia by inverse modeling constrained by aircraft and tower CO2 measurements

Abstract: [1] Being one of the largest carbon reservoirs in the world, the Siberian carbon sink however remains poorly understood due to the limited numbers of observation. We present the first results of atmospheric CO2 inversions utilizing measurements from a Siberian tower network (Japan-Russia Siberian Tall Tower Inland Observation Network; JR-STATION) and four aircraft sites, in addition to surface background flask measurements by the National Oceanic and Atmospheric Administration (NOAA). Our inversion with only the NOAA data yielded a boreal Eurasian CO2 flux of −0.56 ± 0.79 GtC yr−1, whereas we obtained a weaker uptake of −0.35 ± 0.61 GtC yr−1 when the Siberian data were also included. This difference is mainly explained by a weakened summer uptake, especially in East Siberia. We also found the inclusion of the Siberian data had significant impacts on inversion results over northeastern Europe as well as boreal Eurasia. The inversion with the Siberian data reduced the regional uncertainty by 22% on average in boreal Eurasia, and further uncertainty reductions up to 80% were found in eastern and western Siberia. Larger interannual variability was clearly seen in the inversion which includes the Siberia data than the inversion without the Siberia data. In the inversion with NOAA plus Siberia data, east Siberia showed a larger interannual variability than that in west and central Siberia. Finally, we conducted forward simulations using estimated fluxes and confirmed that the fit to independent measurements over central Siberia, which were not included in inversions, was greatly improved.