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.

The maximum likelihood ensemble filter performances in chaotic systems

Abstract: The performance of the maximum likelihood ensemble filter (MLEF), is investigated in the context of generic systems featuring the essential ingredients of unstable dynamics and on a spatially extended system displaying chaos. The main objective is to clarify the response of the filter to different regimes of motion and highlighting features which may help its optimization in more realistic applications. It is found that, in view of the minimization procedure involved in the filter analysis update, the algorithm provides accurate estimates even in the presence of prominent non-linearities. Most importantly, the filter ensemble size can be designed in connection to the properties of the system attractor (Kaplan–Yorke dimension), thus facilitating the filter setup and limiting the computational cost by using an optimal ensemble. As a corollary, this latter finding indicates that the ensemble perturbations in the MLEF reflect the intrinsic system error dynamics rather than a sampling of realizations of an unknown error covariance.

Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

Abstract: The Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind s...

Applications of Data Assimilation in the Geosciences

Abstract: In this final chapter, we present how the different forms of data assimilation presented in this book are used in the geosciences. We shall attempt to represent as many of the geoscience disciplines as possible, but acknowledge we cannot cover all of them.

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

Abstract: . In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March–April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial–temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.

Atmospheric concentrations and deposition of reactive nitrogen in Grand Teton National Park

Abstract: [1] The Grand Teton Reactive Nitrogen Deposition Study (GrandTReNDS) was conducted to provide a more complete look at atmospheric concentrations and deposition fluxes of various reactive nitrogen species in and around Grand Teton National Park (GTNP). Daily measurements of wet deposition, PM2.5 composition, and gaseous ammonia and nitric acid concentrations were made at three locations. Weekly measurements of gaseous ammonia were made at eight additional sites. Ammonia concentrations were higher at the western sites; the study average ammonia concentration west of GTNP was 35 nmol m−3 and on the east side of the park it was 18 nmol m−3. Concentrations of other measured reactive nitrogen species were lower than NH3 and fairly similar at all sites, with averages of approximately 9, 1, and 3 nmol m−3 for ammonium, nitrate, and nitric acid, respectively. Wet deposition of ammonium and dry deposition of ammonia were the largest reactive nitrogen deposition pathways, together accounting for 56% and 62% of the nitrogen deposition on the east and west sides of GTNP, respectively. Nitrogen deposition of measured species totaled 2.38 kg N ha−1 west of GTNP at Driggs, ID (6 April to 21 September 2011), 0.85 kg N ha−1 west of GTNP at a high-elevation site (28 July to 21 September 2011) and 1.23 kg N · ha−1 at a location on the east side of GTNP (15 May to 21 September 2011). These measurements highlight the significant inputs of reactive nitrogen to regional ecosystems over the few months studied, the importance of including NH3 dry deposition in nitrogen deposition budgets, and the need to conduct further research to capture sources and the annual cycle of deposition.