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.

A Performance Comparison between Multiphysics and Stochastic Approaches within a North American RAP Ensemble

Abstract: A stochastic parameter perturbation (SPP) scheme consisting of spatially and temporally varying perturbations of uncertain parameters in the Grell–Freitas convective scheme and the Mellor–Yamada–Nakanishi–Niino planetary boundary scheme was developed within the Rapid Refresh ensemble system based on the Weather Research and Forecasting Model. Alone the stochastic parameter perturbations generate insufficient spread to be an alternative to the operational configuration that utilizes combinations of multiple parameterization schemes. However, when combined with other stochastic parameterization schemes, such as the stochastic kinetic energy backscatter (SKEB) scheme or the stochastic perturbation of physics tendencies (SPPT) scheme, the stochastic ensemble system has comparable forecast performance. An additional analysis quantifies the added value of combining SPP and SPPT over an ensemble that uses SPPT only, which is generally beneficial, especially for surface variables. The ensemble combining a...

Introduction of Snow and Geomorphic Disturbance Variables into Predictive Models of Alpine Plant Distribution in the Western Swiss Alps

Abstract: Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presence-absence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was importa...

Earlier onset of the spring fine dust season in the southwestern United States

Abstract: Particulate matter (PM)2.5 dust concentrations (mineral particles with aerodynamic diameters less than 2.5 µm) typically peak in spring and early summer at rural and remote sites across the southwestern United States. Trend analyses indicate that springtime regional mean PM2.5 dust concentrations have increased from 1995 to 2014, especially in March (5.4% yr−1, p < 0.01). This increase reflects an earlier onset of the spring dust season across the Southwest by 1 to 2 weeks over the 20 year time period. March dust concentrations were strongly correlated with the Pacific Decadal Oscillation index (r = −0.65, p < 0.01), which was mostly in its negative phase from 2007 to 2014, during which the region was drier, windier, and less vegetated. The positive spring trend and its association with large-scale climate variability have several important implications for visibility, particulate matter, health effects, and the hydrologic cycle in the region.

Characterization of speciated aerosol direct radiative forcing over California

Abstract: A fully coupled meteorology-chemistry model (WRF-Chem) with added capability of diagnosing the spatial and seasonal distribution of radiative forcings for individual aerosol species over California is used to characterize the radiative forcing of speciated aerosols in California. Model simulations for the year of 2005 are evaluated with various observations including meteorological data from California Irrigation Management Information System (CIMIS), aerosol mass concentrations from US EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE), and aerosol optical depth from AErosol RObotic NETwork (AERONET) and satellites. The model well captures the observed seasonal meteorological conditions over California. Overall, the simulation is able to reproduce the observed spatial and seasonal distribution of mass concentration of total PM2.5 and the relative contribution from individual aerosol species, except the model significantly underestimates the surface concentrations of organic matter (OM) and elemental carbon (EC), potentially due to uncertainty in the anthropogenic emissions of OM and EC and the outdated secondary organic aerosol mechanism used in the model. A sensitivity simulation with anthropogenic EC emission doubled significantly reduces the model low bias of EC. The simulation reveals high anthropogenic aerosol loading over the Central Valley and the Los Angeles metropolitan regions and highmore » natural aerosol (dust) loading over southeastern California. The seasonality of aerosol surface concentration is mainly determined by vertical turbulent mixing, ventilation, and photochemical activity, with distinct characteristics for individual aerosol species and between urban and rural areas. The simulations show that anthropogenic aerosols dominate the aerosol optical depth (AOD). The ratio of AOD to AAOD (aerosol absorption optical depth) shows distinct seasonality with a winter maximum and a summer minimum. Aerosol radiative forcing is presented along with the contribution from individual aerosol species from the simulation with anthropogenic EC emission doubled. On statewide average over California, aerosol reduces the seasonal-average surface radiation fluxes by about 3 W m-2 with a maximum of 10 W m-2 in summer. In the atmosphere, aerosol introduces a warming effect of about 2 W m-2 with a maximum of 10 W m-2 also in summer. EC and dust contribute about 75-95% and 1-10% of the total warming through the seasons, respectively. At the top of atmosphere (TOA), the overall aerosol radiative effect is cooling with a maximum of -3.5 W m-2. EC contributes exclusively to the TOA warming of up to about 0.7 W m-2. The encouraging performance of WRF-Chem in simulating aerosols and their radiative forcing suggests that the model is suitable for further investigation of the impact of emission control on radiative forcing and regional climate over California.« less

A Lagrangian Snow-Evolution System for Sea-Ice Applications (SnowModel-LG): Part I—Model Description

Abstract: A Lagrangian snow-evolution model (SnowModel-LG) was used to produce daily, pan-Arctic, snow-on-sea-ice, snow property distributions on a 25 × 25-km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective-Analysis for Research and Applications-Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis-5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14-km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static-surfaces and blowing-snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing-snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt-season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA-2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first-order control on snow property evolution.