ALBERT

Description: Estimates of ocean circulation constrained by in situ and remotely sensed observations have become routinely available during the past five years, and they are being applied to myriad scientific and operational problems [Stammer et al.,2002]. Under the Global Ocean Data Assimilation Experiment (GODAE), several regional and global estimates have evolved for applications in climate research, seasonal forecasting, naval operations, marine safety, fisheries,the offshore oil industry, coastal management, and other areas. This article reports on recent progress by one effort, the consortium for Estimating the Circulation and Climate of the Ocean (ECCO), toward a next-generation synthesis of ocean and sea-ice data that is global, that covers the full ocean depth, and that permits eddies.

Description: Hurricane Katrina was the sixth most intense hurricane in the Atlantic. Katrina's forecast poses major challenges, the most important of which is its rapid intensification. Hurricane intensity forecast with General Circulation Models (GCMs) is difficult because of their coarse resolution. In this article, six 5-day simulations with the ultra-high resolution finite-volume GCM are conducted on the NASA Columbia supercomputer to show the effects of increased resolution on the intensity predictions of Katrina. It is found that the 0.125 degree runs give comparable tracks to the 0.25 degree, but provide better intensity forecasts, bringing the center pressure much closer to observations with differences of only plus or minus 12 hPa. In the runs initialized at 1200 UTC 25 AUG, the 0.125 degree simulates a more realistic intensification rate and better near-eye wind distributions. Moreover, the first global 0.125 degree simulation without convection parameterization (CP) produces even better intensity evolution and near-eye winds than the control run with CP.

Description: Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite 'IBUKI' (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (X(CO2)) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is approx.1132 for 1-yr of the 74 055 GOSAT X(CO2) observations, which indicates that GOSAT provides approx.1132 independent pieces of information about surface fluxes. We quantify the impact of GOSAT's spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.

Description: It is known that the General Circulation Models (GCMs) have sufficient resolution to accurately simulate hurricane near-eye structure and intensity. To overcome this limitation, the mesoscale-resolving finite-element GCM (fvGCM) has been experimentally deployed on the NASA Columbia supercomputer, and its performance is evaluated choosing hurricane Katrina as an example in this study. On late August 2005 Katrina underwent two stages of rapid intensification and became the sixth most intense hurricane in the Atlantic. Six 5-day simulations of Katrina at both 0.25 deg and 0.125 deg show comparable track forecasts, but the 0,125 deg runs provide much better intensity forecasts, producing center pressure with errors of only +/- 12 hPa. The 0.125 deg simulates better near-eye wind distributions and a more realistic average intensification rate. A convection parameterization (CP) is one of the major limitations in a GCM, the 0.125 deg run with CP disabled produces very encouraging results.