Keeley Rochelle Costigan

Four corners: The largest US methane anomaly viewed from space

Methane (CH4) is a potent greenhouse gas and ozone precursor. Quantifying methane emissions is critical for projecting and mitigating changes to climate and air quality. Here we present CH4 observations made from space combined with Earth-based remote sensing column measurements. Results indicate the largest anomalous CH4 levels viewable from space over the conterminous U.S. are located at the Four Corners region in the Southwest U.S. Emissions exceeding inventory estimates, totaling 0.59 Tg CH4/yr [0.50–0.67; 2σ], are necessary to bring high-resolution simulations and observations into agreement. This underestimated source approaches 10% of the EPA estimate of total U.S. CH4 emissions from natural gas. The persistence of this CH4 signal from 2003 onward indicates that the source is likely from established gas, coal, and coalbed methane mining and processing. This work demonstrates that space-based observations can identify anomalous CH4 emission source regions and quantify their emissions with the use of a transport model.

Virtual watersheds: simulating the water balance of the Rio Grande Basin

Managers of water resources in arid and semi-arid regions must allocate increasingly variable surface water supplies and limited groundwater resources. This challenge is leading to a new generation of detailed computational models that can link multiple sources to a wide range of demands. Detailed computational models of complex natural-human systems can help decision makers allocate scarce natural resources such as water. This article describes a virtual watershed model, the Los Alamos Distributed Hydrologic System (LADHS), which contains the essential physics of all elements of a regional hydrosphere and allows feedback between them. Unlike real watersheds, researchers can perform experiments on virtual watersheds, produce them relatively cheaply (once a modeling framework is established), and run them faster than real time. Furthermore, physics-based virtual watersheds do not require extensive tuning and are flexible enough to accommodate novel boundary conditions such as land-use change or increased climate variability. Essentially, virtual watersheds help resource managers evaluate the risks of alternatives once uncertainties have been quantified.

Atmospheric/hydrologic models for the Rio Grande Basin: simulations of precipitation variability

Abstract The headwaters of the Rio Grande are located in the San Juan Mountains of southwestern Colorado and the upper portions of the river are fed primarily by snowmelt from winter storms. In contrast, the lower portions of the river accumulate runoff from thunderstorms of the summer monsoon season. Thus, the waters of the Rio Grande are strongly influenced by regional climate and could be vulnerable to climate change. In order to study water resources in the Rio Grande Basin and how they may be affected by changes in regional climate, a modeling system, which relies on the use of coupled atmospheric, runoff, and ground water models, is being developed. Preliminary work on the project has focused on winter precipitation simulations of the upper Rio Grande Basin and evaluation of the suitability of the atmospheric model for simulating regional climate. This paper describes the spatial and temporal precipitation variability predicted by this model. To examine the temporal variability, results of simulations carried out with the Regional Atmospheric Modeling System (RAMS), at 20 km resolution, are presented for the month of January 1996, representing a dry extreme for the region, and January 1993, representing a recent wet extreme. Results are also presented of a case study with higher resolution (5 km) over the upper Rio Grande Basin to examine spatial variability of the snowpack within complex terrain. The simulation results are compared to observations of daily-accumulated precipitation in the region. The comparisons of model predicted precipitation indicate that the RAMS model can reproduce the interannual changes in precipitation patterns found in the western US. In the month of January 1996, both RAMS and observed precipitation are highest in the northern mountain ranges of the domain. Likewise, in the month of January 1993, both predicted and observed precipitation in the southern tier of states are dramatically higher. Results of the simulations with increased model grid resolution indicate a modest improvement of precipitation estimates with the finer grid resolution over the Rio Grande Basin.

Meteorological simulations of boundary-layer structure during the 1996 Paso del Norte Ozone Study

Meteorological simulations centered around the border cities of El Paso and Ciudad Juárez have been performed during an ozone episode that occurred on August 13, 1996 during the 1996 Paso del Norte Ozone Study field campaign. Simulations were performed using the HOTMAC boundary-layer meteorological model using a 1, 2, 4 and 8-km horizontal grid size nested mesh system. Investigation of the vertical structure and evolution of the atmospheric boundary layer for the August 12-14 time period is emphasized in this paper due to its suspected importance in precipitating the ozone episode [Sci Total Environ (2001)]. This period was characterized by a slowly-evolving high pressure system over the region, a persistent upper-level jet at 2500-3500 m above ground level (agl), deep daytime mixed layer heights of 3500 m depth and unusually deep nighttime stable layers extending up to 2500 m above the ground. The fact that the boundary-layer growth stalled on the morning of August 13 relative to that on August 12 has been suggested as a possible reason for the ozone episode on the 13th. In addition, relatively weak surface-level winds were measured on August 13. Using both model results and experimental data we hypothesize explanations for the slower mixed-layer growth on the morning of the 13th and the stronger surface-level winds found on the 12th and 14th.

W14_greenhousegas Multi-scale Atmospheric Modeling of Green House Gas Dispersion in Complex Terrain: Controlled Release Study

This slide deals with the following: Affordable artificial neural network and mini-sensor system to locate and quantify methane leaks on a well pad; ARPA-e project schematic for monitoring methane leaks

Multi-scale Atmospheric Modeling of Green House Gas Dispersion in Complex Terrain. Controlled Release Study

This report discusses the ghgas IC project which when applied, allows for an evaluation of LANLs HIGRAD model which can be used to create atmospheric simulations.

Multi-scale Atmospheric Modeling of Green House Gas Dispersion in Complex Terrain. Atmospheric Methane at Four Corners

Atmospheric models are compared in collaboration with LANL and the University of Michigan to understand emissions and the condition of the atmosphere from a model perspective.