Ruby Leung

The North American Regional Climate Change Assessment Program: Overview of Phase I Results

The North American Regional Climate Change Assessment Program (NARCCAP) is an international effort designed to investigate the uncertainties in regional-scale projections of future climate and produce highresolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere–ocean general circulation models (AOGCMs) forced with the Special Report on Emission Scenarios (SRES) A2 scenario, with a common domain covering the conterminous United States, northern Mexico, and most of Canada. The program also includes an evaluation component (phase I) wherein the participating RCMs, with a grid spacing of 50 km, are nested within 25 years of National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis II. This paper provides an overview of evaluations of the phase I domain-wide simulations focusing on monthly and seasonal temperature and precipitation, as well as more detailed investigation of four subregions. The overall quality of the simulations i...

North American extreme temperature events and related large scale meteorological patterns: A review of statistical methods, dynamics, modeling, and trends

Abstract The objective of this paper is to review statistical methods, dynamics, modeling efforts, and trends related to temperature extremes, with a focus upon extreme events of short duration that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). The statistics, dynamics, and modeling sections of this paper are written to be autonomous and so can be read separately. Methods to define extreme events statistics and to identify and connect LSMPs to extreme temperature events are presented. Recent advances in statistical techniques connect LSMPs to extreme temperatures through appropriately defined covariates that supplement more straightforward analyses. Various LSMPs, ranging from synoptic to planetary scale structures, are associated with extreme temperature events. Current knowledge about the synoptics and the dynamical mechanisms leading to the associated LSMPs is incomplete. Systematic studies of: the physics of LSMP life cycles, comprehensive model assessment of LSMP-extreme temperature event linkages, and LSMP properties are needed. Generally, climate models capture observed properties of heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreak frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Modeling studies have identified the impact of large-scale circulation anomalies and land–atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs to more specifically understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated. The paper concludes with unresolved issues and research questions.

Investigating the nexus of climate, energy, water, and land at decision-relevant scales: the Platform for Regional Integrated Modeling and Analysis (PRIMA)

The Platform for Regional Integrated Modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture and land use, socioeconomics, and energy systems using a flexible coupling approach. Stakeholder decision support needs underpin the application of the platform to regional issues, and an uncertainty characterization process is used to identify robust decisions. The platform can be customized to inform a variety of complex questions, such as how a policy in one sector might affect the ability to meet climate mitigation targets or adaptation goals in another sector. Current numerical experiments focus on the eastern United States, but the framework is designed to be regionally flexible. This paper provides a high-level overview of PRIMA’s functional capabilities and describes some key challenges and opportunities associated with integrated regional modeling.

Error Characteristics of Two Grid Refinement Approaches in Aquaplanet Simulations: MPAS-A and WRF

AbstractThis study compares the error characteristics associated with two grid refinement approaches including global variable resolution and nesting for high-resolution regional climate modeling. The global variable-resolution model, Model for Prediction Across Scales-Atmosphere (MPAS-A), and the limited-area model, Weather Research and Forecasting Model (WRF), are compared in an idealized aquaplanet context. For MPAS-A, simulations have been performed with a quasi-uniform-resolution global domain at coarse (1°) and high (0.25°) resolution, and a variable-resolution domain with a high-resolution region at 0.25° configured inside a coarse-resolution global domain at 1° resolution. Similarly, WRF has been configured to run on a coarse (1°) and high (0.25°) tropical channel domain as well as a nested domain with a high-resolution region at 0.25° nested two-way inside the coarse-resolution (1°) tropical channel. The variable-resolution or nested simulations are compared against the high-resolution simulation...

A modeling study of coastal inundation induced by storm surge, sea-level rise, and subsidence in the Gulf of Mexico

Abstract The northern coasts of the Gulf of Mexico (GoM) are highly vulnerable to the direct threats of climate change, such as hurricane-induced storm surge, and such risks are exacerbated by land subsidence and global sea-level rise. This paper presents an application of a coastal storm surge model to study the coastal inundation process induced by tide and storm surge, and its response to the effects of land subsidence and sea-level rise in the northern Gulf coast. The unstructured-grid finite-volume coastal ocean model was used to simulate tides and hurricane-induced storm surges in the GoM. Simulated distributions of co-amplitude and co-phase lines for semi-diurnal and diurnal tides are in good agreement with previous modeling studies. The storm surges induced by four historical hurricanes (Rita, Katrina, Ivan, and Dolly) were simulated and compared to observed water levels at National Oceanic and Atmospheric Administration tide stations. Effects of coastal subsidence and future global sea-level rise on coastal inundation in the Louisiana coast were evaluated using a “change of inundation depth” parameter through sensitivity simulations that were based on a projected future subsidence scenario and 1-m global sea-level rise by the end of the century. Model results suggested that hurricane-induced storm surge height and coastal inundation could be exacerbated by future global sea-level rise and subsidence, and that responses of storm surge and coastal inundation to the effects of sea-level rise and subsidence are highly nonlinear and vary on temporal and spatial scales.

A case study of urbanization impact on summer precipitation in the Greater Beijing Metropolitan Area: Urban heat island versus aerosol effects

Convection-resolving ensemble simulations using the WRF-Chem model coupled with a single-layer Urban Canopy Model are conducted to investigate the individual and combined impacts of land use and anthropogenic pollutant emissions from urbanization on a heavy rainfall event in the Greater Beijing Metropolitan Area (GBMA) in China. The simulation with the urbanization effect included generally captures the spatial pattern and temporal variation of the rainfall event. An improvement of precipitation is found in the experiment including aerosol effect on both clouds and radiation. The expanded urban land cover and increased aerosols have an opposite effect on precipitation processes, with the latter playing a more dominant role, leading to suppressed convection and rainfall over the upstream (northwest) area, and enhanced convection and more precipitation in the downstream (southeast) region of the GBMA. In addition, the influence of aerosol indirect effect is found to overwhelm that of direct effect on precipitation in this rainfall event. Increased aerosols lead to more cloud droplets with smaller size, which favor evaporative cooling and reduce updrafts and suppress convection over the upstream (northwest) region in the early stage of the rainfall event. As the rainfall system propagates southeastward, more latent heat is released due to the freezing of larger number of smaller cloud drops that are lofted above the freezing level, which is responsible for the increased updraft strength and convective invigoration over the downstream (southeast) area.

Reply to “Comments on ‘The North American Regional Climate Change Assessment Program: Overview of Phase I Results'”

The authors of Mearns et al. (2012) are well aware of the role of driving RCMs with reanalyses and have written extensively on the roles of different types of RCM simulations (e.g., Giorgi and Mearns, 1999; Leung et al., 2003). Thus, we agree that the skill of dynamical downscaling in which global reanalysis is used to provide boundary conditions in general indicates an upper bound of skill compared to dynamical downscaling in which the boundary conditions come from global climate model simulations. This finding has long been established as global climate model simulations cannot outperform global reanalysis in providing boundary conditions since the latter is constrained by observations through data assimilation (that is unless the reanalyses themselves have been shown to have serious deficiences, e.g. Cerezo-Mota et al, 2011). The classification of different types of dynamical downscaling introduced by Castro et al. (2005) further adds clarity to this point.

Recent progress and review of issues related to Physics Dynamics Coupling in geophysical models

AbstractNumerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid ...Geophysical models of the atmosphere and ocean invariably involve parameterizations. These represent two distinct areas: a) Subgrid processes which the model cannot (yet) resolve, due to its discrete resolution, and b) sources in the equation, due to radiation for example. Hence coupling between these physics parameterizations and the resolved fluid dynamics and also between the dynamics of the different fluids in the system (air and water) is necessary. This coupling is an important aspect of geophysical models. However, often model development is strictly segregated into either physics or dynamics. Hence, this area has many more unanswered questions than in-depth understanding. Furthermore, recent developments in the design of dynamical cores (e.g. significant increase of resolution, move to non-hydrostatic equation sets etc), extended process physics (e.g. prognostic micro physics, 3D turbulence, non-vertical radiation etc) and predicted future changes of the computational infrastructure (e.g. Exascale with its need for task parallelism, data locality and asynchronous time stepping for example) is adding even more complexity and new questions. This paper reviews the state-of-the-art of the physics-dynamics coupling in geophysical models, surveys the analysis techniques, and points out the open questions in this research field.