Reference evapotranspiration from coarse-scale and dynamically downscaled data in complex terrain: Sensitivity to interpolation and resolution

The main objective of this study was to investigate whether dynamically downscaled high resolution (4-km) climate data from the Weather Research and Forecasting (WRF) model provide physically meaningful additional information for reference evapotranspiration (E) calculation compared to the recently published GridET framework that uses interpolation from coarser-scale simulations run at 32-km resolution. The analysis focuses on complex terrain of Utah in the western United States for years 1985–2010, and comparisons were made statewide with supplemental analyses specifically for regions with irrigated agriculture. E was calculated using the standardized equation and procedures proposed by the American Society of Civil Engineers from hourly data, and climate inputs from WRF and GridET were debiased relative to the same set of observations. For annual mean values, E from WRF (EW) and E from GridET (EG) both agreed well with E derived from observations (r2 = 0.95, bias \u3c 2 mm). Domain-wide, EW and EG were well correlated spatially (r2 = 0.89), however local differences ΔE=EW-EG were as large as +439 mm year−1 (+26%) in some locations, and ΔE averaged +36 mm year−1. After linearly removing the effects of contrasts in solar radiation and wind speed, which are characteristically less reliable under downscaling in complex terrain, approximately half the residual variance was accounted for by contrasts in temperature and humidity between GridET and WRF. These contrasts stemmed from GridET interpolating using an assumed lapse rate of Γ = 6.5K km−1, whereas WRF produced a thermodynamically-driven lapse rate closer to 5K km−1 as observed in mountainous terrain. The primary conclusions are that observed lapse rates in complex terrain differ markedly from the commonly assumed Γ = 6.5K km−1, these lapse rates can be realistically resolved via dynamical downscaling, and use of constant Γ produces differences in E of order as large as 102 mm year−1

Characteristics of historical precipitation in high mountain asia based on a 15-year high resolution dynamical downscaling

The mountains of High Mountain Asia serve as an important source of water for roughly one billion people living downstream. This research uses 15 years of dynamically downscaled precipitation produced by the Weather Research and Forecasting (WRF) model to delineate contrasts in precipitation characteristics and events between regions dominated by the Indian Summer Monsoon (ISM) versus westerly disturbances during the cool season (December to March). Cluster analysis reveals a more complex spatial pattern than indicated by some previous studies and illustrates the increasing importance of westerly disturbances at higher elevations. Although prior research suggests that a small number of westerly disturbances dominate precipitation in the western Himalaya and Karakoram, the WRF-downscaled precipitation is less dominated by infrequent large events. Integrated vapor transport (IVT) and precipitation are tightly coupled in both regions during the cool season, with precipitation maximizing for IVT from the south-southwest over the Karakoram and southeast-southwest over the western Himalaya. During the ISM, Karakoram precipitation is not strongly related to IVT direction, whereas over the western Himalaya, primary and secondary precipitation maxima occur for flow from the west-southwest and northwest, respectively. These differences in the drivers and timing of precipitation have implications for hydrology, glacier mass balance, snow accumulation, and their sensitivity to climate variability and change

iSAW: Integrating Structure, Actors, and Water to Study Socio-Hydro-Ecological Systems

Urbanization, climate, and ecosystem change represent major challenges for managing water resources. Although water systems are complex, a need exists for a generalized representation of these systems to identify important components and linkages to guide scientific inquiry and aid water management. We developed an integrated Structure-Actor-Water framework (iSAW) to facilitate the understanding of and transitions to sustainable water systems. Our goal was to produce an interdisciplinary framework for water resources research that could address management challenges across scales (e.g., plot to region) and domains (e.g., water supply and quality, transitioning, and urban landscapes). The framework was designed to be generalizable across all human–environment systems, yet with sufficient detail and flexibility to be customized to specific cases. iSAW includes three major components: structure (natural, built, and social), actors (individual and organizational), and water (quality and quantity). Key linkages among these components include: (1) ecological/hydrologic processes, (2) ecosystem/geomorphic feedbacks, (3) planning, design, and policy, (4) perceptions, information, and experience, (5) resource access and risk, and (6) operational water use and management. We illustrate the flexibility and utility of the iSAW framework by applying it to two research and management problems: understanding urban water supply and demand in a changing climate and expanding use of green storm water infrastructure in a semi-arid environment. The applications demonstrate that a generalized conceptual model can identify important components and linkages in complex and diverse water systems and facilitate communication about those systems among researchers from diverse disciplines

Climate Modeling to Support Urban Water Management in the Wasatch Range

Urban water management involves providing water supply, stormwater drainage control, and wastewater management in cities. In the metropolitan areas along the Wasatch Front metropolitan areas area faced with numerous urban water management challenges and climate is a factor in most cases. This is similar to most other metropolitan areas in the world. However, along the Wasatch Front and elsewhere, due to many factors those responsible for urban water management have yet to embrace climate information in the management of water resources. As part of the Cyberinfrastructure to Advance High Performance Water Resource Modeling (CI-WATER) project, we are developing software tools to bridge the computationally expensive gap between global climate models (~100-km spatial scale) and urban water resource models (scale). We are also developing analysis capacity and data resources in cooperation with local urban water management professionals to aid the transformation of advanced climate-water resources modeling into a tool used by the urban water management community. Our first step focuses on understanding the future of water along the Wasatch front and how it impacts urban water management. For example, Pacific modes of variability such as the El Niño-Southern Oscillation (ENSO) influence Wasatch precipitation over a range of time scales (Hidalgo and Dracup, 2003; Wang et al. 2010). The latest climate model projections for the next century (CMIP5; Taylor et al. [2011]) remain widely varied in their simulation of ENSO (Guilyardi et al. 2012), and quantifying water resources in the Wasatch and Intermountain West in general will require quantifying how the uncertain state of the Pacific combines with projected climate change to alter the probability space of total precipitation, rainsnow partitioning, and melt timing. Our second step will utilize basin-scale statistical downscaling and dynamical downscaling of coarse-scale climate model output into forms useable by urban water supply system, urban watershed, and stormwater runoff models. The urban water modeling systems will be embedded within a stochastic simulation framework to enable uncertainty analysis to be added into urban water management. The research is investigating urban water management modeling needs that can be informed by downscaled climate model output and the impacts of natural variability versus climate change projections on urban water management systems. Guilyardi, E., H. Bellenger, P. Braconnot, M. Collins, S. Ferett, J. Leloup, W. Cai, A. Wittenberg, S.-W. Yeh, and Y.-G. Ham, 2012: A first look at ENSO in CMIP5. WCRP Workshop on CMIP5 Model Analysis, University of Hawaii, Honolulu, HI, 5-9 March 2012. Hidalgo, Hugo G., John A. Dracup, 2003: ENSO and PDO Effects on Hydroclimatic Variations of the Upper Colorado River Basin. J. Hydrometeor, 4, 5–23. Taylor, K.E., Stouffer, R.J., and Meehl, G.A. (2011). “An overview of CMIP5 and the experiment design.” Bulletin of the American Meteorological Society, DOI 10.1175/BAMS-D-11-00094.1 Wang, Shih-Yu, Robert R. Gillies, Jiming Jin, Lawrence E. Hipps, 2010: Coherence between the Great Salt Lake Level and the Pacific Quasi-Decadal Oscillation. J. Climate, 23, 2161–2177

Filling the Polar Data Gap in Sea Ice Concentration Fields Using Partial Differential Equations

The “polar data gap” is a region around the North Pole where satellite orbit inclination and instrument swath for SMMR and SSM/I-SSMIS satellites preclude retrieval of sea ice concentrations. Data providers make the irregularly shaped data gap round by centering a circular “pole hole mask” over the North Pole. The area within the pole hole mask has conventionally been assumed to be ice-covered for the purpose of sea ice extent calculations, but recent conditions around the perimeter of the mask indicate that this assumption may already be invalid. Here we propose an objective, partial differential equation based model for estimating sea ice concentrations within the area of the pole hole mask. In particular, the sea ice concentration field is assumed to satisfy Laplace’s equation with boundary conditions determined by observed sea ice concentrations on the perimeter of the gap region. This type of idealization in the concentration field has already proved to be quite useful in establishing an objective method for measuring the “width” of the marginal ice zone—a highly irregular, annular-shaped region of the ice pack that interacts with the ocean, and typically surrounds the inner core of most densely packed sea ice. Realistic spatial heterogeneity in the idealized concentration field is achieved by adding a spatially autocorrelated stochastic field with temporally varying standard deviation derived from the variability of observations around the mask. To test the model, we examined composite annual cycles of observation-model agreement for three circular regions adjacent to the pole hole mask. The composite annual cycle of observation-model correlation ranged from approximately 0.6 to 0.7, and sea ice concentration mean absolute deviations were of order 10 − 2 or smaller. The model thus provides a computationally simple approach to solving the increasingly important problem of how to fill the polar data gap. Moreover, this approach based on solving an elliptic partial differential equation with given boundary conditions has sufficient generality to also provide more sophisticated models which could potentially be more accurate than the Laplace equation version. Such generalizations and potential validation opportunities are discussed

The Role of Tropospheric Rossby Wave Breaking in the Pacific Decadal Oscillation

The leading pattern of extratropical Pacific sea surface temperature variability [the Pacific decadal oscillation (PDO)] is shown to depend on observed variability in the spatiotemporal distribution of tropospheric Rossby wave breaking (RWB), where RWB is the irreversible overturning of potential vorticity on isentropic surfaces. Composite analyses based on hundreds of RWB cases show that anticyclonic (cyclonic) RWB is associated with a warm, moist (cool, dry) column that extends down to a surface anticyclonic (cyclonic) circulation, and that the moisture and temperature advection associated with the surface circulation patterns force turbulent heat flux anomalies that project onto the spatial pattern of the PDO. The RWB patterns that are relevant to the PDO are closely tied to El Niño–Southern Oscillation, the Pacific–North American pattern, and the northern annular mode. These results explain the free troposphere-to-surface segment of the atmospheric bridge concept wherein El Niño anomalies emerge in summer and modify circulation patterns that act over several months to force sea surface temperature anomalies in the extratropical Pacific during late winter or early spring. Leading patterns of RWB account for a significant fraction of PDO interannual variability for any month of the year. A multilinear model is developed in which the January mean PDO index for 1958–2006 is regressed upon the leading principal components of cyclonic and anticyclonic RWB from the immediately preceding winter and summer months (four indexes in all), accounting for more than two-thirds of the variance