Experimental Measurements of Expected Mass Fraction in a Contaminant Plume

The sudden release of a quantity of gas into the atmospheric boundary layer produces a contaminant cloud. The expected mass fraction function provides a relatively simple measure of the contaminant concentration values found within the cloud and represents the ensemble-averaged fraction of the conserved release mass found at the different contaminant concentration intervals as the cloud evolves. The plume generated by a line source in grid turbulence is used to investigate the expected mass fraction function as it applies to scalar concentration values found on a typical line normal to the plume axis. Simultaneous particle image velocimetry and planar laser induced fluorescence are used to measure velocity and concentration fields, respectively. The measured expected mass fraction functions are observed to be approximately self-similar when concentration values are normalized by the centreline mean concentration. The moments of the expected mass fraction function are observed to be simply related to the centreline moments of the probability density function of scalar concentration. Arguments based on a source fluid, non-source fluid decomposition of the scalar probability density function are used to explain these observations. The results are compared with the theoretical and experimental results established for a line source of scalar in grid turbulence.     

Analysis of the surface temperature and wind forecast errors of the NCAR-AirDat operational CONUS 4-km WRF forecasting system

Investigating the characteristics of model-forecast errors using various statistical and object-oriented methods is necessary for providing useful guidance to end-users and model developers as well. To this end, the random and systematic errors (i.e., biases) of the 2-m temperature and 10-m wind predictions of the NCAR-AirDat weather research and forecasting (WRF)-based real-time four-dimensional data assimilation (RTFDDA) and forecasting system are analyzed. This system has been running operationally over a contiguous United States (CONUS) domain at a 4-km grid spacing with four forecast cycles daily from June 2009 to September 2010. In the result an exceptionally useful forecast dataset was generated and used for studying the error properties of the model forecasts, in terms of both a longer time period and a broader coverage of geographic regions than previously studied. Spatiotemporal characteristics of the errors are investigated based on the 24-h forecasts between June 2009 and April 2010, and the 72-h forecasts between May and September 2010. It was found that the biases of both wind and temperature forecasts vary greatly seasonally and diurnally, with dependency on the forecast length, station elevation, geographical location, and meteorological conditions. The temperature showed systematic cold biases during the daytime at all station elevations and warm biases during the nighttime above 1,000 m above sea level (ASL), while below 600 m ASL cold biases occurred during the nighttime. The forecasts of surface wind speed exhibited strong positive biases during the nighttime, while the negative biases were observed in the spring and summer afternoons. The surface wind speed was mostly over-predicted except for the stations located between 1,000 and 2,100 m ASL, for which negative biases were identified for most forecast cycles. The highest wind-speed errors were found over the high terrain and near sea-level stations. The wind-direction errors were relatively large at the high-terrain elevation in the Rocky and Appalachian mountain ranges and the western coastal areas and the error structure exhibited notable diurnal variability.     

Leveraging modern climatology to increase adaptive capacity across protected area networks

Human-driven changes in the global environment pose an increasingly urgent challenge for the management of ecosystems that is made all the more difficult by the uncertain future of both environmental conditions and ecological responses. Land managers need strategies to increase regional adaptive capacity, but relevant and rapid assessment approaches are lacking. To address this need, we developed a method to assess regional protected area networks across biophysically important climatic gradients often linked to biodiversity and ecosystem function. We plot the land of the southwestern United States across axes of historical climate space, and identify landscapes that may serve as strategic additions to current protected area portfolios. Considering climate space is straightforward, and it can be applied using a variety of relevant climate parameters across differing levels of land protection status. The resulting maps identify lands that are climatically distinct from existing protected areas, and may be utilized in combination with other ecological and socio-economic information essential to collaborative landscape-scale decision-making. Alongside other strategies intended to protect species of special concern, natural resources, and other ecosystem services, the methods presented herein provide another important hedging strategy intended to increase the adaptive capacity of protected area networks.     

Analysis of drought determinants for the Colorado River Basin

Ongoing drought in the Colorado River Basin, unprecedented urban growth in the watershed, and numerical model simulations showing higher temperatures and lower precipitation totals in the future have all combined to heighten interest in drought in this region. In this investigation, we use principal components analysis (PCA) to independently assess the influence of various teleconnections on Basin-wide and sub-regional winter season Palmer Hydrological Drought Index (PHDI) and precipitation variations in the Basin. We find that the Pacific Decadal Oscillation (PDO) explains more variance in PHDI than El Niño-Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), and the planetary temperature combined for the Basin as a whole. When rotated PCA is used to separate the Basin into two regions, the lower portion of the Basin is similar to the Basin as a whole while the upper portion, which contains the high-elevation locations important to hydrologic yield for the watershed, demonstrates poorly defined relationships with the teleconnections. The PHDI for the two portions of the Basin are shown to have been out of synch for much of the twentieth century. In general, teleconnection indices account for 19% of the variance in PHDI leaving large uncertainties in drought forecasting.     

A study of arctic sea ice and sea‐level pressure using POP and neural network methods

Abstract

We examine Arctic sea‐ice concentration (SIC) and sea‐level pressure (SLP) data using principal oscillation pattern (POP) and neural network methods. The POP method extracts oscillating patterns from multivariate time series, each pattern being characterized by an oscillation period and a decay time. Predictions can be made for patterns whose decay time is comparable with the period. For both the SIC and SLP, however, the decay times are much shorter than the oscillation periods, and therefore the forcast skill is poor. A neural network is a model of the learning behaviour of a living neural system. Presented with training data, a neural network can learn the linear or non‐linear rules embedded in the data. We trained neural networks with sea‐ice and sea‐level pressure data, and estimated the forecast skill using a cross‐validation technique. The neural networks did not exhibit forecast skill significantly better than that of persistence. We contrast the Arctic situation with previous studies in which POP and neural networks were successfully used to forecast El Niño at lead times up to 6 months. Reasons for the lack of skill in both methods are discussed.     

Application of the Canadian regional climate model to the Laurentian great lakes region: Implementation of a lake model

Abstract

This study reports on the implementation of an interactive mixed‐layer/thermodynamic‐ice lake model coupled with the Canadian Regional Climate Model (CRCM). For this application the CRCM, which uses a grid mesh of 45 km on a polar stereographic projection, 10 vertical levels, and a timestep of 15 min, is nested with the second generation Canadian General Circulation Model (GCM) simulated output. A numerical simulation of the climate of eastern North America, including the Laurentian Great Lakes, is then performed in order to evaluate the coupled model. The lakes are represented by a “mixed layer” model to simulate the evolution of the surface water temperature, and a thermodynamic ice model to simulate evolution of the ice cover. The mixed‐layer depth is allowed to vary spatially. Lake‐ice leads are parametrized as a function of ice thickness based on observations. Results from a 5‐year integration show that the coupled CRCM/lake model is capable of simulating the seasonal evolution of surface temperature and ice cover in the Great Lakes. When compared with lake climatology, the simulated mean surface water temperature agrees within 0.12°C on average. The seasonal evolution of the lake‐ice cover is realistic but the model tends to underestimate the monthly mean ice concentration on average. The simulated winter lake‐induced precipitation is also shown, and snow accumulation patterns on downwind shores of the lakes are found to be realistic when compared with observations.     

The climate-population nexus in the East African Horn: Emerging degradation trends in rangeland and pastoral livelihood zones

Increasing climate variability and extreme weather conditions along with declining trends in both rainfall and temperature represent major risk factors affecting agricultural production and food security in many regions of the world. The rangelands of Ethiopia, Kenya, and Somalia in the East African Horn remain one of the world's most food insecure regions, yet have substantially increasing human populations predominantly dependent on pastoralist and agro-pastoralist livelihoods. We identify regions where substantial rainfall decrease between two periods interrupted by the 1998 El Nino event (1981–2012) in the East African Horn is coupled with human population density increases. Vegetation in this region is characterized by a variable mosaic of land covers, generally dominated by grasslands necessary for agro-pastoralism, interspersed by woody vegetation. Recent assessments indicate that vegetation degradation is occurring, adversely impacting fragile ecosystems and human livelihoods. Using AVHRR and MODIS vegetation products from 1981 to 2012, we observe changes in vegetation patterns and productivity over the last decade across the East African Horn. We observe vegetation browning trends in areas experiencing reduced main-growing season precipitation; these areas are also concurrently experiencing increasing population pressures. We also found that the drying precipitation patterns only partially statistically explain the vegetation browning trends, indicating that other factors such as population pressures and land use changes might be responsible for the observed declining vegetation condition. Furthermore, we show that the general vegetation browning trends persist even during years with normal rainfall conditions such as 2012, pointing to potential long-term degradation of rangelands on which approximately 10 million people depend. These findings may have implications for current and future regional food security monitoring and forecasting as well as for mitigation and adaptation strategies in a region where population is expected to continue increasing against a backdrop of drying climate trends and increased climatic variability.     

On the climate response of the low-latitude Pacific Ocean to changes in the global freshwater cycle

Under global warming, the predicted intensification of the global freshwater cycle will modify the net freshwater flux at the ocean surface. Since the freshwater flux maintains ocean salinity structures, changes to the density-driven ocean circulation are likely. A modified ocean circulation could further alter the climate, potentially allowing rapid changes, as seen in the past. The relevant feedback mechanisms and timescales are poorly understood in detail, however, especially at low latitudes where the effects of salinity are relatively subtle. In an attempt to resolve some of these outstanding issues, we present an investigation of the climate response of the low-latitude Pacific region to changes in freshwater forcing. Initiated from the present-day thermohaline structure, a control run of a coupled ocean–atmosphere general circulation model is compared with a perturbation run in which the net freshwater flux is prescribed to be zero over the ocean. Such an extreme experiment helps to elucidate the general adjustment mechanisms and their timescales. The atmospheric greenhouse gas concentrations are held constant, and we restrict our attention to the adjustment of the upper 1,000 m of the Pacific Ocean between 40°N and 40°S, over 100 years. In the perturbation run, changes to the surface buoyancy, near-surface vertical mixing and mixed-layer depth are established within 1 year. Subsequently, relative to the control run, the surface of the low-latitude Pacific Ocean in the perturbation run warms by an average of 0.6°C, and the interior cools by up to 1.1°C, after a few decades. This vertical re-arrangement of the ocean heat content is shown to be achieved by a gradual shutdown of the heat flux due to isopycnal (i.e. along surfaces of constant density) mixing, the vertical component of which is downwards at low latitudes. This heat transfer depends crucially upon the existence of density-compensating temperature and salinity gradients on isopycnal surfaces. The timescale of the thermal changes in the perturbation run is therefore set by the timescale for the decay of isopycnal salinity gradients in response to the eliminated freshwater forcing, which we demonstrate to be around 10–20 years. Such isopycnal heat flux changes may play a role in the response of the low-latitude climate to a future accelerated freshwater cycle. Specifically, the mechanism appears to represent a weak negative sea surface temperature feedback, which we speculate might partially shield from view the anthropogenically-forced global warming signal at low latitudes. Furthermore, since the surface freshwater flux is shown to play a role in determining the ocean’s thermal structure, it follows that evaporation and/or precipitation biases in general circulation models are likely to cause sea surface temperature biases.