Variable-density flow in the subsurface of oceanic islands : physical experiments and numerical modeling

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Snow Depth Distribution Patterns and Consistency from Airborne Lidar Time Series

Snow provides fresh meltwater to over a billion people worldwide. Snow dominated watersheds drive western US water supply and are increasingly important as demand depletes reservoir and groundwater recharge capabilities. This motivates our inter- and intra-annual investigation of snow distribution patterns, leveraging the most comprehensive airborne lidar survey (ALS) dataset for snow. Validation results for ALS from both the NASA SnowEx 2017 campaign in Grand Mesa, Colorado and the time series dataset from the Tuolumne River Basin in the Sierra Nevada, in California, are presented. We then assess the consistency in the snow depth patterns for the entire basin (at 20-m resolution) and for subbasin regions (at 3-m resolution) from a collection of 51 ALS that span a six-year period (2013-2018) in the Tuolumne Basin. Strong correlations between ALS from different years near peak SWE confirm that spatial patterns exist between snow seasons. Year-to-year snow depth differs in absolute magnitude, but relative differences are consistent spatially, such that deep and shallow zones occur in the same location. We further show that elevation is the terrain parameter with the largest correlation to snow depth at the basin scale, and we map the expected pattern distribution for periods with similar snow-covered extents. Lastly, we show at a subbasin scale that distribution patterns are more consistent in vegetation-limited areas (bedrock dominated terrain and open meadows) compared to vegetation-rich zones (valley hillslopes and dense canopy cover). The maps of snow patterns and their consistency can be used to determine optimal locations of new long-term monitoring sites, design sampling strategies for future snow surveys, and to improve high resolution snow models

As zonas de vida baseadas em condições bioclimáticas no estado do Ceará, Brasil

The Holdridge life zone approach is a useful tool for planning the territorial management of natural resources as well as for supporting the development of strategies and public policies that result in the definition of priority areas for conservation and sustainable use of forests. Thus, in the present study, we aimed to identify and describe the life zones that occur in the state of Ceará based on the Holdridge model. For this purpose, we used data on annual precipitation, biotemperature and potential evapotranspiration ratio. The results indicated that, although the state of Ceará is mostly under the influence of a semi-arid macroclimate, it presents a heterogeneous geographic space, in which different life zones associated with bioclimatic diversity occur. The most important bioclimatic variable for the classification of life zones was the potential evapotranspiration ratio, which represents the amount of water that is transferred to the atmosphere in relation to the amount of water that is precipitated in a given location. The Holdridge climatic classification identified eight life zones, all located in the tropical latitudinal zone and basal (90.04% of the Ceará territory) and premontane (9.96%) altitudinal zones, which vary, in terms of humidity, from very dry forests to humid forests. The most extensive life zone comprises the transition areas between very dry forest and basal tropical dry forest, occupying 64,825.69 km2, which covers 43.54% of the Ceará territory.A definição das zonas de vida de Holdridge é uma ferramenta útil para o planejamento da gestão territorial dos recursos naturais, bem como para subsidiar a elaboração de estratégias e políticas públicas que resultem na definição de áreas prioritárias para conservação e uso sustentável das florestas. Desse modo, o presente estudo teve por objetivo identificar e descrever as zonas de vida que ocorrem no estado do Ceará com base no modelo de Holdridge. Para esse propósito, foram utilizados dados de precipitação anual, biotemperatura e relação de evapotranspiração potencial. Os resultados indicaram que, embora o estado do Ceará esteja majoritariamente sob a influência de um macroclima semiárido, apresenta um espaço geográfico heterogêneo, no qual ocorrem diferentes zonas de vida associadas à diversidade bioclimática. A variável bioclimática mais importante para a classificação das zonas de vida foi a relação de evapotranspiração potencial, que representa a quantidade de água que é transferida para a atmosfera em relação a quantidade de água que é precipitada em determinado local. A classificação climática de Holdridge identificou oito zonas de vida em que todas pertencem à faixa latitudinal tropical e abrangem faixas altitudinais basais (90,04% do território cearense) e premontanas (9,96%), que variam em termos de umidade, desde florestas muito secas até florestas úmidas. A zona de vida mais extensa compreende as áreas de transição entre floresta muito seca e floresta seca tropical basal, ocupando 64.825,69 km2, que recobre 43,54% da área total do estado

The Influence of PBL Parameterization on the Practical Predictability of Convection Initiation During the Mesoscale Predictability Experiment (MPEX)

This study evaluates the influence of planetary boundary layer (PBL) parameterizations on short-range (0-15 h) forecasts of convection initiation (CI) within convection-allowing ensembles that utilize sub-synoptic-scale observations collected during the Mesoscale Predictability Experiment (MPEX). Running five thirty-member ensembles with the Advanced Research Weather Research and Forecasting Model (WRF-ARW) with each differing only in the chosen PBL parameterization, forecast skill, PBL sensitivity on the environment in which CI occurred, and the variability within are examined. Three MPEX cases, 19-20 May 2013, 31 May-1 June 2013, and 8-9 June 2013 are considered, each characterized by a different large-scale flow pattern to analyze a wider spectrum of events. Using an object-based method to verify and analyze the forecasts of CI, it was found that none of the Five PBL schemes analyzed significantly improved the forecast skill. The non-local mixing PBL schemes, MYJ and QNSE, had in all cases higher probability of detection (POD) but consequently had a higher false alarm ratio (FAR) resulting from the models overproducing the number of CI objects, with all PBLs, and thus resulting in relative high bias scores as well. The CSI showed only subtle changes between PBL schemes suggesting no one PBL scheme drastically outperforms the other. The temporal distribution of errors associated with the “hits” in the CI object matching showed an approximate normal distribution around a mean of 0-s suggesting little systematic timing bias. While the spatial distribution of errors yielded skewed distributions with on average a mean (median) distance error of just over 44-km (28-km). Analysis of cumulative distribution functions (CDFs) of the “hits” highlighted limits to increased forecast skill beyond temporal and spatial thresholds of 60-min and 100-km. Mean error (ME) plots computed for surface features as well as vertical profiles in pre-convective environments highlighted biases in both the initial conditions as well as between ensembles. In agreement with previous studies, it was found that non-local mixing PBL schemes tend to produce PBLs that are too shallow, cool, and moist while local mixing schemes tend to be deeper, warmer, and drier as a function of the stronger (weaker) vertical mixing within the local (non-local) PBL schemes. Relative to the analysis of the vertical profiles, it was seen that the model has an inherent inability to accurately represent strong capping inversions in models across all PBL schemes suggesting an issue with the handling of vertical diffusion within the PBL and the implicit damping associated with the discretization schemes used within WRF

Resilient Urban Futures

This open access book addresses the way in which urban and urbanizing regions profoundly impact and are impacted by climate change. The editors and authors show why cities must wage simultaneous battles to curb global climate change trends while adapting and transforming to address local climate impacts. This book addresses how cities develop anticipatory and long-range planning capacities for more resilient futures, earnest collaboration across disciplines, and radical reconfigurations of the power regimes that have institutionalized the disenfranchisement of minority groups. Although planning processes consider visions for the future, the editors highlight a more ambitious long-term positive visioning approach that accounts for unpredictability, system dynamics and equity in decision-making. This volume brings the science of urban transformation together with practices of professionals who govern and manage our social, ecological and technological systems to design processes by which cities may achieve resilient urban futures in the face of climate change

Resilient Urban Futures

This open access book addresses the way in which urban and urbanizing regions profoundly impact and are impacted by climate change. The editors and authors show why cities must wage simultaneous battles to curb global climate change trends while adapting and transforming to address local climate impacts. This book addresses how cities develop anticipatory and long-range planning capacities for more resilient futures, earnest collaboration across disciplines, and radical reconfigurations of the power regimes that have institutionalized the disenfranchisement of minority groups. Although planning processes consider visions for the future, the editors highlight a more ambitious long-term positive visioning approach that accounts for unpredictability, system dynamics and equity in decision-making. This volume brings the science of urban transformation together with practices of professionals who govern and manage our social, ecological and technological systems to design processes by which cities may achieve resilient urban futures in the face of climate change