Operational snow modeling: Addressing the challenges of an energy balance model for National Weather Service forecasts

Prediction of snowmelt has become a critical issue in much of the western United States given the increasing demand for water supply, changing snow cover patterns, and the subsequent requirement of optimal reservoir operation. The increasing importance of hydrologic predictions necessitates that traditional forecasting systems be re-evaluated periodically to assure continued evolution of the operational systems given scientific advancements in hydrology. The National Weather Service (NWS) SNOW17, a conceptually based model used for operational prediction of snowmelt, has been relatively unchanged for decades. In this study, the Snow-Atmosphere-Soil Transfer (SAST) model, which employs the energy balance method, is evaluated against the SNOW17 for the simulation of seasonal snowpack (both accumulation and melt) and basin discharge. We investigate model performance over a 13-year period using data from two basins within the Reynolds Creek Experimental Watershed located in southwestern Idaho. Both models are coupled to the NWS runoff model [SACramento Soil Moisture Accounting model (SACSMA)] to simulate basin streamflow. Results indicate that while in many years simulated snowpack and streamflow are similar between the two modeling systems, the SAST more often overestimates SWE during the spring due to a lack of mid-winter melt in the model. The SAST also had more rapid spring melt rates than the SNOW17, leading to larger errors in the timing and amount of discharge on average. In general, the simpler SNOW17 performed consistently well, and in several years, better than, the SAST model. Input requirements and related uncertainties, and to a lesser extent calibration, are likely to be primary factors affecting the implementation of an energy balance model in operational streamflow prediction. © 2008 Elsevier B.V. All rights reserved

Scenarios of Solar Energy Use on the “Roof of the World” : Potentials and Environmental Benefits

Peripheral mountain areas in developing countries are often characterized by energy poverty but also by high solar energy potential. The Eastern Pamirs of Tajikistan are a prime example of this situation, with their lack of energy infrastructure, remoteness, pressure on local natural resources, and high incident radiation amounts. An integrative assessment of the potential for photovoltaic power generation is lacking for this region, as well as for many other mountain environments. We assessed the natural potential, feasibility, and likely effects of increased photovoltaic electricity generation, using climate data, biomass data, a spatial radiation model, and fieldwork- and literature-based scenarios of energy requirements and financial conditions. Results indicated that using a photovoltaic power plant to generate enough energy for boiling water is feasible in the study area within reasonable cost limits. This could significantly alleviate energy poverty, increase carbon sequestration by up to 1500 t/y, and reduce the loss of dwarf shrub stands by up to 2000 ha/y. Our results illustrate that the integrative approach presented in this article can be applied straightforwardly when some climatic measurements and field observations are available and that photovoltaic energy is an important renewable-energy resource for the sustainable development of peripheral high-mountain communities

Aerosol-cloud-precipitation interaction based on remote sensing and cloud-resolving modeling over the Central Himalayas

The Central Himalayan region experiences pronounced orographic precipitation related to the South Asian summer monsoon, typically occurring from June to September. Atmospheric aerosols can influence regional and global climate through aerosol-radiation (ARI) and aerosol-cloud interactions (ACI). The study of the aerosol-precipitation relationship over the Central Himalayan region during the summer monsoon season is important due to extreme pollution over the upwind Indo-Gangetic Plains, enhanced moisture supply through monsoonal flow, and steep terrain of the Himalayas modulating the orographic forcing. This dissertation aims to study the impact of atmospheric aerosols, from natural and anthropogenic sources, in modulating the monsoonal precipitation, cloud processes, and freezing isotherm over the central Himalayas. The long-term (2002 – 2017) satellite-retrieved and reanalysis datasets showed regardless of the meteorological forcing, compared to relatively cleaner days, polluted days with higher aerosol optical depth is characterized by the invigorated clouds and enhanced precipitation over the southern slopes and foothills of the Himalayas. The mean freezing isotherm increased by 136.2 meters in a polluted environment, which can be crucial and significantly impact the hydroclimate of the Himalayas. Due to the limitations of satellite-retrieved observational data, these results underlined the need for state-of-the-art Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in a cloud-resolving scale to better represent and study the impact of the aerosols from different sources through radiation and microphysics pathways over the complex terrain of the Central Himalayas. A cloud-resolving WRF-Chem simulation is performed to assess the impact of anthropogenic and remotely transported dust aerosols on the convective processes and elevation-dependent precipitation. Long-range transported dust aerosols significantly impacted cloud microphysical properties and enhanced the precipitation by 9.3% over the southern slopes of the Nepal Himalayas. The mid-elevation of the Central Himalayas, generally between 1000 and 3000 meters, acted as the region below and above which the diurnal variation and precipitation of various intensities (light, moderate, and heavy) responded differently for ARI, ACI, and the combined effect of aerosols. Due to the ARI effect of aerosols, the light precipitation is suppressed by 17% over the Central Himalayas. The ACI effect dominated and resulted in enhanced heavy precipitation by 12% below 2000 m ASL, which can potentially increase the risk for extreme events (floods and landslides). In contrast, above 2000 m ASL, the suppression of precipitation due to aerosols can be critical for the regional supply of water resources. The overview of the study suggests that the natural and anthropogenic aerosols significantly modulate the convective processes, monsoonal precipitation, and freezing isotherm over the Central Himalayan region, which could pose significant consequences to the changing Himalayan hydroclimate

Surface radiation budget for climate applications

The Surface Radiation Budget (SRB) consists of the upwelling and downwelling radiation fluxes at the surface, separately determined for the broadband shortwave (SW) (0 to 5 micron) and longwave (LW) (greater than 5 microns) spectral regions plus certain key parameters that control these fluxes, specifically, SW albedo, LW emissivity, and surface temperature. The uses and requirements for SRB data, critical assessment of current capabilities for producing these data, and directions for future research are presented

Dissémination des bactéries indicatrices de contamination fécale dans les hydrosystèmes tropicaux : transport et devenir d'Escherichia coli dans le bassin versant du Mékong au Laos

La contamination fécale des eaux de surface demeure une menace majeure pour la santé publique, en particulier dans les zones rurales des pays en développement. Les maladies diarrhéiques sont l'une des principales causes de décès notamment chez les enfants de moins de cinq ans, en raison de manque d'infrastructures sanitaires, et du faible accès aux ressources en eau salubre et aux soins médicaux. Plus de 70 millions de personnes dépendent de ressources en eau non améliorées dans le bassin inférieur du Mékong. Les progrès significatifs réalisés pour mieux comprendre la dynamique de la contamination fécale en milieu tempéré, de nombreuses lacunes subsistent en milieu tropical. Pour réduire la morbidité, il est nécessaire de mieux comprendre la dynamique des pathogènes fécaux surtout dans le contexte de changements globaux (croissance démographique, changements d'usage des terres, barrages hydroélectriques, et changement climatique). L'utilisation d'une approche multidisciplinaire est essentielle pour évaluer les risques contamination fécale à l'interface animal-homme-écosystème. L'objectif principal de la thèse est d'identifier les facteurs clés contrôlant le devenir et transport de la bactérie fécale indicatrice (FBI), Escherichia coli (E. coli), à différentes échelles spatiales des tributaires du Mekong au Laos. Cette thèse présente les résultats basés sur (i) les données in situ collectées dans les principaux tributaires du Mékong au Laos, afin d'identifier les facteurs (hydrologie et utilisation des terres) contrôlant les concentrations d'E. coli à l'échelle du bassin versant ; (ii) une approche expérimentale pour évaluer deux facteurs clés (rayonnement solaire et dépôt de particules en suspension) contrôlant la mortalié/survie d'E. coli dans une zone humide tropicale montagneuse; et (iii) des approches statistiques et de modélisation pour évaluer l'impact d'un barrage hydroélectrique sur la dynamique hydro-sédimentaire et d'E. coli dans un tributaire majeur du Mékong, la Nam Khan, au Laos. Les résultats des campagnes de mesures in situ ont révélé des variabilités saisonnières des concentrations d'E. coli dans les cours d'eau, plus élevées pendant la saison humide, et fortement corrélées aux concentrations en matières en suspension (MES) et aux pourcentages de forêts exploitées à l'échelle du bassin versant. Ces résultats soulignent le rôle des MES en tant que vecteurs pour le transport bactérien, ainsi que l'importance de des usages des terres comme l'un des facteurs clés ayant un impact sur la dissémination d'E. coli à l'échelle du bassin versant dans un contexte tropical érosif. La majorité des tributaires échantillonnés présentaient des concentrations d'E. coli pendant la saison des pluies, dépassant 500 colonies par 100 ml, seuil au-delà duquel l'OMS considère que le risque de maladie gastro-intestinale après une seule exposition est de 10 %. Le rôle des MES a été mis en évidence dans l'approche expérimentale, où les bactéries attachées à des particules étaient prédominantes (91%) et présentaient des taux de mortalité plus faibles que ceux des bactéries sous forme libre. Alors que le processus de dépôt était le principal facteur de réduction du stock d'E. coli dans la colonne d'eau, comparé aux radiations solaires, nous avons constaté que la remise en suspension temporaire des sédiments déposés suggérait un potentiel de survie ou même de croissance d'E. coli dans les sédiments en milieu tropical. Enfin, étant donné l'importance de la dynamique hydro-sédimentaire sur la dissémination bactérienne, nous avons évalué l'impact du barrage, reflété par des diminutions brutales en termes de débit (en moyenne de 42%), et les concentrations en MES et E. coli (en moyenne de 89%) mesurées en aval du barrage. Cette approche fournit de nouvelles preuves de l'atténuation de la contamination bactérienne induite par le barrage. Dans l'ensemble, ces résultats de thèse fournissent de nouvelles informations sur la dynamique des FBI dans le bassin inférieur du Mékong, qui pourraient être utiles dans l'établissement des stratégies efficaces de gestion des ressources en eau.Fecal contamination of surface water remains a major threat to public health especially in the rural areas of developing countries. Diarrheal diseases are a leading cause of death especially among children under age five, due to inadequate sanitation infrastructure, low access to safe water resources, and poor medical care in developing countries. Over 70 million people depend on unimproved water resources in the lower Mekong basin stretching from southern Chinese border to the delta in southern Vietnam. Despite the significant advances made towards a better understanding of the fecal contamination dynamics in temperate regions, yet many knowledge gaps exist in tropical conditions. Reducing the disease burden, requires a better understanding of fecal pathogens dynamics in the context of rapid global changes, e.g. population growth, land use changes, hydropower dam constructions, and climate change. Therefore, the use of a multi-disciplinary approach is essential to adress existing and potential risks of fecal contamination at the animal-human-ecosystems interface. The main objective here was to identify key factors controlling the fate and transport of the fecal indicator bacteria (FIB), Escherichia coli (E. coli), at different spatial scales of major Mekong tributaries in Lao PDR. This research work presents the results from (i) in-situ data collected from major Mekong tributaries from northern to southern Lao PDR aiming to identify main factors (hydrology and land use) controlling the in-stream E. coli concentrations at watershed-scale; (ii) experimental approach to assess two key factors (solar radiation exposition and suspended particles deposition) controlling E. coli decay/survival in a mountainous tropical headwater wetland; and (iii) statistical and modeling approaches to assess the impact of hydropower dam on hydro-sedimentary and E. coli dynamics in a major Mekong tributary, the Nam Khan in northern Lao PDR. Our spatial and temporal monitoring results reported seasonal variabilities of in-stream E. coli concentrations, significantly higher during the wet season, and strongly correlated to total suspended sediment (TSS) concentration, and unstocked forests percentage areas at watershed-scale. These results point out the role of TSS as an important vector for bacterial transport, as well as the importance of land use management as one of major factors affecting E. coli dissemination at watershed-scale in a tropical context prone to soil erosion. The majority of sampled tributaries had E. coli concentrations during the rainy season, exceeding 500 colonies per 100 mL, the threshold above which the WHO considers a 10% risk of gastrointestinal illness after one single exposure. The role of TSS in E. coli dynamics was further highlighted in the experimental approach, where particle-attached E. coli were predominant (91%) and showed lower decay rates as opposed to those of free-living E. coli. While deposition process was the main factor for E. coli stock reduction in the water column as opposed to solar radiation, we found that temporary resuspension of deposited sediments suggested a potential E. coli survival or even a regrowth in the sediment under tropical conditions. At last, given the importance of the hydro-sedimentary dynamics on bacterial dissemination, we assessed the dam impact reflected by abrupt decreases in terms of discharge (by an average of 42%), as well as TSS and E. coli concentrations (by an average of 89% for both) measured downstream of the dam. These statistical and modeling approaches provide new evidence of the attenuation of the bacterial contamination by the dam reservoir. Overall, this thesis work provides new insights on FIB dynamics in a tropical context that could be helpful in establishing effective strategies for water resource management

A Concept To Assess The Performance Of A Permafrost Model Run Fully Coupled With A Climate Model

Thesis (Ph.D.) University of Alaska Fairbanks, 2009Soil-temperatures simulated by the fully coupled Community Climate System Model LCM version 3.0 (CCSM3) are evaluated using three gridded Russian soil-temperature climatologies (1951-1980, 1961-1990, and 1971-2000) to assess the performance of permafrost and/or soil simulations. CCSM3 captures the annual phase of the soil-temperature cycle well, but not the amplitude. It provides slightly too high (low) soil-temperatures in winter (summer) with a better performance in summer than winter. In winter, soil-temperature biases reach up to 6 K. Simulated near-surface air temperatures agree well with the near-surface air temperatures from reanalysis data. Discrepancies in CCSM3-simulated near-surface air temperatures significantly correlate with discrepancies in CCSM3-simulated soil-temperatures, i.e. contribute to discrepancy in soil-temperature simulation. Evaluation of cloud-fraction by means of the International Satellite Cloud Climatology project data reveals that errors in simulated cloud fraction explain some of the soil-temperature discrepancies in summer. Evaluation by means of the Global Precipitation Climatology Centre data identifies inaccurately-simulated precipitation as a contributor to underestimating summer soil-temperatures. Comparison to snow-depth observations shows that overestimating snow-depth leads to winter soil-temperature overestimation. Sensitivity studies reveal that uncertainty in mineral-soil composition notably contributes to discrepancies between CCSM3-simulated and observed soil-temperature climatology while differences between the assumed vegetation in CCSM3 and the actual vegetation in nature marginally contribute to the discrepancies in soil-temperature. Out of the 6 K bias in CCSM3 soil-temperature simulation, about 2.5 K of the bias may result from the incorrect simulation of the observed forcing and about 2 K of the bias may be explained by uncertainties due network density in winter. This means that about 1.5 K winter-bias may result from measurement errors and/or model deficiencies. Overall, the performance of a permafrost/soil model fully coupled with a climate model depends partly on the permafrost/soil model itself, the accuracy of the forcing data and design of observational network

Harmonization of remote sensing land surface products : correction of clear-sky bias and characterization of directional effects

Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Deteção Remota), Universidade de Lisboa, Faculdade de Ciências, 2018Land surface temperature (LST) is the mean radiative skin temperature of an area of land resulting from the mean energy balance at the surface. LST is an important climatological variable and a diagnostic parameter of land surface conditions, since it is the primary variable determining the upward thermal radiation and one of the main controllers of sensible and latent heat fluxes between the surface and the atmosphere. The reliable and long-term estimation of LST is therefore highly relevant for a wide range of applications, including, amongst others: (i) land surface model validation and monitoring; (ii) data assimilation; (iii) hydrological applications; and (iv) climate monitoring. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Satellite LST products generally rely on measurements in the thermal infrared (IR) atmospheric window, i.e., within the 8-13 micrometer range. Beside the relatively weak atmospheric attenuation under clear sky conditions, this band includes the peak of the Earth’s spectral radiance, considering surface temperature of the order of 300K (leading to maximum emission at approximately 9.6 micrometer, according to Wien’s Displacement Law). The estimation of LST from remote sensing instruments operating in the IR is being routinely performed for nearly 3 decades. Nevertheless, there is still a long list of open issues, some of them to be addressed in this PhD thesis. First, the viewing position of the different remote sensing platforms may lead to variability of the retrieved surface temperature that depends on the surface heterogeneity of the pixel – dominant land cover, orography. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should correspond to the ensemble directional radiometric temperature of all surface elements within the FOV. In this thesis, a geometric model is presented that allows the upscaling of in situ measurements to the any viewing configuration. This model allowed generating a synthetic database of directional LST that was used consistently to evaluate different parametric models of directional LST. Ultimately, a methodology is proposed that allows the operational use of such parametric models to correct angular effects on the retrieved LST. Second, the use of infrared data limits the retrieval of LST to clear sky conditions, since clouds “close” the atmospheric window. This effect introduces a clear-sky bias in IR LST datasets that is difficult to quantify since it varies in space and time. In addition, the cloud clearing requirement severely limits the space-time sampling of IR measurements. Passive microwave (MW) measurements are much less affected by clouds than IR observations. LST estimates can in principle be derived from MW measurements, regardless of the cloud conditions. However, retrieving LST from MW and matching those estimations with IR-derived values is challenging and there have been only a few attempts so far. In this thesis, a methodology is presented to retrieve LST from passive MW observations. The MW LST dataset is examined comprehensively against in situ measurements and multiple IR LST products. Finally, the MW LST data is used to assess the spatial-temporal patterns of the clear-sky bias at global scale.Fundação para a Ciência e a Tecnologia, SFRH/BD/9646

Multi-Scale Modelling of Cold Regions Hydrology

Numerical computer simulations are increasingly important tools required to address both research and operational water resource issues related to the hydrological cycle. Cold region hydrological models have requirements to calculate phase change in water via consideration of the energy balance which has high spatial variability. This motivates the inclusion of explicit spatial heterogeneity and field-testable process representations in such models. However, standard techniques for spatial representation such as raster discretization can lead to prohibitively large computational costs and increased uncertainty due to increased degrees of freedom. As well, semi-distributed approaches may not sufficiently represent all the spatial variability. Further, there is uncertainty regarding which process conceptualizations are used and the degree of required complexity, motivating modelling approaches that allow testing multiple working hypotheses. This thesis considers two themes. In the first, the development of improved modelling techniques to efficiently include spatial heterogeneity, investigate warranted model complexity, and appropriate process representation in cold region models is addressed. In the second, the issues of non-linear process cascades, emergence, and compensatory behaviours in cold regions hydrological process representations is addressed. To address these themes, a new modelling framework, the Canadian Hydrological Model (CHM), is presented. Key design goals for CHM include the ability to: capture spatial heterogeneity in an efficient manner, include multiple process representations, be able to change, remove, and decouple hydrological process algorithms, work both at point and spatially distributed scales, reduce computational overhead to facilitate uncertainty analysis, scale over multiple spatial extents, and utilize a variety of boundary and initial conditions. To enable multi-scale modelling in CHM, a novel multi-objective unstructured mesh generation software *mesher* is presented. Mesher represents the landscape using a multi-scale, variable resolution surface mesh. It was found that this explicitly captured the spatial heterogeneity important for emergent behaviours and cold regions processes, and reduced the total number of computational elements by 50\% to 90\% from that of a uniform mesh. Four energy balance snowpack models of varying complexity and degree of coupling of the energy and mass budget were used to simulate SWE in a forest clearing in the Canadian Rocky Mountains. It was found that 1) a compensatory response was present in the fully coupled models’ energy and mass balance that reduced their sensitivity to errors in meteorology and albedo and 2) the weakly coupled models produced less accurate simulations and were more sensitive to errors in forcing meteorology and albedo. The results suggest that the inclusion of a fully coupled mass and energy budget improves prediction of snow accumulation and ablation, but there was little advantage by introducing a multi-layered snowpack scheme. This helps define warranted complexity model decisions for this region. Lastly, a 3-D advection-diffusion blowing snow transport and sublimation model using a finite volume method discretization via a variable resolution unstructured mesh was developed. This found that the blowing snow calculation was able to represent the spatial redistribution of SWE over a sub-arctic mountain basin when compared to detailed snow surveys and the use of the unstructured mesh provided a 62\% reduction in computational elements. Without the inclusion of blowing snow, unrealistic homogeneous snow covers were simulated which would lead to incorrect melt rates and runoff contributions. This thesis shows that there is a need to: use fully coupled energy and mass balance models in mountains terrain, capture snow-drift resolving scales in next-generation hydrological models, employ variable resolution unstructured meshes as a way to reduce computational time, and consider cascading process interactions