Detection of intensification of the global water cycle: the potential role of FRIEND

Diagnostic studies of 14-year, 2 — 2°, Variable Infiltration Capacity (VIC) model off-line simulations of the global terrestrial water budget suggest that, given the annual variability in the major components of continental hydrological cycles (precipitation, evaporation, and runoff), several decades to perhaps centuries of measurements may be needed to detect with high confidence the intensification predicted by recent global climate model (GCM) studies simulating plausible global warming scenarios. Furthermore, these measurements may need to originate from a wider geographic expanse than is currently investigated within large-scale hydrological assessment programmes, such as the Global Energy and Water Experiment (GEWEX). Smaller, geographically dispersed basins, including many of those participating in the International Flow Regimes from International Experimental and Network Data (FRIEND) programme, could therefore play important roles in detection of an intensification in the global water cycle

Seasonal hydrologic responses to climate change in the Pacific Northwest

Increased temperatures and changes in precipitation will result in fundamental changes in the seasonal distribution of streamflow in the Pacific Northwest and will have serious implications for water resources management. To better understand local impacts of regional climate change, we conducted model experiments to determine hydrologic sensitivities of annual, seasonal, and monthly runoff to imposed annual and seasonal changes in precipitation and temperature. We used the Variable Infiltration Capacity (VIC) land‐surface hydrology model applied at 1/16° latitude‐longitude spatial resolution over the Pacific Northwest (PNW), a scale sufficient to support analyses at the hydrologic unit code eight (HUC‐8) basin level. These experiments resolve the spatial character of the sensitivity of future water supply to precipitation and temperature changes by identifying the seasons and locations where climate change will have the biggest impact on runoff. The PNW exhibited a diversity of responses, where transitional (intermediate elevation) watersheds experience the greatest seasonal shifts in runoff in response to cool season warming. We also developed a methodology that uses these hydrologic sensitivities as basin‐specific transfer functions to estimate future changes in long‐term mean monthly hydrographs directly from climate model output of precipitation and temperature. When principles of linearity and superposition apply, these transfer functions can provide feasible first‐order estimates of the likely nature of future seasonal streamflow change without performing downscaling and detailed model simulations

HUBUNGAN PENINGKATAN BERAT BADAN FE4NGAN KONVERSI SPUTUM PADA PASIEN TUBERKULOSIS DI RSUDZA BANDA ACEH

ABSTRAKKonversi sputum pada fase awal pengobatan merupakan salah satu indikator awal keberhasilan terapi obat anti tuberkulosis (OAT). Nutrisi merupakan faktor penting yang juga mempengaruhi kesembuhan pasien tuberkulosis Penelitian ini bertujuan untuk mengetahui hubungan peningkatan berat badan dengan konversi sputum setelah fase awal pada pasien TB di Rumah Sakit Umum dr. Zainoel Abidin Banda Aceh (RSUDZA). Jenis penelitian yang digunakan adalah Cross sectional. Subjek penelitian terdiri atas 92 pasien tuberkulosis di poliklinik DOTS RSUDZA Banda Aceh yang diperoleh dengan metode total sampling terhitung dari Januari sampai dengan Desember 2013. Hasil penelitian dianalisis menggunakan uji statistik Fisher dengan Confident interval 95%. Hasil uji statistik menunjukkan p = 0,107 (p > 0,05) yang menunjukkan bahwa tidak ada hubungan antara peningkatan berat badan dengan konversi sputum pada penderita tuberkulosis yang telah mendapatkan OAT fase awal. Diharapkan adanya penelitian yang lebih lanjut mengenai hubungan nutrisi dengan konversi sputum dengan jumlah sampel yang lebih besar dan desain penelitian yang lebih baik. Kata Kunci : Tuberkulosis, Konversi sputum, Berat badan ABSTRACTSputum conversion at the initial phase of treatment is one of the early indicators of the success of anti-tuberculosis drug therapy (OAT). Nutrition is an important factor that also effects the recovery of tuberculosis patients The aim of this study was to determine the relationship of weight gain and sputum conversion after the initial phase of TB patients at the General Hospital dr. Zainoel Abidin Banda Aceh (RSUDZA). This research was cross sectional study. Subjects consisted of 92 outpatient DOTS tuberculosis in RSUDZA Banda Aceh obtained with total sampling method starting from January to December 2013. Results were analyzed using Fisher test with 95% confident interval. Statistical test results p= 0,107 (p > 0,05) that showed there is no association between increased weight to conversion of sputum in patients with tuberculosis who have earned OAT initial phase, It is expected that the presence of further reaserh on the relationship of nutrition with sputum convertion with a larger number of sampel and design better research. Keywords: Tuberculosis, Sputum conversion, Weight los

A unified approach for process-based hydrologic modeling: 1. Modeling concept

This work advances a unified approach to process-based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. In this paper, we introduce the general approach used in SUMMA, detailing the spatial organization and model simplifications, and how different representations of multiple physical processes can be combined within a single modeling framework. We discuss how SUMMA can be used to systematically pursue the method of multiple working hypotheses in hydrology. In particular, we discuss how SUMMA can help tackle major hydrologic modeling challenges, including defining the appropriate complexity of a model, selecting among competing flux parameterizations, representing spatial variability across a hierarchy of scales, identifying potential improvements in computational efficiency and numerical accuracy as part of the numerical solver, and improving understanding of the various sources of model uncertainty.Keywords: unified model, hydrometeorology, scaling behavio

Compounding climate change impacts during high stress periods for a high wind and solar power system in Texas

Power system planning aims at ensuring that sufficient supply- and demand-side assets exist to meet electricity demand at all times. For a Texas electric power system with high wind and solar penetrations, we quantify how climate change will affect supply and demand during three types of high stress periods for the power grid: high demand hours, high net demand hours, and high system ramp hours. We specifically quantify effects on demand, reductions in available thermal capacity (i.e. thermal deratings), wind and solar generation, and net demand. We estimate each using meteorological variables from five climate change projections (2041-2050) assuming Representative Concentration Pathway 8.5 and from a reference period (1996-2005). All five projections indicate that climate change will increase demand by up to 2 GWh during high demand hours (4% of demand in the reference period) and increase net demand by up to 3 GWh during high net demand periods (6% of net demand in the reference period). All five projections also indicate thermal deratings will increase during high demand and net demand periods by up to 2 GWh and high net demand ramps will increase by up to 2 GW. Overall, our results indicate compounding effects of climate change in Texas will necessitate greater investment in peak and flexible capacity.</p

Land Surface Climate in the Regional Arctic System Model

The article of record as published may be found at http://dx.doi.org/10.1175/JCLI-D-15-0415.1The Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979-2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2 degrees C; however, in the cold seasons there are local biases that exceed 6 degrees C. Compared to satellite observations, RASM captures the annual cycle of snow-covered area well, although melt progresses about two weeks faster than observations in the late spring at high latitudes. With respect to derived fluxes, such as latent heat or runoff, RASM is shown to have similar performance statistics as ERA-Interim while differing substantially from MERRA, which consistently overestimates the evaporative flux across the Arctic region.U.S. Department of Energy (DOE) [DE-FG02-07ER64460, DE-SC0006856, DE-SC0006178]; DO

Toward Open and Reproducible Environmental Modeling by Integrating Online Data Repositories, Computational Environments, and Model Application Programming Interfaces

Cyberinfrastructure needs to be advanced to enable open and reproducible environmental modeling research. Recent efforts toward this goal have focused on advancing online repositories for data and model sharing, online computational environments along with containerization technology and notebooks for capturing reproducible computational studies, and Application Programming Interfaces (APIs) for simulation models to foster intuitive programmatic control. The objective of this research is to show how these efforts can be integrated to support reproducible environmental modeling. We present first the high-level concept and general approach for integrating these three components. We then present one possible implementation that integrates HydroShare (an online repository), CUAHSI JupyterHub and CyberGIS-Jupyter for Water (computational environments), and pySUMMA (a model API) to support open and reproducible hydrologic modeling. We apply the example implementation for a hydrologic modeling use case to demonstrate how the approach can advance reproducible environmental modeling through the seamless integration of cyberinfrastructure services

Evaluation of the atmosphere–land–ocean–sea ice interface processes in the Regional Arctic System Model version 1 (RASM1) using local and globally gridded observations

The Regional Arctic System Model version 1 (RASM1) has been developed to provide high-resolution simulations of the Arctic atmosphere–ocean–sea ice–land system. Here, we provide a baseline for the capability of RASM to simulate interface processes by comparing retrospective simulations from RASM1 for 1990–2014 with the Community Earth System Model version 1 (CESM1) and the spread across three recent reanalyses. Evaluations of surface and 2 m air temperature, surface radiative and turbulent fluxes, precipitation, and snow depth in the various models and reanalyses are performed using global and regional datasets and a variety of in situ datasets, including flux towers over land, ship cruises over oceans, and a field experiment over sea ice. These evaluations reveal that RASM1 simulates precipitation that is similar to CESM1, reanalyses, and satellite gauge combined precipitation datasets over all river basins within the RASM domain. Snow depth in RASM is closer to upscaled surface observations over a flatter region than in more mountainous terrain in Alaska. The sea ice–atmosphere interface is well simulated in regards to radiation fluxes, which generally fall within observational uncertainty. RASM1 monthly mean surface temperature and radiation biases are shown to be due to biases in the simulated mean diurnal cycle. At some locations, a minimal monthly mean bias is shown to be due to the compensation of roughly equal but opposite biases between daytime and nighttime, whereas this is not the case at locations where the monthly mean bias is higher in magnitude. These biases are derived from errors in the diurnal cycle of the energy balance (radiative and turbulent flux) components. Therefore, the key to advancing the simulation of SAT and the surface energy budget would be to improve the representation of the diurnal cycle of radiative and turbulent fluxes. The development of RASM2 aims to address these biases. Still, an advantage of RASM1 is that it captures the interannual and interdecadal variability in the climate of the Arctic region, which global models like CESM cannot do

A Unified Approach for Process-Based Hydrologic Modeling: 2. Model Implementation and Case Studies

This work advances a unified approach to process-based hydrologic modeling, which we term the “Structure for Unifying Multiple Modeling Alternatives (SUMMA).” The modeling framework, introduced in the companion paper, uses a general set of conservation equations with flexibility in the choice of process parameterizations (closure relationships) and spatial architecture. This second paper specifies the model equations and their spatial approximations, describes the hydrologic and biophysical process parameterizations currently supported within the framework, and illustrates how the framework can be used in conjunction with multivariate observations to identify model improvements and future research and data needs. The case studies illustrate the use of SUMMA to select among competing modeling approaches based on both observed data and theoretical considerations. Specific examples of preferable modeling approaches include the use of physiological methods to estimate stomatal resistance, careful specification of the shape of the within-canopy and below-canopy wind profile, explicitly accounting for dust concentrations within the snowpack, and explicitly representing distributed lateral flow processes. Results also demonstrate that changes in parameter values can make as much or more difference to the model predictions than changes in the process representation. This emphasizes that improvements in model fidelity require a sagacious choice of both process parameterizations and model parameters. In conclusion, we envisage that SUMMA can facilitate ongoing model development efforts, the diagnosis and correction of model structural errors, and improved characterization of model uncertainty