Changes to precipitation patterns and extremes over the Nepalese Himalayas were examined using a high‐resolution, station‐based daily dataset, Asian Precipitation‐Highly Resolved Observational Data Integration Towards Evaluation (0.05° × 0.05° APHRODITE) from 1951 to 2007. The annual statistics of extreme precipitation across Nepal show a significant increase since the end of the 20th century. However, seasonal mean precipitation shows a remarkable decrease in western Nepal, particularly since 1980, forming an east–west division in the precipitation change. This decreasing trend of precipitation led to a reduction to the dry‐season stream flow of Karnali River, the major river in western Nepal. At the same time, the increasing extreme precipitation produced greater threat of flash flood in Nepal. This east–west division of the precipitation trend agrees with the second leading mode of the mean precipitation variability, which was traced to the interannual variability of the Indian Ocean sea surface temperature that showed a slowdown of warming. Similar to the APHRODITE trends, precipitation simulated by the fifth phase of the Coupled Model Intercomparison Project (CMIP5) models depicted the decreasing historical trend in western Nepal, but future projections reverse that trend towards an all‐Nepal increase. CMIP5 future climate projections depict continual warming in the Indian Ocean, potentially reversing the historical decreasing trends of precipitation in western Nepal.
Winter storms are often accompanied by strong winds, especially over complex terrain. Under such conditions freshly fallen snow can be readily suspended. Most of that snow will be redistributed across the landscape (e.g., behind obstacles), but some may be lofted into the turbulent boundary layer, and even into the free atmosphere in areas of boundary layer separation near terrain crests, or in hydraulic jumps. Blowing snow ice crystals, mostly small fractured particles, thus may enhance snow growth in clouds. This may explain why shallow orographic clouds, with cloud-top temperatures too high for significant ice initiation, may produce (usually light) snowfall with remarkable persistence. While drifting snow has been studied extensively, the impact of blowing snow on precipitation on snowfall itself has not. Airborne radar and lidar data are presented to demonstrate the presence of blowing snow, boundary layer separation, and the glaciation of shallow supercooled orographic clouds. Further evidence for the presence of blowing snow comes from a comparison between snow size distributions measured at Storm Peak Laboratory (SPL) on Mount Werner (Colorado) versus those measured aboard an aircraft while passing overhead, and from an examination of snow size distributions at SPL under diverse weather conditions. Ice splintering following the collision of supercooled droplets on rimed surfaces such as trees does not appear to explain the large concentrations of small ice crystals sometimes observed at SPL.
We investigate historical and projected precipitation in Tanzania using observational and climate model data. Precipitation in Tanzania is highly variable in both space and time due to topographical variations, coastal influences, and the presence of lakes. Annual and seasonal precipitation trend analyses from 1961 to 2016 show maximum rainfall decline in Tanzania during the long rainy season in the fall (March–May), and an increasing precipitation trend in northwestern Tanzania during the short rainy season in the spring (September–November). Empirical orthogonal function (EOF) analysis applied to Tanzania’s precipitation patterns shows a stronger correlation with warmer temperatures in the western Indian Ocean than with the eastern-central Pacific Ocean. Years with decreasing precipitation in Tanzania appear to correspond with increasing sea surface temperatures (SST) in the Indian Ocean, suggesting that the Indian Ocean Dipole (IOD) may have a greater effect on rainfall variability in Tanzania than the El Niño-Southern Oscillation (ENSO) does. Overall, the climate model ensemble projects increasing precipitation trend in Tanzania that is opposite with the historical decrease in precipitation. This observed drying trend also contradicts a slightly increasing precipitation trend from climate models for the same historical time period, reflecting challenges faced by modern climate models in representing Tanzania’s precipitation.
Electrostatic forces could contribute significantly toward enzyme−solid interactions, and controlling these charge−charge interactions while maintaining high affinity, benign adsorption of enzymes on solids is a challenge. Here, we demonstrate that chemical modification of the surface carboxyl groups of enzymes can be used to adjust the net charge of the enzyme and control binding affinities to solid surfaces. Negatively charged nanosolid, α-Zr(HPO 4 ) 2 •H 2 O (abbreviated as α-ZrP) and two negatively charged proteins, glucose oxidase (GO) and methemoglobin (Hb), have been chosen as model systems. A limited number of the aspartate and glutamate side chains of these proteins are covalently modified with tetraethylenepentamine (TEPA) to convert these negatively charged proteins into the corresponding positively charged ones (cationized). Cationized proteins retained their structure and activities to a significant extent, and the influence of cationization on binding affinities has been tested. Cationized GO, for example, showed 250-fold increase in affinity for the negatively charged α-ZrP, when compared to that of the unmodified GO, and cationized Hb, similarly, indicated 26-fold increase in affinity. Circular dichroism spectra showed that α-ZrP-bound cationized GO retained native-like structure to a significant extent, and activity studies showed that cationized GO/α-ZrP complex is ∼2.5-fold more active than GO/α-ZrP. Cationized Hb/α-ZrP retained ∼75% of activity of Hb/α-ZrP. Therefore, enzyme cationization enhanced affinities by 1−2 orders of magnitude, while retaining considerable activity for the bound biocatalyst. This benign, chemical control over enzyme charge provided a powerful new strategy to rationally modulate enzyme−solid interactions while retaining their biocatalytic properties.
Natural small-scale microphysical and dynamical mechanisms are identified in a winter orographic snowstorm over the Sierra Madre Range of Wyoming during an intensive observational period (IOP) from the AgI Seeding Cloud Impact Investigation (ASCII; January–March 2012). A suite of high-resolution radars, including a ground-based scanning X-band dual-polarization Doppler on Wheels radar, vertically pointing Ka-band Micro Rain Radar (MRR), and airborne W-band Wyoming Cloud Radar (WCR), and additional in situ and remote sensing instruments are used in the analysis. The analysis focuses on a deep postfrontal period on 16 January 2012 (IOP2) when clouds extended throughout the troposphere and cloud liquid water was absent following the passage of a baroclinic front. A turbulent shear layer was observed in this postfrontal environment that was created by a midlevel cross-barrier jet riding over a decoupled Arctic air mass that extended above mountaintop. MRR and WCR observations indicate additional regions of turbulence aloft that favor rapid particle growth at upper levels of the cloud. Plunging flow in the lee of the Sierra Madre was also observed during this case, which caused sublimation of snow up to 20 km downwind. The multi-instrument analysis in this paper suggests that 1) shear-induced turbulent overturning cells do exist over cold continental mountain ranges like the Sierra Madre, 2) the presence of cross-barrier jets favors these turbulent shear zones, 3) this turbulence is a key mechanism in enhancing snow growth, and 4) snow growth enhanced by turbulence primarily occurs through deposition and aggregation in these cold (<−15°C) postfrontal continental environments.
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