Nuclei of pleochroic halos in biotites of some Sierra Nevada granitic rocks.
Sierra Nevada granite halos in biotite nuclei, discussing relation between biotite zircon content and halo production
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Sierra Nevada granite halos in biotite nuclei, discussing relation between biotite zircon content and halo production
California's water resources rely heavily on cool‐season (November–March) precipitation in the Sierra Nevada. Interannual variability is highly volatile and seasonal forecasting has little to no skill, making water management particularly challenging. Over 1902–2020, Sierra Nevada cool‐season precipitation totals exhibited significant 2.2‐ and 13–15‐year cycles, accounting for approximately 40% of total variability and perhaps signifying potential as seasonal forecasting tools. However, the underlying climate dynamics are not well understood and it is unclear whether these cycles are stable over the long‐term. We use tree rings to reconstruct Sierra Nevada cool‐season precipitation back to 1400. The reconstruction is skillful, accounting for 55–74% of observed variability and capturing the 20th‐century 2.2‐ and 13–15‐year cycles. Prior to 1900, the reconstruction indicates no other century‐long periods of significant spectral power in the 2.2‐ or 13–15‐year bands. The reconstruction does indicate significant cyclicity over other extended periods of several decades or longer, however, with dominant periodicities in the ranges of 2.1–2.7 and 3.5–8 years. The late 1700s through 1800s exhibited the highest‐amplitude cycles in the reconstruction, with periodicities of 2.4 and 5.7–7.4 years. The reconstruction should serve to caution against extrapolating the observed 2.2‐ and 13–15‐year cycles to guide future expectations. On the other hand, observations and the reconstruction suggest that interannual variability of Sierra Nevada cool‐season precipitation is not a purely white noise process and research should aim to diagnose the dynamical drivers of extended periods of cyclicity in this critical natural resource.
The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.
A regional study of the distribution and elevations of Pleistocene moraines in the Andes requires a method of determining relative age from space. One of our primary objectives is to establish the relative chronology of major climatic events responsible for glaciation in the Andes and other regions that are difficult to access on the ground and where suitable material for absolute age determination is lacking. The sensitivity of radar to surface roughness makes it possible to develop a remotely-based relative dating technique for landforms for which surface age and roughness can be correlated. We are developing such a technique with Airborne Synthetic Aperture Radar (AIRSAR) imagery of the eastern Sierra Nevada where independent evidence is available for the ages and physical characteristics of moraines. The Sierra Nevada moraines are similar in form and environmental setting to Andean moraines that we have targeted for study during the pending Shuttle Imaging Radar-C (SIR-C) mission. SAR imagery is used to differentiate the ages of five moraine sequences of Walker Valley in the eastern Sierra Nevada. Other aspects of this investigation are briefly discussed.
Extreme drought from 2013 to 2015 has been linked to extensive tree dieback in the Sierra-Nevada region of California. Landsat satellite imagery was analysed for the region from Lake Tahoe to the southern Sequoia National Forest with the objective of understanding the patterns of tree mortality in the years of 2013 to 2015 and into the near-normal precipitation year of 2016. The main mapping results for Landsat moisture index differences from year-to-year showed that the highest coverage of tree dieback was located in the Sierra and Sequoia National Forests, at four to five times greater area each year than within any other National Park or National Forest unit. Since 2013, over 50% of the Sierra Nevada forest dieback area was detected in the mid elevation zone of 1000-2000 m. The total area of tree mortality in the lower elevation zone of 500-1000 m did not grow notably from 2015 to 2016. Within the largest California river drainages in the Sierra region, new tree mortality in 2015 was detected mainly below 1200 m elevation, whereas new tree mortality in 2016 was detected mainly at higher elevations, up to about 2200 m. In three out of the four years studied, results showed that about 60% of all new tree mortality areas were located on north-facing hill slopes.
Ice formation in orographic mixed-phase clouds can enhance precipitation and depends on the type of aerosols that serve as ice nucleating particles (INP). The resulting precipitation from these clouds is a viable source of water, especially for regions such as the California Sierra Nevada. Thus, a better understanding of the sources of INP that impact orographic clouds is important for assessing water availability in California. This study presents a multi-site, multi-year analysis of single particle insoluble residues in precipitation samples that likely influenced cloud ice and precipitation formation above Yosemite National Park. Dust and biological particles represented the dominant fraction of the residues (64% on average). Cloud glaciation, determined using GOES satellite observations, not only depended on high cloud tops (greater than 6.2 km) and low temperatures (less than -26 C), but also on the composition of the dust and biological residues. The greatest prevalence of ice-phase clouds occurred in conjunction with biologically-rich residues and mineral dust rich in calcium, followed by iron and aluminosilicates. Dust and biological particles are known to be efficient INP, thus these residues are what likely influenced ice formation in clouds above the sites and subsequent precipitation quantities reaching the surface during events with similar meteorology. The goal of this study is to use precipitation chemistry information to gain a better understanding of the potential sources of INP in the south-central Sierra Nevada, where cloud-aerosol-precipitation interactions are under-studied and where mixed-phase orographic clouds represent a key element in the generation of precipitation and thus the water supply in California.
This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.
The author has identified the following significant results. ERTS-1 imagery used in conjunction with the surface-drift cards indicated a southerly flow direction of the central California near surface coastal currents during mid-June 1973. The near-surface currents off northern California and southern Oregon were more complex. Some drift cards were recovered north and some south of their release points; however, the prevalent direction of flow was northerly. General agreement in flow direction of coastal currents obtained from ERTS-1 imagery and drift card data reinforces the image interpretation. Complete seasonal coverage of nearshore circulation interpreted from ERTS-1 imagery will provide information necessary for proper coastal zone management. Extent of snow cover can be readily delimited on ERTS-1 band 5. In the central Sierra Nevada Mountains this past winter season, the snow line, as recorded by ERTS-1, reached an elevation of less than 1500 meters in January but had melted back to between 2500 and 3000 meters by the end of May. ERTS-1 imagery seems to provide sufficient resolution to make it a useful tool for monitoring changes in snow cover in the Sierra Nevada Mountains.
Detection and monitoring of forest insect infestation in Sierra Nevada Mountains of California
The analysis of ERTS-1 imagery of areas in the Sierra Nevada Mountains of California is discussed. The data is used to detect two types of insect infestational and to determine the extent of timber resources. Addition applications are the mapping of stream courses, mountain meadows, lakes, rock outcrops, and grazing land. The ERTS-1 data and underflight photography are used for this purpose.
The influences of upper air characteristics along the coast of California upon the winter time precipitation in the Sierra Nevada region were investigated. Most precipitation episodes in the Sierra are associated with moist southwesterly winds and also tend to occur when the 700-mb temperature is close to -2 C. This favored wind direction and temperature signifies the equal importance of moisture transport and orographic lifting for maximum precipitation frequency. Making use of this observation, simple linear models were formulated to quantify the precipitation totals observed at different sites as a function of moisture transport. The skill of the model is least for daily precipitation and increases with time scale of aggregation. In terms of incremental gain, the skill of the model is optimal for an aggregation period of 5-7 days, which is also the duration of the most frequent precipitation events in the Sierra. This indicates that upper air moisture transport at can be used to make reasonable estimates of the precipitation totals for most frequent events in the Sierra region.
A film loop from SMS-2 imagery shows snow melt over the Sierra Nevadas from May 10 to July 8, 1975. The sequence indicates a successful application of geostationary satellite data for monitoring dynamic hydrologic conditions.
The author has identified the following significant results. Several lineaments observed in ERTS-1 MSS imagery over the southern Sierra Nevada of California have been studied in the field in an attempt to explain their geologic origins and significance. The lineaments are expressed topographically as alignments of linear valleys, elongate ridges, breaks in slope or combinations of these. Natural outcrop exposures along them are characteristically poor. Two lineaments were found to align with foliated metamorphic roof pendants and screens within granitic country rocks. Along other lineaments, the most consistant correlations were found to be alignments of diabase dikes of Cretaceous age, and younger cataclastic shear zones and minor faults. The location of several Pliocene and Pleistocene volcanic centers at or near lineament intersections suggests that the lineaments may represent zones of crustal weakness which have provided conduits for rising magma.
Landsat imagery was analyzed to understand changes in subalpine forest stands since the mid-1980s in the Sierra-Nevada region of California. At locations where long-term plot measurements have shown that stands are becoming denser in the number of small tree stems (compared to the early 1930s), the 30-year analysis of Landsat greenness index (NDVI) indicated that no consistent increases in canopy leaf cover have occurred at these same locations since the mid-1980s. Interannual variations in stand NDVI closely followed snow accumulation amounts recorded at nearby stations. In contrast, at eastern Sierra whitebark pine stand locations where it has been observed that widespread tree mortality has occurred, decreasing NDVI trends over the past 5-10 years were consistent with rapid loss of forest canopy cover. Landsat imagery was further analyzed to understand patterns of post-wildfire vegetation recovery, focusing on high burn severity (HBS) patches within burned areas dating from the late 1940s. Analysis of landscape metrics showed that the percentage of total HBS area comprised by the largest patch of recovered woody cover was relatively small in all fires that occurred since 1995, but increased rapidly with time since fire. Patch complexity of recovered woody cover decreased notably after more than 50 years of regrowth, but was not readily associated with time for fires that occurred since the mid 1990s. The aggregation level of patches with recovery of woody cover increased steadily with time since fire. The study approach using satellite remote sensing can be expanded to assess the consequences of stand-replacing wildfires in all forests of the region.
The author has identified the following significant results. Studies were conducted in key field areas in the Sierra Nevada, the Basin Range Province and the Colorado Plateau to evaluate the origins and significance of geologic and structural anomalies expressed in the ERTS-1 data. The investigation included development of image enhancement and analysis techniques and comparison of remote sensing data available over the test site. The ERTS-1 MSS imagery has proven to be an effective tool for studying the interrelationsships between Cenozoic tectonic patterns and the distributions of Cenozoic plutonism and volcanism, seismic activity, geologic hazards, and known mineral, geothermal and ground water resources. Recommendations are made for applications of ERTS-1 data to natural and resource exploration and management.
A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.
Fission track and K-Ar ages of coexisting minerals in drill core from heat-flow boreholes in western central Sierra Nevada batholith
The author has identified the following significant results. Analysis of ERTS-1 imagery with underflight aerial photo support including U-2, in the Sierra Nevada Mountains of California, indicates promising possibilities of detecting and monitoring forest insect outbreaks visually with some mechanical support utilizing the VP-8 image analyzer. Visually, it is possible at a scale of 1:1,000,000 to discriminate between large areas of damaged and undamaged forests; timbered and non-timbered areas; pasture land and cultivated fields; desert and riparian vegetation. At a scale of 1:80,000 it is possible to distinguish among three classes of tree mortality; defoliated and undefoliated areas; non-host mixed conifers; and mountain meadows, rock domes, lakes and glaciers. Machine tests showed significant differences in image densities among various bands and mortality areas.