Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes

Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modelling and paleo-observations. The sub-continental region of Beringia (Northeast Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia’s early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present day simulations of regional climate, one with modern and one with 11 ka geography, plus another simulation for 6 ka. In addition, we performed five ? 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka “Control”, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present day distribution of lakes and wetlands; and (v) post-11 ka “All”, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season

Subsurface monitoring of reservoir pressure, temperature, relative humidity, and water content at the CAES Field Experiment, Pittsfield, Illinois: system design

This subsurface-instrumentation design has been developed for the first Compressed Air Energy Storage (CAES) field experiment to be performed in porous media. Energy storage will be accomplished by alternating the injection and withdrawal of compressed air in a confined sandstone aquifer near Pittsfield, Illinois. The overall experiment objective is to characterize the reservoir's geochemical and thermohydraulic response to imposed CAES conditions. Specific experiment objectives require monitoring: air-bubble development; thermal development; cyclic pressure response; reservoir dehydration; and water coning. Supporting these objectives, four parameters will be continuously monitored at depth in the reservoir. They are: temperature; pressure; pore-air relative humidity; and pore-water content. Reservoir temperatures and pressures will range to maximum values approaching 200/sup 0/C and 300 psi, respectively. Both pore-air relative humidity and pore-water content will range from approx. 0 to 100%. This report discusses: instrumentation design; sensor and sensor system calibration; field installation and testing; and instrument-system operation. No comprehensive off-the-shelf instrument package exists to adequately monitor CAES reservoir parameters at depth. The best available sensors were selected and adapted for use under expected ranges of reservoir conditions. The instrumentation design criteria required: suitable sensor accuracy; continuous monitoring capability; redundancy; maximum sensor integrity; contingency planning; and minimum cost-information ratio. Three wells will be instrumented: the injection/withdrawal (I/W) well and the two instrument wells. Sensors will be deployed by wireline suspension in both open and backfilled (with sand) wellbores. The sensors deployed in the I/W well will be retrievable; the instrument-well sensors will not

Accommodation Space in a High-Wave-Energy Inner-Shelf During the Holocene Marine Transgression: Correlation of Onshore and Offshore Inner-Shelf Deposits (0–12 ka) in the Columbia River Littoral Cell System, Washington and Oregon, USA

The Columbia River Littoral Cell (CRLC), a high-wave-energy littoral system, extends 160 km alongshore, generally north of the large Columbia River, and 10–15 km in across-shelf distance from paleo-beach backshores to about 50 m present water depths. Onshore drill holes (19 in number and 5–35 m in subsurface depth) and offshore vibracores (33 in number and 1–5 m in subsurface depth) constrain inner-shelf sand grain sizes (sample means 0.13–0.25 mm) and heavy mineral source indicators (\u3e 90% Holocene Columbia River sand) of the inner-shelf facies (≥ 90% fine sand). Stratigraphic correlation of the transgressive ravinement surface in onshore drill holes and in offshore seismic reflection profiles provide age constraints (0–12 ka) on post-ravinement inner-shelf deposits, using paleo-sea level curves and radiocarbon dates. Post-ravinement deposit thickness (1–50 m) and long-term sedimentation rates (0.4–4.4 m ka− 1) are positively correlated to the cross-shelf gradients (0.36–0.63%) of the transgressive ravinement surface. The total post-ravinement fill volume of fine littoral sand (2.48x1010m3) in the inner-shelf represents about 2.07x106 m3 yr− 1 fine sand accumulation rate during the last 12 ka, or about one third of the estimated middle- to late-Holocene Columbia River bedload or sand discharge (5–6x106 m3 yr− 1) to the littoral zone. The fine sand accumulation in the inner-shelf represents post-ravinement accommodation space resulting from 1) geometry and depth of the transgressive ravinement surface, 2) post-ravinement sea-level rise, and 3) fine sand dispersal in the inner-shelf by combined high-wave-energy and geostrophic flow/down-welling drift currents during major winter storms

Assessment of NAAPS-RA performance in Maritime Southeast Asia during CAMP2Ex

Monitoring and modeling aerosol particle life cycle in Southeast Asia (SEA) is challenged by high cloud cover, complex meteorology, and the wide range of aerosol species, sources, and transformations found throughout the region. Satellite observations are limited, and there are few in situ observations of aerosol extinction profiles, aerosol properties, and environmental conditions. Therefore, accurate aerosol model outputs are crucial for the region. This work evaluates the Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA) aerosol optical thickness (AOT) and light extinction products using airborne aerosol and meteorological measurements from the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) conducted in 2019 during the SEA southwest monsoon biomass burning season. Modeled AOTs and extinction coefficients are compared to those retrieved with a high spectral resolution lidar (HSRL-2). Agreement between simulated and retrieved AOT (R2Combining double low line 0.78, relative bias Combining double low line-5 %, normalized root mean square error (NRMSE) Combining double low line 48 %) and aerosol extinction coefficients (R2Combining double low line 0.80, 0.81, and 0.42; relative bias Combining double low line 3 %, -6 %, and -7 %; NRMSE Combining double low line 47 %, 53 %, and 118 % for altitudes between 40-500, 500-1500, and >1500 m, respectively) is quite good considering the challenging environment and few opportunities for assimilations of AOT from satellites during the campaign. Modeled relative humidities (RHs) are negatively biased at all altitudes (absolute bias Combining double low line-5 %, -8 %, and -3 % for altitudes 1500 m, respectively), motivating interest in the role of RH errors in AOT and extinction simulations. Interestingly, NAAPS-RA AOT and extinction agreement with the HSRL-2 does not change significantly (i.e., NRMSE values do not all decrease) when RHs from dropsondes are substituted into the model, yet biases all move in a positive direction. Further exploration suggests changes in modeled extinction are more sensitive to the actual magnitude of both the extinction coefficients and the dropsonde RHs being substituted into the model as opposed to the absolute differences between simulated and measured RHs. Finally, four case studies examine how model errors in RH and the hygroscopic growth parameter, γ, affect simulations of extinction in the mixed layer (ML). We find NAAPS-RA overestimates the hygroscopicity of (i) smoke particles from biomass burning in the Maritime Continent (MC) and (ii) anthropogenic emissions transported from East Asia. This work mainly provides insight into the relationship between errors in modeled RH and simulations of AOT and extinction in a humid and tropical environment influenced by a myriad of meteorological conditions and particle types. These results can be interpreted and addressed by the modeling community as part of the effort to better understand, quantify, and forecast atmospheric conditions in SEA. Copyright © 2022 Eva-Lou Edwards et al.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]