Representation of western disturbances in CMIP5 models

Western disturbances (WDs) are synoptic extratropical disturbances embedded in the subtropical westerly jet stream. They are an integral part of the South Asian winter climate, both for the agriculture-supporting precipitation they bring to the region and for the associated isolated extreme events that can induce devastating flash flooding. Here, WD behaviour and impacts are characterised in 23 CMIP5 historical simulations and compared with reanalysis and observations. It is found that WD frequency has a strong relationship with model resolution: higher resolution models produce significantly more WDs, and a disproportionately high fraction of extreme events. Exploring metrics of jet strength and shape, we find that the most probable cause of this relationship is that the jet is wider in models with coarser resolution, and therefore the northern edge in which WDs are spun up sits too far north of India. The frequency of WDs in both winter and summer is found to be overestimated by most models, and thus the winter frequency of WDs estimated from the multi-model mean (30 winter−1) is above the reanalysis mean (26 winter−1). In this case, the error cannot be adequately explained by local jet position and strength. Instead, we show that it is linked with a positive bias in upstream mid-tropospheric baroclinicity. Despite a positive winter precipitation bias in CMIP5 models over most of India and Pakistan and a dry bias in the western Himalaya, the fraction of winter precipitation for which WDs are responsible is accurately represented. Using partial correlation, it is shown that the overestimation in WD frequency is the largest contributor to this bias, with a secondary, spatially heterogeneous contribution coming from the overestimation of WD intensity

Falling trend of western disturbances in future climate simulations

Western disturbances (WDs) are synoptic-scale cyclonic weather systems advected over Pakistan and north India by the subtropical westerly jet stream. There, they are responsible for most of the winter precipitation, crucial for agriculture of the rabi crop, as well as more extreme precipitation events, which can lead to local flooding and avalanches. Despite their importance, there has not yet been an attempt to objectively determine the fate of WDs in future climate GCMs. Here, a tracking algorithm is used to build up a catalogue of WDs in both CMIP5 historical and representative concentration pathway (RCP) experiments of the future. It is shown that in business-as-usual (RCP8.5) future climate simulations, WD frequency falls by around 15% by the end of the twenty-first century, with the largest relative changes coming in pre- and post-monsoon months. Meanwhile, mean WD intensity will decrease, with central vorticity expected to become less cyclonic by about 12% over the same period. Changes in WD frequency are attributed to the projected widening and weakening of the winter subtropical jet; as well as decreasing meridional wind shear and mid-tropospheric baroclinic vorticity tendency, which also explain the changes in intensity. Finally, the impact of these changes on regional precipitation is explored. The decline in WD frequency and intensity will cause a decrease in mean winter rainfall over Pakistan and north India amounting to about 15% of the mean -- subject to the ability of the models to represent the processes responsible. The effect on extreme precipitation events, however, remains unclear

Integrated Focal Plane Arrays for Millimeter-wave Astronomy

We are developing focal plane arrays of bolometric detectors for sub-millimeter and millimeter-wave astrophysics. We propose a flexible array architecture using arrays of slot antennae coupled via low-loss superconducting Nb transmission line to microstrip filters and antenna-coupled bolometers. By combining imaging and filtering functions with transmission line, we are able to realize unique structures such as a multi-band polarimeter and a planar, dispersive spectrometer. Micro-strip bolometers have significantly smaller active volume than standard detectors with extended absorbers, and can realize higher sensitivity and speed of response. The integrated array has natural immunity to stray radiation or spectral leaks, and minimizes the suspended mass operating at 0.1 - 0.3 K. We also discuss future space-borne spectroscopy and polarimetry applications

The effect of soil moisture perturbations on Indian Monsoon Depressions in a numerical weather prediction model

Indian monsoon depressions (MDs) are synoptic-scale cyclonic systems that propagate across peninsular India three or four times per monsoon season. They are responsible for the majority of rainfall in agrarian north India, thus constraining precipitation estimates is of high importance. Here, we use a case study from August 2014 to explore the relationship between varying soil moisture and the resulting track and structure of an incident MD using the Met Office Unified Model. We use this case study with the view to increasing understanding of the general impact of soil moisture perturbations on monsoon depressions. It is found that increasing soil moisture in the monsoon trough region results in deeper inland penetration and a more developed structure - e.g. a warmer core in the mid-troposphere and a stronger bimodal potential vorticity core in the middle/lower troposphere - with more precipitation, and a structure that in general more closely resembles that found in depressions over the ocean, indicating that soil moisture may enhance the convective mechanism that drives depressions over land. This experiment also shows that these changes are most significant when the depression is deep, and negligible when it is weakening. Increasing soil moisture in the sub-Himalayan arable zone, a region with large irrigation coverage, also caused deeper inland penetration and some feature enhancement in the upper troposphere but no significant changes were found in the track heading or lower-tropospheric structure

Comparison of the prediction of Indian monsoon low pressure systems by subseasonal-to-seasonal prediction models

This study analyzes the prediction of Indian monsoon low pressure systems (LPSs) on an extended time scale of 15 days by models of the Subseasonal-to-Seasonal (S2S) prediction project. Using a feature-tracking algorithm, LPSs are identified in 11 S2S models during a common reforecast period of June–September 1999–2010, and then compared with 290 and 281 LPSs tracked in ERA-Interim and MERRA-2 reanalysis datasets. The results show that all S2S models underestimate the frequency of LPSs. They are able to represent transits, genesis, and lysis of LPSs; however, large biases are observed in the Australian Bureau of Meteorology, China Meteorological Administration (CMA), and Hydrometeorological Centre of Russia (HMCR) models. The CMA model exhibits large LPS track position error and the intensity of LPSs is overestimated (underestimated) by most models when verified against ERA-Interim (MERRA-2). The European Centre for Medium-Range Weather Forecasts and Met Office models have the best ensemble spread–error relationship for the track position and intensity, whereas the HMCR model has the worst. Most S2S models are underdispersive—more so for the intensity than the position. We find the influence of errors in the LPS simulation on the pattern of total precipitation biases in all S2S models. In most models, precipitation biases increase with forecast lead time over most of the monsoon core zone. These results demonstrate the potential for S2S models at simulating LPSs, thereby giving the possibility of improved disaster preparedness and water resources planning

Extreme daily rainfall in Pakistan and north India: scale-interactions, mechanisms, and precursors

While much of India is used to heavy precipitation and frequent low-pressure systems during the summer monsoon, towards the northwest and into Pakistan, such events are uncommon. Here, as much as a third of the annual rainfall is delivered sporadically during the winter monsoon by western disturbances. Such events of sparse but heavy precipitation in this region of typically mountainous valleys in the north and desert in the south can be catastrophic, as in the case of the Pakistan floods of July 2010. In this study, we identify extreme precipitation events (EPEs) in a box approximately covering this region (65◦ -78◦W, 25◦ -38◦N) using the APHRODITE gauge-based precipitation product. The role of the large-scale circulation in causing EPEs is investigated: it is found that, during winter, they often coexist with an upper-tropospheric Rossby wave train that has prominent anomalous southerlies over the region of interest. These winter EPEs are also found to be strongly colocated with incident western disturbances whereas those occurring during the summer are found to have a less direct relationship. Conversely, summer EPEs are found to have a strong relationship with tropical lows. A detailed Lagrangian method is used to explore possible sources of moisture for such events, and suggests that in winter, the moisture is mostly drawn from the Arabian Sea, whereas during the summer, it comes from along the African coast and the Indian monsoon trough region

Transition-edge superconducting antenna-coupled bolometer

We report test results for a single pixel antenna-coupled bolometric detector. Our device consists of a dual slot microstrip antenna coupled to an Al/Ti/Au voltage-biased transition edge superconducting bolometer (TES). The coupling architecture involves propagating the signal along superconducting microstrip lines and terminating the lines at a normal metal resistor colocated with a TES on a thermally isolated island. The device, which is inherently polarization sensitive, is optimized for 140 GHz band measurements. In the thermal bandwidth of the TES, we measure a noise equivalent power of 2.0 × 10^(-17) W/√Hz in dark tests that agrees with calculated NEP including only contributions from thermal, Johnson and amplifier noise. We do not measure any excess noise at frequencies between 1 and 200 Hz. We measure a thermal conductance G ~5.5 × 10^(-11) W/K. We measure a thermal time constant as low as 437μs at 3μV bias when stimulating the TES directly using an LED

How interactions between tropical depressions and western disturbances affect heavy precipitation in South Asia

Interactions over South Asia between tropical depressions (TDs) and extratropical storms known as western disturbances (WDs) are known to cause extreme precipitation events, including those responsible for the 2013 floods over northern India. In this study, existing databases of WD and TD tracks are used to identify potential WD–TD interactions from 1979–2015; these are filtered according to proximity and intensity, leaving 59 cases which form the basis of this paper. Synoptic charts, vorticity budgets, and moisture trajectory analyses are employed to identify and elucidate common interaction types among these cases. Two broad families of interaction emerge. Firstly, a dynamical coupling of the WD and TD, whereby either the upper- and lower-level vortices superpose (a vortex merger), or the TD is intensified as it passes into the entrance region of a jet streak associated with the WD (a jet-streak excitation). Secondly, a moisture exchange between the WD and TD, whereby either anomalous moisture is advected from the TD to the WD, resulting in anomalous precipitation near the WD (a TD-to-WD moisture exchange), or anomalous moisture is advected from the WD to the TD (a WD-to-TD moisture exchange). Interactions are most common in the post-monsoon period as the subtropical jet, which brings WDs to the subcontinent, returns south; there is a smaller peak in May and June, driven by monsoon onset vortices. Precipitation is heaviest in dynamically-coupled interactions, particularly jet–streak excitations. Criteria for automated identification of interaction types are proposed, and schematics for each type are presented to highlight key mechanisms

Occurrence and sources of radium in groundwater associated with oil fields in the southern San Joaquin Valley, California

Author Posting. © American Chemical Society, 2019. This is an open access article published under an ACS AuthorChoice License. The definitive version was published in Environmental Science and Technology 53(16), (2019): 9398-9406, doi:10.1021/acs.est.9b02395.Geochemical data from 40 water wells were used to examine the occurrence and sources of radium (Ra) in groundwater associated with three oil fields in California (Fruitvale, Lost Hills, South Belridge). 226Ra+228Ra activities (range = 0.010–0.51 Bq/L) exceeded the 0.185 Bq/L drinking-water standard in 18% of the wells (not drinking-water wells). Radium activities were correlated with TDS concentrations (p < 0.001, ρ = 0.90, range = 145–15,900 mg/L), Mn + Fe concentrations (p < 0.001, ρ = 0.82, range = <0.005–18.5 mg/L), and pH (p < 0.001, ρ = −0.67, range = 6.2–9.2), indicating Ra in groundwater was influenced by salinity, redox, and pH. Ra-rich groundwater was mixed with up to 45% oil-field water at some locations, primarily infiltrating through unlined disposal ponds, based on Cl, Li, noble-gas, and other data. Yet 228Ra/226Ra ratios in pond-impacted groundwater (median = 3.1) differed from those in oil-field water (median = 0.51). PHREEQC mixing calculations and spatial geochemical variations suggest that the Ra in the oil-field water was removed by coprecipitation with secondary barite and adsorption on Mn–Fe precipitates in the near-pond environment. The saline, organic-rich oil-field water subsequently mobilized Ra from downgradient aquifer sediments via Ra-desorption and Mn/Fe-reduction processes. This study demonstrates that infiltration of oil-field water may leach Ra into groundwater by changing salinity and redox conditions in the subsurface rather than by mixing with a high-Ra source.This article was improved by the reviews of John Izbicki and anonymous reviewers for the journal. This work was funded by the California State Water Resources Control Board’s Regional Groundwater Monitoring in Areas of Oil and Gas Production Program and the USGS Cooperative Water Program. A.V., A.J.K., and Z.W were supported by USDA-NIFA grant (#2017-68007-26308). Any use of trade, firm, or product names is for description purposes only and does not imply endorsement by the U.S. Government