Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer

Integrating Data from GRACE and Other Observing Systems for Hydrological Research and Applications

The Gravity Recovery and Climate Experiment (GRACE) mission provides a unique view of water cycle dynamics, enabling the only space based observations of water on and beneath the land surface that are not limited by depth. GRACE data are immediately useful for large scale applications such as ice sheet ablation monitoring, but they are even more valuable when combined with other types of observations, either directly or within a data assimilation system. Here we describe recent results of hydrological research and applications projects enabled by GRACE. These include the following: 1) global monitoring of interannual variability of terrestrial water storage and groundwater; 2) water balance estimates of evapotranspiration over several large river basins; 3) NASA's Energy and Water Cycle Study (NEWS) state of the global water budget project; 4) drought indicator products now being incorporated into the U.S. Drought Monitor; 5) GRACE data assimilation over several regions

Randomized Benchmarking of Quantum Gates

A key requirement for scalable quantum computing is that elementary quantum gates can be implemented with sufficiently low error. One method for determining the error behavior of a gate implementation is to perform process tomography. However, standard process tomography is limited by errors in state preparation, measurement and one-qubit gates. It suffers from inefficient scaling with number of qubits and does not detect adverse error-compounding when gates are composed in long sequences. An additional problem is due to the fact that desirable error probabilities for scalable quantum computing are of the order of 0.0001 or lower. Experimentally proving such low errors is challenging. We describe a randomized benchmarking method that yields estimates of the computationally relevant errors without relying on accurate state preparation and measurement. Since it involves long sequences of randomly chosen gates, it also verifies that error behavior is stable when used in long computations. We implemented randomized benchmarking on trapped atomic ion qubits, establishing a one-qubit error probability per randomized pi/2 pulse of 0.00482(17) in a particular experiment. We expect this error probability to be readily improved with straightforward technical modifications.Comment: 13 page

Two stages of parafoveal processing during reading: Evidence from a display change detection task

We used a display change detection paradigm (Slattery, Angele, & Rayner Human Perception and Performance, 37, 1924–1938 2011) to investigate whether display change detection uses orthographic regularity and whether detection is affected by the processing difficulty of the word preceding the boundary that triggers the display change. Subjects were significantly more sensitive to display changes when the change was from a nonwordlike preview than when the change was from a wordlike preview, but the preview benefit effect on the target word was not affected by whether the preview was wordlike or nonwordlike. Additionally, we did not find any influence of preboundary word frequency on display change detection performance. Our results suggest that display change detection and lexical processing do not use the same cognitive mechanisms. We propose that parafoveal processing takes place in two stages: an early, orthography-based, preattentional stage, and a late, attention-dependent lexical access stage

Quantum control, quantum information processing, and quantum-limited metrology with trapped ions

We briefly discuss recent experiments on quantum information processing using trapped ions at NIST. A central theme of this work has been to increase our capabilities in terms of quantum computing protocols, but we have also applied the same concepts to improved metrology, particularly in the area of frequency standards and atomic clocks. Such work may eventually shed light on more fundamental issues, such as the quantum measurement problem.Comment: Proceedings of the International Conference on Laser Spectroscopy (ICOLS), 10 pages, 5 figure

Long-lived qubit memory using atomic ions

We demonstrate experimentally a robust quantum memory using a magnetic-field-independent hyperfine transition in 9Be+ atomic ion qubits at a magnetic field B ~= 0.01194 T. We observe that the single physical qubit memory coherence time is greater than 10 seconds, an improvement of approximately five orders of magnitude from previous experiments with 9Be+. We also observe long coherence times of decoherence-free subspace logical qubits comprising two entangled physical qubits and discuss the merits of each type of qubit.Comment: 5 pages, 4 figure

Soil Moisture Active Passive (SMAP) Mission Level 4 Surface and Root Zone Soil Moisture (L4_SM) Product Specification Document

This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project. The Soil Moisture Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial soil moisture and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends